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Yang M, Yang K, Wu M, Huang L, Ding W, Pan L, Yin L. LGENet: disentangle anatomy and pathology features for late gadolinium enhancement image segmentation. Med Biol Eng Comput 2025:10.1007/s11517-025-03326-w. [PMID: 39992518 DOI: 10.1007/s11517-025-03326-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2024] [Accepted: 02/08/2025] [Indexed: 02/25/2025]
Abstract
Myocardium scar segmentation is essential for clinical diagnosis and prognosis for cardiac vascular diseases. Late gadolinium enhancement (LGE) imaging technology has been widely utilized to visualize left atrial and ventricular scars. However, automatic scar segmentation remains challenging due to the imbalance between scar and background and the variation in scar sizes. To address these challenges, we introduce an innovative network, i.e., LGENet, for scar segmentation. LGENet disentangles anatomy and pathology features from LGE images. Note that inherent spatial relationships exist between the myocardium and scarring regions. We proposed a boundary attention module to allow the scar segmentation conditioned on anatomical boundary features, which could mitigate the imbalance problem. Meanwhile, LGENet can predict scar regions across multiple scales with a multi-depth decision module, addressing the scar size variation issue. In our experiments, we thoroughly evaluated the performance of LGENet using LAScarQS 2022 and EMIDEC datasets. The results demonstrate that LGENet achieved promising performance for cardiac scar segmentation.
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Affiliation(s)
- Mingjing Yang
- College of Physics and Information Engineering, Fuzhou University, Fuzhou, Fujian, China
| | - Kangwen Yang
- College of Physics and Information Engineering, Fuzhou University, Fuzhou, Fujian, China
| | - Mengjun Wu
- College of Physics and Information Engineering, Fuzhou University, Fuzhou, Fujian, China
| | - Liqin Huang
- College of Physics and Information Engineering, Fuzhou University, Fuzhou, Fujian, China
| | - Wangbin Ding
- School of Medical Imaging, Fujian Medical University, Fuzhou, Fujian, China
| | - Lin Pan
- College of Physics and Information Engineering, Fuzhou University, Fuzhou, Fujian, China.
| | - Lei Yin
- The Departments of Radiology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, Fujian, China.
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Pius C, Niort B, Radcliffe EJ, Trafford AW. A refined, minimally invasive, reproducible ovine ischaemia-reperfusion-infarction model using implantable defibrillators: Methodology and validation. Exp Physiol 2025; 110:215-229. [PMID: 39702979 PMCID: PMC11782204 DOI: 10.1113/ep091760] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Accepted: 10/10/2024] [Indexed: 12/21/2024]
Abstract
Ischaemic heart disease remains a leading cause of premature mortality and morbidity. Understanding the associated pathophysiological mechanisms of cardiac dysfunction arising from ischaemic heart disease and the identification of sites for new therapeutic interventions requires a preclinical model that reproduces the key clinical characteristics of myocardial ischaemia, reperfusion and infarction. Here, we describe and validate a refined and minimally invasive translationally relevant approach to induce ischaemia, reperfusion and infarction in the sheep. The novelty and refinement in the procedure stems from utilization of implantable cardiac defibrillators prior to coronary engagement, balloon angioplasty to induce infarction, and intra-operative anti-arrhythmic drug protocols to reduce adverse arrhythmic events. The protocol is readily adoptable by researchers with access to standard fluoroscopic instrumentation, and it requires minimally invasive surgery. These refinements lead to a substantial reduction of intra-operative mortality to 6.7% from previously published values ranging between 13% and 43%. The model produces key characteristics associated with the fourth universal definition of myocardial infarction, including ECG changes, elevated cardiac biomarkers and cardiac wall motility defects. In conclusion, the model closely replicates the clinical paradigm of myocardial ischaemia, reperfusion and infarction in a translationally relevant large animal setting, and the applied refinements reduce the incidence of intra-operative mortality typically associated with preclinical myocardial infarction models.
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Affiliation(s)
- Charlene Pius
- Division of Cardiovascular Science, School of Medical Science, Faculty of Biology Medicine and Health, University of ManchesterManchester Academic Health Science CentreManchesterUK
| | - Barbara Niort
- Division of Cardiovascular Science, School of Medical Science, Faculty of Biology Medicine and Health, University of ManchesterManchester Academic Health Science CentreManchesterUK
| | - Emma J. Radcliffe
- Division of Cardiovascular Science, School of Medical Science, Faculty of Biology Medicine and Health, University of ManchesterManchester Academic Health Science CentreManchesterUK
| | - Andrew W. Trafford
- Division of Cardiovascular Science, School of Medical Science, Faculty of Biology Medicine and Health, University of ManchesterManchester Academic Health Science CentreManchesterUK
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Redondo‐Rodríguez A, Ramos‐Prada A, Quintanilla JG, Calvo D, Sánchez‐González J, Enríquez‐Vázquez D, Marina‐Breysse M, Alfonso‐Almazán JM, González‐Ferrer JJ, Cañadas‐Godoy V, Salgado‐Aranda R, Morillo CA, Pérez‐Villacastín J, Pérez‐Castellano N, Filgueiras‐Rama D. Dispersion of Activation in Single-Beat Global Maps During Programmed Ventricular Stimulation Identifies Infarct-Related Ventricular Tachycardia Isthmus Sites. J Am Heart Assoc 2024; 13:e038441. [PMID: 39575703 PMCID: PMC11681573 DOI: 10.1161/jaha.124.038441] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2024] [Accepted: 10/15/2024] [Indexed: 01/18/2025]
Abstract
BACKGROUND Electrophysiological characterization of ventricular tachycardia (VT) isthmus sites is complex and time-consuming. We aimed at developing and validating a global mapping strategy during programmed ventricular stimulation (PVS) to reveal the underlying electrophysiological properties of the infarct-related substrate and to enable identification of highly heterogeneous activation sites associated with protected VT isthmus sites. METHODS AND RESULTS Experimental study that included 22 pigs with established myocardial infarction undergoing in vivo characterization of the anatomical and functional myocardial substrate associated with potential arrhythmogenicity. High-density sequential activation maps during ventricular pacing and VT were compared with single-beat maps using a 64-pole basket catheter positioned in the left ventricle. Further analyses were performed using a novel local activation time-dispersion score to identify regional activation time heterogeneities on both baseline drive pacing and each of the extrastimuli of the PVS protocol. Basket catheter splines covered a median of 81.2% of the endocardial surface of the left ventricle. Basket-catheter-derived single-beat activation maps (N=16) during pacing showed a linear relationship with high-density sequential activation maps. Induction of ventricular arrhythmias was associated with higher local activation time-dispersion score values on single-beat global maps during PVS (N=6, 46 arrhythmia induction attempts). Single-beat-derived local activation time-dispersion score maps during successive coupled extrastimuli of the PVS showed a progressive increase in the predictive performance to identify monomorphic VT isthmus sites within the scar region (area under the curve = 0.779 in S2, area under the curve = 0.859 in S4; N=7). CONCLUSIONS Sixty-four-pole-derived single-beat local activation time-dispersion score global maps during PVS identify infarct-related endocardial regions with highly heterogeneous activation times that are associated with protected VT isthmus sites.
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Affiliation(s)
- Andrés Redondo‐Rodríguez
- Centro Nacional de Investigaciones Cardiovasculares (CNIC)Novel Arrhythmogenic Mechanisms ProgramMadridSpain
| | - Alba Ramos‐Prada
- Centro Nacional de Investigaciones Cardiovasculares (CNIC)Novel Arrhythmogenic Mechanisms ProgramMadridSpain
- Fundación Interhospitalaria para la Investigación CardiovascularMadridSpain
| | - Jorge G. Quintanilla
- Centro Nacional de Investigaciones Cardiovasculares (CNIC)Novel Arrhythmogenic Mechanisms ProgramMadridSpain
- Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV)MadridSpain
- Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC)Cardiovascular InstituteMadridSpain
| | - David Calvo
- Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV)MadridSpain
- Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC)Cardiovascular InstituteMadridSpain
| | | | - Daniel Enríquez‐Vázquez
- Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV)MadridSpain
- Complexo Hospitalario Universitario A Coruña. Servicio de Cardiología, Instituto de Investigación Biomédica A Coruña (INIBIC)A CoruñaSpain
| | - Manuel Marina‐Breysse
- Centro Nacional de Investigaciones Cardiovasculares (CNIC)Novel Arrhythmogenic Mechanisms ProgramMadridSpain
- Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV)MadridSpain
| | - Jose Manuel Alfonso‐Almazán
- Centro Nacional de Investigaciones Cardiovasculares (CNIC)Novel Arrhythmogenic Mechanisms ProgramMadridSpain
| | - Juan José González‐Ferrer
- Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV)MadridSpain
- Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC)Cardiovascular InstituteMadridSpain
| | - Victoria Cañadas‐Godoy
- Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV)MadridSpain
- Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC)Cardiovascular InstituteMadridSpain
| | - Ricardo Salgado‐Aranda
- Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV)MadridSpain
- Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC)Cardiovascular InstituteMadridSpain
| | - Carlos A. Morillo
- Centro Nacional de Investigaciones Cardiovasculares (CNIC)Novel Arrhythmogenic Mechanisms ProgramMadridSpain
- Department of Cardiac Sciences, Libin Cardiovascular Institute, Cumming School of MedicineUniversity of CalgaryCalgaryAlbertaCanada
| | - Julián Pérez‐Villacastín
- Fundación Interhospitalaria para la Investigación CardiovascularMadridSpain
- Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV)MadridSpain
- Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC)Cardiovascular InstituteMadridSpain
| | - Nicasio Pérez‐Castellano
- Fundación Interhospitalaria para la Investigación CardiovascularMadridSpain
- Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV)MadridSpain
- Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC)Cardiovascular InstituteMadridSpain
| | - David Filgueiras‐Rama
- Centro Nacional de Investigaciones Cardiovasculares (CNIC)Novel Arrhythmogenic Mechanisms ProgramMadridSpain
- Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV)MadridSpain
- Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC)Cardiovascular InstituteMadridSpain
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Sohn SH, Kang Y, Kim JS, Park EA, Lee W, Hwang HY. Impact of Myocardial Viability on Long-term Outcomes after Surgical Revascularization. Thorac Cardiovasc Surg 2024; 72:441-448. [PMID: 38092064 DOI: 10.1055/a-2228-7104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
BACKGROUND This study was conducted to evaluate whether myocardial viability assessed with cardiac magnetic resonance (CMR) affected long-term clinical outcomes after coronary artery bypass grafting (CABG) in patients with ischemic cardiomyopathy (ICMP). METHODS Preoperative CMR with late gadolinium enhancement (LGE) was performed in 103 patients (64.9 ± 10.1 years, male:female = 82:21) with 3-vessel disease and left ventricular dysfunction (ejection fraction ≤ 0.35). Transmural extent of LGE was evaluated on a 16-segment model, and transmurality was graded on a 5-point scale: grades-0, absence; 1, 1 to 25%; 2, 26 to 50%; 3, 51 to 75%; 4, 76 to 100%. Median follow-up duration was 65.5 months (interquartile range = 27.5-95.3 months). Primary endpoint was the composite of all-cause mortality or hospitalization for congestive heart failure. RESULTS Operative mortality was 1.9%. During the follow-up, all-cause mortality and readmission for congestive heart failure occurred in 29 and 8 patients, respectively. The cumulative incidence of the primary endpoint was 31.3 and 46.8% at 5 and 10 years, respectively. Multivariable analysis demonstrated that the number of segments with LGE grade 4 was a significant risk factor (hazard ratio 1.42, 95% confidence interval 1.10-1.83, p = 0.007) for the primary endpoint among the variables assessed by CMR. Other risk factors included age, dialysis, chronic obstructive pulmonary disease, and EuroSCORE II. CONCLUSION The number of myocardial segments with transmurality of LGE >75% might be a prognostic factor associated with the composite of all-cause mortality or hospitalization for congestive heart failure after CABG in patients with 3-vessel disease and ICMP.
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Affiliation(s)
- Suk Ho Sohn
- Department of Thoracic and Cardiovascular Surgery, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Yoonjin Kang
- Department of Thoracic and Cardiovascular Surgery, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Ji Seong Kim
- Department of Thoracic and Cardiovascular Surgery, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Eun-Ah Park
- Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Whal Lee
- Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Ho Young Hwang
- Department of Thoracic and Cardiovascular Surgery, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
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Shah ND, Krishnam M, Ambale Venkatesh B, Khan F, Smith M, Jones DR, Koon P, Mao X, Janich MA, Brau ACS, Salerno M, Dash R, Chan F, Yang PC. Wideband radiofrequency pulse sequence for evaluation of myocardial scar in patients with cardiac implantable devices. FRONTIERS IN RADIOLOGY 2024; 4:1327406. [PMID: 39175870 PMCID: PMC11339872 DOI: 10.3389/fradi.2024.1327406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 07/17/2024] [Indexed: 08/24/2024]
Abstract
Background Cardiac magnetic resonance is a useful clinical tool to identify late gadolinium enhancement in heart failure patients with implantable electronic devices. Identification of LGE in patients with CIED is limited by artifact, which can be improved with a wide band radiofrequency pulse sequence. Objective The authors hypothesize that image quality of LGE images produced using wide-band pulse sequence in patients with devices is comparable to image quality produced using standard LGE sequences in patients without devices. Methods Two independent readers reviewed LGE images of 16 patients with CIED and 7 patients without intracardiac devices to assess for image quality, device-related artifact, and presence of LGE using the American Society of Echocardiography/American Heart Association 17 segment model of the heart on a 4-point Likert scale. The mean and standard deviation for image quality and artifact rating were determined. Inter-observer reliability was determined by calculating Cohen's kappa coefficient. Statistical significance was determined by T-test as a p {less than or equal to} 0.05 with a 95% confidence interval. Results All patients underwent CMR without any adverse events. Overall IQ of WB LGE images was significantly better in patients with devices compared to standard LGE in patients without devices (p = 0.001) with reduction in overall artifact rating (p = 0.05). Conclusion Our study suggests wide-band pulse sequence for LGE can be applied safely to heart failure patients with devices in detection of LV myocardial scar while maintaining image quality, reducing artifact, and following routine imaging protocol after intravenous gadolinium contrast administration.
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Affiliation(s)
- Neil D. Shah
- Department of Medicine, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Mayil Krishnam
- Department of Radiology, Stanford University, Stanford, CA, United States
| | - Bharat Ambale Venkatesh
- Department of Medicine, Division of Cardiovascular Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Fouzia Khan
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University, Stanford, CA, United States
| | - Michele Smith
- Department of Radiology, Stanford University, Stanford, CA, United States
| | - Darwin R. Jones
- Department of Radiology, Stanford University, Stanford, CA, United States
| | | | | | | | | | - Michael Salerno
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University, Stanford, CA, United States
| | - Rajesh Dash
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University, Stanford, CA, United States
| | - Frandics Chan
- Department of Radiology, Stanford University, Stanford, CA, United States
| | - Phillip C. Yang
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University, Stanford, CA, United States
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Cui H, Li Y, Wang Y, Xu D, Wu LM, Xia Y. Toward Accurate Cardiac MRI Segmentation With Variational Autoencoder-Based Unsupervised Domain Adaptation. IEEE TRANSACTIONS ON MEDICAL IMAGING 2024; 43:2924-2936. [PMID: 38546999 DOI: 10.1109/tmi.2024.3382624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/02/2024]
Abstract
Accurate myocardial segmentation is crucial in the diagnosis and treatment of myocardial infarction (MI), especially in Late Gadolinium Enhancement (LGE) cardiac magnetic resonance (CMR) images, where the infarcted myocardium exhibits a greater brightness. However, segmentation annotations for LGE images are usually not available. Although knowledge gained from CMR images of other modalities with ample annotations, such as balanced-Steady State Free Precession (bSSFP), can be transferred to the LGE images, the difference in image distribution between the two modalities (i.e., domain shift) usually results in a significant degradation in model performance. To alleviate this, an end-to-end Variational autoencoder based feature Alignment Module Combining Explicit and Implicit features (VAMCEI) is proposed. We first re-derive the Kullback-Leibler (KL) divergence between the posterior distributions of the two domains as a measure of the global distribution distance. Second, we calculate the prototype contrastive loss between the two domains, bringing closer the prototypes of the same category across domains and pushing away the prototypes of different categories within or across domains. Finally, a domain discriminator is added to the output space, which indirectly aligns the feature distribution and forces the extracted features to be more favorable for segmentation. In addition, by combining CycleGAN and VAMCEI, we propose a more refined multi-stage unsupervised domain adaptation (UDA) framework for myocardial structure segmentation. We conduct extensive experiments on the MSCMRSeg 2019, MyoPS 2020 and MM-WHS 2017 datasets. The experimental results demonstrate that our framework achieves superior performances than state-of-the-art methods.
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Jani VP, Ostovaneh M, Chamera E, Kato Y, Lima JAC, Ambale-Venkatesh B. Deep learning for automatic volumetric segmentation of left ventricular myocardium and ischaemic scar from multi-slice late gadolinium enhancement cardiovascular magnetic resonance. Eur Heart J Cardiovasc Imaging 2024; 25:829-838. [PMID: 38244222 DOI: 10.1093/ehjci/jeae022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 12/09/2023] [Accepted: 01/16/2024] [Indexed: 01/22/2024] Open
Abstract
AIMS This study details application of deep learning for automatic volumetric segmentation of left ventricular (LV) myocardium and scar and automated quantification of myocardial ischaemic scar burden from late gadolinium enhancement cardiovascular magnetic resonance (LGE-CMR). METHODS AND RESULTS We included 501 images and manual segmentations of short-axis LGE-CMR from over 20 multinational sites, from which 377 studies were used for training and 124 studies from unique participants for internal validation. A third test set of 52 images was used for external evaluation. Three models, U-Net, Cascaded U-Net, and U-Net++, were trained with a novel adaptive weighted categorical cross-entropy loss function. Model performance was evaluated using concordance correlation coefficients (CCCs) for LV mass and per cent myocardial scar burden. Cascaded U-Net was found to be the best model for the quantification of LV mass and scar percentage. The model exhibited a mean difference of -5 ± 23 g for LV mass, -0.4 ± 11.2 g for scar mass, and -0.8 ± 7% for per cent scar. CCC were 0.87, 0.77, and 0.78 for LV mass, scar mass, and per cent scar burden, respectively, in the internal validation set and 0.75, 0.71, and 0.69, respectively, in the external test set. For segmental scar mass, CCC was 0.74 for apical scar, 0.91 for mid-ventricular scar, and 0.73 for basal scar, demonstrating moderate to strong agreement. CONCLUSION We successfully trained a convolutional neural network for volumetric segmentation and analysis of LV scar burden from LGE-CMR images in a large, multinational cohort of participants with ischaemic scar.
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Affiliation(s)
- Vivek P Jani
- Division of Cardiology, Johns Hopkins University School of Medicine, 600 N Wolfe St, Blalock 524, Baltimore, MD 21297-0409, USA
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Mohammad Ostovaneh
- Division of Cardiology, Johns Hopkins University School of Medicine, 600 N Wolfe St, Blalock 524, Baltimore, MD 21297-0409, USA
| | - Elzbieta Chamera
- Division of Cardiology, Johns Hopkins University School of Medicine, 600 N Wolfe St, Blalock 524, Baltimore, MD 21297-0409, USA
| | - Yoko Kato
- Division of Cardiology, Johns Hopkins University School of Medicine, 600 N Wolfe St, Blalock 524, Baltimore, MD 21297-0409, USA
| | - Joao A C Lima
- Division of Cardiology, Johns Hopkins University School of Medicine, 600 N Wolfe St, Blalock 524, Baltimore, MD 21297-0409, USA
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Hoh T, Margolis I, Weine J, Joyce T, Manka R, Weisskopf M, Cesarovic N, Fuetterer M, Kozerke S. Impact of late gadolinium enhancement image acquisition resolution on neural network based automatic scar segmentation. J Cardiovasc Magn Reson 2024; 26:101031. [PMID: 38431078 PMCID: PMC10981112 DOI: 10.1016/j.jocmr.2024.101031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Accepted: 02/23/2024] [Indexed: 03/05/2024] Open
Abstract
BACKGROUND Automatic myocardial scar segmentation from late gadolinium enhancement (LGE) images using neural networks promises an alternative to time-consuming and observer-dependent semi-automatic approaches. However, alterations in data acquisition, reconstruction as well as post-processing may compromise network performance. The objective of the present work was to systematically assess network performance degradation due to a mismatch of point-spread function between training and testing data. METHODS Thirty-six high-resolution (0.7×0.7×2.0 mm3) LGE k-space datasets were acquired post-mortem in porcine models of myocardial infarction. The in-plane point-spread function and hence in-plane resolution Δx was retrospectively degraded using k-space lowpass filtering, while field-of-view and matrix size were kept constant. Manual segmentation of the left ventricle (LV) and healthy remote myocardium was performed to quantify location and area (% of myocardium) of scar by thresholding (≥ SD5 above remote). Three standard U-Nets were trained on training resolutions Δxtrain = 0.7, 1.2 and 1.7 mm to predict endo- and epicardial borders of LV myocardium and scar. The scar prediction of the three networks for varying test resolutions (Δxtest = 0.7 to 1.7 mm) was compared against the reference SD5 thresholding at 0.7 mm. Finally, a fourth network trained on a combination of resolutions (Δxtrain = 0.7 to 1.7 mm) was tested. RESULTS The prediction of relative scar areas showed the highest precision when the resolution of the test data was identical to or close to the resolution used during training. The median fractional scar errors and precisions (IQR) from networks trained and tested on the same resolution were 0.0 percentage points (p.p.) (1.24 - 1.45), and - 0.5 - 0.0 p.p. (2.00 - 3.25) for networks trained and tested on the most differing resolutions, respectively. Deploying the network trained on multiple resolutions resulted in reduced resolution dependency with median scar errors and IQRs of 0.0 p.p. (1.24 - 1.69) for all investigated test resolutions. CONCLUSION A mismatch of the imaging point-spread function between training and test data can lead to degradation of scar segmentation when using current U-Net architectures as demonstrated on LGE porcine myocardial infarction data. Training networks on multi-resolution data can alleviate the resolution dependency.
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Affiliation(s)
- Tobias Hoh
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland.
| | - Isabel Margolis
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland.
| | - Jonathan Weine
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Thomas Joyce
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland.
| | - Robert Manka
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland; Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland; Department of Cardiology, University Heart Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
| | - Miriam Weisskopf
- Center of Surgical Research, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
| | - Nikola Cesarovic
- Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland; Department of Cardiothoracic and Vascular Surgery, German Heart Center Berlin, Berlin, Germany.
| | - Maximilian Fuetterer
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland.
| | - Sebastian Kozerke
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland.
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Kato Y, Lee WH, Natsumeda M, Ambale-Venkatesh B, Takagi K, Ikari Y, Lima JAC. Left atrial diastasis strain slope is a marker of hemodynamic recovery in post-ST elevation myocardial infarction: the Laser Atherectomy for STemi, Pci Analysis with Scintigraphy Study (LAST-PASS). FRONTIERS IN RADIOLOGY 2024; 4:1294398. [PMID: 38450099 PMCID: PMC10914933 DOI: 10.3389/fradi.2024.1294398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Accepted: 01/30/2024] [Indexed: 03/08/2024]
Abstract
Background Left atrial (LA) mechanics are strongly linked with left ventricular (LV) filling. The LA diastasis strain slope (LADSS), which spans between the passive and active LA emptying phases, may be a key indicator of the LA-LV interplay during diastole. Aim This study aimed to investigate the LA-LV interdependencies in post-ST elevation myocardial infarction (STEMI), with particular focus on the LADSS. Materials and methods Patients with post-anterior STEMI who received primary percutaneous coronary intervention underwent contrast cardiac magnetic resonance imaging (MRI) during acute (5-9 days post-STEMI) and chronic (at 6 months) phases. The LADSS was categorized into three groups: Groups 1, 2, and 3 representing positive, flat, and negative slopes, respectively. Cross-sectional correlates of LADSS Group 2 or 3 compared to Group 1 were identified, adjusting for demographics, LA indices, and with or without LV indices. The associations of acute phase LADSS with the recovery of LV ejection fraction (LVEF) and scar amount were investigated. Results Sixty-six acute phase (86.4% male, 63.1 ± 11.8 years) and 59 chronic phase cardiac MRI images were investigated. The distribution across LADSS Groups 1, 2, and 3 in the acute phase was 24.2%, 28.9%, and 47.0%, respectively, whereas in the chronic phase, it was 33.9%, 22.0%, and 44.1%, respectively. LADSS Group 3 demonstrated a higher heart rate than Group 1 in the acute phase (61.9 ± 8.7 vs. 73.5 ± 11.9 bpm, p < 0.01); lower LVEF (48.7 ± 8.6 vs. 41.8 ± 9.9%, p = 0.041) and weaker LA passive strain rate (SR) (-1.1 ± 0.4 vs. -0.7 [-1.2 to -0.6] s-1, p = 0.037) in the chronic phase. Chronic phase Group 3 exhibited weaker LA passive SR [relative risk ratio (RRR) = 8.8, p = 0.012] than Group 1 after adjusting for demographics and LA indices; lower LVEF (RRR = 0.85, p < 0.01), higher heart rate (RRR = 1.1, p = 0.070), and less likelihood of being male (RRR = 0.08, p = 0.058) after full adjustment. Acute phase LADSS Groups 2 and 3 predicted poor recovery of LVEF when adjusted for demographics and LA indices; LADSS Group 2 remained a predictor in the fully adjusted model (β = -5.8, p = 0.013). Conclusion The LADSS serves both as a marker of current LV hemodynamics and its recovery in post-anterior STEMI. The LADSS is an important index of LA-LV interdependency during diastole. Clinical Trial Registration https://clinicaltrials.gov/, identifier NCT03950310.
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Affiliation(s)
- Yoko Kato
- Division of Cardiology, Johns Hopkins University, Baltimore, MD, United States
| | - Wei Hao Lee
- Division of Cardiology, Johns Hopkins University, Baltimore, MD, United States
| | | | | | - Kensuke Takagi
- Department of Cardiology, Ogaki Municipal Hospital, Ogaki, Japan
- Department of Cardiology, National Cerebral and Cardiovascular Center, Suita, Japan
| | - Yuji Ikari
- Department of Cardiology, Tokai University, Isehara, Japan
| | - Joao A. C. Lima
- Division of Cardiology, Johns Hopkins University, Baltimore, MD, United States
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10
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Koo HJ, Lee SA, Jung SH, Kang JW, Yang DH. Tailored Planning of Surgical Myectomy in Obstructive Hypertrophic Cardiomyopathy. Radiographics 2024; 44:e230050. [PMID: 38060425 DOI: 10.1148/rg.230050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
Hypertrophic cardiomyopathy (HCM) is a genetic myocardial disease characterized by abnormal thickening of the myocardium caused by myocardial disarray and interstitial fibrosis. HCM is associated with sudden cardiac-related events, such as ventricular fibrillation, tachycardia, and syncope. Moreover, left ventricular or midcavity obstruction due to the thickened myocardium can result in severe heart failure and mortality in patients with HCM. Surgical myectomy is a standard treatment option for patients with symptomatic obstructive HCM; however, it is a complex procedure that requires careful planning and execution to avoid complications, such as residual flow obstruction, persistent obliteration of the left ventricular cavity in systole, or iatrogenic ventricular septal defects. Therefore, a thorough understanding of the mechanics of HCM and precise evaluation of the location and extent of the hypertrophic myocardium to be removed are crucial for preoperative planning. Multiphase cardiac CT postprocessing is important for preoperative evaluation and planning of surgical myectomy in patients with HCM. In this review, the authors highlight use of multiphase cardiac CT with step-by-step postprocessing methods to simulate successful surgical myectomy. The transaortic surgeon's view on end-diastolic phase images accurately represents the surgical field. Moreover, myocardial segmentation can be used to generate volume-rendered images and three-dimensional printing. CT evaluation can also assist in identifying concurrent abnormalities, such as mitral valve or papillary muscle abnormalities. In addition to CT, other imaging modalities for preoperative evaluation of HCM and postmyectomy evaluation methods are presented. ©RSNA, 2023 Test Your Knowledge questions in the supplemental material and the slide presentation from the RSNA Annual Meeting are available for this article.
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Affiliation(s)
- Hyun Jung Koo
- From the Department of Radiology and Research Institute of Radiology, Cardiac Imaging Center (H.J.K., J.W.K., D.H.Y.), Division of Cardiology, Internal Medicine, Cardiac Imaging Center (S.A.L.), and Department of Thoracic and Cardiovascular Surgery (S.H.J.), University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, South Korea
| | - Seung-Ah Lee
- From the Department of Radiology and Research Institute of Radiology, Cardiac Imaging Center (H.J.K., J.W.K., D.H.Y.), Division of Cardiology, Internal Medicine, Cardiac Imaging Center (S.A.L.), and Department of Thoracic and Cardiovascular Surgery (S.H.J.), University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, South Korea
| | - Sung Ho Jung
- From the Department of Radiology and Research Institute of Radiology, Cardiac Imaging Center (H.J.K., J.W.K., D.H.Y.), Division of Cardiology, Internal Medicine, Cardiac Imaging Center (S.A.L.), and Department of Thoracic and Cardiovascular Surgery (S.H.J.), University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, South Korea
| | - Joon-Won Kang
- From the Department of Radiology and Research Institute of Radiology, Cardiac Imaging Center (H.J.K., J.W.K., D.H.Y.), Division of Cardiology, Internal Medicine, Cardiac Imaging Center (S.A.L.), and Department of Thoracic and Cardiovascular Surgery (S.H.J.), University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, South Korea
| | - Dong Hyun Yang
- From the Department of Radiology and Research Institute of Radiology, Cardiac Imaging Center (H.J.K., J.W.K., D.H.Y.), Division of Cardiology, Internal Medicine, Cardiac Imaging Center (S.A.L.), and Department of Thoracic and Cardiovascular Surgery (S.H.J.), University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, South Korea
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11
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Lecesne E, Simon A, Garreau M, Barone-Rochette G, Fouard C. Segmentation of cardiac infarction in delayed-enhancement MRI using probability map and transformers-based neural networks. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2023; 242:107841. [PMID: 37865006 DOI: 10.1016/j.cmpb.2023.107841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 09/15/2023] [Accepted: 10/01/2023] [Indexed: 10/23/2023]
Abstract
BACKGROUND AND OBJECTIVE Automatic segmentation of myocardial infarction is of great clinical interest for the quantitative evaluation of myocardial infarction (MI). Late Gadolinium Enhancement cardiac MRI (LGE-MRI) is commonly used in clinical practice to quantify MI, which is crucial for clinical diagnosis and treatment of cardiac diseases. However, the segmentation of infarcted tissue in LGE-MRI is highly challenging due to its high anisotropy and inhomogeneities. METHODS The innovative aspect of our work lies in the utilization of a probability map of the healthy myocardium to guide the localization of infarction, as well as the combination of 2D U-Net and U-Net transformers to achieve the final segmentation. Instead of employing a binary segmentation map, we propose using a probability map of the normal myocardium, obtained through a dedicated 2D U-Net. To leverage spatial information, we employ a U-Net transformers network where we incorporate the probability map into the original image as an additional input. Then, To address the limitations of U-Net in segmenting accurately the contours, we introduce an adapted loss function. RESULTS Our method has been evaluated on the 2020 MICCAI EMIDEC challenge dataset, yielding competitive results. Specifically, we achieved a Dice score of 92.94% for the myocardium and 92.36% for the infarction. These outcomes highlight the competitiveness of our approach. CONCLUSION In the case of the infarction class, our proposed method outperforms state-of-the-art techniques across all metrics evaluated in the challenge, establishing its superior performance in infarction segmentation. This study further reinforces the importance of integrating a contour loss into the segmentation process.
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Affiliation(s)
- Erwan Lecesne
- Univ Rennes, Inserm, LTSI - UMR 1099, Rennes, 35000, France.
| | - Antoine Simon
- Univ Rennes, Inserm, LTSI - UMR 1099, Rennes, 35000, France
| | | | - Gilles Barone-Rochette
- Clinic of Cardiology, Cardiovascular and Thoracic Department, University Hospital of Grenoble, Grenoble, 38000, France
| | - Céline Fouard
- Univ. Grenoble Alpes, CNRS, UMR 5525, VetAgro Sup, Grenoble INP, TIMC, Grenoble, 38000, France
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12
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Ding W, Li L, Qiu J, Wang S, Huang L, Chen Y, Yang S, Zhuang X. Aligning Multi-Sequence CMR Towards Fully Automated Myocardial Pathology Segmentation. IEEE TRANSACTIONS ON MEDICAL IMAGING 2023; 42:3474-3486. [PMID: 37347625 DOI: 10.1109/tmi.2023.3288046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/24/2023]
Abstract
Myocardial pathology segmentation (MyoPS) is critical for the risk stratification and treatment planning of myocardial infarction (MI). Multi-sequence cardiac magnetic resonance (MS-CMR) images can provide valuable information. For instance, balanced steady-state free precession cine sequences present clear anatomical boundaries, while late gadolinium enhancement and T2-weighted CMR sequences visualize myocardial scar and edema of MI, respectively. Existing methods usually fuse anatomical and pathological information from different CMR sequences for MyoPS, but assume that these images have been spatially aligned. However, MS-CMR images are usually unaligned due to the respiratory motions in clinical practices, which poses additional challenges for MyoPS. This work presents an automatic MyoPS framework for unaligned MS-CMR images. Specifically, we design a combined computing model for simultaneous image registration and information fusion, which aggregates multi-sequence features into a common space to extract anatomical structures (i.e., myocardium). Consequently, we can highlight the informative regions in the common space via the extracted myocardium to improve MyoPS performance, considering the spatial relationship between myocardial pathologies and myocardium. Experiments on a private MS-CMR dataset and a public dataset from the MYOPS2020 challenge show that our framework could achieve promising performance for fully automatic MyoPS.
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13
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Jukema RA, de Winter RW, Hopman LHGA, Driessen RS, van Diemen PA, Appelman Y, Twisk JWR, Planken RN, Raijmakers PG, Knaapen P, Danad I. Impact of cardiac history and myocardial scar on increase of myocardial perfusion after revascularization. Eur J Nucl Med Mol Imaging 2023; 50:3897-3909. [PMID: 37561140 PMCID: PMC10611874 DOI: 10.1007/s00259-023-06356-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2023] [Accepted: 07/22/2023] [Indexed: 08/11/2023]
Abstract
PURPOSE We sought to assess the impact of coronary revascularization on myocardial perfusion and fractional flow reserve (FFR) in patients without a cardiac history, with prior myocardial infarction (MI) or non-MI percutaneous coronary intervention (PCI). Furthermore, we studied the impact of scar tissue. METHODS Symptomatic patients underwent [15O]H2O positron emission tomography (PET) and FFR before and after revascularization. Patients with prior CAD, defined as prior MI or PCI, underwent scar quantification by magnetic resonance imaging late gadolinium enhancement. RESULTS Among 137 patients (87% male, age 62.2 ± 9.5 years) 84 (61%) had a prior MI or PCI. The increase in FFR and hyperemic myocardial blood flow (hMBF) was less in patients with prior MI or non-MI PCI compared to those without a cardiac history (FFR: 0.23 ± 0.14 vs. 0.20 ± 0.12 vs. 0.31 ± 0.18, p = 0.02; hMBF: 0.54 ± 0.75 vs. 0.62 ± 0.97 vs. 0.91 ± 0.96 ml/min/g, p = 0.04). Post-revascularization FFR and hMBF were similar across patients without a cardiac history or with prior MI or non-MI PCI. An increase in FFR was strongly associated to hMBF increase in patients without a cardiac history or with prior MI/non-MI PCI (r = 0.60 and r = 0.60, p < 0.01 for both). Similar results were found for coronary flow reserve. In patients with prior MI scar was negatively correlated to hMBF increase and independently predictive of an attenuated CFR increase. CONCLUSIONS Post revascularization FFR and perfusion were similar among patients without a cardiac history, with prior MI or non-MI PCI. In patients with prior MI scar burden was associated to an attenuated perfusion increase.
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Affiliation(s)
- Ruurt A Jukema
- Departments of Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Ruben W de Winter
- Departments of Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Luuk H G A Hopman
- Departments of Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Roel S Driessen
- Departments of Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Pepijn A van Diemen
- Departments of Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Yolande Appelman
- Departments of Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Jos W R Twisk
- Epidemiology & Data Science, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - R Nils Planken
- Radiology, Nuclear Medicine & PET Research, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Pieter G Raijmakers
- Radiology, Nuclear Medicine & PET Research, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Paul Knaapen
- Departments of Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Ibrahim Danad
- Departments of Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
- Department of Cardiology, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands.
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Kovacs B, Ghannam M, Liang J, Moccoro E, Attili A, Cochet H, Helms A, Latchamsetty R, Jongnarangsin K, Morady F, Bogun F. Value of genotyping and scar-phenotyping for VT ablation procedures in patients with nonischemic left ventricular cardiomyopathies. J Cardiovasc Electrophysiol 2023; 34:1835-1842. [PMID: 37579221 DOI: 10.1111/jce.16039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 08/02/2023] [Accepted: 08/04/2023] [Indexed: 08/16/2023]
Abstract
INTRODUCTION Variants of cardiomyopathy genes in patients with nonischemic cardiomyopathy (NICM) generate various phenotypes of cardiac scar and delayed enhancement cardiac magnetic resonance (DE-CMR) imaging which may impact ventricular tachycardia (VT) management. METHODS The objective was to compare the findings of cardiomyopathy genetic testing on DE-CMR imaging and long-term outcomes among patients with NICM undergoing VT ablation procedures. Image phenotyping and genotyping were performed in a consecutive series of patients referred for VT ablation and correlated to survival free of VT. Scar depth index (SDI) (% of scar at 0-3 mm, 3-5 mm and >5 mm projected on the closest endocardial surface) was determined. RESULTS Forty-three patients were included (11 women, 55 ± 14 years, ejection fraction (EF) 45 ± 16%) and were followed for 3.4 ± 2.9 years. Pathogenic variants (PV) were identified in 16 patients (37%) in the following genes: LMNA (n = 5), TTN (n = 5), DSP (n = 2), AMLS1 (n = 1), MYBPC3 (n = 1), PLN (n = 1), and SCN5A (n = 1). A ring-like septal scar (RLSS) pattern was more often seen in patients with pathogenic variants (66% vs 15%, p = .001). RLSS was associated with deeper seated scars (SDI >5 mm 30.6 ± 22.6% vs 12.4 ± 16.2%, p = .005), and increased VT recurrence (HR 5.7 95% CI[1.8-18.4], p = .003). After adjustment for age, sex, EF, and total scar burden, the presence of a PV remained independently associated with worse outcomes (HR 4.7 95% CI[1.22-18.0], p = .02). CONCLUSIONS Preprocedural genotyping and scar phenotyping is beneficial to identify patients with a favorable procedural outcome. Some PVs are associated with an intramural, deeper seated scar phenotype and have an increase of VT recurrence after ablation.
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Affiliation(s)
- Boldizsar Kovacs
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Michael Ghannam
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Jackson Liang
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Emmeline Moccoro
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Anil Attili
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Hubert Cochet
- Department of Radiology, University of Bordeaux, Bordeaux, France
| | - Adam Helms
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Rakesh Latchamsetty
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Krit Jongnarangsin
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Fred Morady
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Frank Bogun
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, Michigan, USA
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Chen BH, An DA, Wu CW, Yue T, Bautista M, Ouchi E, Xu JR, Hu J, Zhou Y, Pu J, Wu LM. Prognostic significance of non-infarcted myocardium correlated with microvascular impairment evaluated dynamically by native T1 mapping. Insights Imaging 2023; 14:50. [PMID: 36941401 PMCID: PMC10027971 DOI: 10.1186/s13244-022-01360-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 12/19/2022] [Indexed: 03/22/2023] Open
Abstract
OBJECTIVES This study aimed to investigate the influence of microvascular impairment on myocardial characteristic alterations in remote myocardium at multiple time points, and its prognostic significance after acute ST-segment elevation myocardial infarction (STEMI). METHODS Patients were enrolled prospectively and performed CMR at baseline, 30 days, and 6 months. The primary endpoint was major adverse cardiac events (MACE): death, myocardial reinfarction, malignant arrhythmia, and hospitalization for heart failure. Cox proportional hazards regression modeling was analyzed to estimate the correlation between T1 mapping of remote myocardium and MACE in patients with and without microvascular obstruction (MVO). RESULTS A total of 135 patients (mean age 60.72 years; 12.70% female, median follow-up 510 days) were included, of whom 86 (63.70%) had MVO and 26 (19.26%) with MACE occurred in patients. Native T1 values of remote myocardium changed dynamically. At 1 week and 30 days, T1 values of remote myocardium in the group with MVO were higher than those without MVO (p = 0.030 and p = 0.001, respectively). In multivariable cox regression analysis of 135 patients, native1w T1 (HR 1.03, 95%CI 1.01-1.04, p = 0.002), native30D T1 (HR 1.05, 95%CI 1.03-1.07, p < 0.001) and LGE (HR 1.10, 95%CI 1.05-1.15, p < 0.001) were joint independent predictors of MACE. In multivariable cox regression analysis of 86 patients with MVO, native30D T1 (HR 1.05, 95%CI 1.04-1.07, p < 0.001) and LGE (HR 1.10, 95%CI 1.05-1.15, p < 0.001) were joint independent predictors of MACE. CONCLUSIONS The evolution of native T1 in remote myocardium was associated with the extent of microvascular impairment after reperfusion injury. In patients with MVO, native30D T1 and LGE were joint independent predictors of MACE.
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Affiliation(s)
- Bing-Hua Chen
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, No.160 PuJian Road, Shanghai, 200127, P. R. China
| | - Dong-Aolei An
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, No.160 PuJian Road, Shanghai, 200127, P. R. China
| | - Chong-Wen Wu
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, No.160 PuJian Road, Shanghai, 200127, P. R. China
| | - Ting Yue
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, No.160 PuJian Road, Shanghai, 200127, P. R. China
| | - Matthew Bautista
- Department of Radiology, Wayne State University, Detroit, MI, 48201, USA
| | - Erika Ouchi
- Department of Radiology, Wayne State University, Detroit, MI, 48201, USA
| | - Jian-Rong Xu
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, No.160 PuJian Road, Shanghai, 200127, P. R. China
| | - Jiani Hu
- Department of Radiology, Wayne State University, Detroit, MI, 48201, USA
| | - Yan Zhou
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, No.160 PuJian Road, Shanghai, 200127, P. R. China.
| | - Jun Pu
- Department of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, No.160 PuJian Road, Shanghai, 200127, P. R. China.
| | - Lian-Ming Wu
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, No.160 PuJian Road, Shanghai, 200127, P. R. China.
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16
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Wang S, Abdelaty AMSEK, Parke K, Arnold JR, McCann GP, Tyukin IY. MyI-Net: Fully Automatic Detection and Quantification of Myocardial Infarction from Cardiovascular MRI Images. ENTROPY (BASEL, SWITZERLAND) 2023; 25:431. [PMID: 36981320 PMCID: PMC10048138 DOI: 10.3390/e25030431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 02/17/2023] [Accepted: 02/22/2023] [Indexed: 06/18/2023]
Abstract
Myocardial infarction (MI) occurs when an artery supplying blood to the heart is abruptly occluded. The "gold standard" method for imaging MI is cardiovascular magnetic resonance imaging (MRI) with intravenously administered gadolinium-based contrast (with damaged areas apparent as late gadolinium enhancement [LGE]). However, no "gold standard" fully automated method for the quantification of MI exists. In this work, we propose an end-to-end fully automatic system (MyI-Net) for the detection and quantification of MI in MRI images. It has the potential to reduce uncertainty due to technical variability across labs and the inherent problems of data and labels. Our system consists of four processing stages designed to maintain the flow of information across scales. First, features from raw MRI images are generated using feature extractors built on ResNet and MoblieNet architectures. This is followed by atrous spatial pyramid pooling (ASPP) to produce spatial information at different scales to preserve more image context. High-level features from ASPP and initial low-level features are concatenated at the third stage and then passed to the fourth stage where spatial information is recovered via up-sampling to produce final image segmentation output into: (i) background, (ii) heart muscle, (iii) blood and (iv) LGE areas. Our experiments show that the model named MI-ResNet50-AC provides the best global accuracy (97.38%), mean accuracy (86.01%), weighted intersection over union (IoU) of 96.47%, and bfscore of 64.46% for the global segmentation. However, in detecting only LGE tissue, a smaller model, MI-ResNet18-AC, exhibited higher accuracy (74.41%) than MI-ResNet50-AC (64.29%). New models were compared with state-of-the-art models and manual quantification. Our models demonstrated favorable performance in global segmentation and LGE detection relative to the state-of-the-art, including a four-fold better performance in matching LGE pixels to contours produced by clinicians.
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Affiliation(s)
- Shuihua Wang
- Department of Cardiovascular Sciences, University of LeicesterGlenfield Hospital, Leicester LE3 9QP, UK
- The NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester LE3 9QP, UK
- School of Computing and Mathematical Sciences, University of Leicester, Leicester LE1 7RH, UK
| | - Ahmed M. S. E. K. Abdelaty
- Department of Cardiovascular Sciences, University of LeicesterGlenfield Hospital, Leicester LE3 9QP, UK
- The NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester LE3 9QP, UK
| | - Kelly Parke
- Department of Cardiovascular Sciences, University of LeicesterGlenfield Hospital, Leicester LE3 9QP, UK
- The NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester LE3 9QP, UK
| | - Jayanth Ranjit Arnold
- Department of Cardiovascular Sciences, University of LeicesterGlenfield Hospital, Leicester LE3 9QP, UK
- The NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester LE3 9QP, UK
| | - Gerry P. McCann
- Department of Cardiovascular Sciences, University of LeicesterGlenfield Hospital, Leicester LE3 9QP, UK
- The NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester LE3 9QP, UK
| | - Ivan Y. Tyukin
- Department of Mathematics, King’s College London, London WC2R 2LS, UK
- Department of Geoscience and Petroleum, Norwegian University of Science and Technology, 7491 Trondheim, Norway
- Department of Automation and Control Processes, Saint-Petersburg State Electrotechnical University, 197022 Saint-Petersburg, Russia
- Laboratory of Advanced Methods for High-Dimensional Data Analysis, Lobachevsky University, 603105 Nizhni Novgorod, Russia
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17
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Artificial Intelligence as a Diagnostic Tool in Non-Invasive Imaging in the Assessment of Coronary Artery Disease. Med Sci (Basel) 2023; 11:medsci11010020. [PMID: 36976528 PMCID: PMC10053913 DOI: 10.3390/medsci11010020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Revised: 02/20/2023] [Accepted: 02/22/2023] [Indexed: 03/02/2023] Open
Abstract
Coronary artery disease (CAD) remains a leading cause of mortality and morbidity worldwide, and it is associated with considerable economic burden. In an ageing, multimorbid population, it has become increasingly important to develop reliable, consistent, low-risk, non-invasive means of diagnosing CAD. The evolution of multiple cardiac modalities in this field has addressed this dilemma to a large extent, not only in providing information regarding anatomical disease, as is the case with coronary computed tomography angiography (CCTA), but also in contributing critical details about functional assessment, for instance, using stress cardiac magnetic resonance (S-CMR). The field of artificial intelligence (AI) is developing at an astounding pace, especially in healthcare. In healthcare, key milestones have been achieved using AI and machine learning (ML) in various clinical settings, from smartwatches detecting arrhythmias to retinal image analysis and skin cancer prediction. In recent times, we have seen an emerging interest in developing AI-based technology in the field of cardiovascular imaging, as it is felt that ML methods have potential to overcome some limitations of current risk models by applying computer algorithms to large databases with multidimensional variables, thus enabling the inclusion of complex relationships to predict outcomes. In this paper, we review the current literature on the various applications of AI in the assessment of CAD, with a focus on multimodality imaging, followed by a discussion on future perspectives and critical challenges that this field is likely to encounter as it continues to evolve in cardiology.
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18
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Doughan M, Chehab O, de Vasconcellos HD, Zeitoun R, Varadarajan V, Doughan B, Wu CO, Blaha MJ, Bluemke DA, Lima JAC. Periodontal Disease Associated With Interstitial Myocardial Fibrosis: The Multiethnic Study of Atherosclerosis. J Am Heart Assoc 2023; 12:e8146. [PMID: 36718872 PMCID: PMC9973639 DOI: 10.1161/jaha.122.027974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Background Periodontitis is a chronic inflammatory disease common among adults. It has been suggested that periodontal disease (PD) may be a contributing risk factor for cardiovascular disease; however, pathways underlying such a relationship require further investigation. Methods and Results A total of 665 men (mean age 68±9 years) and 611 women (mean age 67±9 years) enrolled in the MESA (Multiethnic Study of Atherosclerosis) underwent PD assessment using a 2-item questionnaire at baseline (2000-2002) and had cardiovascular magnetic resonance 10 years later. PD was defined when participants reported either a history of periodontitis or gum disease or lost teeth caused by periodontitis or gum disease. Multivariable linear regression models were constructed to assess the associations of baseline self-reported PD with cardiovascular magnetic resonance-obtained measures of interstitial myocardial fibrosis (IMF), including extracellular volume and native T1 time. Men with a self-reported history of PD had greater extracellular volume percent (ß=0.6%±0.2, P=0.01). This association was independent of age, left ventricular mass, traditional cardiovascular risk factors, and history of myocardial infarction. In a subsequent model, substituting myocardial infarction for coronary artery calcium score, the association of PD with IMF remained significant (ß=0.6%±0.3, P=0.03). In women, a self-reported history of PD was not linked to higher IMF. Importantly, a self-reported history of PD was not found to be associated with myocardial scar independent of sex (odds ratio, 1.01 [95% CI, 0.62-1.65]; P=0.9). Conclusions In a community-based setting, men but not women with a self-reported PD history at baseline were found to be associated with increased measures of IMF. These findings support a plausible link between PD, a proinflammatory condition, and subclinical IMF.
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Affiliation(s)
- Maria Doughan
- Division of Orthodontics, Department of DentistryUniversity of MarylandBaltimoreMD
| | - Omar Chehab
- Division of Cardiology, Department of MedicineJohns Hopkins UniversityBaltimoreMD
| | | | - Ralph Zeitoun
- Division of Cardiology, Department of MedicineJohns Hopkins UniversityBaltimoreMD
| | - Vinithra Varadarajan
- Division of Cardiology, Department of MedicineJohns Hopkins UniversityBaltimoreMD
| | - Bassel Doughan
- Faculty of Dental SurgeryCôte d’Azur UniversityNiceFrance
| | - Colin O. Wu
- Office of Biostatistics Research, National Heart, Lung, and Blood Institute, National Institutes of HealthBethesdaMD
| | - Michael J Blaha
- Division of Cardiology, Department of MedicineJohns Hopkins UniversityBaltimoreMD
| | - David A. Bluemke
- Department of RadiologyUniversity of Wisconsin School of Medicine and Public HeathMadisonWI
| | - Joao A. C. Lima
- Division of Cardiology, Department of MedicineJohns Hopkins UniversityBaltimoreMD
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19
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Demirkiran A, van der Geest RJ, Hopman LHGA, Robbers LFHJ, Handoko ML, Nijveldt R, Greenwood JP, Plein S, Garg P. Association of left ventricular flow energetics with remodeling after myocardial infarction: New hemodynamic insights for left ventricular remodeling. Int J Cardiol 2022; 367:105-114. [PMID: 36007668 DOI: 10.1016/j.ijcard.2022.08.040] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 08/08/2022] [Accepted: 08/18/2022] [Indexed: 12/13/2022]
Abstract
BACKGROUND Myocardial infarction leads to complex changes in left ventricular (LV) hemodynamics. It remains unknown how four-dimensional acute changes in LV-cavity blood flow kinetic energy affects LV-remodeling. METHODS AND RESULTS In total, 69 revascularised ST-segment elevation myocardial infarction (STEMI) patients were enrolled. All patients underwent cardiovascular magnetic resonance (CMR) examination within 2 days of the index event and at 3-month. CMR examination included cine, late gadolinium enhancement, and whole-heart four-dimensional flow acquisitions. LV volume-function, infarct size (indexed to body surface area), microvascular obstruction, mitral inflow, and blood flow KEi (kinetic energy indexed to end-diastolic volume) characteristics were obtained. Adverse LV-remodeling was defined and categorized according to increase in LV end-diastolic volume of at least 10%, 15%, and 20%. Twenty-four patients (35%) developed at least 10%, 17 patients (25%) at least 15%, 11 patients (16%) at least 20% LV-remodeling. Demographics and clinical history were comparable between patients with/without LV-remodeling. In univariable regression-analysis, A-wave KEi was associated with at least 10%, 15%, and 20% LV-remodeling (p = 0.03, p = 0.02, p = 0.02, respectively), whereas infarct size only with at least 10% LV-remodeling (p = 0.02). In multivariable regression-analysis, A-wave KEi was identified as an independent marker for at least 10%, 15%, and 20% LV-remodeling (p = 0.09, p < 0.01, p < 0.01, respectively), yet infarct size only for at least 10% LV-remodeling (p = 0.03). CONCLUSION In patients with STEMI, LV hemodynamic assessment by LV blood flow kinetic energetics demonstrates a significant inverse association with adverse LV-remodeling. Late-diastolic LV blood flow kinetic energetics early after acute MI was independently associated with adverse LV-remodeling.
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Affiliation(s)
- Ahmet Demirkiran
- Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
| | - Rob J van der Geest
- Department of Radiology, Division of Image Processing, Leiden University Medical Center, Leiden, the Netherlands
| | - Luuk H G A Hopman
- Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
| | - Lourens F H J Robbers
- Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
| | - M Louis Handoko
- Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
| | - Robin Nijveldt
- Department of Cardiology, Radboud University Medical Center, Nijmegen, the Netherlands
| | - John P Greenwood
- Multidisciplinary Cardiovascular Research Centre & Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - Sven Plein
- Multidisciplinary Cardiovascular Research Centre & Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - Pankaj Garg
- Department of Cardiology, Norfolk Medical School, University of East Anglia, Norwich, United Kingdom.
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20
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Heiberg E, Engblom H, Carlsson M, Erlinge D, Atar D, Aletras AH, Arheden H. Infarct quantification with cardiovascular magnetic resonance using "standard deviation from remote" is unreliable: validation in multi-centre multi-vendor data. J Cardiovasc Magn Reson 2022; 24:53. [PMID: 36336693 PMCID: PMC9639305 DOI: 10.1186/s12968-022-00888-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2022] [Accepted: 09/08/2022] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND The objective of the study was to investigate variability and agreement of the commonly used image processing method "n-SD from remote" and in particular for quantifying myocardial infarction by late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR). LGE-CMR in tandem with the analysis method "n-SD from remote" represents the current reference standard for infarct quantification. This analytic method utilizes regions of interest (ROIs) and defines infarct as the tissue with a set number of standard deviations (SD) above the signal intensity of remote nulled myocardium. There is no consensus on what the set number of SD is supposed to be. Little is known about how size and location of ROIs and underlying signal properties in the LGE images affect results. Furthermore, the method is frequently used elsewhere in medical imaging often without careful validation. Therefore, the usage of the "n-SD" method warrants a thorough validation. METHODS Data from 214 patients from two multi-center cardioprotection trials were included. Infarct size from different remote ROI positions, ROI size, and number of standard deviations ("n-SD") were compared with reference core lab delineations. RESULTS Variability in infarct size caused by varying ROI position, ROI size, and "n-SD" was 47%, 48%, and 40%, respectively. The agreement between the "n-SD from remote" method and the reference infarct size by core lab delineations was low. Optimal "n-SD" threshold computed on a slice-by-slice basis showed high variability, n = 5.3 ± 2.2. CONCLUSION The "n-SD from remote" method is unreliable for infarct quantification due to high variability which depends on different placement and size of remote ROI, number "n-SD", and image signal properties related to the CMR-scanner and sequence used. Therefore, the "n-SD from remote" method should not be used, instead methods validated against an independent standard are recommended.
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Affiliation(s)
- Einar Heiberg
- Department of Clinical Sciences Lund, Clinical Physiology, Skåne University Hospital, Lund University, 222 42, Lund, SE, Sweden.
- Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden.
| | - Henrik Engblom
- Department of Clinical Sciences Lund, Clinical Physiology, Skåne University Hospital, Lund University, 222 42, Lund, SE, Sweden
| | - Marcus Carlsson
- Department of Clinical Sciences Lund, Clinical Physiology, Skåne University Hospital, Lund University, 222 42, Lund, SE, Sweden
- Laboratory of Clinical Physiology, National Heart, Lung, and Blood Institute, NIH, Bethesda, USA
| | - David Erlinge
- Department of Cardiology, Skåne University Hospital, Lund University Hospital, Lund University, Lund, Sweden
| | - Dan Atar
- Department of Cardiology, Oslo University Hospital Ullevål, University of Oslo, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Anthony H Aletras
- Department of Clinical Sciences Lund, Clinical Physiology, Skåne University Hospital, Lund University, 222 42, Lund, SE, Sweden
- Laboratory of Computing, Medical Informatics and Biomedical-Imaging Technologies, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Håkan Arheden
- Department of Clinical Sciences Lund, Clinical Physiology, Skåne University Hospital, Lund University, 222 42, Lund, SE, Sweden
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21
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Influence of the cardio-ankle vascular index on chronic-phase left ventricular dysfunction after ST-segment elevation myocardial infarction. J Hypertens 2022; 40:1478-1486. [PMID: 35881449 DOI: 10.1097/hjh.0000000000003165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/16/2022]
Abstract
OBJECTIVE This study aimed to investigate the possible influence of arterial stiffness assessed by the cardio-ankle vascular index (CAVI) on chronic-phase left ventricular dysfunction in patients with ST-segment elevation myocardial infarction (STEMI). METHODS A total of 208 consecutive patients with first STEMI (age, 64 ± 11 years; 86% men) who underwent reperfusion therapy within 12 h of onset were enrolled. We analysed arterial stiffness by measuring CAVI in a stable phase after admission and performed two-dimensional echocardiography at baseline and 7 months' follow-up. Subsequently, we assessed left ventricular global longitudinal strain (LV-GLS) to evaluate left ventricular function. A total of 158 (75.9%) patients underwent baseline cardiac magnetic resonance (CMR). We estimated left ventricular infarct size by measuring peak levels of creatine kinase-myocardial band (CK-MB), and CMR-late gadolinium enhancement (LGE). RESULTS On the basis of the median CAVI value, the patients were allocated into high CAVI (CAVI ≥ 8.575) and low CAVI (CAVI < 8.575) groups. The groups showed no statistically significant differences in LV-GLS at baseline (-13.5% ± 3.1 vs. -13.9% ± 2.7%, P = 0.324). However, LV-GLS was significantly worse in the high CAVI group than in the low-CAVI group at 7 months (-14.0% ± 2.9 vs. -15.6% ± 3.0%, P < 0.001). Stratified by CAVI and peak CK-MB or LGE, the four groups showed significant differences in LV-GLS at 7 months after STEMI (both P < 0.001). Multivariate linear regression analysis with the forced inclusion model showed that CAVI was an independent predictor of LV-GLS at 7 months ( P = 0.015). CONCLUSION CAVI early after STEMI onset was significantly associated with chronic-phase LV-GLS. In addition, combining CAVI with CK-MB or LGE improves its predictive ability for evaluation of chronic-phase LV-GLS. Thus, the arterial stiffness assessment by CAVI was an important factor related to chronic-phase left ventricular dysfunction after the first STEMI.
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22
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Zhuang X, Xu J, Luo X, Chen C, Ouyang C, Rueckert D, Campello VM, Lekadir K, Vesal S, RaviKumar N, Liu Y, Luo G, Chen J, Li H, Ly B, Sermesant M, Roth H, Zhu W, Wang J, Ding X, Wang X, Yang S, Li L. Cardiac segmentation on late gadolinium enhancement MRI: A benchmark study from multi-sequence cardiac MR segmentation challenge. Med Image Anal 2022; 81:102528. [PMID: 35834896 DOI: 10.1016/j.media.2022.102528] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Revised: 09/06/2021] [Accepted: 07/01/2022] [Indexed: 11/28/2022]
Abstract
Accurate computing, analysis and modeling of the ventricles and myocardium from medical images are important, especially in the diagnosis and treatment management for patients suffering from myocardial infarction (MI). Late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) provides an important protocol to visualize MI. However, compared with the other sequences LGE CMR images with gold standard labels are particularly limited. This paper presents the selective results from the Multi-Sequence Cardiac MR (MS-CMR) Segmentation challenge, in conjunction with MICCAI 2019. The challenge offered a data set of paired MS-CMR images, including auxiliary CMR sequences as well as LGE CMR, from 45 patients who underwent cardiomyopathy. It was aimed to develop new algorithms, as well as benchmark existing ones for LGE CMR segmentation focusing on myocardial wall of the left ventricle and blood cavity of the two ventricles. In addition, the paired MS-CMR images could enable algorithms to combine the complementary information from the other sequences for the ventricle segmentation of LGE CMR. Nine representative works were selected for evaluation and comparisons, among which three methods are unsupervised domain adaptation (UDA) methods and the other six are supervised. The results showed that the average performance of the nine methods was comparable to the inter-observer variations. Particularly, the top-ranking algorithms from both the supervised and UDA methods could generate reliable and robust segmentation results. The success of these methods was mainly attributed to the inclusion of the auxiliary sequences from the MS-CMR images, which provide important label information for the training of deep neural networks. The challenge continues as an ongoing resource, and the gold standard segmentation as well as the MS-CMR images of both the training and test data are available upon registration via its homepage (www.sdspeople.fudan.edu.cn/zhuangxiahai/0/mscmrseg/).
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Affiliation(s)
- Xiahai Zhuang
- School of Data Science, Fudan University, Shanghai, China. https://www.sdspeople.fudan.edu.cn/zhuangxiahai/?
| | - Jiahang Xu
- School of Data Science, Fudan University, Shanghai, China.
| | - Xinzhe Luo
- School of Data Science, Fudan University, Shanghai, China
| | - Chen Chen
- Biomedical Image Analysis Group, Imperial College London, London, UK
| | - Cheng Ouyang
- Biomedical Image Analysis Group, Imperial College London, London, UK
| | - Daniel Rueckert
- Biomedical Image Analysis Group, Imperial College London, London, UK
| | - Victor M Campello
- Department Mathematics & Computer Science, Universitat de Barcelona, Barcelona, Spain
| | - Karim Lekadir
- Department Mathematics & Computer Science, Universitat de Barcelona, Barcelona, Spain
| | - Sulaiman Vesal
- Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
| | | | - Yashu Liu
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Gongning Luo
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Jingkun Chen
- Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Hongwei Li
- Department of Informatics, Technical University of Munich, Germany
| | - Buntheng Ly
- INRIA, Université Côte d'Azur, Sophia Antipolis, France
| | | | | | | | - Jiexiang Wang
- School of Informatics, Xiamen University, Xiamen, China
| | - Xinghao Ding
- School of Informatics, Xiamen University, Xiamen, China
| | - Xinyue Wang
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Sen Yang
- College of Electrical Engineering, Sichuan University, Chengdu, China; Tencent AI Lab, Shenzhen, China
| | - Lei Li
- School of Data Science, Fudan University, Shanghai, China; School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
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23
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Myocardial fibrosis and ventricular ectopy in patients with non-ischemic systolic heart failure: results from the DANISH trial. Int J Cardiovasc Imaging 2022; 38:2437-2445. [DOI: 10.1007/s10554-022-02653-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 05/19/2022] [Indexed: 11/05/2022]
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24
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Nies HMJM, Gommers S, Bijvoet GP, Heckman LIB, Prinzen FW, Vogel G, Van De Heyning CM, Chiribiri A, Wildberger JE, Mihl C, Holtackers RJ. Histopathological validation of semi-automated myocardial scar quantification techniques for dark-blood late gadolinium enhancement magnetic resonance imaging. Eur Heart J Cardiovasc Imaging 2022; 24:364-372. [PMID: 35723673 PMCID: PMC9936958 DOI: 10.1093/ehjci/jeac107] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 05/06/2022] [Accepted: 05/10/2022] [Indexed: 11/13/2022] Open
Abstract
AIMS To evaluate the performance of various semi-automated techniques for quantification of myocardial infarct size on both conventional bright-blood and novel dark-blood late gadolinium enhancement (LGE) images using histopathology as reference standard. METHODS AND RESULTS In 13 Yorkshire pigs, reperfused myocardial infarction was experimentally induced. At 7 weeks post-infarction, both bright-blood and dark-blood LGE imaging were performed on a 1.5 T magnetic resonance scanner. Following magnetic resonance imaging (MRI), the animals were sacrificed, and histopathology was obtained. The percentage of infarcted myocardium was assessed per slice using various semi-automated scar quantification techniques, including the signal threshold vs. reference mean (STRM, using 3 to 8 SDs as threshold) and full-width at half-maximum (FWHM) methods, as well as manual contouring, for both LGE methods. Infarct size obtained by histopathology was used as reference. In total, 24 paired LGE MRI slices and histopathology samples were available for analysis. For both bright-blood and dark-blood LGE, the STRM method with a threshold of 5 SDs led to the best agreement to histopathology without significant bias (-0.23%, 95% CI [-2.99, 2.52%], P = 0.862 and -0.20%, 95% CI [-2.12, 1.72%], P = 0.831, respectively). Manual contouring significantly underestimated infarct size on bright-blood LGE (-1.57%, 95% CI [-2.96, -0.18%], P = 0.029), while manual contouring on dark-blood LGE outperformed semi-automated quantification and demonstrated the most accurate quantification in this study (-0.03%, 95% CI [-0.22, 0.16%], P = 0.760). CONCLUSION The signal threshold vs. reference mean method with a threshold of 5 SDs demonstrated the most accurate semi-automated quantification of infarcted myocardium, without significant bias compared to histopathology, for both conventional bright-blood and novel dark-blood LGE.
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Affiliation(s)
| | - Suzanne Gommers
- Department of Radiology & Nuclear Medicine, Maastricht University Medical Centre, PO Box 5800, AZ 6202, Maastricht, The Netherlands
| | - Geertruida P Bijvoet
- Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, The Netherlands,Department of Cardiology, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Luuk I B Heckman
- Department of Physiology, Maastricht University, Maastricht, The Netherlands
| | - Frits W Prinzen
- Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, The Netherlands,Department of Physiology, Maastricht University, Maastricht, The Netherlands
| | - Gaston Vogel
- Pie Medical Imaging, Maastricht, The Netherlands
| | - Caroline M Van De Heyning
- Department of Cardiology, Antwerp University Hospital and GENCOR, University of Antwerp, Antwerp, Belgium
| | - Amedeo Chiribiri
- School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
| | - Joachim E Wildberger
- Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, The Netherlands,Department of Radiology & Nuclear Medicine, Maastricht University Medical Centre, PO Box 5800, AZ 6202, Maastricht, The Netherlands
| | - Casper Mihl
- Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, The Netherlands,Department of Radiology & Nuclear Medicine, Maastricht University Medical Centre, PO Box 5800, AZ 6202, Maastricht, The Netherlands
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25
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Demirkiran A, van der Hoeven NW, Janssens GN, Lemkes JS, Everaars H, van de Ven PM, van Pouderoijen N, van Cauteren YJM, van Leeuwen MAH, Nap A, Teunissen PF, Hopman LHGA, Bekkers SCAM, Smulders MW, van Royen N, van Rossum AC, Robbers LFHJ, Nijveldt R. Left ventricular function, strain, and infarct characteristics in patients with transient ST-segment elevation myocardial infarction compared to ST-segment and non-ST-segment elevation myocardial infarctions. Eur Heart J Cardiovasc Imaging 2022; 23:836-845. [PMID: 34195800 PMCID: PMC9159742 DOI: 10.1093/ehjci/jeab114] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Accepted: 05/19/2021] [Indexed: 11/30/2022] Open
Abstract
AIMS This study aims to explore cardiovascular magnetic resonance (CMR)-derived left ventricular (LV) function, strain, and infarct size characteristics in patients with transient ST-segment elevation myocardial infarction (TSTEMI) compared to patients with ST-segment and non-ST-segment elevation myocardial infarctions (STEMI and NSTEMI, respectively). METHODS AND RESULTS In total, 407 patients were enrolled in this multicentre observational prospective cohort study. All patients underwent CMR examination 2-8 days after the index event. CMR cine imaging was performed for functional assessment and late gadolinium enhancement to determine infarct size and identify microvascular obstruction (MVO). TSTEMI patients demonstrated the highest LV ejection fraction and the most preserved global LV strain (longitudinal, circumferential, and radial) across the three groups (overall P ≤ 0.001). The CMR-defined infarction was less frequently observed in TSTEMI than in STEMI patients [77 (65%) vs. 124 (98%), P < 0.001] but was comparable with NSTEMI patients [77 (65%) vs. 66 (70%), P = 0.44]. A remarkably smaller infarct size was seen in TSTEMI compared to STEMI patients [1.4 g (0.0-3.9) vs. 13.5 g (5.3-26.8), P < 0.001], whereas infarct size was not significantly different from that in NSTEMI patients [1.4 g (0.0-3.9) vs. 2.1 g (0.0-8.6), P = 0.06]. Whilst the presence of MVO was less frequent in TSTEMI compared to STEMI patients [5 (4%) vs. 53 (31%), P < 0.001], no significant difference was seen compared to NSTEMI patients [5 (4%) vs. 5 (5%), P = 0.72]. CONCLUSION TSTEMI yielded favourable cardiac LV function, strain, and infarct-related scar mass compared to STEMI and NSTEMI. LV function and infarct characteristics of TSTEMI tend to be more similar to NSTEMI than STEMI.
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Affiliation(s)
- Ahmet Demirkiran
- Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Cardiovascular Sciences, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
| | - Nina W van der Hoeven
- Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Cardiovascular Sciences, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
| | - Gladys N Janssens
- Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Cardiovascular Sciences, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
| | - Jorrit S Lemkes
- Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Cardiovascular Sciences, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
| | - Henk Everaars
- Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Cardiovascular Sciences, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
| | - Peter M van de Ven
- Department of Epidemiology and Data Science, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Nikki van Pouderoijen
- Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Cardiovascular Sciences, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
| | | | | | - Alexander Nap
- Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Cardiovascular Sciences, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
| | - Paul F Teunissen
- Department of Cardiology, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands
| | - Luuk H G A Hopman
- Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Cardiovascular Sciences, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
| | | | - Martijn W Smulders
- Department of Cardiology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Niels van Royen
- Department of Cardiology, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands
| | - Albert C van Rossum
- Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Cardiovascular Sciences, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
| | - Lourens F H J Robbers
- Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Cardiovascular Sciences, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
| | - Robin Nijveldt
- Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Cardiovascular Sciences, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
- Department of Cardiology, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands
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26
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Polacin M, Karolyi M, Blüthgen C, Pilz N, Eberhard M, Alkadhi H, Kozerke S, Manka R. Simplified image acquisition and detection of ischemic and non-ischemic myocardial fibrosis with fixed short inversion time magnetic resonance late gadolinium enhancement. Br J Radiol 2022; 95:20210966. [PMID: 35195448 PMCID: PMC10993981 DOI: 10.1259/bjr.20210966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Revised: 01/24/2022] [Accepted: 01/25/2022] [Indexed: 11/05/2022] Open
Abstract
OBJECTIVES Late gadolinium enhancement with fixed short inversion time (LGEshort) provides excellent tissue contrast with dark scar and bright blood pool and does not need prior myocardial nulling. We hypothesize better visibility of ischemic scars and equal visibility of non-ischemic LGE in LGEshort compared to clinically established LGE (LGEstandard). METHODS LGEshort and LGEstandard were retrospectively evaluated in 179 patients (3043 segments) with suspected or known coronary artery disease by four blinded readers (reader A: most experienced - D: least experienced). The amount of ischemic and non-ischemic LGE as well as visibility (4: very good - 1: poor) of ischemic LGE was visually assessed. RESULTS All readers detected more infarcted segments in LGEshort compared to LGEstandard (378 segments reported as infarcted; A:p = 0.5, B:p = 0.8, C,D:p = 0.03). Scar visibility was scored higher in LGEshort by all readers (A,B:p = 0.03; C,D:p = 0.02), especially for subendocardial infarcts (A,B:p = 0.04, C,D:p = 0.02). Less experienced readers detected significantly more infarcted papillary muscles (C:p = 0.02, D:p = 0.03) in a shorter reading time in LGEshort (C:p = 0.04, D:p = 0.02). Non-ischemic LGE was equally visible in both sequences (A:p = 0.9, B:p = 0.8, C,D:p = 0.6). CONCLUSIONS LGEshort detects more ischemic LGE with improved scar visibility compared to LGEstandard, independent of experience level. The visibility of non-ischemic LGE is equivalent to LGEstandard. Less experienced readers can diagnose ischemic and non-ischemic LGE faster in LGEshort. ADVANCES IN KNOWLEDGE LGEshort with its maximal operational simplicity can be used for visualization of all types of fibrosis - ischemic and non-ischemic - instead of LGEstandard, independent of experience level.
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Affiliation(s)
- Malgorzata Polacin
- Institute of Diagnostic and Interventional Radiology,
University Hospital Zurich, University of Zurich,
Zurich, Switzerland
- Institute for Biomedical Engineering, University and ETH
Zurich, Zurich,
Switzerland
| | - Mihaly Karolyi
- Institute of Diagnostic and Interventional Radiology,
University Hospital Zurich, University of Zurich,
Zurich, Switzerland
| | - Christian Blüthgen
- Institute of Diagnostic and Interventional Radiology,
University Hospital Zurich, University of Zurich,
Zurich, Switzerland
| | - Nik Pilz
- Institute of Diagnostic and Interventional Radiology,
University Hospital Zurich, University of Zurich,
Zurich, Switzerland
| | - Matthias Eberhard
- Institute of Diagnostic and Interventional Radiology,
University Hospital Zurich, University of Zurich,
Zurich, Switzerland
| | - Hatem Alkadhi
- Institute of Diagnostic and Interventional Radiology,
University Hospital Zurich, University of Zurich,
Zurich, Switzerland
| | - Sebastian Kozerke
- Institute for Biomedical Engineering, University and ETH
Zurich, Zurich,
Switzerland
| | - Robert Manka
- Institute of Diagnostic and Interventional Radiology,
University Hospital Zurich, University of Zurich,
Zurich, Switzerland
- Institute for Biomedical Engineering, University and ETH
Zurich, Zurich,
Switzerland
- Department of Cardiology, University Heart Center, University
Hospital Zurich, University of Zurich,
Zurich, Switzerland
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27
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Ostovaneh MR, Ward C, Ambale-Venkatesh B, Chamera E, Kato Y, Bolli R, Mitrani R, Perin EC, Henry TD, Hare JM, Moyé L, Nazarian S, Lima JAC. Reproducibility of CMR in Patients With Cardiac Implantable Electrical Devices: Multicenter CONCERT-HF Trial. JACC Cardiovasc Imaging 2022; 15:952-954. [PMID: 35033497 DOI: 10.1016/j.jcmg.2021.11.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Revised: 11/23/2021] [Accepted: 11/30/2021] [Indexed: 11/29/2022]
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Kolentinis M, Carerj LM, Vidalakis E, Giokoglu E, Martin S, Arendt C, Vogl TJ, Nagel E, Puntmann VO. Determination of scar area using native and post-contrast T1 mapping: Agreement with late gadolinium enhancement. Eur J Radiol 2022; 150:110242. [PMID: 35290909 DOI: 10.1016/j.ejrad.2022.110242] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 02/28/2022] [Accepted: 03/05/2022] [Indexed: 11/15/2022]
Abstract
The purpose of this study is to ascertain agreement in measurements of the scar area between late gadolinium enhancement (LGE), native and post-contrast T1 mapping in patients with known ischemic heart disease. 132 patients (age 60 ± 11 yrs, male 82%) were included in the study. Corresponding 3 short axis slices images of LGE, native and post contrast T1 mapping were used. Scar area was evaluated semi- quantitatively with FWHM methods, in which scar is automatically determined by specialized post-processing software. Agreement per culprit vessel was also assessed. Concordance and inter- intraobserver reproducibility were assessed with Bland-Altman analysis. The results show that scar area amounted to 12.6% of myocardium for LGE, 9.1% for native (p < 0.05) and 19.4% (p < 0.05) for post-contrast T1 mapping. LAD and RCA territory infarcts showed statistical discrepancy for both T1 acquisitions. Intraobserver differences in infarct size were comparable at 0.39% ± 0.28, 2.93% ± 0.03 and 0.97% ± 0.01 respectively (p≫0.05). Interobserver differences were 5.56% ± 0.91 for LGE, 11.87% ± 3.21 (p < 0.05) for native and 5.55% ± 2.87 (p≫0.05) for post-contrast T1 mapping. In conclusion, native T1 acquisitions systematically underestimated infarct size in comparison to LGE, while post-contrast T1 overestimated it. Variances in measurements were most pronounced for LAD and RCA territory infarcts. Intraobserver reproducibility was similar with both methods, whereas interobserver variability for native T1 mapping acquisition was worse.
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Affiliation(s)
- Michael Kolentinis
- Institute of Experimental and Translational Cardiovascular Imaging, DZHK (German Centre for Cardiovascular Research) Centre for Cardiovascular Imaging, partner site Rhein-Main, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany.
| | - Ludovica M Carerj
- Institute of Experimental and Translational Cardiovascular Imaging, DZHK (German Centre for Cardiovascular Research) Centre for Cardiovascular Imaging, partner site Rhein-Main, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany; Department of Biomedical Sciences and Morphological and Functional Imaging, University of Messina, Piazza Pugliatti 1, 98122, Messina, Italy
| | - Eleftherios Vidalakis
- Institute of Experimental and Translational Cardiovascular Imaging, DZHK (German Centre for Cardiovascular Research) Centre for Cardiovascular Imaging, partner site Rhein-Main, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany
| | - Eleni Giokoglu
- Institute of Experimental and Translational Cardiovascular Imaging, DZHK (German Centre for Cardiovascular Research) Centre for Cardiovascular Imaging, partner site Rhein-Main, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany; Department of Cardiology, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany
| | - Simon Martin
- Institute of Experimental and Translational Cardiovascular Imaging, DZHK (German Centre for Cardiovascular Research) Centre for Cardiovascular Imaging, partner site Rhein-Main, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany; Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany
| | - Christophe Arendt
- Institute of Experimental and Translational Cardiovascular Imaging, DZHK (German Centre for Cardiovascular Research) Centre for Cardiovascular Imaging, partner site Rhein-Main, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany; Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany
| | - Thomas J Vogl
- Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany
| | - Eike Nagel
- Institute of Experimental and Translational Cardiovascular Imaging, DZHK (German Centre for Cardiovascular Research) Centre for Cardiovascular Imaging, partner site Rhein-Main, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany
| | - Valentina O Puntmann
- Institute of Experimental and Translational Cardiovascular Imaging, DZHK (German Centre for Cardiovascular Research) Centre for Cardiovascular Imaging, partner site Rhein-Main, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany
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Demirkiran A, Hassell MECJ, Garg P, Elbaz MSM, Delewi R, Greenwood JP, Piek JJ, Plein S, van der Geest RJ, Nijveldt R. Left ventricular four-dimensional blood flow distribution, energetics, and vorticity in chronic myocardial infarction patients with/without left ventricular thrombus. Eur J Radiol 2022; 150:110233. [PMID: 35278980 DOI: 10.1016/j.ejrad.2022.110233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Revised: 02/23/2022] [Accepted: 02/26/2022] [Indexed: 11/17/2022]
Abstract
BACKGROUND Left ventricular thrombus (LVT) formation is a frequent and serious complication of myocardial infarction (MI). How global LV flow characteristics are related to this phenomenon is yet uncertain. In this study, we investigated LV flow differences using 4D flow cardiovascular magnetic resonance (CMR) between chronic MI patients with LVT [MI-LVT(+)] and without LVT [MI-LVT(-)], and healthy controls. METHODS In this prospective cohort study, the 4D flow CMR data were acquired in 19 chronic MI patients (MI-LVT(+), n = 9 and MI-LVT(-), n = 10) and 9 age-matched controls. All included subjects were in sinus rhythm. The following LV flow parameters were obtained: LV flow components (direct, retained, delayed, residual), mean and peak kinetic energy (KE) values (indexed to instantaneous LV volume), mean and peak vorticity values, and diastolic vortex ring properties (position, orientation, shape). RESULTS The MI patients demonstrated a significantly larger amount of delayed and residual flow, and a smaller amount of direct flow compared to controls (p = 0.02, p = 0.03, and p < 0.001, respectively). The MI-LVT(+) patients demonstrated numerically increased residual flow and reduced retained and direct flow in comparison to MI-LVT(-) patients. Systolic mean and peak LV blood flow KE values were significantly lower in MI patients compared to controls (p = 0.04, p = 0.03, respectively). Overall, the mean and peak LV vorticity values were significantly lower in MI patients compared to controls. The mean and peak systolic vorticity at the basal level were significantly higher in MI-LVT(+) than in MI-LVT(-) patients (p < 0.01, for both). The vortex ring core during E-wave in MI-LVT(+) group was located in a less tilted orientation to the LV compared to MI-LVT(-) group (p < 0.01). CONCLUSIONS Chronic MI patients with LVT express a different distribution of LV flow components, irregular vorticity vector fields, and altered diastolic vortex ring geometric properties as assessed by 4D flow CMR. Larger prospective studies are warranted to further evaluate the significance of these initial observations.
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Affiliation(s)
- Ahmet Demirkiran
- Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
| | | | - Pankaj Garg
- Multidisciplinary Cardiovascular Research Centre & Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - Mohammed S M Elbaz
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA; Department of Radiology, Division of Image Processing, Leiden University Medical Center, Leiden, the Netherlands
| | - Ronak Delewi
- Department of Cardiology, Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, the Netherlands
| | - John P Greenwood
- Multidisciplinary Cardiovascular Research Centre & Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - Jan J Piek
- Department of Cardiology, Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, the Netherlands
| | - Sven Plein
- Multidisciplinary Cardiovascular Research Centre & Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - Rob J van der Geest
- Department of Radiology, Division of Image Processing, Leiden University Medical Center, Leiden, the Netherlands
| | - Robin Nijveldt
- Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands; Department of Cardiology, Radboud University Medical Center, Nijmegen, the Netherlands.
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Mont L, Roca-Luque I, Althoff TF. Ablation Lesion Assessment with MRI. Arrhythm Electrophysiol Rev 2022; 11:e02. [PMID: 35444808 PMCID: PMC9014705 DOI: 10.15420/aer.2021.63] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Accepted: 12/11/2021] [Indexed: 12/17/2022] Open
Abstract
Late gadolinium enhancement (LGE) MRI is capable of detecting not only native cardiac fibrosis, but also ablation-induced scarring. Thus, it offers the unique opportunity to assess ablation lesions non-invasively. In the atrium, LGE-MRI has been shown to accurately detect and localise gaps in ablation lines. With a negative predictive value close to 100% it can reliably rule out pulmonary vein reconnection non-invasively and thus may avoid unnecessary invasive repeat procedures where a pulmonary vein isolation only approach is pursued. Even LGE-MRI-guided repeat pulmonary vein isolation has been demonstrated to be feasible as a standalone approach. LGE-MRI-based lesion assessment may also be of value to evaluate the efficacy of ventricular ablation. In this respect, the elimination of LGE-MRI-detected arrhythmogenic substrate may serve as a potential endpoint, but validation in clinical studies is lacking. Despite holding great promise, the widespread use of LGE-MRI is still limited by the absence of standardised protocols for image acquisition and post-processing. In particular, reproducibility across different centres is impeded by inconsistent thresholds and internal references to define fibrosis. Thus, uniform methodological and analytical standards are warranted to foster a broader implementation in clinical practice.
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Affiliation(s)
- Lluís Mont
- Arrhythmia Section, Cardiovascular Institute, Clínic – University Hospital Barcelona Barcelona, Catalonia, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain
- Centro de Investigación Biomédica en Red Cardiovascular (CIBERCV), Madrid, Spain
| | - Ivo Roca-Luque
- Arrhythmia Section, Cardiovascular Institute, Clínic – University Hospital Barcelona Barcelona, Catalonia, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain
- Centro de Investigación Biomédica en Red Cardiovascular (CIBERCV), Madrid, Spain
| | - Till F Althoff
- Arrhythmia Section, Cardiovascular Institute, Clínic – University Hospital Barcelona Barcelona, Catalonia, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain
- Department of Cardiology and Angiology, Charité University Medicine Berlin, Berlin, Germany
- German Centre for Cardiovascular Research (DZHK), Berlin, Germany
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Shah DV, Kalekar DT, Gupta DA, Lamghare DP. Role of Late Gadolinium Enhancement in the Assessment of Myocardial Viability. Cureus 2022; 14:e22844. [PMID: 35382188 PMCID: PMC8977074 DOI: 10.7759/cureus.22844] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/04/2022] [Indexed: 11/29/2022] Open
Abstract
Background: Prior to any revascularization procedure for coronary artery disease, it is essential to identify viable myocardium which will likely benefit from it. In such a situation, delayed enhanced cardiac MRI is beneficial. Methods: Our study consisted of 50 patients with at least a one-month prior history of myocardial infarction (MI), abnormal findings on electrocardiography (ECG), and 2D-echocardiography (2D-ECHO), who were subjected to cardiac MRI performed on a 3T MRI machine. The MRI scans were evaluated for anatomical and especially functional characteristics of the heart, such as wall motion. On late gadolinium enhancement (LGE), the diseased segments were classified into two categories: < 50% LGE (viable) and > 50% LGE (non-viable). Results: Of the 378 diseased segments detected on LGE, 137 (36.2%) segments showed < 50% LGE and 241 (63.8%) segments showed > 50% LGE. The segments showing < 50% LGE showed normokinesia or hypokinesia, with none of the segments showing akinesia or dyskinesia, whereas the segments showing > 50% LGE showed akinesia or dyskinesia predominantly. This was found to be statistically highly significant (p-value < 0.001). Conclusion: Delayed enhanced-cardiac magnetic resonance (DE-CMR) imaging in patients with ischemic heart disease (IHD) helps evaluate the severity of the infarcted myocardium by classifying the diseased myocardium into viable and non-viable, as viable myocardium is more likely to regain functional recovery than non-viable myocardium. It also predicts the functional recovery of the myocardium after revascularization therapy.
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Ramirez FD, Winterfield JR, Shi X, Chou D, Robinson D, Angel N, Shah P, Sorrell T, Ghafoori E, Vanderper A, Mariappan L, Soré B, Peyrat JM, Loyer V, Nakatani Y, Cochet H, Jaïs P. Non-contact whole-chamber charge density mapping of the left ventricle: preclinical evaluation in a sheep model. Heart Rhythm 2022; 19:828-836. [PMID: 35032670 DOI: 10.1016/j.hrthm.2022.01.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 01/06/2022] [Accepted: 01/07/2022] [Indexed: 11/19/2022]
Abstract
BACKGROUND Conventional contact-based electroanatomic mapping is poorly suited for rapid or dynamic ventricular arrhythmias. Whole-chamber charge density (CD) mapping could efficiently characterize complex ventricular tachyarrhythmias and yield insights into their underlying mechanisms. OBJECTIVE This study sought to evaluate the feasibility and accuracy of non-contact whole-chamber left ventricular (LV) CD mapping, and to characterize CD activation patterns during sinus rhythm, ventricular pacing, and ventricular fibrillation (VF). METHODS Ischemic scar as defined by CD amplitude thresholds was compared to late gadolinium enhancement criteria on magnetic resonance imaging using an iterative closest point algorithm. Electrograms recorded at sites of tissue contact were compared to the nearest non-contact CD-derived electrograms to calculate signal morphology cross-correlations and time differences. Regions of consistently slow conduction were examined relative to areas of scar and to localized irregular activation (LIA) during VF. RESULTS Areas under receiver operating characteristic curves (AUCs) of CD-defined dense and total LV scar were 0.92 ± 0.03 and 0.87 ± 0.06, with accuracies of 0.86±0.03 and 0.80±0.05, respectively. Morphology cross-correlation between 8,677 contact and corresponding non-contact electrograms was 0.93±0.10, with a mean time difference of 2.5±5.6 msec. Areas of consistently slow conduction tended to occur at scar borders and exhibited spatial agreement with LIA during VF (AUC 0.90±0.02). CONCLUSION Non-contact LV CD mapping can accurately delineate ischemic scar. CD-derived ventricular electrograms correlate strongly with conventional contact-based electrograms. Regions with consistently slow conduction are often at scar borders and tend to harbor LIA during VF.
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Affiliation(s)
- F Daniel Ramirez
- Electrophysiology and Heart Modelling Institute (LIRYC), Bordeaux-Pessac, France; Department of Electrophysiology and Cardiac Stimulation, Centre Hospitalier Universitaire de Bordeaux, Bordeaux-Pessac, France; Division of Cardiology, University of Ottawa Heart Institute, Ottawa, Ontario Canada
| | - Jeffrey R Winterfield
- Division of Cardiology, Medical University of South Carolina, Charleston, South Carolina
| | | | | | - Dave Robinson
- Acutus Medical, Carlsbad, California; inHEART, Bordeaux-Pessac, France
| | | | | | | | | | | | | | | | | | - Virginie Loyer
- Electrophysiology and Heart Modelling Institute (LIRYC), Bordeaux-Pessac, France
| | - Yosuke Nakatani
- Electrophysiology and Heart Modelling Institute (LIRYC), Bordeaux-Pessac, France; Department of Electrophysiology and Cardiac Stimulation, Centre Hospitalier Universitaire de Bordeaux, Bordeaux-Pessac, France
| | - Hubert Cochet
- Electrophysiology and Heart Modelling Institute (LIRYC), Bordeaux-Pessac, France; Department of Electrophysiology and Cardiac Stimulation, Centre Hospitalier Universitaire de Bordeaux, Bordeaux-Pessac, France; inHEART, Bordeaux-Pessac, France
| | - Pierre Jaïs
- Electrophysiology and Heart Modelling Institute (LIRYC), Bordeaux-Pessac, France; Department of Electrophysiology and Cardiac Stimulation, Centre Hospitalier Universitaire de Bordeaux, Bordeaux-Pessac, France; inHEART, Bordeaux-Pessac, France.
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Frøysa V, Berg GJ, Eftestøl T, Woie L, Ørn S. Texture-based probability mapping for automatic scar assessment in late gadolinium-enhanced cardiovascular magnetic resonance images. Eur J Radiol Open 2021; 8:100387. [PMID: 34926726 PMCID: PMC8649215 DOI: 10.1016/j.ejro.2021.100387] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 11/16/2021] [Accepted: 11/22/2021] [Indexed: 01/18/2023] Open
Abstract
Purpose To evaluate a novel texture-based probability mapping (TPM) method for scar size estimation in LGE-CMRI. Methods This retrospective proof-of-concept study included chronic myocardial scars from 52 patients. The TPM was compared with three signal intensity-based methods: manual segmentation, full-width-half-maximum (FWHM), and 5-standard deviation (5-SD). TPM is generated using machine learning techniques, expressing the probability of scarring in pixels. The probability is derived by comparing the texture of the 3 × 3 pixel matrix surrounding each pixel with reference dictionaries from patients with established myocardial scars. The Sørensen-Dice coefficient was used to find the optimal TPM range. A non-parametric test was used to test the correlation between infarct size and remodeling parameters. Bland-Altman plots were performed to assess agreement among the methods. Results The study included 52 patients (76.9% male; median age 64.5 years (54, 72.5)). A TPM range of 0.328–1.0 was found to be the optimal probability interval to predict scar size compared to manual segmentation, median dice (25th and 75th percentiles)): 0.69(0.42–0.81). There was no significant difference in the scar size between TPM and 5-SD. However, both 5-SD and TPM yielded larger scar sizes compared with FWHM (p < 0.001 and p = 0.002). There were strong correlations between scar size measured by TPM, and left ventricular ejection fraction (LVEF, r = −0.76, p < 0.001), left ventricular end-diastolic volume index (r = 0.73, p < 0.001), and left ventricular end-systolic volume index (r = 0.75, p < 0.001). Conclusion The TPM method is comparable with current SI-based methods, both for the scar size assessment and the relationship with left ventricular remodeling when applied on LGE-CMRI.
Texture based probability mapping can be used to evaluate myocardial scar size. The method can assess myocardial fibrosis independent of signal intensity. The TPM method shows strong correlations between scar size and left ventricular ejection fraction.
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Affiliation(s)
- Vidar Frøysa
- Department of Cardiology, Stavanger University Hospital, Armauer Hansens vei 20, 4011, Stavanger, Norway
| | - Gøran J Berg
- Department of Electrical and Computer Science, University of Stavanger, P.O. box 8600, 4036 Stavanger, Norway
| | - Trygve Eftestøl
- Department of Electrical and Computer Science, University of Stavanger, P.O. box 8600, 4036 Stavanger, Norway
| | - Leik Woie
- Department of Electrical and Computer Science, University of Stavanger, P.O. box 8600, 4036 Stavanger, Norway
| | - Stein Ørn
- Department of Cardiology, Stavanger University Hospital, Armauer Hansens vei 20, 4011, Stavanger, Norway.,Department of Electrical and Computer Science, University of Stavanger, P.O. box 8600, 4036 Stavanger, Norway
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Hedeer F, Ostenfeld E, Hedén B, Prinzen FW, Arheden H, Carlsson M, Engblom H. To what extent are perfusion defects seen by myocardial perfusion SPECT in patients with left bundle branch block related to myocardial infarction, ECG characteristics, and myocardial wall motion? J Nucl Cardiol 2021; 28:2910-2922. [PMID: 32451797 PMCID: PMC8709823 DOI: 10.1007/s12350-020-02180-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Accepted: 04/25/2020] [Indexed: 12/04/2022]
Abstract
INTRODUCTION We investigated if uptake pattern on myocardial perfusion SPECT (MPS) in patients with left bundle branch block (LBBB) is related to myocardial fibrosis, myocardial wall motion, and electrocardiography (ECG) characteristics. METHODS Twenty-three patients (9 women) with LBBB, examined with MPS and cardiac magnetic resonance (CMR), were included. Tracer uptake on MPS was classified by visual interpretation as typical LBBB pattern (Defect+, n = 13) or not (Defect-, n = 10) and quantitatively. CMR images were evaluated for wall thickness and for myocardial wall motion both by visual assessment and by regional myocardial radial strain from feature tracking, and for presence and location of myocardial fibrosis. ECGs were analyzed regarding QRS duration and the presence of strict criteria for LBBB. RESULTS Wall thickness was slightly lower in the septum compared to the lateral wall in Defect+ patients (5.6 ± 1.1 vs 6.0 ± 1.3 mm, P = 0.03) but not in Defect- patients (5.6 ± 1.0 vs 5.6 ± 0.9 mm, P = 0.84). Defect+ patients showed a larger proportion of dyskinetic segments in the septum and hyperkinetic segments in the lateral wall compared to Defect- patients (P = 0.006 and P = 0.004, respectively). Decreased myocardial radial strain was associated with decreased tracer uptake by MPS (R = 0.37, P < 0.001). Areas of fibrosis did not match areas with uptake defect on MPS. No differences in ECG variables were seen. CONCLUSION The heterogeneous regional tracer uptake in some patients with LBBB is related to underlying regional myocardial dyskinesia, wall thickening, and wall thickness rather than stress-induced ischemia, myocardial fibrosis, or specific ECG characteristics.
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Affiliation(s)
- Fredrik Hedeer
- Department of Clinical Physiology, Lund University, Skåne University Hospital, Lund, Sweden
| | - Ellen Ostenfeld
- Department of Clinical Physiology, Lund University, Skåne University Hospital, Lund, Sweden
| | - Bo Hedén
- Department of Clinical Physiology, Lund University, Skåne University Hospital, Lund, Sweden
| | - Frits W Prinzen
- Department of Physiology, Cardiovascular Research Institute (CARIM), Maastricht University, Maastricht, The Netherlands
| | - Håkan Arheden
- Department of Clinical Physiology, Lund University, Skåne University Hospital, Lund, Sweden
| | - Marcus Carlsson
- Department of Clinical Physiology, Lund University, Skåne University Hospital, Lund, Sweden
| | - Henrik Engblom
- Department of Clinical Physiology, Lund University, Skåne University Hospital, Lund, Sweden.
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Chen Z, Lalande A, Salomon M, Decourselle T, Pommier T, Qayyum A, Shi J, Perrot G, Couturier R. Automatic deep learning-based myocardial infarction segmentation from delayed enhancement MRI. Comput Med Imaging Graph 2021; 95:102014. [PMID: 34864579 DOI: 10.1016/j.compmedimag.2021.102014] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Revised: 10/04/2021] [Accepted: 11/04/2021] [Indexed: 10/19/2022]
Abstract
Delayed Enhancement cardiac MRI (DE-MRI) has become indispensable for the diagnosis of myocardial diseases. However, to quantify the disease severity, doctors need time to manually annotate the scar and myocardium. To address this issue, in this paper we propose an automatic myocardial infarction segmentation approach on the left ventricle from short-axis DE-MRI based on Convolutional Neural Networks (CNN). The objective is to segment myocardial infarction on short-axis DE-MRI images of the left ventricle acquired 10 min after the injection of a gadolinium-based contrast agent. The segmentation of the infarction area is realized in two stages: a first CNN model finds the contour of myocardium and a second CNN model segments the infarction. Compared to the manual intra-observer and inter-observer variations for the segmentation of myocardial infarction, and to the automatic segmentation with Gaussian Mixture Model, our proposal achieves satisfying segmentation results on our dataset of 904 DE-MRI slices.
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Affiliation(s)
- Zhihao Chen
- FEMTO-ST Institute, UMR6174 CNRS, Univ. Bourgogne Franche-Comté, Belfort, France
| | - Alain Lalande
- ImViA Laboratory, EA7535, Univ. Bourgogne Franche-Comté, Dijon, France; Department of Medical Imaging, University Hospital of Dijon, Dijon, France
| | - Michel Salomon
- FEMTO-ST Institute, UMR6174 CNRS, Univ. Bourgogne Franche-Comté, Belfort, France
| | | | - Thibaut Pommier
- Department of Cardiology, University Hospital of Dijon, Dijon, France
| | - Abdul Qayyum
- ImViA Laboratory, EA7535, Univ. Bourgogne Franche-Comté, Dijon, France
| | - Jixi Shi
- FEMTO-ST Institute, UMR6174 CNRS, Univ. Bourgogne Franche-Comté, Belfort, France; IRSEEM, EA4353, ESIGELEC, Univ. Normandie, Rouen, France
| | - Gilles Perrot
- FEMTO-ST Institute, UMR6174 CNRS, Univ. Bourgogne Franche-Comté, Belfort, France
| | - Raphaël Couturier
- FEMTO-ST Institute, UMR6174 CNRS, Univ. Bourgogne Franche-Comté, Belfort, France.
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Whitaker J, Neji R, Kim S, Connolly A, Aubriot T, Calvo JJ, Karim R, Roney CH, Murfin B, Richardson C, Morgan S, Ismail TF, Harrison J, de Vos J, Aalders MCG, Williams SE, Mukherjee R, O'Neill L, Chubb H, Tschabrunn C, Anter E, Camporota L, Niederer S, Roujol S, Bishop MJ, Wright M, Silberbauer J, Razavi R, O'Neill M. Late Gadolinium Enhancement Cardiovascular Magnetic Resonance Assessment of Substrate for Ventricular Tachycardia With Hemodynamic Compromise. Front Cardiovasc Med 2021; 8:744779. [PMID: 34765656 PMCID: PMC8576410 DOI: 10.3389/fcvm.2021.744779] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 09/20/2021] [Indexed: 11/13/2022] Open
Abstract
Background: The majority of data regarding tissue substrate for post myocardial infarction (MI) VT has been collected during hemodynamically tolerated VT, which may be distinct from the substrate responsible for VT with hemodynamic compromise (VT-HC). This study aimed to characterize tissue at diastolic locations of VT-HC in a porcine model. Methods: Late Gadolinium Enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging was performed in eight pigs with healed antero-septal infarcts. Seven pigs underwent electrophysiology study with venous arterial-extra corporeal membrane oxygenation (VA-ECMO) support. Tissue thickness, scar and heterogeneous tissue (HT) transmurality were calculated at the location of the diastolic electrograms of mapped VT-HC. Results: Diastolic locations had median scar transmurality of 33.1% and a median HT transmurality 7.6%. Diastolic activation was found within areas of non-transmural scar in 80.1% of cases. Tissue activated during the diastolic component of VT circuits was thinner than healthy tissue (median thickness: 5.5 mm vs. 8.2 mm healthy tissue, p < 0.0001) and closer to HT (median distance diastolic tissue: 2.8 mm vs. 11.4 mm healthy tissue, p < 0.0001). Non-scarred regions with diastolic activation were closer to steep gradients in thickness than non-scarred locations with normal EGMs (diastolic locations distance = 1.19 mm vs. 9.67 mm for non-diastolic locations, p < 0.0001). Sites activated late in diastole were closest to steep gradients in tissue thickness. Conclusions: Non-transmural scar, mildly decreased tissue thickness, and steep gradients in tissue thickness represent the structural characteristics of the diastolic component of reentrant circuits in VT-HC in this porcine model and could form the basis for imaging criteria to define ablation targets in future trials.
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Affiliation(s)
- John Whitaker
- School of Biomedical Engineering and Imaging Sciences, King's College, London, United Kingdom
| | - Radhouene Neji
- School of Biomedical Engineering and Imaging Sciences, King's College, London, United Kingdom.,Siemens Healthcare, Frimley, United Kingdom
| | - Steven Kim
- Abbott Medical, St Paul, MN, United States
| | - Adam Connolly
- School of Biomedical Engineering and Imaging Sciences, King's College, London, United Kingdom
| | | | - Justo Juliá Calvo
- Brighton and Sussex University Hospitals NHS Trust, Brighton, United Kingdom
| | - Rashed Karim
- School of Biomedical Engineering and Imaging Sciences, King's College, London, United Kingdom
| | - Caroline H Roney
- School of Biomedical Engineering and Imaging Sciences, King's College, London, United Kingdom
| | - Brendan Murfin
- Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom
| | - Carla Richardson
- Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom
| | - Stephen Morgan
- Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom
| | - Tevfik F Ismail
- School of Biomedical Engineering and Imaging Sciences, King's College, London, United Kingdom.,Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom
| | - James Harrison
- School of Biomedical Engineering and Imaging Sciences, King's College, London, United Kingdom
| | - Judith de Vos
- Department of Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Maurice C G Aalders
- Department of Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Steven E Williams
- School of Biomedical Engineering and Imaging Sciences, King's College, London, United Kingdom.,Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, United Kingdom
| | - Rahul Mukherjee
- School of Biomedical Engineering and Imaging Sciences, King's College, London, United Kingdom
| | - Louisa O'Neill
- School of Biomedical Engineering and Imaging Sciences, King's College, London, United Kingdom
| | - Henry Chubb
- School of Biomedical Engineering and Imaging Sciences, King's College, London, United Kingdom
| | - Cory Tschabrunn
- Division of Cardiovascular Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Elad Anter
- Cleveland Clinic, Cleveland, OH, United States
| | - Luigi Camporota
- Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom
| | - Steven Niederer
- School of Biomedical Engineering and Imaging Sciences, King's College, London, United Kingdom
| | - Sébastien Roujol
- School of Biomedical Engineering and Imaging Sciences, King's College, London, United Kingdom
| | - Martin J Bishop
- School of Biomedical Engineering and Imaging Sciences, King's College, London, United Kingdom
| | - Matthew Wright
- Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom
| | - John Silberbauer
- Brighton and Sussex University Hospitals NHS Trust, Brighton, United Kingdom
| | - Reza Razavi
- School of Biomedical Engineering and Imaging Sciences, King's College, London, United Kingdom
| | - Mark O'Neill
- School of Biomedical Engineering and Imaging Sciences, King's College, London, United Kingdom
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Mamalakis M, Garg P, Nelson T, Lee J, Wild JM, Clayton RH. MA-SOCRATIS: An automatic pipeline for robust segmentation of the left ventricle and scar. Comput Med Imaging Graph 2021; 93:101982. [PMID: 34481237 DOI: 10.1016/j.compmedimag.2021.101982] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 08/19/2021] [Accepted: 08/23/2021] [Indexed: 11/18/2022]
Abstract
Multi-atlas segmentation of cardiac regions and total infarct scar (MA-SOCRATIS) is an unsupervised automatic pipeline to segment left ventricular myocardium and scar from late gadolinium enhanced MR images (LGE-MRI) of the heart. We implement two different pipelines for myocardial and scar segmentation from short axis LGE-MRI. Myocardial segmentation has two steps; initial segmentation and re-estimation. The initial segmentation step makes a first estimate of myocardium boundaries by using multi-atlas segmentation techniques. The re-estimation step refines the myocardial segmentation by a combination of k-means clustering and a geometric median shape variation technique. An active contour technique determines the unhealthy and healthy myocardial wall. The scar segmentation pipeline is a combination of a Rician-Gaussian mixture model and full width at half maximum (FWHM) thresholding, to determine the intensity pixels in scar regions. Following this step a watershed method with an automatic seed-points framework segments the final scar region. MA-SOCRATIS was evaluated using two different datasets. In both datasets ground truths were based on manual segmentation of short axis images from LGE-MRI scans. The first dataset included 40 patients from the MS-CMRSeg 2019 challenge dataset (STACOM at MICCAI 2019). The second is a collection of 20 patients with scar regions that are challenging to segment. MA-SOCRATIS achieved robust and accurate performance in automatic segmentation of myocardium and scar regions without the need of training or tuning in both cohorts, compared with state-of-the-art techniques (intra-observer and inter observer myocardium segmentation: 81.9% and 70% average Dice value, and scar (intra-observer and inter observer segmentation: 70.5% and 70.5% average Dice value).
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Affiliation(s)
- Michail Mamalakis
- Insigneo Institute for In-Silico Medicine, University of Sheffield, Sheffield, UK; Department of Computer Science, University of Sheffield, Regent Court, Sheffield S1 4DP, UK.
| | - Pankaj Garg
- Department of Cardiology, Sheffield Teaching Hospitals NHS Trust, Sheffield S5 7AU, UK
| | - Tom Nelson
- Department of Cardiology, Sheffield Teaching Hospitals NHS Trust, Sheffield S5 7AU, UK
| | - Justin Lee
- Department of Cardiology, Sheffield Teaching Hospitals NHS Trust, Sheffield S5 7AU, UK
| | - Jim M Wild
- Insigneo Institute for In-Silico Medicine, University of Sheffield, Sheffield, UK; Polaris, Imaging Sciences, Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, UK
| | - Richard H Clayton
- Insigneo Institute for In-Silico Medicine, University of Sheffield, Sheffield, UK; Department of Computer Science, University of Sheffield, Regent Court, Sheffield S1 4DP, UK
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38
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Ananthakrishna R, Lee SL, Foote J, Sallustio BC, Binda G, Mangoni AA, Woodman R, Semsarian C, Horowitz JD, Selvanayagam JB. Randomized controlled trial of perhexiline on regression of left ventricular hypertrophy in patients with symptomatic hypertrophic cardiomyopathy (RESOLVE-HCM trial). Am Heart J 2021; 240:101-113. [PMID: 34175315 DOI: 10.1016/j.ahj.2021.06.010] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Accepted: 06/20/2021] [Indexed: 11/17/2022]
Abstract
BACKGROUND The presence and extent of left ventricular hypertrophy (LVH) is a major determinant of symptoms in patients with hypertrophic cardiomyopathy (HCM). There is increasing evidence to suggest that myocardial energetic impairment represents a central mechanism leading to LVH in HCM. There is currently a significant unmet need for disease-modifying therapy that regresses LVH in HCM patients. Perhexiline, a potent carnitine palmitoyl transferase-1 (CPT-1) inhibitor, improves myocardial energetics in HCM, and has the potential to reduce LVH in HCM. OBJECTIVE The primary objective is to evaluate the effects of perhexiline treatment on the extent of LVH, in symptomatic HCM patients with at least moderate LVH. METHODS/DESIGN RESOLVE-HCM is a prospective, multicenter double-blind placebo-controlled randomized trial enrolling symptomatic HCM patients with at least moderate LVH. Sixty patients will be randomized to receive either perhexiline or matching placebo. The primary endpoint is change in LVH, assessed utilizing cardiovascular magnetic resonance (CMR) imaging, after 12-months treatment with perhexiline. SUMMARY RESOLVE-HCM will provide novel information on the utility of perhexiline in regression of LVH in symptomatic HCM patients. A positive result would lead to the design of a Phase 3 clinical trial addressing long-term effects of perhexiline on risk of heart failure and mortality in HCM patients.
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Affiliation(s)
- Rajiv Ananthakrishna
- College of Medicine and Public Health, Flinders University, Adelaide, Australia; South Australian Health and Medical Research Institute, Adelaide, Australia; Department of Cardiovascular Medicine, Flinders Medical Centre, Adelaide, Australia
| | - Sau L Lee
- Department of Cardiovascular Medicine, Flinders Medical Centre, Adelaide, Australia
| | - Jonathon Foote
- South Australian Health and Medical Research Institute, Adelaide, Australia
| | - Benedetta C Sallustio
- Department of Clinical Pharmacology, Basil Hetzel Institute for Translational Health Research, The Queen Elizabeth Hospital, Adelaide, Australia; Discipline of Pharmacology, Adelaide Medical School, University of Adelaide, Australia
| | - Giulia Binda
- South Australian Health and Medical Research Institute, Adelaide, Australia; Department of Cardiovascular Medicine, Flinders Medical Centre, Adelaide, Australia
| | - Arduino A Mangoni
- Department of Clinical Pharmacology, College of Medicine and Public Health, Flinders University and Flinders Medical Centre, Adelaide, Australia
| | - Richard Woodman
- Flinders Centre for Epidemiology and Biostatistics, College of Medicine and Public Health, Flinders University, Adelaide, Australia
| | - Christopher Semsarian
- Agnes Ginges Centre for Molecular Cardiology, Centenary Institute and Sydney Medical School, University of Sydney, Australia; Department of Cardiology, Royal Prince Alfred Hospital, Sydney, Australia
| | - John D Horowitz
- The Queen Elizabeth Hospital, Basil Hetzel Institute for Translational Research, University of Adelaide, Adelaide, Australia
| | - Joseph B Selvanayagam
- College of Medicine and Public Health, Flinders University, Adelaide, Australia; South Australian Health and Medical Research Institute, Adelaide, Australia; Department of Cardiovascular Medicine, Flinders Medical Centre, Adelaide, Australia.
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Merino-Caviedes S, Gutierrez LK, Alfonso-Almazán JM, Sanz-Estébanez S, Cordero-Grande L, Quintanilla JG, Sánchez-González J, Marina-Breysse M, Galán-Arriola C, Enríquez-Vázquez D, Torres C, Pizarro G, Ibáñez B, Peinado R, Merino JL, Pérez-Villacastín J, Jalife J, López-Yunta M, Vázquez M, Aguado-Sierra J, González-Ferrer JJ, Pérez-Castellano N, Martín-Fernández M, Alberola-López C, Filgueiras-Rama D. Time-efficient three-dimensional transmural scar assessment provides relevant substrate characterization for ventricular tachycardia features and long-term recurrences in ischemic cardiomyopathy. Sci Rep 2021; 11:18722. [PMID: 34580343 PMCID: PMC8476552 DOI: 10.1038/s41598-021-97399-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 08/17/2021] [Indexed: 11/21/2022] Open
Abstract
Delayed gadolinium-enhanced cardiac magnetic resonance (LGE-CMR) imaging requires novel and time-efficient approaches to characterize the myocardial substrate associated with ventricular arrhythmia in patients with ischemic cardiomyopathy. Using a translational approach in pigs and patients with established myocardial infarction, we tested and validated a novel 3D methodology to assess ventricular scar using custom transmural criteria and a semiautomatic approach to obtain transmural scar maps in ventricular models reconstructed from both 3D-acquired and 3D-upsampled-2D-acquired LGE-CMR images. The results showed that 3D-upsampled models from 2D LGE-CMR images provided a time-efficient alternative to 3D-acquired sequences to assess the myocardial substrate associated with ischemic cardiomyopathy. Scar assessment from 2D-LGE-CMR sequences using 3D-upsampled models was superior to conventional 2D assessment to identify scar sizes associated with the cycle length of spontaneous ventricular tachycardia episodes and long-term ventricular tachycardia recurrences after catheter ablation. This novel methodology may represent an efficient approach in clinical practice after manual or automatic segmentation of myocardial borders in a small number of conventional 2D LGE-CMR slices and automatic scar detection.
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Affiliation(s)
| | - Lilian K Gutierrez
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Myocardial Pathophysiology Area, Madrid, Spain
| | | | | | - Lucilio Cordero-Grande
- Universidad Politécnica de Madrid, Biomedical Image Technologies, ETSI Telecomunicación, Madrid, Spain.,Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain
| | - Jorge G Quintanilla
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Myocardial Pathophysiology Area, Madrid, Spain.,Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Cardiovascular Institute, Madrid, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain
| | | | - Manuel Marina-Breysse
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Myocardial Pathophysiology Area, Madrid, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain
| | - Carlos Galán-Arriola
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Myocardial Pathophysiology Area, Madrid, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain
| | - Daniel Enríquez-Vázquez
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Myocardial Pathophysiology Area, Madrid, Spain.,Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Cardiovascular Institute, Madrid, Spain
| | - Carlos Torres
- Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Cardiovascular Institute, Madrid, Spain
| | - Gonzalo Pizarro
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Myocardial Pathophysiology Area, Madrid, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain.,Hospital Ruber Juan Bravo Quironsalud UEM, Cardiology Department, Madrid, Spain
| | - Borja Ibáñez
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Myocardial Pathophysiology Area, Madrid, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain.,IIS-University Hospital Fundación Jiménez Díaz, Cardiology Department, Madrid, Spain
| | - Rafael Peinado
- Hospital Universitario La Paz, Cardiology Department, Madrid, Spain
| | - Jose Luis Merino
- Hospital Universitario La Paz, Cardiology Department, Madrid, Spain
| | - Julián Pérez-Villacastín
- Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Cardiovascular Institute, Madrid, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain.,Fundación Interhospitalaria para la Investigación Cardiovascular (FIC), Madrid, Spain
| | - José Jalife
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Myocardial Pathophysiology Area, Madrid, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain
| | | | - Mariano Vázquez
- Barcelona Supercomputing Center (BSC), Barcelona, Spain.,ELEM Biotech SL., Barcelona, Spain
| | | | - Juan José González-Ferrer
- Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Cardiovascular Institute, Madrid, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain
| | - Nicasio Pérez-Castellano
- Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Cardiovascular Institute, Madrid, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain.,Fundación Interhospitalaria para la Investigación Cardiovascular (FIC), Madrid, Spain
| | | | | | - David Filgueiras-Rama
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Myocardial Pathophysiology Area, Madrid, Spain. .,Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Cardiovascular Institute, Madrid, Spain. .,Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain.
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Mewton N, Roubille F, Bresson D, Prieur C, Bouleti C, Bochaton T, Ivanes F, Dubreuil O, Biere L, Hayek A, Derimay F, Akodad M, Alos B, Haider L, El Jonhy N, Daw R, De Bourguignon C, Dhelens C, Finet G, Bonnefoy-Cudraz E, Bidaux G, Boutitie F, Maucort-Boulch D, Croisille P, Rioufol G, Prunier F, Angoulvant D. Effect of Colchicine on Myocardial Injury in Acute Myocardial Infarction. Circulation 2021; 144:859-869. [PMID: 34420373 PMCID: PMC8462445 DOI: 10.1161/circulationaha.121.056177] [Citation(s) in RCA: 69] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Supplemental Digital Content is available in the text. Background: Inflammation is a key factor of myocardial damage in reperfused ST-segment–elevation myocardial infarction. We hypothesized that colchicine, a potent anti-inflammatory agent, may reduce infarct size (IS) and left ventricular (LV) remodeling at the acute phase of ST-segment–elevation myocardial infarction. Methods: In this double-blind multicenter trial, we randomly assigned patients admitted for a first episode of ST-segment–elevation myocardial infarction referred for primary percutaneous coronary intervention to receive oral colchicine (2-mg loading dose followed by 0.5 mg twice a day) or matching placebo from admission to day 5. The primary efficacy outcome was IS determined by cardiac magnetic resonance imaging at 5 days. The relative LV end-diastolic volume change at 3 months and IS at 3 months assessed by cardiac magnetic resonance imaging were among the secondary outcomes. Results: We enrolled 192 patients, 101 in the colchicine group and 91 in the control group. At 5 days, the gadolinium enhancement–defined IS did not differ between the colchicine and placebo groups with a mean of 26 interquartile range (IQR) [16–44] versus 28.4 IQR [14–40] g of LV mass, respectively (P=0.87). At 3 months follow-up, there was no significant difference in LV remodeling between the colchicine and placebo groups with a +2.4% (IQR, –8.3% to 11.1%) versus –1.1% (IQR, –8.0% to 9.9%) change in LV end-diastolic volume (P=0.49). Infarct size at 3 months was also not significantly different between the colchicine and placebo groups (17 IQR [10–28] versus 18 IQR [10–27] g of LV mass, respectively; P=0.92). The incidence of gastrointestinal adverse events during the treatment period was greater with colchicine than with placebo (34% versus 11%, respectively; P=0.0002). Conclusions: In this randomized, placebo-controlled trial, oral administration of high-dose colchicine at the time of reperfusion and for 5 days did not reduce IS assessed by cardiac magnetic resonance imaging. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03156816.
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Affiliation(s)
- Nathan Mewton
- Hôpital Cardiovasculaire Louis Pradel, Clinical Investigation Center, INSERM 1407 and INSERM CarMeN 1060, Hospices Civils de Lyon and Claude Bernard University, Lyon, France (N.M., C.P., T.B., A.H., F.D., L.H., N.E.J, R.D., C.D.B., G.F., E.B.-C., G.R.)
| | - François Roubille
- PhyMedExp, Université de Montpellier, INSERM, CNRS, Cardiology Department, CHU de Montpellier, France (F.R., M.A.)
| | - Didier Bresson
- Cardiology Division, University Hospital of Mulhouse, Hôpital Emile Muller, Mulhouse, France (D.B.)
| | - Cyril Prieur
- Hôpital Cardiovasculaire Louis Pradel, Clinical Investigation Center, INSERM 1407 and INSERM CarMeN 1060, Hospices Civils de Lyon and Claude Bernard University, Lyon, France (N.M., C.P., T.B., A.H., F.D., L.H., N.E.J, R.D., C.D.B., G.F., E.B.-C., G.R.)
| | - Claire Bouleti
- Université de Poitiers, CIC Inserm 1402n CHU de Poitiers, France (C.B., B.A.)
| | - Thomas Bochaton
- Hôpital Cardiovasculaire Louis Pradel, Clinical Investigation Center, INSERM 1407 and INSERM CarMeN 1060, Hospices Civils de Lyon and Claude Bernard University, Lyon, France (N.M., C.P., T.B., A.H., F.D., L.H., N.E.J, R.D., C.D.B., G.F., E.B.-C., G.R.)
| | - Fabrice Ivanes
- Cardiology Department CHRU de Tours and EA4245 T2i Tours University, France (F.I., D.A.)
| | - Olivier Dubreuil
- Centre Hospitalier Saint-Joseph Saint-Luc, Invasive Cardiology Department, Lyon, France (O.D.)
| | - Loïc Biere
- Institut MITOVASC, CNRS 6015 INSERM U1083, Université d'Angers, Cardiology Division, CHU Angers, France (L.B., F.P.)
| | - Ahmad Hayek
- Hôpital Cardiovasculaire Louis Pradel, Clinical Investigation Center, INSERM 1407 and INSERM CarMeN 1060, Hospices Civils de Lyon and Claude Bernard University, Lyon, France (N.M., C.P., T.B., A.H., F.D., L.H., N.E.J, R.D., C.D.B., G.F., E.B.-C., G.R.)
| | - François Derimay
- Hôpital Cardiovasculaire Louis Pradel, Clinical Investigation Center, INSERM 1407 and INSERM CarMeN 1060, Hospices Civils de Lyon and Claude Bernard University, Lyon, France (N.M., C.P., T.B., A.H., F.D., L.H., N.E.J, R.D., C.D.B., G.F., E.B.-C., G.R.)
| | - Mariama Akodad
- PhyMedExp, Université de Montpellier, INSERM, CNRS, Cardiology Department, CHU de Montpellier, France (F.R., M.A.)
| | - Benjamin Alos
- Université de Poitiers, CIC Inserm 1402n CHU de Poitiers, France (C.B., B.A.)
| | - Lamis Haider
- Hôpital Cardiovasculaire Louis Pradel, Clinical Investigation Center, INSERM 1407 and INSERM CarMeN 1060, Hospices Civils de Lyon and Claude Bernard University, Lyon, France (N.M., C.P., T.B., A.H., F.D., L.H., N.E.J, R.D., C.D.B., G.F., E.B.-C., G.R.)
| | - Naoual El Jonhy
- Hôpital Cardiovasculaire Louis Pradel, Clinical Investigation Center, INSERM 1407 and INSERM CarMeN 1060, Hospices Civils de Lyon and Claude Bernard University, Lyon, France (N.M., C.P., T.B., A.H., F.D., L.H., N.E.J, R.D., C.D.B., G.F., E.B.-C., G.R.)
| | - Rachel Daw
- Hôpital Cardiovasculaire Louis Pradel, Clinical Investigation Center, INSERM 1407 and INSERM CarMeN 1060, Hospices Civils de Lyon and Claude Bernard University, Lyon, France (N.M., C.P., T.B., A.H., F.D., L.H., N.E.J, R.D., C.D.B., G.F., E.B.-C., G.R.)
| | - Charles De Bourguignon
- Hôpital Cardiovasculaire Louis Pradel, Clinical Investigation Center, INSERM 1407 and INSERM CarMeN 1060, Hospices Civils de Lyon and Claude Bernard University, Lyon, France (N.M., C.P., T.B., A.H., F.D., L.H., N.E.J, R.D., C.D.B., G.F., E.B.-C., G.R.)
| | - Carole Dhelens
- Pharmacy Department, FRIPHARM-RC (C.D.), Hospices Civils de Lyon, France
| | - Gérard Finet
- Hôpital Cardiovasculaire Louis Pradel, Clinical Investigation Center, INSERM 1407 and INSERM CarMeN 1060, Hospices Civils de Lyon and Claude Bernard University, Lyon, France (N.M., C.P., T.B., A.H., F.D., L.H., N.E.J, R.D., C.D.B., G.F., E.B.-C., G.R.)
| | - Eric Bonnefoy-Cudraz
- Hôpital Cardiovasculaire Louis Pradel, Clinical Investigation Center, INSERM 1407 and INSERM CarMeN 1060, Hospices Civils de Lyon and Claude Bernard University, Lyon, France (N.M., C.P., T.B., A.H., F.D., L.H., N.E.J, R.D., C.D.B., G.F., E.B.-C., G.R.)
| | | | - Florent Boutitie
- UMR 5558 CNRS UCBL Biostatistics Departement (F.B., D.M.-B.), Hospices Civils de Lyon, France.,INSERM CarMeN 1060, IRIS Team, Claude Bernard University, Lyon, France (F.B.)
| | - Delphine Maucort-Boulch
- UMR 5558 CNRS UCBL Biostatistics Departement (F.B., D.M.-B.), Hospices Civils de Lyon, France
| | - Pierre Croisille
- CREATIS CNRS 5220 INSERM U1206 Research Lab, Radiology Department, University Hospital/CHU Saint Etienne, France (P.C.)
| | - Gilles Rioufol
- Hôpital Cardiovasculaire Louis Pradel, Clinical Investigation Center, INSERM 1407 and INSERM CarMeN 1060, Hospices Civils de Lyon and Claude Bernard University, Lyon, France (N.M., C.P., T.B., A.H., F.D., L.H., N.E.J, R.D., C.D.B., G.F., E.B.-C., G.R.)
| | - Fabrice Prunier
- Institut MITOVASC, CNRS 6015 INSERM U1083, Université d'Angers, Cardiology Division, CHU Angers, France (L.B., F.P.)
| | - Denis Angoulvant
- Cardiology Department CHRU de Tours and EA4245 T2i Tours University, France (F.I., D.A.)
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Beijnink CWH, van der Hoeven NW, Konijnenberg LSF, Kim RJ, Bekkers SCAM, Kloner RA, Everaars H, El Messaoudi S, van Rossum AC, van Royen N, Nijveldt R. Cardiac MRI to Visualize Myocardial Damage after ST-Segment Elevation Myocardial Infarction: A Review of Its Histologic Validation. Radiology 2021; 301:4-18. [PMID: 34427461 DOI: 10.1148/radiol.2021204265] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Cardiac MRI is a noninvasive diagnostic tool using nonionizing radiation that is widely used in patients with ST-segment elevation myocardial infarction (STEMI). Cardiac MRI depicts different prognosticating components of myocardial damage such as edema, intramyocardial hemorrhage (IMH), microvascular obstruction (MVO), and fibrosis. But how do cardiac MRI findings correlate to histologic findings? Shortly after STEMI, T2-weighted imaging and T2* mapping cardiac MRI depict, respectively, edema and IMH. The acute infarct size can be determined with late gadolinium enhancement (LGE) cardiac MRI. T2-weighted MRI should not be used for area-at-risk delineation because T2 values change dynamically over the first few days after STEMI and the severity of T2 abnormalities can be modulated with treatment. Furthermore, LGE cardiac MRI is the most accurate method to visualize MVO, which is characterized by hemorrhage, microvascular injury, and necrosis in histologic samples. In the chronic setting post-STEMI, LGE cardiac MRI is best used to detect replacement fibrosis (ie, final infarct size after injury healing). Finally, native T1 mapping has recently emerged as a contrast material-free method to measure infarct size that, however, remains inferior to LGE cardiac MRI. Especially LGE cardiac MRI-defined infarct size and the presence and extent of MVO may be used to monitor the effect of new therapeutic interventions in the treatment of reperfusion injury and infarct size reduction. © RSNA, 2021 Online supplemental material is available for this article.
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Affiliation(s)
- Casper W H Beijnink
- From the Department of Cardiology, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, the Netherlands (C.W.H.B., L.S.F.K., S.E.M., N.v.R., R.N.); Department of Cardiology, Amsterdam University Medical Center, Amsterdam, the Netherlands (N.W.v.d.H., H.E., A.C.v.R.); Department of Medicine, Duke University School of Medicine, Durham, NC (R.J.K.); Department of Cardiology, Maastricht University Medical Center, Maastricht, the Netherlands (S.C.A.M.B.); Huntington Medical Research Institutes, Pasadena, Calif (R.A.K.); and Division of Cardiovascular Medicine, Department of Medicine, Keck School of Medicine of University of Southern California, Los Angeles, Calif (R.A.K.)
| | - Nina W van der Hoeven
- From the Department of Cardiology, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, the Netherlands (C.W.H.B., L.S.F.K., S.E.M., N.v.R., R.N.); Department of Cardiology, Amsterdam University Medical Center, Amsterdam, the Netherlands (N.W.v.d.H., H.E., A.C.v.R.); Department of Medicine, Duke University School of Medicine, Durham, NC (R.J.K.); Department of Cardiology, Maastricht University Medical Center, Maastricht, the Netherlands (S.C.A.M.B.); Huntington Medical Research Institutes, Pasadena, Calif (R.A.K.); and Division of Cardiovascular Medicine, Department of Medicine, Keck School of Medicine of University of Southern California, Los Angeles, Calif (R.A.K.)
| | - Lara S F Konijnenberg
- From the Department of Cardiology, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, the Netherlands (C.W.H.B., L.S.F.K., S.E.M., N.v.R., R.N.); Department of Cardiology, Amsterdam University Medical Center, Amsterdam, the Netherlands (N.W.v.d.H., H.E., A.C.v.R.); Department of Medicine, Duke University School of Medicine, Durham, NC (R.J.K.); Department of Cardiology, Maastricht University Medical Center, Maastricht, the Netherlands (S.C.A.M.B.); Huntington Medical Research Institutes, Pasadena, Calif (R.A.K.); and Division of Cardiovascular Medicine, Department of Medicine, Keck School of Medicine of University of Southern California, Los Angeles, Calif (R.A.K.)
| | - Raymond J Kim
- From the Department of Cardiology, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, the Netherlands (C.W.H.B., L.S.F.K., S.E.M., N.v.R., R.N.); Department of Cardiology, Amsterdam University Medical Center, Amsterdam, the Netherlands (N.W.v.d.H., H.E., A.C.v.R.); Department of Medicine, Duke University School of Medicine, Durham, NC (R.J.K.); Department of Cardiology, Maastricht University Medical Center, Maastricht, the Netherlands (S.C.A.M.B.); Huntington Medical Research Institutes, Pasadena, Calif (R.A.K.); and Division of Cardiovascular Medicine, Department of Medicine, Keck School of Medicine of University of Southern California, Los Angeles, Calif (R.A.K.)
| | - Sebastiaan C A M Bekkers
- From the Department of Cardiology, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, the Netherlands (C.W.H.B., L.S.F.K., S.E.M., N.v.R., R.N.); Department of Cardiology, Amsterdam University Medical Center, Amsterdam, the Netherlands (N.W.v.d.H., H.E., A.C.v.R.); Department of Medicine, Duke University School of Medicine, Durham, NC (R.J.K.); Department of Cardiology, Maastricht University Medical Center, Maastricht, the Netherlands (S.C.A.M.B.); Huntington Medical Research Institutes, Pasadena, Calif (R.A.K.); and Division of Cardiovascular Medicine, Department of Medicine, Keck School of Medicine of University of Southern California, Los Angeles, Calif (R.A.K.)
| | - Robert A Kloner
- From the Department of Cardiology, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, the Netherlands (C.W.H.B., L.S.F.K., S.E.M., N.v.R., R.N.); Department of Cardiology, Amsterdam University Medical Center, Amsterdam, the Netherlands (N.W.v.d.H., H.E., A.C.v.R.); Department of Medicine, Duke University School of Medicine, Durham, NC (R.J.K.); Department of Cardiology, Maastricht University Medical Center, Maastricht, the Netherlands (S.C.A.M.B.); Huntington Medical Research Institutes, Pasadena, Calif (R.A.K.); and Division of Cardiovascular Medicine, Department of Medicine, Keck School of Medicine of University of Southern California, Los Angeles, Calif (R.A.K.)
| | - Henk Everaars
- From the Department of Cardiology, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, the Netherlands (C.W.H.B., L.S.F.K., S.E.M., N.v.R., R.N.); Department of Cardiology, Amsterdam University Medical Center, Amsterdam, the Netherlands (N.W.v.d.H., H.E., A.C.v.R.); Department of Medicine, Duke University School of Medicine, Durham, NC (R.J.K.); Department of Cardiology, Maastricht University Medical Center, Maastricht, the Netherlands (S.C.A.M.B.); Huntington Medical Research Institutes, Pasadena, Calif (R.A.K.); and Division of Cardiovascular Medicine, Department of Medicine, Keck School of Medicine of University of Southern California, Los Angeles, Calif (R.A.K.)
| | - Saloua El Messaoudi
- From the Department of Cardiology, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, the Netherlands (C.W.H.B., L.S.F.K., S.E.M., N.v.R., R.N.); Department of Cardiology, Amsterdam University Medical Center, Amsterdam, the Netherlands (N.W.v.d.H., H.E., A.C.v.R.); Department of Medicine, Duke University School of Medicine, Durham, NC (R.J.K.); Department of Cardiology, Maastricht University Medical Center, Maastricht, the Netherlands (S.C.A.M.B.); Huntington Medical Research Institutes, Pasadena, Calif (R.A.K.); and Division of Cardiovascular Medicine, Department of Medicine, Keck School of Medicine of University of Southern California, Los Angeles, Calif (R.A.K.)
| | - Albert C van Rossum
- From the Department of Cardiology, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, the Netherlands (C.W.H.B., L.S.F.K., S.E.M., N.v.R., R.N.); Department of Cardiology, Amsterdam University Medical Center, Amsterdam, the Netherlands (N.W.v.d.H., H.E., A.C.v.R.); Department of Medicine, Duke University School of Medicine, Durham, NC (R.J.K.); Department of Cardiology, Maastricht University Medical Center, Maastricht, the Netherlands (S.C.A.M.B.); Huntington Medical Research Institutes, Pasadena, Calif (R.A.K.); and Division of Cardiovascular Medicine, Department of Medicine, Keck School of Medicine of University of Southern California, Los Angeles, Calif (R.A.K.)
| | - Niels van Royen
- From the Department of Cardiology, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, the Netherlands (C.W.H.B., L.S.F.K., S.E.M., N.v.R., R.N.); Department of Cardiology, Amsterdam University Medical Center, Amsterdam, the Netherlands (N.W.v.d.H., H.E., A.C.v.R.); Department of Medicine, Duke University School of Medicine, Durham, NC (R.J.K.); Department of Cardiology, Maastricht University Medical Center, Maastricht, the Netherlands (S.C.A.M.B.); Huntington Medical Research Institutes, Pasadena, Calif (R.A.K.); and Division of Cardiovascular Medicine, Department of Medicine, Keck School of Medicine of University of Southern California, Los Angeles, Calif (R.A.K.)
| | - Robin Nijveldt
- From the Department of Cardiology, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, the Netherlands (C.W.H.B., L.S.F.K., S.E.M., N.v.R., R.N.); Department of Cardiology, Amsterdam University Medical Center, Amsterdam, the Netherlands (N.W.v.d.H., H.E., A.C.v.R.); Department of Medicine, Duke University School of Medicine, Durham, NC (R.J.K.); Department of Cardiology, Maastricht University Medical Center, Maastricht, the Netherlands (S.C.A.M.B.); Huntington Medical Research Institutes, Pasadena, Calif (R.A.K.); and Division of Cardiovascular Medicine, Department of Medicine, Keck School of Medicine of University of Southern California, Los Angeles, Calif (R.A.K.)
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Myocardial Infarction Quantification from Late Gadolinium Enhancement MRI Using Top-Hat Transforms and Neural Networks. ALGORITHMS 2021. [DOI: 10.3390/a14080249] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Late gadolinium enhancement (LGE) MRI is the gold standard technique for myocardial viability assessment. Although the technique accurately reflects the damaged tissue, there is no clinical standard to quantify myocardial infarction (MI). Moreover, commercial software used in clinical practice are mostly semi-automatic, and hence require direct intervention of experts. In this work, a new automatic method for MI quantification from LGE-MRI is proposed. Our novel segmentation approach is devised for accurately detecting not only hyper-enhanced lesions, but also microvascular obstruction areas. Moreover, it includes a myocardial disease detection step which extends the algorithm for working under healthy scans. The method is based on a cascade approach where firstly, diseased slices are identified by a convolutional neural network (CNN). Secondly, by means of morphological operations a fast coarse scar segmentation is obtained. Thirdly, the segmentation is refined by a boundary-voxel reclassification strategy using an ensemble of very light CNNs. We tested the method on a LGE-MRI database with healthy (n = 20) and diseased (n = 80) cases following a 5-fold cross-validation scheme. Our approach segmented myocardial scars with an average Dice coefficient of 77.22 ± 14.3% and with a volumetric error of 1.0 ± 6.9 cm3. In a comparison against nine reference algorithms, the proposed method achieved the highest agreement in volumetric scar quantification with the expert delineations (p< 0.001 when compared to the other approaches). Moreover, it was able to reproduce the scar segmentation intra- and inter-rater variability. Our approach was shown to be a good first attempt towards automatic and accurate myocardial scar segmentation, although validation over larger LGE-MRI databases is needed.
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Almeida AG, Carpenter JP, Cameli M, Donal E, Dweck MR, Flachskampf FA, Maceira AM, Muraru D, Neglia D, Pasquet A, Plein S, Gerber BL. Multimodality imaging of myocardial viability: an expert consensus document from the European Association of Cardiovascular Imaging (EACVI). Eur Heart J Cardiovasc Imaging 2021; 22:e97-e125. [PMID: 34097006 DOI: 10.1093/ehjci/jeab053] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Indexed: 12/17/2022] Open
Abstract
In clinical decision making, myocardial viability is defined as myocardium in acute or chronic coronary artery disease and other conditions with contractile dysfunction but maintained metabolic and electrical function, having the potential to improve dysfunction upon revascularization or other therapy. Several pathophysiological conditions may coexist to explain this phenomenon. Cardiac imaging may allow identification of myocardial viability through different principles, with the purpose of prediction of therapeutic response and selection for treatment. This expert consensus document reviews current insight into the underlying pathophysiology and available methods for assessing viability. In particular the document reviews contemporary viability imaging techniques, including stress echocardiography, single photon emission computed tomography, positron emission tomography, cardiovascular magnetic resonance, and computed tomography and provides clinical recommendations for how to standardize these methods in terms of acquisition and interpretation. Finally, it presents clinical scenarios where viability assessment is clinically useful.
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Affiliation(s)
- Ana G Almeida
- Faculty of Medicine, Lisbon University, University Hospital Santa Maria/CHLN, Portugal
| | - John-Paul Carpenter
- Cardiology Department, University Hospitals Dorset, NHS Foundation Trust, Poole Hospital, Longfleet Road, Poole, Dorset BH15 2JB, United Kingdom
| | - Matteo Cameli
- Department of Medical Biotechnologies, Division of Cardiology, University of Siena, Viale Bracci 16, Siena, Italy
| | - Erwan Donal
- Department of Cardiology, CHU Rennes, Inserm, LTSI-UMR 1099, Université de Rennes 1, Rennes F-35000, France
| | - Marc R Dweck
- BHF Centre for Cardiovascular Science, The University of Edinburgh & Edinburgh Heart Centre, Chancellors Building Little France Crescent, Edinburgh EH16 4SB, United Kingdom
| | - Frank A Flachskampf
- Dept. of Med. Sciences, Uppsala University, and Cardiology and Clinical Physiology, Uppsala University Hospital, Akademiska, 751 85 Uppsala, Sweden
| | - Alicia M Maceira
- Cardiovascular Imaging Unit, Ascires Biomedical Group Colon St, 1, Valencia 46004, Spain; Department of Medicine, Health Sciences School, CEU Cardenal Herrera University, Lluís Vives St. 1, 46115 Alfara del Patriarca, Valencia, Spain
| | - Denisa Muraru
- Department of Medicine and Surgery, University of Milano-Bicocca, Via Cadore 48, 20900, Monza, Italy; Department of Cardiovascular, Neural and Metabolic Sciences, Istituto Auxologico Italiano, IRCCS, Piazzale Brescia 20, 20149, Milan, Italy
| | - Danilo Neglia
- Fondazione Toscana G. Monasterio-Via G. Moruzzi 1, Pisa, Italy
| | - Agnès Pasquet
- Service de Cardiologie, Département Cardiovasculaire, Cliniques Universitaires St. Luc, and Division CARD, Institut de Recherche Expérimental et Clinique (IREC), UCLouvain, Av Hippocrate 10, B-1200 Brussels, Belgium
| | - Sven Plein
- Department of Biomedical Imaging Science, Leeds, Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Clarendon Way, Leeds LS2 9JT, United Kingdom
| | - Bernhard L Gerber
- Department of Biomedical Imaging Science, Leeds, Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Clarendon Way, Leeds LS2 9JT, United Kingdom
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Kato Y, Kizer JR, Ostovaneh MR, Lazar J, Peng Q, van der Geest RJ, Lima JAC, Ambale-Venkatesh B. Extracellular volume-guided late gadolinium enhancement analysis for non-ischemic cardiomyopathy: The Women's Interagency HIV Study. BMC Med Imaging 2021; 21:116. [PMID: 34315432 PMCID: PMC8314536 DOI: 10.1186/s12880-021-00649-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Accepted: 07/16/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Quantification of non-ischemic myocardial scar remains a challenge due to the patchy diffuse nature of fibrosis. Extracellular volume (ECV) to guide late gadolinium enhancement (LGE) analysis may achieve a robust scar assessment. METHODS Three cohorts of 80 non-ischemic-training, 20 non-ischemic-validation, and 10 ischemic-validation were prospectively enrolled and underwent 3.0 Tesla cardiac MRI. An ECV cutoff to differentiate LGE scar from non-scar was identified in the training cohort from the receiver-operating characteristic curve analysis, by comparing the ECV value against the visually-determined presence/absence of the LGE scar at the highest signal intensity (SI) area of the mid-left ventricle (LV) LGE. Based on the ECV cutoff, an LGE semi-automatic threshold of n-times of standard-deviation (n-SD) above the remote-myocardium SI was optimized in the individual cases ensuring correspondence between LGE and ECV images. The inter-method agreement of scar amount in comparison with manual (for non-ischemic) or full-width half-maximum (FWHM, for ischemic) was assessed. Intra- and inter-observer reproducibility were investigated in a randomly chosen subset of 40 non-ischemic and 10 ischemic cases. RESULTS The non-ischemic groups were all female with the HIV positive rate of 73.8% (training) and 80% (validation). The ischemic group was all male with reduced LV function. An ECV cutoff of 31.5% achieved optimum performance (sensitivity: 90%, specificity: 86.7% in training; sensitivity: 100%, specificity: 81.8% in validation dataset). The identified n-SD threshold varied widely (range 3 SD-18 SD), and was independent of scar amount (β = -0.01, p = 0.92). In the non-ischemic cohorts, results suggested that the manual LGE assessment overestimated scar (%) in comparison to ECV-guided analysis [training: 4.5 (3.2-6.4) vs. 0.92 (0.1-2.1); validation: 2.5 (1.2-3.7) vs. 0.2 (0-1.6); P < 0.01 for both]. Intra- and inter-observer analyses of global scar (%) showed higher reproducibility in ECV-guided than manual analysis with CCC = 0.94 and 0.78 versus CCC = 0.86 and 0.73, respectively (P < 0.01 for all). In ischemic validation, the ECV-guided LGE analysis showed a comparable scar amount and reproducibility with the FWHM. CONCLUSIONS ECV-guided LGE analysis is a robust scar quantification method for a non-ischemic cohort. Trial registration ClinicalTrials.gov; NCT00000797, retrospectively-registered 2 November 1999; NCT02501811, registered 15 July 2015.
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Affiliation(s)
- Yoko Kato
- Department of Cardiology, Johns Hopkins University, Baltimore, MD, USA
| | - Jorge R Kizer
- Cardiology Section, San Francisco Veterans Affairs Health Care System, and Departments of Medicine, Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | | | - Jason Lazar
- SUNY Downstate Medical Center, New York, NY, USA
| | - Qi Peng
- Albert Einstein College of Medicine, New York, NY, USA
| | - Rob J van der Geest
- Department of Radiology, Leiden University Medical Centre, Leiden, The Netherlands
| | - Joao A C Lima
- Department of Cardiology, Johns Hopkins University, Baltimore, MD, USA
| | - Bharath Ambale-Venkatesh
- Division of Radiology, Johns Hopkins University School of Medicine, 600 N Wolfe Street MR 110, Baltimore, MD, 21287, USA.
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Ostovaneh MR, Makkar RR, Ambale-Venkatesh B, Ascheim D, Chakravarty T, Henry TD, Kowalchuk G, Aguirre FV, Kereiakes DJ, Povsic TJ, Schatz R, Traverse JH, Pogoda J, Smith RD, Marbán L, Marbán E, Lima JAC. Effect of cardiosphere-derived cells on segmental myocardial function after myocardial infarction: ALLSTAR randomised clinical trial. Open Heart 2021; 8:e001614. [PMID: 34233913 PMCID: PMC8264869 DOI: 10.1136/openhrt-2021-001614] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Accepted: 06/01/2021] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Most cell therapy trials failed to show an improvement in global left ventricular (LV) function measures after myocardial infarction (MI). Myocardial segments are heterogeneously impacted by MI. Global LV function indices are not able to detect the small treatment effects on segmental myocardial function which may have prognostic implications for cardiac events. We aimed to test the efficacy of allogeneic cardiosphere-derived cells (CDCs) for improving regional myocardial function and contractility. METHODS In this exploratory analysis of a randomised clinical trial, 142 patients with post-MI with LVEF <45% and 15% or greater LV scar size were randomised in 2:1 ratio to receive intracoronary infusion of allogenic CDCs or placebo, respectively. Change in segmental myocardial circumferential strain (Ecc) by MRI from baseline to 6 months was compared between CDCs and placebo groups. RESULTS In total, 124 patients completed the 6-month follow-up (mean (SD) age 54.3 (10.8) and 108 (87.1%) men). Segmental Ecc improvement was significantly greater in patients receiving CDC (-0.5% (4.0)) compared with placebo (0.2% (3.7), p=0.05). The greatest benefit for improvement in segmental Ecc was observed in segments containing scar tissue (change in segmental Ecc of -0.7% (3.5) in patients receiving CDC vs 0.04% (3.7) in the placebo group, p=0.04). CONCLUSIONS In patients with post-MI LV dysfunction, CDC administration resulted in improved segmental myocardial function. Our findings highlight the importance of segmental myocardial function indices as an endpoint in future clinical trials of patients with post-MI. TRIAL REGISTRATION NUMBER NCT01458405.
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Affiliation(s)
- Mohammad R Ostovaneh
- Division of Cardiology, Johns Hopkins University, Baltimore, Maryland, USA
- Department of Medicine, Penn State Milton S Hershey Medical Center, Hershey, Pennsylvania, USA
| | - Raj R Makkar
- Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angles, California, USA
| | | | | | - Tarun Chakravarty
- Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angles, California, USA
| | | | - Glen Kowalchuk
- Sanger Heart and Vascular Institute, Charlotte, North Carolina, USA
| | | | | | - Thomas J Povsic
- Duke Clinical Research Institute and Duke Medicine, Durham, North Carolina, USA
| | | | - Jay H Traverse
- Minneapolis Heart Institute Foundation, Minneapolis, Minnesota, USA
| | - Janice Pogoda
- Cipher Biostatistics and Reporting, Reno, Nevada, USA
| | | | - Linda Marbán
- Capricor Therapeutics Inc, Los Angles, California, USA
| | - Eduardo Marbán
- Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angles, California, USA
| | - Joao A C Lima
- Division of Cardiology, Johns Hopkins University, Baltimore, Maryland, USA
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CMR-Based Risk Stratification of Sudden Cardiac Death and Use of Implantable Cardioverter-Defibrillator in Non-Ischemic Cardiomyopathy. Int J Mol Sci 2021; 22:ijms22137115. [PMID: 34281168 PMCID: PMC8268120 DOI: 10.3390/ijms22137115] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 06/27/2021] [Accepted: 06/29/2021] [Indexed: 01/04/2023] Open
Abstract
Non-ischemic cardiomyopathy (NICM) is one of the most important entities for arrhythmias and sudden cardiac death (SCD). Previous studies suggest a lower benefit of implantable cardioverter–defibrillator (ICD) therapy in patients with NICM as compared to ischemic cardiomyopathy (ICM). Nevertheless, current guidelines do not differentiate between the two subgroups in recommending ICD implantation. Hence, risk stratification is required to determine the subgroup of patients with NICM who will likely benefit from ICD therapy. Various predictors have been proposed, among others genetic mutations, left-ventricular ejection fraction (LVEF), left-ventricular end-diastolic volume (LVEDD), and T-wave alternans (TWA). In addition to these parameters, cardiovascular magnetic resonance imaging (CMR) has the potential to further improve risk stratification. CMR allows the comprehensive analysis of cardiac function and myocardial tissue composition. A range of CMR parameters have been associated with SCD. Applicable examples include late gadolinium enhancement (LGE), T1 relaxation times, and myocardial strain. This review evaluates the epidemiological aspects of SCD in NICM, the role of CMR for risk stratification, and resulting indications for ICD implantation.
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Ghannam M, Liang JJ, Attili A, Cochet H, Jais P, Latchamsetty R, Jongnarangsin K, Morady F, Bogun F. Cardiac Magnetic Resonance Imaging and Ventricular Tachycardias Involving the Sinuses of Valsalva in Patients With Nonischemic Cardiomyopathy. JACC Clin Electrophysiol 2021; 7:1243-1253. [PMID: 34217653 DOI: 10.1016/j.jacep.2021.03.017] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 03/22/2021] [Accepted: 03/23/2021] [Indexed: 11/17/2022]
Abstract
OBJECTIVES The goal of this study was to investigate the relationship between cardiac scar on late gadolinium enhancement cardiac resonance imaging (LGE-CMR) and the presence of ventricular tachycardia (VT) ablation target sites within the sinuses of Valsalva (SV). BACKGROUND Patients with idiopathic dilated cardiomyopathy (IDCM) often have scarring involving the basal myocardium, including the SV, allowing targeting of VTs from within the SV. METHODS Forty-three consecutive patients with IDCM underwent a VT ablation procedure with pre-procedure LGE-CMR. Retrospectively, scar characteristics were compared between patients with and without VT target sites in the SV. The ratio between SV-related scarring and the total cardiac scarring was defined as the SV scar index: SV-related scarring/total cardiac scarring. RESULTS VT target sites were identified in the SV in 22 (51%) of 43 patients. LGE-CMR identified peri-aortic scarring involving the SV in 34 patients (79%). Scarring extended to the septum in 26 patients, involved the lateral basal wall in 4, and both areas in 13 patients. Scar volume within the SV was larger in patients with SV-VT targets (1.7 ± 0.9 cm3 vs. 0.7 ± 0.6 cm3; p < 0.0001) compared with other patients. A cutoff scar volume identifying SV-VT targets was 1.23 cm3 in the short-axis view (area under the curve 0.82; sensitivity 0.64; specificity 0.91). The SV scar index was significantly greater in patients who had SV-VT target sites (0.33 ± 0.2 vs. 0.09 ± 0.09; p < 0.0001). CONCLUSIONS Patients with IDCM undergoing ablation of VT often have peri-aortic scarring visualized on LGE-CMR. Both the presence and the extent of scarring adjacent to the aortic annulus are associated with the presence of VT target sites within the SV.
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Affiliation(s)
- Michael Ghannam
- Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Jackson J Liang
- Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Anil Attili
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Hubert Cochet
- Bordeaux University Hospital and University of Bordeaux, Bordeaux, France; INRIA, Sophia Antipolis, France
| | - Pierre Jais
- Bordeaux University Hospital and University of Bordeaux, Bordeaux, France; INRIA, Sophia Antipolis, France
| | - Rakesh Latchamsetty
- Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Krit Jongnarangsin
- Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Fred Morady
- Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Frank Bogun
- Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, Michigan, USA.
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van der Velde N, Hassing HC, Bakker BJ, Wielopolski PA, Lebel RM, Janich MA, Kardys I, Budde RPJ, Hirsch A. Improvement of late gadolinium enhancement image quality using a deep learning-based reconstruction algorithm and its influence on myocardial scar quantification. Eur Radiol 2021; 31:3846-3855. [PMID: 33219845 PMCID: PMC8128730 DOI: 10.1007/s00330-020-07461-w] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Revised: 10/09/2020] [Accepted: 11/03/2020] [Indexed: 11/29/2022]
Abstract
OBJECTIVES The aim of this study was to assess the effect of a deep learning (DL)-based reconstruction algorithm on late gadolinium enhancement (LGE) image quality and to evaluate its influence on scar quantification. METHODS Sixty patients (46 ± 17 years, 50% male) with suspected or known cardiomyopathy underwent CMR. Short-axis LGE images were reconstructed using the conventional reconstruction and a DL network (DLRecon) with tunable noise reduction (NR) levels from 0 to 100%. Image quality of standard LGE images and DLRecon images with 75% NR was scored using a 5-point scale (poor to excellent). In 30 patients with LGE, scar size was quantified using thresholding techniques with different standard deviations (SD) above remote myocardium, and using full width at half maximum (FWHM) technique in images with varying NR levels. RESULTS DLRecon images were of higher quality than standard LGE images (subjective quality score 3.3 ± 0.5 vs. 3.6 ± 0.7, p < 0.001). Scar size increased with increasing NR levels using the SD methods. With 100% NR level, scar size increased 36%, 87%, and 138% using 2SD, 4SD, and 6SD quantification method, respectively, compared to standard LGE images (all p values < 0.001). However, with the FWHM method, no differences in scar size were found (p = 0.06). CONCLUSIONS LGE image quality improved significantly using a DL-based reconstruction algorithm. However, this algorithm has an important impact on scar quantification depending on which quantification technique is used. The FWHM method is preferred because of its independency of NR. Clinicians should be aware of this impact on scar quantification, as DL-based reconstruction algorithms are being used. KEY POINTS • The image quality based on (subjective) visual assessment and image sharpness of late gadolinium enhancement images improved significantly using a deep learning-based reconstruction algorithm that aims to reconstruct high signal-to-noise images using a denoising technique. • Special care should be taken when scar size is quantified using thresholding techniques with different standard deviations above remote myocardium because of the large impact of these advanced image enhancement algorithms. • The full width at half maximum method is recommended to quantify scar size when deep learning algorithms based on noise reduction are used, as this method is the least sensitive to the level of noise and showed the best agreement with visual late gadolinium enhancement assessment.
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Affiliation(s)
- Nikki van der Velde
- Department of Cardiology, Erasmus MC, University Medical Center Rotterdam, Dr. Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - H Carlijne Hassing
- Department of Cardiology, Erasmus MC, University Medical Center Rotterdam, Dr. Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Brendan J Bakker
- Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Piotr A Wielopolski
- Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | | | | | - Isabella Kardys
- Department of Cardiology, Erasmus MC, University Medical Center Rotterdam, Dr. Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
| | - Ricardo P J Budde
- Department of Cardiology, Erasmus MC, University Medical Center Rotterdam, Dr. Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Alexander Hirsch
- Department of Cardiology, Erasmus MC, University Medical Center Rotterdam, Dr. Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands.
- Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
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Fully Automatic Scar Segmentation for Late Gadolinium Enhancement MRI Images in Left Ventricle with Myocardial Infarction. Curr Med Sci 2021; 41:398-404. [PMID: 33877559 DOI: 10.1007/s11596-021-2360-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2020] [Accepted: 10/21/2020] [Indexed: 12/31/2022]
Abstract
Numerous methods have been published to segment the infarct tissue in the left ventricle, most of them either need manual work, post-processing, or suffer from poor reproducibility. We proposed an automatic segmentation method for segmenting the infarct tissue in left ventricle with myocardial infarction. Cardiac images of a total of 60 diseased hearts (55 human hearts and 5 porcine hearts) were used in this study. The epicardial and endocardial boundaries of the ventricles in every 2D slice of the cardiac magnetic resonance with late gadolinium enhancement images were manually segmented. The subsequent pipeline of infarct tissue segmentation is fully automatic. The segmentation results with the automatic algorithm proposed in this paper were compared to the consensus ground truth. The median of Dice overlap between our automatic method and the consensus ground truth is 0.79. We also compared the automatic method with the consensus ground truth using different image sources from different centers with different scan parameters and different scan machines. The results showed that the Dice overlap with the public dataset was 0.83, and the overall Dice overlap was 0.79. The results show that our method is robust with respect to different MRI image sources, which were scanned by different centers with different image collection parameters. The segmentation accuracy we obtained is comparable to or better than that of the conventional semi-automatic methods. Our segmentation method may be useful for processing large amount of dataset in clinic.
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50
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Suwa K. Editorial for "Improved Quantification of Myocardium Scar in Late Gadolinium Enhancement Images: Deep Learning Based Image Fusion Approach". J Magn Reson Imaging 2021; 54:313-314. [PMID: 33783051 DOI: 10.1002/jmri.27619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 03/19/2021] [Indexed: 11/09/2022] Open
Affiliation(s)
- Kenichiro Suwa
- Division of Cardiology, Internal Medicine 3, Hamamatsu University School of Medicine, Hamamatsu, Japan
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