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Basha M, Stavropoulou E, Nikolaidou A, Dividis G, Peteinidou E, Tsioufis P, Kamperidis N, Dimitriadis K, Karamitsos T, Giannakoulas G, Tsioufis K, Ziakas A, Kamperidis V. Diagnosing Heart Failure with Preserved Ejection Fraction in Obese Patients. J Clin Med 2025; 14:1980. [PMID: 40142788 PMCID: PMC11943257 DOI: 10.3390/jcm14061980] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2025] [Revised: 03/09/2025] [Accepted: 03/11/2025] [Indexed: 03/28/2025] Open
Abstract
Obesity is a current pandemic that sets all affected individuals at risk of heart failure (HF), and the majority of them will develop the clinical syndrome of HF with preserved ejection fraction (HFpEF). The diagnosis of HFpEF is challenging as it is based on the detection of subtle functional and structural remodeling of the heart that leads to diastolic dysfunction with increased left ventricular (LV) filling pressures and raised natriuretic peptides (NPs). The accurate diagnosis of HFpEF is even more challenging in patients who are obese, since the echocardiographic imaging quality may be suboptimal, the parameters for the evaluation of cardiac structure are indexed to the body surface area (BSA) and thus may underestimate the severity of the remodeling, and the NPs in patients who are obese have a lower normal threshold. Moreover, patients who are obese are prone to atrial fibrillation (AF) and pulmonary hypertension (PH), making the evaluation of diastolic dysfunction more strenuous. The current review aims to offer insights on the accurate diagnosis of HFpEF in patients who are obese in different clinical scenarios-patients who are obese in different clinical scenarios-such as in sinus rhythm, in atrial fibrillation, and in the case of pulmonary hypertension-by applying multimodality imaging and clinical diagnostic algorithms.
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Affiliation(s)
- Marino Basha
- 1st Department of Cardiology, AHEPA Hospital, School of Medicine, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece; (M.B.); (E.S.); (A.N.); (G.D.); (E.P.); (T.K.); (G.G.); (A.Z.)
| | - Evdoxia Stavropoulou
- 1st Department of Cardiology, AHEPA Hospital, School of Medicine, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece; (M.B.); (E.S.); (A.N.); (G.D.); (E.P.); (T.K.); (G.G.); (A.Z.)
| | - Anastasia Nikolaidou
- 1st Department of Cardiology, AHEPA Hospital, School of Medicine, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece; (M.B.); (E.S.); (A.N.); (G.D.); (E.P.); (T.K.); (G.G.); (A.Z.)
| | - Georgios Dividis
- 1st Department of Cardiology, AHEPA Hospital, School of Medicine, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece; (M.B.); (E.S.); (A.N.); (G.D.); (E.P.); (T.K.); (G.G.); (A.Z.)
| | - Emmanouela Peteinidou
- 1st Department of Cardiology, AHEPA Hospital, School of Medicine, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece; (M.B.); (E.S.); (A.N.); (G.D.); (E.P.); (T.K.); (G.G.); (A.Z.)
| | - Panagiotis Tsioufis
- 1st Department of Cardiology, Ippokrateion Hospital, School of Medicine, National and Kapodistrial University of Athens, 11528 Athens, Greece; (P.T.); (K.D.); (K.T.)
| | - Nikolaos Kamperidis
- Department of IBD, St. Mark’s Hospital, Imperial College London, London HA1 3UJ, UK;
| | - Kyriakos Dimitriadis
- 1st Department of Cardiology, Ippokrateion Hospital, School of Medicine, National and Kapodistrial University of Athens, 11528 Athens, Greece; (P.T.); (K.D.); (K.T.)
| | - Theodoros Karamitsos
- 1st Department of Cardiology, AHEPA Hospital, School of Medicine, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece; (M.B.); (E.S.); (A.N.); (G.D.); (E.P.); (T.K.); (G.G.); (A.Z.)
| | - George Giannakoulas
- 1st Department of Cardiology, AHEPA Hospital, School of Medicine, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece; (M.B.); (E.S.); (A.N.); (G.D.); (E.P.); (T.K.); (G.G.); (A.Z.)
| | - Konstantinos Tsioufis
- 1st Department of Cardiology, Ippokrateion Hospital, School of Medicine, National and Kapodistrial University of Athens, 11528 Athens, Greece; (P.T.); (K.D.); (K.T.)
| | - Antonios Ziakas
- 1st Department of Cardiology, AHEPA Hospital, School of Medicine, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece; (M.B.); (E.S.); (A.N.); (G.D.); (E.P.); (T.K.); (G.G.); (A.Z.)
| | - Vasileios Kamperidis
- 1st Department of Cardiology, AHEPA Hospital, School of Medicine, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece; (M.B.); (E.S.); (A.N.); (G.D.); (E.P.); (T.K.); (G.G.); (A.Z.)
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Al Younis SM, Hadjileontiadis LJ, Khandoker AH, Stefanini C, Soulaidopoulos S, Arsenos P, Doundoulakis I, Gatzoulis KA, Tsioufis K. Prediction of heart failure patients with distinct left ventricular ejection fraction levels using circadian ECG features and machine learning. PLoS One 2024; 19:e0302639. [PMID: 38739639 PMCID: PMC11090346 DOI: 10.1371/journal.pone.0302639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Accepted: 04/09/2024] [Indexed: 05/16/2024] Open
Abstract
Heart failure (HF) encompasses a diverse clinical spectrum, including instances of transient HF or HF with recovered ejection fraction, alongside persistent cases. This dynamic condition exhibits a growing prevalence and entails substantial healthcare expenditures, with anticipated escalation in the future. It is essential to classify HF patients into three groups based on their ejection fraction: reduced (HFrEF), mid-range (HFmEF), and preserved (HFpEF), such as for diagnosis, risk assessment, treatment choice, and the ongoing monitoring of heart failure. Nevertheless, obtaining a definitive prediction poses challenges, requiring the reliance on echocardiography. On the contrary, an electrocardiogram (ECG) provides a straightforward, quick, continuous assessment of the patient's cardiac rhythm, serving as a cost-effective adjunct to echocardiography. In this research, we evaluate several machine learning (ML)-based classification models, such as K-nearest neighbors (KNN), neural networks (NN), support vector machines (SVM), and decision trees (TREE), to classify left ventricular ejection fraction (LVEF) for three categories of HF patients at hourly intervals, using 24-hour ECG recordings. Information from heterogeneous group of 303 heart failure patients, encompassing HFpEF, HFmEF, or HFrEF classes, was acquired from a multicenter dataset involving both American and Greek populations. Features extracted from ECG data were employed to train the aforementioned ML classification models, with the training occurring in one-hour intervals. To optimize the classification of LVEF levels in coronary artery disease (CAD) patients, a nested cross-validation approach was employed for hyperparameter tuning. HF patients were best classified using TREE and KNN models, with an overall accuracy of 91.2% and 90.9%, and average area under the curve of the receiver operating characteristics (AUROC) of 0.98, and 0.99, respectively. Furthermore, according to the experimental findings, the time periods of midnight-1 am, 8-9 am, and 10-11 pm were the ones that contributed to the highest classification accuracy. The results pave the way for creating an automated screening system tailored for patients with CAD, utilizing optimal measurement timings aligned with their circadian cycles.
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Affiliation(s)
- Sona M. Al Younis
- Department of Biomedical Engineering, Healthcare Engineering Innovation Centre (HEIC), Khalifa University, Abu Dhabi, United Arab Emirates
| | - Leontios J. Hadjileontiadis
- Department of Biomedical Engineering, Healthcare Engineering Innovation Centre (HEIC), Khalifa University, Abu Dhabi, United Arab Emirates
- Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Ahsan H. Khandoker
- Department of Biomedical Engineering, Healthcare Engineering Innovation Centre (HEIC), Khalifa University, Abu Dhabi, United Arab Emirates
| | - Cesare Stefanini
- Creative Engineering Design Lab at the BioRobotics Institute, Applied Experimental Sciences Scuola Superiore Sant’Anna, Pontedera (Pisa), Italy
| | - Stergios Soulaidopoulos
- First Cardiology Department, School of Medicine, “Hippokration” General Hospital, National and Kapodistrian University of Athens, Athens, Greece
| | - Petros Arsenos
- First Cardiology Department, School of Medicine, “Hippokration” General Hospital, National and Kapodistrian University of Athens, Athens, Greece
| | - Ioannis Doundoulakis
- First Cardiology Department, School of Medicine, “Hippokration” General Hospital, National and Kapodistrian University of Athens, Athens, Greece
| | - Konstantinos A. Gatzoulis
- First Cardiology Department, School of Medicine, “Hippokration” General Hospital, National and Kapodistrian University of Athens, Athens, Greece
| | - Konstantinos Tsioufis
- First Cardiology Department, School of Medicine, “Hippokration” General Hospital, National and Kapodistrian University of Athens, Athens, Greece
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Al Younis SM, Hadjileontiadis LJ, Al Shehhi AM, Stefanini C, Alkhodari M, Soulaidopoulos S, Arsenos P, Doundoulakis I, Gatzoulis KA, Tsioufis K, Khandoker AH. Investigating automated regression models for estimating left ventricular ejection fraction levels in heart failure patients using circadian ECG features. PLoS One 2023; 18:e0295653. [PMID: 38079417 PMCID: PMC10712857 DOI: 10.1371/journal.pone.0295653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 11/22/2023] [Indexed: 12/18/2023] Open
Abstract
Heart Failure (HF) significantly impacts approximately 26 million people worldwide, causing disruptions in the normal functioning of their hearts. The estimation of left ventricular ejection fraction (LVEF) plays a crucial role in the diagnosis, risk stratification, treatment selection, and monitoring of heart failure. However, achieving a definitive assessment is challenging, necessitating the use of echocardiography. Electrocardiogram (ECG) is a relatively simple, quick to obtain, provides continuous monitoring of patient's cardiac rhythm, and cost-effective procedure compared to echocardiography. In this study, we compare several regression models (support vector machine (SVM), extreme gradient boosting (XGBOOST), gaussian process regression (GPR) and decision tree) for the estimation of LVEF for three groups of HF patients at hourly intervals using 24-hour ECG recordings. Data from 303 HF patients with preserved, mid-range, or reduced LVEF were obtained from a multicentre cohort (American and Greek). ECG extracted features were used to train the different regression models in one-hour intervals. To enhance the best possible LVEF level estimations, hyperparameters tuning in nested loop approach was implemented (the outer loop divides the data into training and testing sets, while the inner loop further divides the training set into smaller sets for cross-validation). LVEF levels were best estimated using rational quadratic GPR and fine decision tree regression models with an average root mean square error (RMSE) of 3.83% and 3.42%, and correlation coefficients of 0.92 (p<0.01) and 0.91 (p<0.01), respectively. Furthermore, according to the experimental findings, the time periods of midnight-1 am, 8-9 am, and 10-11 pm demonstrated to be the lowest RMSE values between the actual and predicted LVEF levels. The findings could potentially lead to the development of an automated screening system for patients with coronary artery disease (CAD) by using the best measurement timings during their circadian cycles.
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Affiliation(s)
- Sona M. Al Younis
- Department of Biomedical Engineering, Healthcare Engineering Innovation Centre (HEIC), Khalifa University, Abu Dhabi, United Arab Emirates
| | - Leontios J. Hadjileontiadis
- Department of Biomedical Engineering, Healthcare Engineering Innovation Centre (HEIC), Khalifa University, Abu Dhabi, United Arab Emirates
- Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Aamna M. Al Shehhi
- Department of Biomedical Engineering, Healthcare Engineering Innovation Centre (HEIC), Khalifa University, Abu Dhabi, United Arab Emirates
| | - Cesare Stefanini
- Creative Engineering Design Lab at the BioRobotics Institute, Applied Experimental Sciences Scuola Superiore Sant’Anna, Pontedera (Pisa), Italy
| | - Mohanad Alkhodari
- Department of Biomedical Engineering, Healthcare Engineering Innovation Centre (HEIC), Khalifa University, Abu Dhabi, United Arab Emirates
- Cardiovascular Clinical Research Facility, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Stergios Soulaidopoulos
- First Cardiology Department, School of Medicine, “Hippokration” General Hospital, National and Kapodistrian University of Athens, Athens, Greece
| | - Petros Arsenos
- First Cardiology Department, School of Medicine, “Hippokration” General Hospital, National and Kapodistrian University of Athens, Athens, Greece
| | - Ioannis Doundoulakis
- First Cardiology Department, School of Medicine, “Hippokration” General Hospital, National and Kapodistrian University of Athens, Athens, Greece
| | - Konstantinos A. Gatzoulis
- First Cardiology Department, School of Medicine, “Hippokration” General Hospital, National and Kapodistrian University of Athens, Athens, Greece
| | - Konstantinos Tsioufis
- First Cardiology Department, School of Medicine, “Hippokration” General Hospital, National and Kapodistrian University of Athens, Athens, Greece
| | - Ahsan H. Khandoker
- Department of Biomedical Engineering, Healthcare Engineering Innovation Centre (HEIC), Khalifa University, Abu Dhabi, United Arab Emirates
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Yogev D, Tejman-Yarden S, Feinberg O, Parmet Y, Goldberg T, Illouz S, Nagar N, Freidin D, Vazgovsky O, Chatterji S, Salem Y, Katz U, Goitein O. Proof of concept: Comparative accuracy of semiautomated VR modeling for volumetric analysis of the heart ventricles. Heliyon 2022; 8:e11250. [PMID: 36387466 PMCID: PMC9641195 DOI: 10.1016/j.heliyon.2022.e11250] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 10/12/2022] [Accepted: 10/20/2022] [Indexed: 11/06/2022] Open
Abstract
Introduction Simpson's rule is generally used to estimate cardiac volumes. By contrast, modern methods such as Virtual Reality (VR) utilize mesh modeling to present the object's surface spatial structure, thus enabling intricate volumetric calculations. In this study, two types of semiautomated VR models for cardiac volumetric analysis were compared to the standard Philips dedicated cardiac imaging platform (PDP) which is based on Simpson's rule calculations. Methods This retrospective report examined the cardiac computed tomography angiography (CCTA) of twenty patients with atrial fibrillation obtained prior to a left atrial appendage occlusion procedure. We employed two VR models to evaluate each CCTA and compared them to the PDP: a VR model with Philips-similar segmentations (VR-PS) that included the trabeculae and the papillary muscles within the luminal volume, and a VR model that only included the inner blood pool (VR-IBP). Results Comparison of the VR-PS and the PDP left ventricle (LV) volumes demonstrated excellent correlation with a ρc of 0.983 (95% CI 0.96, 0.99), and a small mean difference and range. The calculated volumes of the right ventricle (RV) had a somewhat lower correlation of 0.89 (95% CI 0.781, 0.95), a small mean difference, and a broader range. The VR-IBP chamber size estimations were significantly smaller than the estimates based on the PDP. Discussion Simpson's rule and polygon summation algorithms produce similar results in normal morphological LVs. However, this correlation failed to emerge when applied to RVs and irregular chambers. Conclusions The findings suggest that the polygon summation method is preferable for RV and irregular LV volume and function calculations.
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Affiliation(s)
- David Yogev
- The Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
- The Engineering Medical Research Lab, Sheba Medical Center, Ramat Gan, Israel
| | - Shai Tejman-Yarden
- The Engineering Medical Research Lab, Sheba Medical Center, Ramat Gan, Israel
- The Edmond J. Safra International Congenital Heart Center, Sheba Medical Center, Ramat Gan, Israel
- Corresponding author.
| | - Omer Feinberg
- The Engineering Medical Research Lab, Sheba Medical Center, Ramat Gan, Israel
| | - Yisrael Parmet
- Department of Industrial Engineering and Management, Ben Gurion University, Beer Sheva, Israel
| | - Tomer Goldberg
- The Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Shay Illouz
- The Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
- The Engineering Medical Research Lab, Sheba Medical Center, Ramat Gan, Israel
| | - Netanel Nagar
- The Engineering Medical Research Lab, Sheba Medical Center, Ramat Gan, Israel
- Industrial Design Department, Bezalel Academy of Art and Design, Jerusalem, Israel
| | - Dor Freidin
- The Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
- The Engineering Medical Research Lab, Sheba Medical Center, Ramat Gan, Israel
| | - Oliana Vazgovsky
- The Engineering Medical Research Lab, Sheba Medical Center, Ramat Gan, Israel
- The Edmond J. Safra International Congenital Heart Center, Sheba Medical Center, Ramat Gan, Israel
| | - Sumit Chatterji
- The Pulmonology Unit, Sheba Medical Center, Ramat Gan, Israel
- Interventional Pulmonology Unit, Sheba Medical Center, Ramat Gan, Israel
| | - Yishay Salem
- The Edmond J. Safra International Congenital Heart Center, Sheba Medical Center, Ramat Gan, Israel
- The Leviev Heart Institute, Sheba Medical Center, Ramat Gan, Israel
| | - Uriel Katz
- The Edmond J. Safra International Congenital Heart Center, Sheba Medical Center, Ramat Gan, Israel
- The Leviev Heart Institute, Sheba Medical Center, Ramat Gan, Israel
| | - Orly Goitein
- Department of Diagnostic Imaging, Sheba Medical Center, Ramat Gan, Israel
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Dziri H, Cherni MA, Ben-Sellem D. New Hybrid Method for Left Ventricular Ejection Fraction Assessment from Radionuclide Ventriculography Images. Curr Med Imaging 2021; 17:623-633. [PMID: 33213328 DOI: 10.2174/1573405616666201118122509] [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: 05/13/2020] [Revised: 09/22/2020] [Accepted: 10/14/2020] [Indexed: 11/22/2022]
Abstract
BACKGROUND In this paper, we propose a new efficient method of radionuclide ventriculography image segmentation to estimate the left ventricular ejection fraction. This parameter is an important prognostic factor for diagnosing abnormal cardiac function. METHODS The proposed method combines the Chan-Vese and the mathematical morphology algorithms. It was applied to diastolic and systolic images obtained from the Nuclear Medicine Department of Salah AZAIEZ Institute. In order to validate our proposed method, we compare the obtained results to those of two methods present in the literature. The first one is based on mathematical morphology, while the second one uses the basic Chan-Vese algorithm. To evaluate the quality of segmentation, we compute accuracy, positive predictive value and area under the ROC curve. We also compare the left ventricle ejection fraction estimated by our method to that of the reference given by the software of the gamma-camera and validated by the expert, using Pearson's correlation coefficient, ANOVA test and linear regression. RESULTS Static results show that the proposed method is very efficient for the detection of the left ventricle. The accuracy was 98.60%, higher than that of the other two methods (95.52% and 98.50%). CONCLUSION Likewise, the positive predictive value was the highest (86.40% vs. 83.63% 71.82%). The area under the ROC curve was also the most important (0.998% vs. 0.926% 0.919%). On the other hand, Pearson's correlation coefficient was the highest (99% vs. 98% 37%). The correlation was significantly positive (p<0.001).
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Affiliation(s)
- Halima Dziri
- Universite de Tunis El Manar, Laboratoire de recherche en Biophysique et Technologies Medicales (LRBTM), Tunis, Tunisia
| | | | - Dorra Ben-Sellem
- Universite de Tunis El Manar, Laboratoire de recherche en Biophysique et Technologies Medicales (LRBTM), Tunis, Tunisia
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Alkhodari M, Jelinek HF, Werghi N, Hadjileontiadis LJ, Khandoker AH. Estimating Left Ventricle Ejection Fraction Levels Using Circadian Heart Rate Variability Features and Support Vector Regression Models. IEEE J Biomed Health Inform 2021; 25:746-754. [PMID: 32750938 DOI: 10.1109/jbhi.2020.3002336] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
OBJECTIVES The purpose of this study was to set an optimal fit of the estimated LVEF at hourly intervals from 24-hour ECG recordings and compare it with the fit based on two gold-standard guidelines. METHODS Support vector regression (SVR) models were applied to estimate LVEF from ECG derived heart rate variability (HRV) data in one-hour intervals from 24-hour ECG recordings of patients with either preserved, mid-range, or reduced LVEF, obtained from the Intercity Digital ECG Alliance (IDEAL) study. A step-wise feature selection approach was used to ensure the best possible estimations of LVEF levels. RESULTS The experimental results have shown that the lowest Root Mean Square Error (RMSE) between the original and estimated LVEF levels was during 3-4 am, 5-6 am and 6-7 pm. CONCLUSION The observations suggest these hours as possible times for intervention and optimal treatment outcomes. In addition, LVEF classifications following the ACCF/AHA guidelines leads to a more accurate assessment of mid-range LVEF. SIGNIFICANCE This study paves the way to explore the use of HRV features in the prediction of LVEF percentages as an indicator of disease progression, which may lead to an automated classification process for CAD patients.
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Abdel Samea ME, Zytoon AA, Abo Mostafa AMAE, Hassanein SAH. Global left ventricular function assessment by ECG-gated multi-detector CT (MDCT): revised role in relation to 2D transthoracic echocardiography. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2020; 51:83. [DOI: 10.1186/s43055-020-00204-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Accepted: 05/12/2020] [Indexed: 08/30/2023] Open
Abstract
Abstract
Background
An accurate and reproducible way for determining the left ventricular function is crucial to provide diagnostic and prognostic aspects of the pump activity of the heart. The MDCT of the heart can be that modality. We compared the 128 MDCT of fifty patients with their 2D echocardiography performed on the same day.
Results
Mean EF, ESV, EDV, and LV mass were 61.22 ± 9.50%, 70.23 ± 38.35, 172.22 ± 53.57, 164.63 ± 52.57 respectively on MDCT, and 61.14 ± 10.90%, 72.13 ± 32.69, 173.76 ± 62.45, 198.32 ± 72.54 respectively on echocardiography with moderate correlation in EF and good correlation in ventricular volumes (p < 0.05) using linear regression analysis. A Bland-Altman analysis showed that MDCT had slightly lower LFEF, LVESV, and LVEDV values with mean value of differences of 0.8, 2.4, and 2.28 respectively.
Conclusion
It is reasonable to use MDCT alone to assess LV function in patients already underwent coronary CT angiography.
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Toia P, La Grutta L, Sollami G, Clemente A, Gagliardo C, Galia M, Maffei E, Midiri M, Cademartiri F. Technical development in cardiac CT: current standards and future improvements-a narrative review. Cardiovasc Diagn Ther 2020; 10:2018-2035. [PMID: 33381441 DOI: 10.21037/cdt-20-527] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Non-invasive depiction of coronary arteries has been a great challenge for imaging specialists since the introduction of computed tomography (CT). Technological development together with improvements in spatial, temporal, and contrast resolution, progressively allowed implementation of the current clinical role of the CT assessment of coronary arteries. Several technological evolutions including hardware and software solutions of CT scanners have been developed to improve spatial and temporal resolution. The main challenges of cardiac computed tomography (CCT) are currently plaque characterization, functional assessment of stenosis and radiation dose reduction. In this review, we will discuss current standards and future improvements in CCT.
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Affiliation(s)
- Patrizia Toia
- Department of Biomedicine, Neurosciences and Advanced Diagnostic (BiND), University of Palermo, Palermo, Italy
| | - Ludovico La Grutta
- Department of Health Promotion Sciences Maternal and Infantile Care, Internal Medicine and Medical Specialities (ProMISE), University of Palermo, Palermo, Italy
| | - Giulia Sollami
- Department of Biomedicine, Neurosciences and Advanced Diagnostic (BiND), University of Palermo, Palermo, Italy
| | - Alberto Clemente
- Fondazione Toscana G. Monasterio CNR - Regione Toscana, Pisa and Massa, Italy
| | - Cesare Gagliardo
- Department of Biomedicine, Neurosciences and Advanced Diagnostic (BiND), University of Palermo, Palermo, Italy
| | - Massimo Galia
- Department of Biomedicine, Neurosciences and Advanced Diagnostic (BiND), University of Palermo, Palermo, Italy
| | - Erica Maffei
- Department of Radiology, Area Vasta 1, ASUR Marche, Urbino (PU), Italy
| | - Massimo Midiri
- Department of Biomedicine, Neurosciences and Advanced Diagnostic (BiND), University of Palermo, Palermo, Italy
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Szilveszter B, Nagy AI, Vattay B, Apor A, Kolossváry M, Bartykowszki A, Simon J, Drobni ZD, Tóth A, Suhai FI, Merkely B, Maurovich-Horvat P. Left ventricular and atrial strain imaging with cardiac computed tomography: Validation against echocardiography. J Cardiovasc Comput Tomogr 2020; 14:363-369. [DOI: 10.1016/j.jcct.2019.12.004] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2019] [Revised: 09/07/2019] [Accepted: 12/05/2019] [Indexed: 12/12/2022]
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Benameur N, Arous Y, Ben Abdallah N, Kraiem T. Comparison Between 3D Echocardiography and Cardiac Magnetic Resonance Imaging (CMRI) in the Measurement of Left Ventricular Volumes and Ejection Fraction. Curr Med Imaging 2020; 15:654-660. [PMID: 32008513 DOI: 10.2174/1573405614666180815115756] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2017] [Revised: 07/17/2018] [Accepted: 07/30/2018] [Indexed: 12/31/2022]
Abstract
BACKGROUND Echocardiography and Cardiac Magnetic Resonance Imaging (CMRI) are two noninvasive techniques for the evaluation of cardiac function for patients with coronary artery diseases. Although echocardiography is the commonly used technique in clinical practice for the assessment of cardiac function, the measurement of LV volumes and left ventricular ejection fraction (LVEF) by the use of this technique is still influenced by several factors inherent to the protocol acquisition, which may affect the accuracy of echocardiography in the measurement of global LV parameters. OBJECTIVE The aim of this study is to compare the end systolic volume (ESV), the end diastolic volume (EDV), and the LVEF values obtained with three dimensional echocardiography (3D echo) with those obtained by CMRI (3 Tesla) in order to estimate the accuracy of 3D echo in the assessment of cardiac function. METHODS 20 subjects, (9 controls, 6 with myocardial infarction, and 5 with myocarditis) with age varying from 18 to 58, underwent 3D echo and CMRI. LV volumes and LVEF were computed from CMRI using a stack of cine MRI images in a short axis view. The same parameters were calculated using the 3D echo. A linear regression analysis and Bland Altman diagrams were performed to evaluate the correlation and the degree of agreement between the measurements obtained by the two methods. RESULTS The obtained results show a strong correlation between the 3D echo and CMR in the measurement of functional parameters (r = 0.96 for LVEF values, r = 0.99 for ESV and r= 0.98 for EDV, p < 0.01 for all) with a little lower values of LV volumes and higher values of LVEF by 3D echo compared to CMRI. According to statistical analysis, there is a slight discrepancy between the measurements obtained by the two methods. CONCLUSION 3D echo represents an accurate noninvasive tool for the assessment of cardiac function. However, other studies should be conducted on a larger population including some complicated diagnostic cases.
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Affiliation(s)
- Narjes Benameur
- Laboratory of Biophysics and Medical Technologies, Higher Institute of Medical Technologies of Tunis, University of Tunis El Manar, Tunis, Tunisia
| | - Younes Arous
- Faculty of Medicine of Tunis, University of Tunis El Manar, Tunis, Tunisia
| | | | - Tarek Kraiem
- Faculty of Medicine of Tunis, University of Tunis El Manar, Tunis, Tunisia
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11
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Kim J, Kim S, Lee Y, Yoon H, Eom K. Contrast Echocardiography in two-dimensional left ventricular measurements: comparison with 256-row multi-detector computed tomography as a reference standard in Beagles. J Vet Sci 2020; 20:e45. [PMID: 31565888 PMCID: PMC6769328 DOI: 10.4142/jvs.2019.20.e45] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Revised: 06/20/2019] [Accepted: 07/17/2019] [Indexed: 12/30/2022] Open
Abstract
Unenhanced echocardiography (UE), commonly used in veterinary practice, is limited by left ventricular (LV) foreshortening and observer dependency. Contrast echocardiography (CE) was used to compare two-dimensional (2D) LV measurements made using UE and 256-row multi-detector computed tomography (MDCT) as a reference standard. Seven healthy beagle dogs were evaluated in this study. Measurements obtained using CE, including LV wall thickness, internal diameter, and longitudinal and transverse length, were significantly greater than those obtained using UE. Measurements of LV internal dimension in diastole (LVIDd) and systole (LVIDs) were significantly larger with CE compared UE. Regardless of the cardiac cycle, LV longitudinal (LVLd and LVLs) and transverse diameter (LVTDd and LVTDs) measurements were significantly different with CE and approximated values from MDCT. Among automatically calculated parameters, LV end-systolic volume and the relative wall thickness were significantly different between UE and CE. In CE, the correlation coefficients of 4 major parameters (r = 0.87 in LVIDd; 0.91 in LVIDs; 0.87 in LVLd; and 0.81 in LVLs) showed higher values compared to the UE (r = 0.68 in LVIDd, 0.71 in LVIDs, 0.69 in LVLd, and 0.35 in LVLs). Inter-observer agreement was highest for MDCT and higher for CE than UE. In conclusion, CE is more accurate and reproducible than UE in assessing 2D LV measurements and can overcome the limitations of UE including LV foreshortening and high observer dependency.
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Affiliation(s)
- Jaehwan Kim
- Helix Animal Medical Center, Seoul 06546, Korea
| | - Soyoung Kim
- Department of Veterinary Medical Imaging, College of Veterinary Medicine, Konkuk University, Seoul 05029, Korea
| | - Yeonhea Lee
- Department of Veterinary Medical Imaging, College of Veterinary Medicine, Konkuk University, Seoul 05029, Korea
| | - Hakyoung Yoon
- Department of Veterinary Medical Imaging, College of Veterinary Medicine, Konkuk University, Seoul 05029, Korea
| | - Kidong Eom
- Department of Veterinary Medical Imaging, College of Veterinary Medicine, Konkuk University, Seoul 05029, Korea.
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12
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Kato TS, Daimon M, Satoh T. Use of Cardiac Imaging to Evaluate Cardiac Function and Pulmonary Hemodynamics in Patients with Heart Failure. Curr Cardiol Rep 2019; 21:53. [PMID: 31076948 DOI: 10.1007/s11886-019-1138-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
PURPOSE OF REVIEW Noninvasive hemodynamic assessments in patients with heart failure (HF) are essential for appropriate diagnosis and establishment of the best treatment strategies. Recently, the impact of pulmonary circulation and right ventricular function on prognosis in HF patients has drawn increasing attention. In this article, we explore the usefulness of cardiac imaging for hemodynamic assessments, mainly focusing on echocardiographic evaluation. RECENT FINDINGS The reliability of Doppler echocardiography as a noninvasive alternative to Swan-Ganz catheterization has been well investigated with higher than 80% accuracy for estimating pulmonary artery pressure. Strain measurement and three-dimensional echocardiography are useful for evaluating right ventricular function together with pulmonary circulation. The accuracy of analyzing left and right ventricular functions by cardiac computed tomography and cardiac magnetic resonate imaging has also been established. These modalities can provide myocardial tissue information and allow calculation of the extracellular volume fraction as well. According to the rapid improvement of technologies, cardiac imaging has become an essential tool for hemodynamic evaluation in HF management.
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Affiliation(s)
- Tomoko S Kato
- Department of Medicine, Division of Cardiology, Showa University Koto Toyosu Hospital, 5-1-38 Toyosu, Koto-ku, Tokyo, 135-8577, Japan. .,Department of Cardiovascular Medicine, Juntendo University School of Medicine, Tokyo, Japan.
| | - Masao Daimon
- Department of Cardiovascular Medicine, The University of Tokyo Hospital, Tokyo, Japan.,Department of Clinical Laboratory, The University of Tokyo Hospital, Tokyo, Japan
| | - Toru Satoh
- Department of Cardiovascular Medicine, Kyorin University, Tokyo, Japan
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13
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Ribeiro ML, Jorge AJL, Nacif MS, Martins WDA. Early Detection and Monitoring of Cancer Chemotherapy-Related Left Ventricular Dysfunction by Imaging Methods. Arq Bras Cardiol 2019; 112:309-316. [PMID: 30916206 PMCID: PMC6424044 DOI: 10.5935/abc.20190022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2018] [Revised: 11/21/2018] [Accepted: 12/05/2018] [Indexed: 11/20/2022] Open
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14
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Fries RC, Gordon SG, Saunders AB, Miller MW, Hariu CD, Schaeffer DJ. Quantitative assessment of two- and three-dimensional transthoracic and two-dimensional transesophageal echocardiography, computed tomography, and magnetic resonance imaging in normal canine hearts. J Vet Cardiol 2018; 21:79-92. [PMID: 30797448 DOI: 10.1016/j.jvc.2018.09.005] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2018] [Revised: 09/08/2018] [Accepted: 09/20/2018] [Indexed: 11/29/2022]
Abstract
INTRODUCTION The objective of the study was to evaluate the accuracy of two- and three-dimensional (2D, 3D) transthoracic echocardiography (TTE), 2D transesophageal echocardiography, and computed tomography angiography (CTA) compared with cardiac magnetic resonance imaging (CMR) in normal dogs and to assess repeatability of 2D and 3D TTE for the assessment of left ventricular (LV) and left atrial (LA) dimensions. ANIMALS The study was performed on six healthy dogs. MATERIALS AND METHODS Transthoracic echocardiography, transesophageal echocardiography, CTA, and CMR were performed on each dog. Right ventricular (RV) and LV volumes (in systole and diastole), ejection fraction (EF), and LA and right atrial (RA) volumes were assessed. Repeatability and intrarater and interrater measurements of variability were quantified by average coefficient of variation (CV) for 2D and 3D TTE. RESULTS No clinically relevant differences in LV volume were detected between CMR and all modalities. Importantly, 3D TTE had the lowest CV (6.45%), correlated with (rs = 0.62, p = 0.01), and had the highest overlap in distribution with CMR (OVL >80%). Left ventricular EF and LA size via CTA compared best with CMR and RV and RA volumes were best estimated by 3D TTE. Assessment of LV and LA volumes via 3D TTE had moderate repeatability (15-21%) compared with LV M-mode measurements and 2D LA-to-aortic ratio (<10%), respectively. For LV size, interrater CV for 3D TTE (19.4%) was lower than 2D TTE (23.1%). CONCLUSIONS Measurements of LV, RV, and RA volumes via 3D TTE and LA volume and LV EF assessed by CTA compared best with CMR. Three-dimensional echocardiography had lower interrater and intrarater CV compared with 2D TTE.
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Affiliation(s)
- R C Fries
- Texas A&M University College of Veterinary Medicine and Biomedical Sciences, 4474 TAMU, College Station, TX 77843-4474, USA.
| | - S G Gordon
- Texas A&M University College of Veterinary Medicine and Biomedical Sciences, 4474 TAMU, College Station, TX 77843-4474, USA
| | - A B Saunders
- Texas A&M University College of Veterinary Medicine and Biomedical Sciences, 4474 TAMU, College Station, TX 77843-4474, USA
| | - M W Miller
- Texas A&M University College of Veterinary Medicine and Biomedical Sciences, 4474 TAMU, College Station, TX 77843-4474, USA
| | - C D Hariu
- Texas A&M University College of Veterinary Medicine and Biomedical Sciences, 4474 TAMU, College Station, TX 77843-4474, USA
| | - D J Schaeffer
- University of Illinois College of Veterinary Medicine, 1008 West Hazelwood Drive, Urbana, IL 61802, USA
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15
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CT-derived left ventricular global strain in aortic valve stenosis patients: A comparative analysis pre and post transcatheter aortic valve implantation. J Cardiovasc Comput Tomogr 2018; 12:240-244. [DOI: 10.1016/j.jcct.2018.01.010] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2017] [Revised: 01/10/2018] [Accepted: 01/23/2018] [Indexed: 11/19/2022]
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16
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Amin MI, Hassan HA, Mousa MI. Utility of 128-row multidetector CT in quantitative evaluation of global left ventricular function in patients with coronary artery disease. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2018. [DOI: 10.1016/j.ejrnm.2017.10.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
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Abstract
Cardiac computed tomography (CT) is increasingly used in the evaluation of cardiomyopathies, particularly in patients who are not able to undergo other non-invasive imaging tests such as magnetic resonance imaging (MRI) due to the presence of MRI-incompatible pacemakers/defibrillators or other contraindications or due to extensive artifacts from indwelling metallic devices. Advances in scanner technology enable acquisition of CT images with high spatial resolution, good temporal resolution, wide field of view and multi-planar reconstruction capabilities. CT is useful in cardiomyopathies in several ways, particularly in the evaluation of coronary arteries, characterization of cardiomyopathy phenotype, quantification of cardiac volumes and function, treatment-planning, and post-treatment evaluation. In this article, we review the imaging techniques and specific applications of CT in the evaluation of cardiomyopathies.
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Affiliation(s)
- Kevin Kalisz
- University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Prabhakar Rajiah
- Cardiothoracic Imaging, Radiology Department, UT Southwestern Medical Center, Dallas, Texas, USA
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18
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Vogel-Claussen J, Elshafee AS, Kirsch J, Brown RK, Hurwitz LM, Javidan-Nejad C, Julsrud PR, Kramer CM, Krishnamurthy R, Laroia AT, Leipsic JA, Panchal KK, Shah AB, White RD, Woodard PK, Abbara S. ACR Appropriateness Criteria ® Dyspnea—Suspected Cardiac Origin. J Am Coll Radiol 2017; 14:S127-S137. [DOI: 10.1016/j.jacr.2017.01.032] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2017] [Revised: 01/18/2017] [Accepted: 01/20/2017] [Indexed: 12/17/2022]
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Hulot JS, Salem JE, Redheuil A, Collet JP, Varnous S, Jourdain P, Logeart D, Gandjbakhch E, Bernard C, Hatem SN, Isnard R, Cluzel P, Le Feuvre C, Leprince P, Hammoudi N, Lemoine FM, Klatzmann D, Vicaut E, Komajda M, Montalescot G, Lompré AM, Hajjar RJ. Effect of intracoronary administration of AAV1/SERCA2a on ventricular remodelling in patients with advanced systolic heart failure: results from the AGENT-HF randomized phase 2 trial. Eur J Heart Fail 2017; 19:1534-1541. [DOI: 10.1002/ejhf.826] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/09/2017] [Revised: 02/17/2017] [Accepted: 03/03/2017] [Indexed: 12/25/2022] Open
Affiliation(s)
- Jean-Sébastien Hulot
- Sorbonne Universités, UPMC Univ Paris 06, AP-HP, CIC Paris-Est 1421, Institute of Cardiometabolism and Nutrition (ICAN); Pitié-Salpêtrière Hospital; F-75013 Paris France
| | - Joe-Elie Salem
- Sorbonne Universités, UPMC Univ Paris 06, AP-HP, CIC Paris-Est 1421, Institute of Cardiometabolism and Nutrition (ICAN); Pitié-Salpêtrière Hospital; F-75013 Paris France
| | - Alban Redheuil
- Sorbonne Universités, UPMC Univ Paris 06, AP-HP, CIC Paris-Est 1421, Institute of Cardiometabolism and Nutrition (ICAN); Pitié-Salpêtrière Hospital; F-75013 Paris France
| | - Jean-Philippe Collet
- Sorbonne Universités, UPMC Univ Paris 06, AP-HP, CIC Paris-Est 1421, Institute of Cardiometabolism and Nutrition (ICAN); Pitié-Salpêtrière Hospital; F-75013 Paris France
| | - Shaida Varnous
- Sorbonne Universités, UPMC Univ Paris 06, AP-HP, CIC Paris-Est 1421, Institute of Cardiometabolism and Nutrition (ICAN); Pitié-Salpêtrière Hospital; F-75013 Paris France
| | | | - Damien Logeart
- UMR-S 942, Université Paris Diderot, DHU FIRE, Department of Cardiology, Lariboisière Hospital; Assistance Publique-Hôpitaux de Paris (AP-HP); Paris France
| | - Estelle Gandjbakhch
- Sorbonne Universités, UPMC Univ Paris 06, AP-HP, CIC Paris-Est 1421, Institute of Cardiometabolism and Nutrition (ICAN); Pitié-Salpêtrière Hospital; F-75013 Paris France
| | - Claude Bernard
- Sorbonne Universités, UPMC Univ Paris 06, AP-HP; Clinical Investigation Center for Biotherapies and Inflammation-Immunopathology-Biotherapy Department; F-75013 Paris France
| | - Stéphane N. Hatem
- Sorbonne Universités, UPMC Univ Paris 06, AP-HP, CIC Paris-Est 1421, Institute of Cardiometabolism and Nutrition (ICAN); Pitié-Salpêtrière Hospital; F-75013 Paris France
| | - Richard Isnard
- Sorbonne Universités, UPMC Univ Paris 06, AP-HP, CIC Paris-Est 1421, Institute of Cardiometabolism and Nutrition (ICAN); Pitié-Salpêtrière Hospital; F-75013 Paris France
| | - Philippe Cluzel
- Sorbonne Universités, UPMC Univ Paris 06, AP-HP, CIC Paris-Est 1421, Institute of Cardiometabolism and Nutrition (ICAN); Pitié-Salpêtrière Hospital; F-75013 Paris France
| | - Claude Le Feuvre
- Sorbonne Universités, UPMC Univ Paris 06, AP-HP, CIC Paris-Est 1421, Institute of Cardiometabolism and Nutrition (ICAN); Pitié-Salpêtrière Hospital; F-75013 Paris France
| | - Pascal Leprince
- Sorbonne Universités, UPMC Univ Paris 06, AP-HP, CIC Paris-Est 1421, Institute of Cardiometabolism and Nutrition (ICAN); Pitié-Salpêtrière Hospital; F-75013 Paris France
| | - Nadjib Hammoudi
- Sorbonne Universités, UPMC Univ Paris 06, AP-HP, CIC Paris-Est 1421, Institute of Cardiometabolism and Nutrition (ICAN); Pitié-Salpêtrière Hospital; F-75013 Paris France
| | - François M. Lemoine
- Sorbonne Universités, UPMC Univ Paris 06, AP-HP; Clinical Investigation Center for Biotherapies and Inflammation-Immunopathology-Biotherapy Department; F-75013 Paris France
| | - David Klatzmann
- Sorbonne Universités, UPMC Univ Paris 06, AP-HP; Clinical Investigation Center for Biotherapies and Inflammation-Immunopathology-Biotherapy Department; F-75013 Paris France
| | - Eric Vicaut
- ACTION Study Group, Unité de Recherche Clinique, Lariboisière; Paris France
| | - Michel Komajda
- Sorbonne Universités, UPMC Univ Paris 06, AP-HP, CIC Paris-Est 1421, Institute of Cardiometabolism and Nutrition (ICAN); Pitié-Salpêtrière Hospital; F-75013 Paris France
| | - Gilles Montalescot
- Sorbonne Universités, UPMC Univ Paris 06, AP-HP, CIC Paris-Est 1421, Institute of Cardiometabolism and Nutrition (ICAN); Pitié-Salpêtrière Hospital; F-75013 Paris France
- ACTION Study Group, Unité de Recherche Clinique, Lariboisière; Paris France
| | - Anne-Marie Lompré
- Sorbonne Universités, UPMC Univ Paris 06, AP-HP, CIC Paris-Est 1421, Institute of Cardiometabolism and Nutrition (ICAN); Pitié-Salpêtrière Hospital; F-75013 Paris France
| | - Roger J. Hajjar
- Cardiovascular Research Center, Icahn School of Medicine at Mount Sinaï; New York NY USA
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Nair N, Gongora E. Role of cardiovascular imaging in selection of donor hearts. World J Transplant 2015; 5:348-353. [PMID: 26722663 PMCID: PMC4689946 DOI: 10.5500/wjt.v5.i4.348] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/28/2015] [Revised: 09/02/2015] [Accepted: 10/13/2015] [Indexed: 02/05/2023] Open
Abstract
AIM: To perform a systematic review of literature on use of cardiovascular imaging in assessment of donor hearts.
METHODS: A systematic search of current literature from January 1965 to August 2015 was performed using PubMed and Google Scholar to investigate the different imaging modalities used to assess donor hearts.
RESULTS: Recent literature still estimates only a 32% utilization of available donor hearts in the United States. Most common imaging modality used is transthoracic echocardiography. Use of advanced imaging modalities such as 3D echocardiography, cardiac computer tomography and cardiac magnetic resonance to evaluate donor hearts is not reported in literature. This review attempts to highlight the relevant imaging modalities that can be used to assess cardiac function in a time-efficient manner. The algorithm suggested in this review would hopefully pave the way to standardized protocols that can be adopted by organ procuring organizations to increase the donor pool.
CONCLUSION: Use of advanced imaging techniques for a thorough assessment of organs will likely increase the donor pool.
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