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Lin Y, Lan Y, Zheng Y, Ma M. Dual-energy CT for evaluating the tumor regression grade of gastric cancer after neoadjuvant chemotherapy. Eur Radiol 2025:10.1007/s00330-025-11508-1. [PMID: 40100398 DOI: 10.1007/s00330-025-11508-1] [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: 09/04/2024] [Revised: 01/19/2025] [Accepted: 02/14/2025] [Indexed: 03/20/2025]
Abstract
OBJECTIVES To evaluate the clinical value of dual-energy CT (DECT) parameters in estimating tumor regression grade (TRG) of gastric cancer after neoadjuvant chemotherapy (NAC). MATERIALS AND METHODS In this retrospective study, the patients with pathologically confirmed gastric cancer were classified into two groups based on TRG results: the effective group and the ineffective group. DECT parameters, including iodine concentration (IC), normalized iodine concentration (NIC), and slope of the energy spectrum curve (λ), were obtained. Quantitative parameters and their change rates were compared before and after chemotherapy. The receiver operating characteristic (ROC) curves were plotted. RESULTS A total of 54 patients were included and divided into the effective group (n = 21) and the ineffective group (n = 33). After NAC, the change rates of parameters in the venous phase (%ΔIC-v, %ΔNIC-v, and %Δλ-v) were notably higher in the effective group were higher than in the ineffective group (all p < 0.05). The consistency between the response evaluation criteria in solid tumors version 1.1 (RECIST 1.1) and TRG was fair, with a Kappa value of 0.299 (p < 0.05). The %ΔIC-v, %ΔIC-d, %ΔNIC-v, %ΔNIC-d, and %Δλ-v exhibited moderate or strong correlations with TRG, with correlation coefficients (r) of -0.624, -0.475, -0.766, -0.516, and -0.431, respectively (all p < 0.05). %ΔNIC-v achieved a significantly greater area under the curve (AUC) compared to RECIST 1.1 (AUC, 0.877; 95% CI: 0.772-0.957; vs AUC, 0.649; 95% CI: 0.496-0.803; p < 0.05) for estimating TRG in gastric cancer. CONCLUSION DECT parameters, particularly %ΔNIC-v, show promise in assessing the efficacy of NAC for gastric cancer. KEY POINTS Question Two-dimensional morphological change is insufficient for accurately assessing the pathological TRG following NAC in gastric cancer. Findings DECT parameters show higher preoperative predictive efficacy than RECIST 1.1 for TRG in gastric cancer. Clinical relevance DECT-derived quantitative parameters offer a reliable and noninvasive tool for the preoperative prediction of pathological response in gastric cancer patients undergoing NAC.
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Affiliation(s)
- Yuying Lin
- Department of Radiology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, China
| | - Yanfen Lan
- Department of Radiology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, China
| | - Yunyan Zheng
- Department of Radiology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, China
| | - Mingping Ma
- Department of Radiology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, China.
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Gong Z, Li J, Han Y, Chen S, Wang L. Nomogram combining dual-energy computed tomography features and radiomics for differentiating parotid warthin tumor from pleomorphic adenoma: a retrospective study. Front Oncol 2025; 15:1505385. [PMID: 40104493 PMCID: PMC11914106 DOI: 10.3389/fonc.2025.1505385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2024] [Accepted: 01/27/2025] [Indexed: 03/20/2025] Open
Abstract
Introduction Accurate differentiation between pleomorphic adenomas (PA) and Warthin tumors (WT) in the parotid gland is challenging owing to overlapping imaging features. This study aimed to evaluate a nomogram combining dual-energy computed tomography (DECT) quantitative parameters and radiomics to enhance diagnostic precision. Methods This retrospective study included 120 patients with pathologically confirmed PA or WT, randomly divided into training and test sets (7:3). DECT features, including tumor CT values from 70 keV virtual monochromatic images (VMIs), iodine concentration (IC), and normalized IC (NIC), were analyzed. Independent predictors were identified via logistic regression. Radiomic features were extracted from segmented regions of interest and filtered using the K-best and least absolute shrinkage and selection operator. Radiomic models based on 70 keV VMIs and material decomposition images were developed using logistic regression (LR), support vector machine (SVM), and random forest (RF). The best-performing radiomics model was combined with independent DECT predictors to construct a model and nomogram. Model performance was assessed using ROC curves, calibration curves, and decision curve analysis (DCA). Results IC (venous phase), NIC (arterial phase), and NIC (venous phase) were independent DECT predictors. The DECT feature model achieved AUCs of 0.842 and 0.853 in the training and test sets, respectively, outperforming the traditional radiomics model (AUCs 0.836 and 0.834, respectively). The DECT radiomics model using arterial phase water-based images with LR showed improved performance (AUCs 0.883 and 0.925). The combined model demonstrated the highest discrimination power, with AUCs of 0.910 and 0.947. The combined model outperformed the DECT features and conventional radiomics models, with AUCs of 0.910 and 0.947, respectively (P<0.05). While the difference in AUC between the combined model and the DECT radiomics model was not statistically significant (P>0.05), it showed higher specificity, accuracy, and precision. DCA found that the nomogram gave the greatest net therapeutic effect across a broad range of threshold probabilities. Discussion The nomogram combining DECT features and radiomics offers a promising non-invasive tool for differentiating PA and WT in clinical practice.
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Affiliation(s)
- Zhiwei Gong
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Jianying Li
- CT Imaging Research Center, GE Healthcare, Shanghai, China
| | - Yilin Han
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Shiyu Chen
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Lijun Wang
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
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Wang Y, Hu H, Ban X, Jiang Y, Su Y, Yang L, Shi G, Yang L, Han R, Duan X. Evaluation of Quantitative Dual-Energy Computed Tomography Parameters for Differentiation of Parotid Gland Tumors. Acad Radiol 2024; 31:2027-2038. [PMID: 37730491 DOI: 10.1016/j.acra.2023.08.024] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 08/15/2023] [Accepted: 08/19/2023] [Indexed: 09/22/2023]
Abstract
RATIONALE AND OBJECTIVES To assess the diagnostic performance of quantitative parameters from dual-energy CT (DECT) in differentiating parotid gland tumors (PGTs). MATERIALS AND METHODS 101 patients with 108 pathologically proved PGTs were enrolled and classified into four groups: pleomorphic adenomas (PAs), warthin tumors (WTs), other benign tumors (OBTs), and malignant tumors (MTs). Conventional CT attenuation and DECT quantitative parameters, including iodine concentration (IC), normalized iodine concentration (NIC), effective atomic number (Zeff), electron density (Rho), double energy index (DEI), and the slope of the spectral Hounsfield unit curve (λHU), were obtained and compared between benign tumors (BTs) and MTs, and further compared among the four subgroups. Logistic regression analysis was used to assess the independent parameters and the receiver operating characteristic (ROC) curves were used to analyze the diagnostic performance. RESULTS Attenuation, Zeff, DEI, IC, NIC, and λHU in the arterial phase (AP) and venous phase (VP) were higher in MTs than in BTs (p < 0.001-0.047). λHU in VP and Zeff in AP were independent predictors with an area under the curve (AUC) of 0.84 after the combination. Furthermore, attenuation, Zeff, DEI, IC, NIC, and λHU in the AP and VP of MTs were higher than those of PAs (p < 0.001-0.047). Zeff and NIC in AP and λHU in VP were independent predictors with an AUC of 0.93 after the combination. Attenuation and Rho in the precontrast phase; attenuation, Rho, Zeff, DEI, IC, NIC, and λHU in AP; and the Rho in the VP of PAs were lower than those of WTs (p < 0.001-0.03). Rho in the precontrast phase and attenuation in AP were independent predictors with an AUC of 0.89 after the combination. MTs demonstrated higher Zeff, DEI, IC, NIC, and λHU in VP and lower Rho in the precontrast phase compared with WTs (p < 0.001-0.04); but no independent predictors were found. CONCLUSION DECT quantitative parameters can help to differentiate PGTs.
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Affiliation(s)
- Yu Wang
- Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang Road West, Guangzhou 510120, Guangdong, China (Y.W., H.H., Y.J., Y.S., L.Y., G.S., L.Y., R.H., X.D.)
| | - Huijun Hu
- Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang Road West, Guangzhou 510120, Guangdong, China (Y.W., H.H., Y.J., Y.S., L.Y., G.S., L.Y., R.H., X.D.)
| | - Xiaohua Ban
- Department of Radiology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou 510060, Guangdong, China (X.B.)
| | - Yusong Jiang
- Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang Road West, Guangzhou 510120, Guangdong, China (Y.W., H.H., Y.J., Y.S., L.Y., G.S., L.Y., R.H., X.D.)
| | - Yun Su
- Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang Road West, Guangzhou 510120, Guangdong, China (Y.W., H.H., Y.J., Y.S., L.Y., G.S., L.Y., R.H., X.D.)
| | - Lingjie Yang
- Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang Road West, Guangzhou 510120, Guangdong, China (Y.W., H.H., Y.J., Y.S., L.Y., G.S., L.Y., R.H., X.D.)
| | - Guangzi Shi
- Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang Road West, Guangzhou 510120, Guangdong, China (Y.W., H.H., Y.J., Y.S., L.Y., G.S., L.Y., R.H., X.D.); Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Medical Research Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, Guangdong, China (G.S., X.D.)
| | - Lu Yang
- Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang Road West, Guangzhou 510120, Guangdong, China (Y.W., H.H., Y.J., Y.S., L.Y., G.S., L.Y., R.H., X.D.)
| | - Riyu Han
- Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang Road West, Guangzhou 510120, Guangdong, China (Y.W., H.H., Y.J., Y.S., L.Y., G.S., L.Y., R.H., X.D.)
| | - Xiaohui Duan
- Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang Road West, Guangzhou 510120, Guangdong, China (Y.W., H.H., Y.J., Y.S., L.Y., G.S., L.Y., R.H., X.D.); Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Medical Research Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, Guangdong, China (G.S., X.D.).
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Viswanathan DJ, Bhalla AS, Manchanda S, Roychoudhury A, Mishra D, Mridha AR. Characterization of tumors of jaw: Additive value of contrast enhancement and dual-energy computed tomography. World J Radiol 2024; 16:82-93. [PMID: 38690548 PMCID: PMC11056855 DOI: 10.4329/wjr.v16.i4.82] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Revised: 03/19/2024] [Accepted: 04/16/2024] [Indexed: 04/25/2024] Open
Abstract
BACKGROUND Currently, the differentiation of jaw tumors is mainly based on the lesion's morphology rather than the enhancement characteristics, which are important in the differentiation of neoplasms across the body. There is a paucity of literature on the enhancement characteristics of jaw tumors. This is mainly because, even though computed tomography (CT) is used to evaluate these lesions, they are often imaged without intravenous contrast. This study hypothesised that the enhancement characteristics of the solid component of jaw tumors can aid in the differentiation of these lesions in addition to their morphology by dual-energy CT, therefore improving the ability to differentiate between various pathologies. AIM To evaluate the role of contrast enhancement and dual-energy quantitative parameters in CT in the differentiation of jaw tumors. METHODS Fifty-seven patients with jaw tumors underwent contrast-enhanced dual-energy CT. Morphological analysis of the tumor, including the enhancing solid component, was done, followed by quantitative analysis of iodine concentration (IC), water concentration (WC), HU, and normalized IC. The study population was divided into four subgroups based on histopathological analysis-central giant cell granuloma (CGCG), ameloblastoma, odontogenic keratocyst (OKC), and other jaw tumors. A one-way ANOVA test for parametric variables and the Kruskal-Wallis test for non-parametric variables were used. If significant differences were found, a series of independent t-tests or Mann-Whitney U tests were used. RESULTS Ameloblastoma was the most common pathology (n = 20), followed by CGCG (n = 11) and OKC. CGCG showed a higher mean concentration of all quantitative parameters than ameloblastomas (P < 0.05). An IC threshold of 31.35 × 100 μg/cm3 had the maximum sensitivity (81.8%) and specificity (65%). Between ameloblastomas and OKC, the former showed a higher mean concentration of all quantitative parameters (P < 0.001), however when comparing unilocular ameloblastomas with OKCs, the latter showed significantly higher WC. Also, ameloblastoma had a higher IC and lower WC compared to "other jaw tumors" group. CONCLUSION Enhancement characteristics of solid components combined with dual-energy parameters offer a more precise way to differentiate between jaw tumors.
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Affiliation(s)
- Deepak Justine Viswanathan
- Department of Radiodiagnosis and Interventional Radiology, All India Institute of Medical Sciences, New Delhi 110029, India
| | - Ashu Seith Bhalla
- Department of Radiodiagnosis and Interventional Radiology, All India Institute of Medical Sciences, New Delhi 110029, India
| | - Smita Manchanda
- Department of Radiodiagnosis and Interventional Radiology, All India Institute of Medical Sciences, New Delhi 110029, India
| | - Ajoy Roychoudhury
- Department of Oral and Maxillofacial Surgery, All India Institute of Medical Sciences, New Delhi 110029, India
| | - Deepika Mishra
- Department of Oral Pathology and Microbiology, All India Institute of Medical Sciences, New Delhi 110029, India
| | - Asit Ranjan Mridha
- Department of Pathology, All India Institute of Medical Sciences, Ansari Nagar, New Delhi 110029, India
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Foti G, Ascenti G, Agostini A, Longo C, Lombardo F, Inno A, Modena A, Gori S. Dual-Energy CT in Oncologic Imaging. Tomography 2024; 10:299-319. [PMID: 38535766 PMCID: PMC10975567 DOI: 10.3390/tomography10030024] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Revised: 02/13/2024] [Accepted: 02/22/2024] [Indexed: 08/25/2024] Open
Abstract
Dual-energy CT (DECT) is an innovative technology that is increasingly widespread in clinical practice. DECT allows for tissue characterization beyond that of conventional CT as imaging is performed using different energy spectra that can help differentiate tissues based on their specific attenuation properties at different X-ray energies. The most employed post-processing applications of DECT include virtual monoenergetic images (VMIs), iodine density maps, virtual non-contrast images (VNC), and virtual non-calcium (VNCa) for bone marrow edema (BME) detection. The diverse array of images obtained through DECT acquisitions offers numerous benefits, including enhanced lesion detection and characterization, precise determination of material composition, decreased iodine dose, and reduced artifacts. These versatile applications play an increasingly significant role in tumor assessment and oncologic imaging, encompassing the diagnosis of primary tumors, local and metastatic staging, post-therapy evaluation, and complication management. This article provides a comprehensive review of the principal applications and post-processing techniques of DECT, with a specific focus on its utility in managing oncologic patients.
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Affiliation(s)
- Giovanni Foti
- Department of Radiology, IRCCS Ospedale Sacro Cuore Don Calabria, Via Don A. Sempreboni 5, 37024 Negrar, Italy; (C.L.); (F.L.)
| | - Giorgio Ascenti
- Department of Biomedical Sciences and Morphological and Functional Imaging, University Hospital Messina, 98122 Messina, Italy;
| | - Andrea Agostini
- Department of Clinical Special and Dental Sciences, University Politecnica delle Marche, 60126 Ancona, Italy
| | - Chiara Longo
- Department of Radiology, IRCCS Ospedale Sacro Cuore Don Calabria, Via Don A. Sempreboni 5, 37024 Negrar, Italy; (C.L.); (F.L.)
| | - Fabio Lombardo
- Department of Radiology, IRCCS Ospedale Sacro Cuore Don Calabria, Via Don A. Sempreboni 5, 37024 Negrar, Italy; (C.L.); (F.L.)
| | - Alessandro Inno
- Department of Oncology, IRCCS Ospedale Sacro Cuore Don Calabria, Via Don A. Sempreboni 5, 37024 Negrar, Italy; (A.I.); (A.M.); (S.G.)
| | - Alessandra Modena
- Department of Oncology, IRCCS Ospedale Sacro Cuore Don Calabria, Via Don A. Sempreboni 5, 37024 Negrar, Italy; (A.I.); (A.M.); (S.G.)
| | - Stefania Gori
- Department of Oncology, IRCCS Ospedale Sacro Cuore Don Calabria, Via Don A. Sempreboni 5, 37024 Negrar, Italy; (A.I.); (A.M.); (S.G.)
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Ban X, Hu H, Li Y, Yang L, Wang Y, Zhang R, Xie C, Zhou C, Duan X. Morphologic CT and MRI features of primary parotid squamous cell carcinoma and its predictive factors for differential diagnosis with mucoepidermoid carcinoma. Insights Imaging 2022; 13:119. [PMID: 35840821 PMCID: PMC9287497 DOI: 10.1186/s13244-022-01256-x] [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: 02/09/2022] [Accepted: 06/09/2022] [Indexed: 11/10/2022] Open
Abstract
Background Primary parotid squamous cell carcinoma (SCC) is a rare entity with a poor prognosis. Pathologically, the diagnosis of it requires the exclusion of parotid mucoepidermoid carcinoma (MEC). Currently, the imaging features of primary parotid SCC and the predictive indicators for differential diagnosis of the two entities have not been well reported. Our purpose was to identify the imaging characteristics of primary parotid SCC and to determine the predictive factors for its’ differential diagnosis. Results Thirty-one participants with primary parotid SCC and 59 with primary parotid MEC were enrolled. Clinical, CT and MRI features were reviewed and compared by univariate analysis. Then, multinomial logistic regression was used to determine the predictors to distinguish parotid SCC from MEC. Most primary parotid SCCs exhibited irregular shape, ill-defined margin, incomplete or no capsule, heterogeneous and marked or moderate enhancement, necrosis, local tumor invasiveness (LTI). Age, maximal dimension, shape, degree of enhancement, gradual enhancement, necrosis, and LTI were different between the primary parotid SCCs and MECs in univariate analysis (p < 0.05). While in multinomial logistic regression analysis, only age and necrosis were the independent predictors for distinguishing parotid SCC from MEC, and this model exhibited an area under curve of 0.914 in ROC curve analysis. Conclusions Primary parotid SCC has some distinct imaging features including the large tumor size, irregular shape, ill-defined margin, and particularly the marked central necrosis. Patients with age ≥ 51.5 years and necrosis on the image of the primary tumor in the parotid gland could be more likely to be SCCs than MECs.
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Affiliation(s)
- Xiaohua Ban
- Department of Radiology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, Guangdong, 510060, People's Republic of China
| | - Huijun Hu
- Department of Radiology, Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, Guangdong, 510120, People's Republic of China
| | - Yue Li
- Department of Radiology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, Guangdong, 510060, People's Republic of China
| | - Lingjie Yang
- Department of Radiology, Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, Guangdong, 510120, People's Republic of China
| | - Yu Wang
- Department of Radiology, Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, Guangdong, 510120, People's Republic of China
| | - Rong Zhang
- Department of Radiology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, Guangdong, 510060, People's Republic of China
| | - Chuanmiao Xie
- Department of Radiology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, Guangdong, 510060, People's Republic of China
| | - Cuiping Zhou
- Department of Radiology, The University of Hong Kong-Shenzhen Hospital, No.1, Haiyuan Road Futian District, Shenzhen, 518000, People's Republic of China.
| | - Xiaohui Duan
- Department of Radiology, Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, Guangdong, 510120, People's Republic of China.
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Plan-Do-Check-Action Circulation Combined with Accelerated Rehabilitation Nursing under Computed Tomography in Prevention and Control of Hospital Infection in Elderly Patients Undergoing Elective Orthopedic Surgery. CONTRAST MEDIA & MOLECULAR IMAGING 2022; 2022:4574730. [PMID: 35548404 PMCID: PMC9061006 DOI: 10.1155/2022/4574730] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 03/30/2022] [Accepted: 04/04/2022] [Indexed: 11/18/2022]
Abstract
To explore the adoption of plan-do-check-action (PDCA) circulation combined with accelerated rehabilitation nursing based on gemstone spectral imaging computed tomography (GSICT) in the prevention and control of hospital infection in the elderly patients undergoing the elective orthopedic surgery, 80 elderly patients who underwent the elective orthopedic surgery in the hospital were selected. Then, according to the randomized controlled principle, these 80 patients were divided into control group (40 cases) with conventional nursing and observation group (40 cases) with accelerated rehabilitation surgical nursing combined with PDCA circulation. All the patients underwent the GSICT examination without any contraindicators. Compared with the conventional CT scan, metal artifacts in GSICT were considerably reduced. In the images processed by GSI and metal artifacts reduction system (MARS), metal artifacts were basically eliminated and the positions, forms, and edges of metal artifacts in the human body were clearly presented. Hospital infection occurred in 1 (2.5%) patient in the observation group and 5 (12.5%) patients in the control group, and the difference was statistically significant (P < 0.05). In terms of temperature increase, patients in control group (37.5%) had a remarkably higher value than that of observation group (7.5%). The increase rate of white blood cell (WBC) count in control group (12.5%) was obviously higher than that in observation group (2.5%). Besides, the differences were statistically significant (P < 0.05). After PDCA circulation combined with accelerated rehabilitation nursing mode was applied, the hospitalization time of observation group (5.3 ± 2.4 days) was markedly lower than that of control group (9.7 ± 3.8 days). Moreover, the total hospitalization cost of observation group (791.44 yuan) was notably lower than that of control group (4068.96 yuan), with significant differences (P < 0.05). Nursing satisfaction in observation group (92.5%) was higher than that in control group (77.5%), and the difference was statistically significant (P < 0.05). In short, GSICT could effectively reduce beam hardening artifacts and metal implant artifacts and improve image quality. Furthermore, accelerated rehabilitation nursing combined with PDCA circulation could effectively reduce the incidence of hospital infection and improve nursing satisfaction.
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Yu X, Cai A, Wang L, Zheng Z, Wang Y, Wang Z, Li L, Yan B. Framelet tensor sparsity with block matching for spectral CT reconstruction. Med Phys 2022; 49:2486-2501. [PMID: 35142376 DOI: 10.1002/mp.15529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Revised: 01/11/2022] [Accepted: 01/21/2022] [Indexed: 11/12/2022] Open
Abstract
PURPOSE Spectral computed tomography (CT) based on the photon-counting detection system has the capability to produce energy-discriminative attenuation maps of objects with a single scan. However, the insufficiency of photons collected into the narrow energy bins results in high quantum noise levels causing low image quality. This work aims to improve spectral CT image quality by developing a novel regularization based on framelet tensor prior. METHODS First, similar patches are extracted from highly correlated inter-channel images in spectral and spatial domains, and stacked to form a third-order tensor after vectorization along the energy channels. Second, the framelet tensor nuclear norm (FTNN) is introduced and applied to construct the regularization to exploit the sparsity embedded in nonlocal similarity of spectral images, and thus the reconstruction problem is modeled as a constrained optimization. Third, an iterative algorithm is proposed by utilizing the alternating direction method of multipliers framework in which efficient solvers are developed for each subproblem. RESULTS Both numerical simulations and real data verifications were performed to evaluate and validate the proposed FTNN based method. Compared to the analytic, TV-based, and the state-of-the-art tensor-based methods, the proposed method achieves higher numerical accuracy on both reconstructed CT images and decomposed material maps in the mouse data indicating the capability in noise suppression and detail preservation of the proposed method. CONCLUSIONS A framelet tensor sparsity-based iterative algorithm is proposed for spectral reconstruction. The qualitative and quantitative comparisons show a promising improvement of image quality, indicating its promising potential in spectral CT imaging. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Xiaohuan Yu
- Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, Zhengzhou, China
| | - Ailong Cai
- Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, Zhengzhou, China
| | - Linyuan Wang
- Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, Zhengzhou, China
| | - Zhizhong Zheng
- Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, Zhengzhou, China
| | - Yizhong Wang
- Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, Zhengzhou, China
| | - Zhe Wang
- Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China
| | - Lei Li
- Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, Zhengzhou, China
| | - Bin Yan
- Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, Zhengzhou, China
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Laroia ST, Yadav K, Kumar S, Rastogi A, Kumar G, Sarin SK. Material decomposition using iodine quantification on spectral CT for characterising nodules in the cirrhotic liver: a retrospective study. Eur Radiol Exp 2021; 5:22. [PMID: 34046753 PMCID: PMC8160046 DOI: 10.1186/s41747-021-00220-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Accepted: 04/07/2021] [Indexed: 12/15/2022] Open
Abstract
Background There is limited scientific evidence on the potential of spectral computed tomography (SCT) for differentiation of nodules in the cirrhotic liver. We aimed to assess SCT-generated material density (MD) parameters for nodule characterisation in cirrhosis. Methods Dynamic dual-energy SCT scans of cirrhotic patients performed over 3 years were retrospectively reviewed. They were classified as hepatocellular carcinoma (HCC), regenerative or indeterminate, according to the European Association for the Study of the Liver criteria. MD maps were generated to calculate the area under the curve (AUC) and cutoff values to discriminate these nodules in the hepatic arterial phase (HAP) and portal venous phase (PVP). MD maps included iodine concentration density (ICD) of the liver and nodule, lesion-to-normal liver ICD ratio (LNR) and difference in nodule ICD between HAP and PVP. Results Three hundred thirty nodules belonging to 300 patients (age 53.0 ± 12.7 years, mean ± standard deviation) were analysed at SCT (size 2.3 ± 0.8 cm, mean ± SD). One hundred thirty-three (40.3%) nodules were classified as HCC, 147 (44.5%) as regenerative and 50 (15.2%) as indeterminate. On histopathology, 136 (41.2%) nodules were classified as HCC, 183 (55.5%) as regenerative and 11 (3.3%) as dysplastic. All MD parameters on HAP and the nodule difference in ICD could discriminate pathologically proven HCC or potentially malignant nodules from regenerative nodules (p < 0.001). The AUC was 82.4% with a cutoff > 15.5 mg/mL for nodule ICD, 81.3% > 1.8 for LNR-HAP and 81.3% for difference in ICD > 3.5 mg/mL. Conclusion SCT-generated MD parameters are viable diagnostic tools for differentiating malignant or potentially malignant from benign nodules in the cirrhotic liver. Supplementary Information The online version contains supplementary material available at 10.1186/s41747-021-00220-6.
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Affiliation(s)
- Shalini Thapar Laroia
- Department of Radiology, Institute of Liver and Biliary Sciences, Sector D-1, Vasant Kunj, New Delhi, 110070, India.
| | - Komal Yadav
- Department of Radiology, Institute of Liver and Biliary Sciences, Sector D-1, Vasant Kunj, New Delhi, 110070, India
| | - Senthil Kumar
- Department of HPB Surgery and Liver Transplantation, Institute of Liver & Biliary Sciences, Sector D-1, Vasant Kunj, New Delhi, 110070, India
| | - Archana Rastogi
- Department of Clinical and Hepato-pathology, Institute of Liver and Biliary Sciences, Sector D-1, Vasant Kunj, New Delhi, 110070, India
| | - Guresh Kumar
- Department of Biostatistics and Research, Institute of Liver & Biliary Sciences, Sector D-1, Vasant Kunj, New Delhi, 110070, India
| | - Shiv Kumar Sarin
- Department of Hepatology, Institute of Liver & Biliary Sciences, Sector D-1, Vasant Kunj, New Delhi, 110 070, India
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10
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Gentili F, Guerrini S, Mazzei FG, Monteleone I, Di Meglio N, Sansotta L, Perrella A, Puglisi S, De Filippo M, Gennaro P, Volterrani L, Castagna MG, Dotta F, Mazzei MA. Dual energy CT in gland tumors: a comprehensive narrative review and differential diagnosis. Gland Surg 2020; 9:2269-2282. [PMID: 33447579 DOI: 10.21037/gs-20-543] [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] [Indexed: 12/11/2022]
Abstract
Dual energy CT (DECT)with image acquisition at two different photon X-ray levels allows the characterization of a specific tissue or material/elements, the extrapolation of virtual unenhanced and monoenergetic images, and the quantification of iodine uptake; such special capabilities make the DECT the perfect technique to support oncological imaging for tumor detection and characterization and treatment monitoring, while concurrently reducing the dose of radiation and iodine and improving the metal artifact reduction. Even though its potential in the field of oncology has not been fully explored yet, DECT is already widely used today thanks to the availability of different CT technologies, such as dual-source, single-source rapid-switching, single-source sequential, single-source twin-beam and dual-layer technologies. Moreover DECT technology represents the future of the imaging innovation and it is subject to ongoing development that increase according its clinical potentiality, in particular in the field of oncology. This review points out recent state-of-the-art in DECT applications in gland tumors, with special focus on its potential uses in the field of oncological imaging of endocrine and exocrine glands.
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Affiliation(s)
- Francesco Gentili
- Unit of Diagnostic Imaging, Department of Radiological Sciences, Azienda Ospedaliero-Universitaria Senese, Siena, Italy
| | - Susanna Guerrini
- Unit of Diagnostic Imaging, Department of Radiological Sciences, Azienda Ospedaliero-Universitaria Senese, Siena, Italy
| | - Francesco Giuseppe Mazzei
- Unit of Diagnostic Imaging, Department of Radiological Sciences, Azienda Ospedaliero-Universitaria Senese, Siena, Italy
| | - Ilaria Monteleone
- Unit of Diagnostic Imaging, Department of Medical, Surgical and Neuro Sciences and of Radiological Sciences, University of Siena, Azienda Ospedaliero-Universitaria Senese, Siena, Italy
| | - Nunzia Di Meglio
- Unit of Diagnostic Imaging, Department of Medical, Surgical and Neuro Sciences and of Radiological Sciences, University of Siena, Azienda Ospedaliero-Universitaria Senese, Siena, Italy
| | - Letizia Sansotta
- Unit of Diagnostic Imaging, Department of Medical, Surgical and Neuro Sciences and of Radiological Sciences, University of Siena, Azienda Ospedaliero-Universitaria Senese, Siena, Italy
| | - Armando Perrella
- Unit of Diagnostic Imaging, Department of Medical, Surgical and Neuro Sciences and of Radiological Sciences, University of Siena, Azienda Ospedaliero-Universitaria Senese, Siena, Italy
| | - Sara Puglisi
- Unit of Radiology, Department of Medicine and Surgery, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
| | - Massimo De Filippo
- Unit of Radiology, Department of Medicine and Surgery, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
| | - Paolo Gennaro
- Department of Maxillofacial Surgery, University of Siena, Azienda Ospedaliera Universitaria Senese, Siena, Italy
| | - Luca Volterrani
- Unit of Diagnostic Imaging, Department of Medical, Surgical and Neuro Sciences and of Radiological Sciences, University of Siena, Azienda Ospedaliero-Universitaria Senese, Siena, Italy
| | - Maria Grazia Castagna
- Unit of Endocrinology, Department of Medical, Surgical and Neuro Sciences, University of Siena, Azienda Ospedaliero-Universitaria Senese, Siena, Italy
| | - Francesco Dotta
- Unit of Diabetology, Department of Medical, Surgical and Neuro Sciences, University of Siena, Azienda Ospedaliero-Universitaria Senese, Siena, Italy
| | - Maria Antonietta Mazzei
- Unit of Diagnostic Imaging, Department of Medical, Surgical and Neuro Sciences and of Radiological Sciences, University of Siena, Azienda Ospedaliero-Universitaria Senese, Siena, Italy
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11
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Zhang W, Liang N, Wang Z, Cai A, Wang L, Tang C, Zheng Z, Li L, Yan B, Hu G. Multi-energy CT reconstruction using tensor nonlocal similarity and spatial sparsity regularization. Quant Imaging Med Surg 2020; 10:1940-1960. [PMID: 33014727 DOI: 10.21037/qims-20-594] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Background Multi-energy computed tomography (MECT) based on a photon-counting detector is an emerging imaging modality that collects projections at several energy bins with a single scan. However, the limited number of photons collected into the divided, narrow energy bins results in high quantum noise levels in reconstructed images. This study aims to improve MECT image quality by minimizing noise levels while retaining image details. Methods A novel MECT reconstruction method was proposed by exploiting the nonlocal tensor similarity among interchannel images and spatial sparsity in single-channel images. Similar patches were initially extracted from the interchannel images in spectral and spatial domains, then stacked into a new three-order tensor. Intrinsic tensor sparsity regularization that combined the Tuker and canonical polyadic (CP) low-rank decomposition techniques were applied to exploit the nonlocal similarity of the formulated tensor. Spatial sparsity in single-channel images was modeled by total variation (TV) regularization that utilizes the compressibility of gradient image. A new MECT reconstruction model was established by simultaneously incorporating the intrinsic tensor sparsity and TV regularizations. The iterative alternating minimization method was utilized to solve the reconstruction model based on a flexible framework. Results The proposed method was applied to the digital phantom and real mouse data to assess its feasibility and reliability. The reconstruction and decomposition results in the mouse data were encouraging and demonstrated the ability of the proposed method in noise suppression while preserving image details, not observed with other methods. Imaging data from the digital phantom illustrated this method as achieving the best intuitive reconstruction and decomposition results among all compared methods. They reduced the root mean square error (RMSE) by 89.75%, 50.75%, and 36.54% on the reconstructed images compared with analytic, TV-based, and tensor-based methods, respectively. This phenomenon was also observed with decomposition results, where the RMSE was also reduced by 97.96%, 67.74%, 72.05%, respectively. Conclusions In this study, we proposed a reconstruction method for photon counting detector-based MECT, using the intrinsic tensor sparsity and TV regularizations. Improvements in noise suppression and detail preservation in the digital phantom and real mouse data were validated by the qualitative and quantitative evaluations on the reconstruction and decomposition results, verifying the potential of the proposed method in MECT reconstruction.
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Affiliation(s)
- Wenkun Zhang
- Key Laboratory of Imaging and Intelligent Processing of Henan Province, PLA Strategic Support Force Information Engineering University, Zhengzhou, China
| | - Ningning Liang
- Key Laboratory of Imaging and Intelligent Processing of Henan Province, PLA Strategic Support Force Information Engineering University, Zhengzhou, China
| | - Zhe Wang
- Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China
| | - Ailong Cai
- Key Laboratory of Imaging and Intelligent Processing of Henan Province, PLA Strategic Support Force Information Engineering University, Zhengzhou, China
| | - Linyuan Wang
- Key Laboratory of Imaging and Intelligent Processing of Henan Province, PLA Strategic Support Force Information Engineering University, Zhengzhou, China
| | - Chao Tang
- Key Laboratory of Imaging and Intelligent Processing of Henan Province, PLA Strategic Support Force Information Engineering University, Zhengzhou, China
| | - Zhizhong Zheng
- Key Laboratory of Imaging and Intelligent Processing of Henan Province, PLA Strategic Support Force Information Engineering University, Zhengzhou, China
| | - Lei Li
- Key Laboratory of Imaging and Intelligent Processing of Henan Province, PLA Strategic Support Force Information Engineering University, Zhengzhou, China
| | - Bin Yan
- Key Laboratory of Imaging and Intelligent Processing of Henan Province, PLA Strategic Support Force Information Engineering University, Zhengzhou, China
| | - Guoen Hu
- Key Laboratory of Imaging and Intelligent Processing of Henan Province, PLA Strategic Support Force Information Engineering University, Zhengzhou, China
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12
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Yu C, Li T, Zhang R, Yang X, Yang Z, Xin L, Zhao Z. Dual-energy CT perfusion imaging for differentiating WHO subtypes of thymic epithelial tumors. Sci Rep 2020; 10:5511. [PMID: 32218504 PMCID: PMC7098982 DOI: 10.1038/s41598-020-62466-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2018] [Accepted: 03/13/2020] [Indexed: 11/09/2022] Open
Abstract
To evaluate the role of conventional contrast-enhanced CT (CECT) imaging and dual-energy spectral CT (DECT) perfusion imaging in differentiating the WHO histological subtypes of thymic epithelial tumours (TETs). Eighty-eight patients with TETs who underwent DECT perfusion scans (n = 51) and conventional CT enhancement scans (n = 37) using a GE Discovery CT750 HD scanner were enrolled in this study. The mean maximal contrast-enhanced range (mean CEmax) and the perfusion and spectral parameters of the lesions were analysed. Among the six WHO subtypes (Type A, AB, B1, B2, and B3 thymoma and thymic carcinoma), the mean CEmax values and most of the perfusion and spectral parameter values of Type A and Type AB were significantly higher than those of the other subtypes (all P < 0.05), and there was no difference among Type B1, B2 and B3 (all P > 0.05). The mean CEmax value was not different between Type B (including Type B1, B2, and B3) and thymic carcinoma (P = 1.000). The PS, IC, NIC and λHU values in the optimal venous phase of thymic carcinoma were higher than those of Type B (all P < 0.05). The parameters of conventional CECT imaging and DECT perfusion imaging can help identify the subtype of TETs, especially those of DECT perfusion imaging in type B thymomas and thymic carcinomas.
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Affiliation(s)
- Chunhai Yu
- Imaging Department, Shanxi Tumor Hospital, The Affiliated Tumor Hospital of Shanxi Medical University, Taiyuan, Shanxi, 030013, P.R. China
| | - Ting Li
- Department of Nephrology, Taiyuan People's Hospital, Taiyuan, Shanxi, 030001, P.R. China
| | - Ruiping Zhang
- Imaging Department, Shanxi Tumor Hospital, The Affiliated Tumor Hospital of Shanxi Medical University, Taiyuan, Shanxi, 030013, P.R. China.
| | - Xiaotang Yang
- Imaging Department, Shanxi Tumor Hospital, The Affiliated Tumor Hospital of Shanxi Medical University, Taiyuan, Shanxi, 030013, P.R. China
| | - Zhao Yang
- Imaging Department, Shanxi Tumor Hospital, The Affiliated Tumor Hospital of Shanxi Medical University, Taiyuan, Shanxi, 030013, P.R. China
| | - Lei Xin
- Imaging Department, Shanxi Tumor Hospital, The Affiliated Tumor Hospital of Shanxi Medical University, Taiyuan, Shanxi, 030013, P.R. China
| | - Zhikai Zhao
- Imaging Department, Shanxi Tumor Hospital, The Affiliated Tumor Hospital of Shanxi Medical University, Taiyuan, Shanxi, 030013, P.R. China
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13
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Huang X, Gao S, Ma Y, Lu X, Jia Z, Hou Y. The optimal monoenergetic spectral image level of coronary computed tomography (CT) angiography on a dual-layer spectral detector CT with half-dose contrast media. Quant Imaging Med Surg 2020; 10:592-603. [PMID: 32269920 DOI: 10.21037/qims.2020.02.17] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Background To investigate the optimal monoenergetic level of spectral reconstructions in coronary computed tomography angiography (coronary CTA) on a dual-layer spectral detector computed tomography (SDCT) with half-dose contrast media. Methods Two hundred patients with suspected coronary artery disease (CAD) were enrolled in this prospective coronary CTA study and randomly divided into a routine-dose contrast media group and a half-dose contrast media group (each n=100). Coronary CTA was performed using SDCT with prospective electrocardiogram (ECG)-gated mode. A tube voltage of 120 kVp was used, along with an automated tube current modulation. A dose of iodixanol 270 mgI/mL of 0.8 and 0.4 mL/kg was administered to the routine and half-dose groups, respectively. For the routine-dose group, 120 kVp polychromatic images with a model-based iterative reconstruction (IMR) (Group A) were reconstructed. For the half-dose group, three monoenergetic levels of images were reconstructed (Group B, 45 keV; Group C, 50 keV; and Group D, 55 keV). Objective indicators [mean CT values; noise; signal-to-noise ratio (SNR); and contrast-to-noise ratio (CNR)] and subjective indicators (contrast, sharpness, subjective noise, and acceptability) in each group were compared. Results There were no significant differences in demographics or radiation dose (1.83±0.51 vs. 1.80±0.53 mSv, P=0.78) between the routine- and half-dose groups. The average iodine loads were 15.33±2.26 and 7.48±1.14 g, respectively. Mean CT values, SNR, CNR, and subjective contrast in Group C were higher than those in Group A (P<0.05), and there were no significant differences in other indicators between Group C and Group A (P>0.05). The objective and subjective noise in Group B were worse than those in Group A (P<0.05). The contrast, sharpness, and acceptability of Group D were all worse than those of Group A (P<0.05). Conclusions Compared to routine polychromatic images, 50 keV monoenergetic images can provide equivalent or improved coronary image quality in coronary CTA performed on SDCT with half the amount of contrast media.
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Affiliation(s)
- Xin Huang
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang 110004, China
| | - Sizhe Gao
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang 110004, China
| | - Yue Ma
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang 110004, China
| | - Xiaomei Lu
- CT Clinical Science, Philips Healthcare, Shenyang 110016, China
| | - Zheng Jia
- CT Clinical Science, Philips Healthcare, Shenyang 110016, China
| | - Yang Hou
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang 110004, China
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14
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Li L, Cheng SN, Zhao YF, Wang XY, Luo DH, Wang Y. Diagnostic accuracy of single-source dual-energy computed tomography and ultrasonography for detection of lateral cervical lymph node metastases of papillary thyroid carcinoma. J Thorac Dis 2019; 11:5032-5041. [PMID: 32030219 DOI: 10.21037/jtd.2019.12.45] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Background Dual-energy computed tomography (DECT) imaging can generate iodine-based material decomposition (MD) images and spectral HU curve. This study aimed to investigate the diagnostic accuracy of single-source dual-energy CT (DECT) and ultrasonography (US) for detecting lateral cervical lymph node metastases of papillary thyroid carcinoma (PTC). Methods Thirty patients with PTC were enrolled in the study and underwent DECT and US examination before thyroidectomy and cervical lymph node dissection. The spectral parameters included iodine concentration (IC), normalized iodine concentration (NIC) and slope (λHU) of lymph nodes. The CT morphological parameters included maximal short diameter, shape, margin, calcification and cystic degeneration of lymph nodes. The US morphological parameters included maximal short diameter, calcification and cystic degeneration of lymph nodes. The diagnostic value of every single spectral parameter, combined gemstone spectral image (GSI) parameters, CT morphological parameters and US morphological parameters between metastatic and non-metastatic lymph nodes were statistically compared. Receiver operating characteristic (ROC) curves, sensitivity, and specificity were used to determine the diagnostic value. Results Ninety-nine lymph nodes from thirty patients were pathologically confirmed. Among them, 70 (70.7%) were metastatic. For single GSI parameters, ROC analysis showed that the area under the curve (AUC) for IC was the highest (AUC =0.937) but the difference was not statistically significant when compared with NIC or slope (λHU) (P>0.05). The optimal diagnostic threshold for IC was 2.56 mg/mL, with a sensitivity, specificity and accuracy of 87.1%, 93.1%, and 88.9%, respectively. The AUC for combined GSI parameter (AUC =0.942) was higher compared with the US morphological parameters (AUC =0.771, P<0.001), with a sensitivity, specificity, and accuracy of 92.9%, 86.2%, and 90.9%, respectively. However AUC did not differ significantly among combined GSI parameters, combined CT morphological parameters and a single application for spectral CT parameters IC (P>0.05). Conclusions Combined GSI parameters showed better diagnostic accuracy in lateral cervical lymph node metastasis of PTC compared with that of combined US morphological parameters. IC alone showed excellent diagnostic stability and could be performed easily.
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Affiliation(s)
- Lin Li
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Sai-Nan Cheng
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Yan-Feng Zhao
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Xiao-Yi Wang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - De-Hong Luo
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Yong Wang
- Department of Ultrasonography, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
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15
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Abstract
Introduction: Dual-energy-computed tomography (DECT) is an advanced form of computed tomography (CT) that enables spectral tissue characterization beyond what is possible with conventional CT scans. DECT can improve non-invasive diagnostic evaluation of the neck, especially for the evaluation of head and neck cancer. Areas covered: This article is a review of current applications of DECT for the evaluation of head and neck cancer, focusing largely on squamous cell carcinoma (HNSCC). The article will begin with a brief overview of principles and different approaches for DECT scanning. This will be followed by a review of different DECT applications in diagnostic imaging and radiation oncology, practical and workflow considerations, and various emerging advanced applications for tumor analysis, including the use of DECT datasets for radiomics and machine learning applications. Expert opinion: Using a multi-parametric approach, different DECT reconstructions can be used to improve diagnostic evaluation and surveillance of head and neck cancer, including improving visibility of HNSCC, determination of tumor boundaries and extent, and invasion of critical organs such as the thyroid cartilage. In the future, the large amount of quantitative information on DECT scans may be leveraged for improving radiomic and machine learning models for tumor characterization.
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Affiliation(s)
- Reza Forghani
- a Department of Radiology , McGill University & McGill University Health Centre , Montreal , Quebec , Canada.,b Cancer Research Program , Research Institute of the McGill University Health Centre , Montreal , Quebec , Canada.,c Segal Cancer Centre and Lady Davis Institute for Medical Research, Jewish General Hospital , Montreal , Quebec , Canada.,d Gerald Bronfman Department of Oncology , McGill University , Montreal , Quebec , Canada.,e Department of Otolaryngology - Head and Neck Surgery , McGill University , Montreal , Quebec , Canada
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Lu X, Lu Z, Yin J, Gao Y, Chen X, Guo Q. Effects of radiation dose levels and spectral iterative reconstruction levels on the accuracy of iodine quantification and virtual monochromatic CT numbers in dual-layer spectral detector CT: an iodine phantom study. Quant Imaging Med Surg 2019; 9:188-200. [PMID: 30976543 DOI: 10.21037/qims.2018.11.12] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Background The purpose of this study is to investigate the accuracy of iodine quantification and virtual monochromatic CT numbers obtained with the dual-layer spectral CT (DLCT) using a phantom at different radiation dose levels and spectral iterative reconstruction (IR) levels. Methods An abdomen phantom with seven iodine inserts (2.0, 2.5, 5.0, 7.5, 10.0, 15.0, 20.0 mg/mL) was imaged using a DLCT scanner. Five repeated scans were performed at computed tomography dose index volume (CTDIvol) levels of 5, 10, 15, 20, 25 mGy at tube voltages of 120 and 140 kVp, respectively. Spectral-based images were reconstructed using four spectral IR levels (spectral level of 0, 2, 4, 6). Iodine density images and virtual monochromatic images (VMI) at energy levels of 50, 70 and 120 keV were created. The absolute percentage bias (APB) of the measured iodine concentration and the true iodine concentration, and the measured VMI CT numbers and the theoretical VMI CT numbers were compared to determine the difference of radiation dose levels and different spectral IR levels. Results At CTDIvol levels of 25, 20, 15, 10 mGy, radiation dose levels had no effect on the accuracy of iodine quantitation; at CTDIvol level of 5 mGy, the accuracy of iodine quantification was the poorest, with the mean APBiodine of 4.33% (P<0.05). There was no significant difference in the accuracy of iodine quantitation between 120 and 140 kVp (P=0.648). At energy levels of 50, 70 and 120 keV, there was no significant difference in the accuracy of the VMI CT numbers among the CTDIvol levels of 25, 20 and 15 mGy. However, the accuracy of VMI CT numbers was significantly degraded at the CTDIvol levels of 10 and 5 mGy (P<0.05). At energy level of 50 keV, the accuracy of VMI CT numbers was not affected by tube voltages (kVps) used (P=0.125). At the energy levels of 70 and 120 keV, 140 kVp produced a smaller bias than 120 kVp, with the mean APBHU at 120 and 140 kVp being of 3.62% vs. 2.99% for 70 keV (P<0.01), and 11.65% vs. 9.28% for 120 keV (P<0.01), respectively. Spectral IR levels did not affect the accuracy of iodine quantification and VMI CT numbers (P=0.998, P=0.963). Conclusions The accuracy of iodine quantification and VMI CT numbers was only affected by very low radiation dose levels. At the clinically applied radiation dose levels of >10 mGy, the accuracy of both iodine quantification and VMI CT numbers is relatively stable and high.
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Affiliation(s)
- Xiaomei Lu
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang 110004, China
| | - Zaiming Lu
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang 110004, China
| | - Jiandong Yin
- Division of Biomedical Engineering, China Medical University, Shenyang 110001, China
| | - Yuying Gao
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang 110004, China
| | - Xingbiao Chen
- CT Clinical Science, Philips Healthcare, Shanghai 200233, China
| | - Qiyong Guo
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang 110004, China
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