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Popov M, Amanturdieva A, Zhaksylyk N, Alkanov A, Saniyazbekov A, Aimyshev T, Ismailov E, Bulegenov A, Kuzhukeyev A, Kulanbayeva A, Kalzhanov A, Temenov N, Kolesnikov A, Sakhov O, Fazli S. Dataset for Automatic Region-based Coronary Artery Disease Diagnostics Using X-Ray Angiography Images. Sci Data 2024; 11:20. [PMID: 38172163 PMCID: PMC10764944 DOI: 10.1038/s41597-023-02871-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 12/20/2023] [Indexed: 01/05/2024] Open
Abstract
X-ray coronary angiography is the most common tool for the diagnosis and treatment of coronary artery disease. It involves the injection of contrast agents into coronary vessels using a catheter to highlight the coronary vessel structure. Typically, multiple 2D X-ray projections are recorded from different angles to improve visualization. Recent advances in the development of deep-learning-based tools promise significant improvement in diagnosing and treating coronary artery disease. However, the limited public availability of annotated X-ray coronary angiography image datasets presents a challenge for objective assessment and comparison of existing tools and the development of novel methods. To address this challenge, we introduce a novel ARCADE dataset with 2 objectives: coronary vessel classification and stenosis detection. Each objective contains 1500 expert-labeled X-ray coronary angiography images representing: i) coronary artery segments; and ii) the locations of stenotic plaques. These datasets will serve as a benchmark for developing new methods and assessing existing approaches for the automated diagnosis and risk assessment of coronary artery disease.
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Affiliation(s)
- Maxim Popov
- Mohamed Bin Zayed University of Artificial Intelligence, Department of Computer Vision, Abu Dhabi, United Arab Emirates.
| | - Akmaral Amanturdieva
- Research Institute of Cardiology and Internal Diseases, Almaty, 050000, Kazakhstan
| | - Nuren Zhaksylyk
- Mohamed Bin Zayed University of Artificial Intelligence, Department of Computer Vision, Abu Dhabi, United Arab Emirates
- Research Institute of Cardiology and Internal Diseases, Almaty, 050000, Kazakhstan
| | - Alsabir Alkanov
- Research Institute of Cardiology and Internal Diseases, Almaty, 050000, Kazakhstan
| | - Adilbek Saniyazbekov
- Research Institute of Cardiology and Internal Diseases, Almaty, 050000, Kazakhstan
| | - Temirgali Aimyshev
- Research Institute of Cardiology and Internal Diseases, Almaty, 050000, Kazakhstan
- CMC Technologies, Astana, 010000, Kazakhstan
| | - Eldar Ismailov
- Research Institute of Cardiology and Internal Diseases, Almaty, 050000, Kazakhstan
- CMC Technologies, Astana, 010000, Kazakhstan
| | - Ablay Bulegenov
- Research Institute of Cardiology and Internal Diseases, Almaty, 050000, Kazakhstan
- CMC Technologies, Astana, 010000, Kazakhstan
| | - Arystan Kuzhukeyev
- Research Institute of Cardiology and Internal Diseases, Almaty, 050000, Kazakhstan
| | - Aizhan Kulanbayeva
- Research Institute of Cardiology and Internal Diseases, Almaty, 050000, Kazakhstan
- Almaty City Cardiological Center, Almaty, 050000, Kazakhstan
| | - Almat Kalzhanov
- Research Institute of Cardiology and Internal Diseases, Almaty, 050000, Kazakhstan
| | - Nurzhan Temenov
- Research Institute of Cardiology and Internal Diseases, Almaty, 050000, Kazakhstan
| | - Alexey Kolesnikov
- Research Institute of Cardiology and Internal Diseases, Almaty, 050000, Kazakhstan
| | - Orazbek Sakhov
- Research Institute of Cardiology and Internal Diseases, Almaty, 050000, Kazakhstan
- Almaty City Cardiological Center, Almaty, 050000, Kazakhstan
| | - Siamac Fazli
- Nazarbayev University, School of Engineering and Digital Sciences, Department of Computer Science, Astana, 010000, Kazakhstan
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2
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Whittington B, Dweck MR, van Beek EJR, Newby D, Williams MC. PET-MRI of Coronary Artery Disease. J Magn Reson Imaging 2023; 57:1301-1311. [PMID: 36524452 DOI: 10.1002/jmri.28554] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 11/22/2022] [Accepted: 11/23/2022] [Indexed: 12/23/2022] Open
Abstract
Simultaneous positron emission tomography and magnetic resonance imaging (PET-MRI) combines the anatomical detail and tissue characterization of MRI with the functional information from PET. Within the coronary arteries, this hybrid technique can be used to identify biological activity combined with anatomically high-risk plaque features to better understand the processes underlying coronary atherosclerosis. Furthermore, the downstream effects of coronary artery disease on the myocardium can be characterized by providing information on myocardial perfusion, viability, and function. This review will describe the current capabilities of PET-MRI in coronary artery disease and discuss the limitations and future directions of this emerging technique. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 3.
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Affiliation(s)
- Beth Whittington
- BHF Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging Facility QMRI, University of Edinburgh, Edinburgh, UK
| | - Marc R Dweck
- BHF Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging Facility QMRI, University of Edinburgh, Edinburgh, UK
| | | | - David Newby
- BHF Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging Facility QMRI, University of Edinburgh, Edinburgh, UK
| | - Michelle C Williams
- BHF Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging Facility QMRI, University of Edinburgh, Edinburgh, UK
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3
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Chen Y, Guo H, Dong P, Li Y, Zhang Z, Mao N, Chu T, Sun Z, Wang F, Feng Z, Wang H, Ma H. Feasibility of 3.0 T balanced fast field echo non-contrast-enhanced whole-heart coronary magnetic resonance angiography. Cardiovasc Diagn Ther 2023; 13:51-60. [PMID: 36864952 PMCID: PMC9971310 DOI: 10.21037/cdt-22-487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Accepted: 12/02/2022] [Indexed: 01/01/2023]
Abstract
Background Coronary artery disease (CAD) is one of the most common diseases seriously harmful to human health caused by atherosclerosis. Besides coronary computed tomography angiography (CCTA) and invasive coronary angiography (ICA), coronary magnetic resonance angiography (CMRA) has become an alternative examination. The purpose of this study was to prospectively evaluate the feasibility of 3.0 T free-breathing whole-heart non-contrast-enhanced coronary magnetic resonance angiography (NCE-CMRA). Methods After Institutional Review Board approval, the NCE-CMRA data sets of 29 patients acquired successfully at 3.0 T were evaluated independently by two blinded readers for visualization and image quality of coronary arteries using the subjective quality grade. The acquisition times were recorded in the meantime. A part of the patients had undergone CCTA, we represented stenosis by scores and used the Kappa to evaluate the consistency between CCTA and NCE-CMRA. Results Six patients did not get diagnostic image quality because of severe artifacts. The image quality score assessed by both radiologists is 3.2±0.7, which means the NCE-CMRA can show the coronary arteries excellently. The main vessels of the coronary artery on NCE-CMRA images are considered reliably assessable. The acquisition time of NCE-CMRA, is 8.8±1.2 min. The Kappa of CCTA and NCE-CMRA on detecting stenosis is 0.842 (P<0.001). Conclusions The NCE-CMRA results in reliable image quality and visualization parameters of coronary arteries within a short scan time. The NCE-CMRA and CCTA have a good agreement for detecting stenosis.
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Affiliation(s)
- Yang Chen
- Department of Medical Imaging, Weifang Medical University, Weifang, China
- Department of Radiology, Qingdao University and Yantai Yuhuangding Hospital, Yantai, China
| | - Hao Guo
- Department of Radiology, Qingdao University and Yantai Yuhuangding Hospital, Yantai, China
| | - Peng Dong
- Department of Medical Imaging, Weifang Medical University, Weifang, China
| | - Yue Li
- Department of Radiology, Qingdao University and Yantai Yuhuangding Hospital, Yantai, China
| | - Zhongsheng Zhang
- Department of Radiology, Qingdao University and Yantai Yuhuangding Hospital, Yantai, China
| | - Ning Mao
- Department of Radiology, Qingdao University and Yantai Yuhuangding Hospital, Yantai, China
| | - Tongpeng Chu
- Department of Radiology, Qingdao University and Yantai Yuhuangding Hospital, Yantai, China
| | - Zehua Sun
- Department of Radiology, Qingdao University and Yantai Yuhuangding Hospital, Yantai, China
| | - Fang Wang
- Department of Radiology, Qingdao University and Yantai Yuhuangding Hospital, Yantai, China
| | - Zhiqiang Feng
- Department of Radiology, Qingdao University and Yantai Yuhuangding Hospital, Yantai, China
| | - Huaying Wang
- Department of Radiology, Qingdao University and Yantai Yuhuangding Hospital, Yantai, China
| | - Heng Ma
- Department of Radiology, Qingdao University and Yantai Yuhuangding Hospital, Yantai, China
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Zhang Y, Zhang X, Jiang Y, Yang P, Hu X, Peng B, Yue X, Li Y, Ma P, Yuan Y, Yu Y, Liu B, Li X. 3D whole-heart noncontrast coronary MR angiography based on compressed SENSE technology: a comparative study of conventional SENSE sequence and coronary computed tomography angiography. Insights Imaging 2023; 14:35. [PMID: 36790611 PMCID: PMC9931966 DOI: 10.1186/s13244-023-01378-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 01/20/2023] [Indexed: 02/16/2023] Open
Abstract
OBJECTIVE The relatively long scan time has hampered the clinical use of whole-heart noncontrast coronary magnetic resonance angiography (NCMRA). The compressed sensitivity encoding (SENSE) technique, also known as the CS technique, has been found to improve scan times. This study aimed to identify the optimal CS acceleration factor for NCMRA. METHODS Thirty-six participants underwent four NCMRA sequences: three sequences using the CS technique with acceleration factors of 4, 5, and 6, and one sequence using the conventional SENSE technique with the acceleration factor of 2. Coronary computed tomography angiography (CCTA) was considered as a reference sequence. The acquisition times of the four NCMRA sequences were assessed. The correlation and agreement between the visible vessel lengths obtained via CCTA and NCMRA were also assessed. The image quality scores and contrast ratio (CR) of eight coronary artery segments from the four NCMRA sequences were quantitatively evaluated. RESULTS The mean acquisition time of the conventional SENSE was 343 s, while that of CS4, CS5, and CS6 was 269, 215, and 190 s, respectively. The visible vessel length from the CS4 sequence showed good correlation and agreement with CCTA. The image quality score and CR from the CS4 sequence were not statistically significantly different from those in the other groups (p > 0.05). Moreover, the image score and CR showed a decreasing trend with the increase in the CS factor. CONCLUSIONS The CS technique could significantly shorten the acquisition time of NCMRA. The CS sequence with an acceleration factor of 4 was generally acceptable for NCMRA in clinical settings to balance the image quality and acquisition time.
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Affiliation(s)
- Yang Zhang
- grid.412679.f0000 0004 1771 3402Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Research Center of Clinical Medical Imaging, Anhui Province Clinical Image Quality Control Center, Hefei, 230032 Anhui Province China ,Department of Radiology, Fuyang People’s Hospital, Fuyang, 236015 Anhui Province China
| | - Xinna Zhang
- grid.412679.f0000 0004 1771 3402Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Research Center of Clinical Medical Imaging, Anhui Province Clinical Image Quality Control Center, Hefei, 230032 Anhui Province China
| | - Yuqi Jiang
- grid.186775.a0000 0000 9490 772XDepartment of Radiology, Fuyang Hospital of Anhui Medical University, Fuyang, 236000 Anhui China
| | - Panpan Yang
- grid.186775.a0000 0000 9490 772XDepartment of Radiology, Fuyang Hospital of Anhui Medical University, Fuyang, 236000 Anhui China
| | - Xiankuo Hu
- Department of Radiology, Fuyang People’s Hospital, Fuyang, 236015 Anhui Province China
| | - Bin Peng
- Department of Radiology, Fuyang People’s Hospital, Fuyang, 236015 Anhui Province China
| | | | - Yuanyuan Li
- Department of Radiology, Fuyang People’s Hospital, Fuyang, 236015 Anhui Province China
| | - Peiqi Ma
- Department of Radiology, Fuyang People’s Hospital, Fuyang, 236015 Anhui Province China
| | - Yushan Yuan
- Department of Radiology, Fuyang People’s Hospital, Fuyang, 236015 Anhui Province China
| | - Yongqiang Yu
- grid.412679.f0000 0004 1771 3402Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Research Center of Clinical Medical Imaging, Anhui Province Clinical Image Quality Control Center, Hefei, 230032 Anhui Province China
| | - Bin Liu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Research Center of Clinical Medical Imaging, Anhui Province Clinical Image Quality Control Center, Hefei, 230032, Anhui Province, China.
| | - Xiaohu Li
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Research Center of Clinical Medical Imaging, Anhui Province Clinical Image Quality Control Center, Hefei, 230032, Anhui Province, China. .,Department of Radiology, Fuyang Hospital of Anhui Medical University, Fuyang, 236000, Anhui, China.
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Bhalke JB, Hiremath S, Makhale C. A cross-sectional study on coronary artery disease diagnosis in patients with peripheral artery disease. J Interv Med 2022; 5:184-189. [DOI: 10.1016/j.jimed.2022.09.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 08/26/2022] [Accepted: 09/18/2022] [Indexed: 11/07/2022] Open
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Assessment of Non-contrast-enhanced Dixon Water-fat Separation Compressed Sensing Whole-heart Coronary MR Angiography at 3.0 T: A Single-center Experience. Acad Radiol 2022; 29 Suppl 4:S82-S90. [PMID: 34127363 DOI: 10.1016/j.acra.2021.05.009] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 05/08/2021] [Accepted: 05/11/2021] [Indexed: 11/23/2022]
Abstract
RATIONALE AND OBJECTIVES The clinical utility of Dixon water-fat separation coronary MR angiography (CMRA) with compressed sensing (CS) reconstruction has not been determined in a patient population. This study was designed to evaluate the performance of 3.0 T non-contrast-enhanced Dixon water-fat separation CS whole-heart CMRA sequence in vitro and in vivo. MATERIALS AND METHODS In vitro phantom MRI, we compared key parameters of the SENSE and CS images. And in this prospective in vivo study, from November 2019 to October 2020, 94 participants were recruited for 3.0 T non-contrast-enhanced Dixon water-fat separation CS whole-heart CMRA. The accuracy of CMRA for detecting a ≥ 50% reduction in diameter was determined using X-ray coronary angiography (CA) as the reference method. RESULTS Compared with SENSE, CS with an appropriate acceleration factor offers both higher SNR/CNR (p < 0.05) and a shortened acquisition. Fifty-eight patients successfully completed the CMRA and CA. The sensitivity, specificity, positive predictive values, negative predictive values, and accuracy of 3.0 T non-contrast-enhanced Dixon water-fat separation CS whole-heart CMRA according to a patient-based analysis were 96.4%, 66.7%, 73.0%, 95.2% and 81.0%, respectively. The area under the receiver-operator characteristic (ROC) curve (AUC) of 3.0 T non-contrast-enhanced Dixon water-fat separation CS whole-heart CMRA for detecting significant coronary artery stenosis is 0.908, 0.895, and 0.904 in patient-, vessel-, and segment-based analyses respectively. CONCLUSION 3.0 T non-contrast-enhanced Dixon water-fat separation whole-heart CMRA using appropriate CS is a promising noninvasive and radiation-free technique to detect clinically significant coronary stenosis on patients with suspected CAD.
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Lu H, Zhao S, Tian D, Yang S, Ma J, Chen Y, Ge M, Zeng M, Jin H. Clinical Application of Non-Contrast-Enhanced Dixon Water-Fat Separation Compressed SENSE Whole-Heart Coronary MR Angiography at 3.0 T With and Without Nitroglycerin. J Magn Reson Imaging 2021; 55:579-591. [PMID: 34254384 DOI: 10.1002/jmri.27829] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Revised: 06/28/2021] [Accepted: 06/30/2021] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND 3.0 T non-contrast-enhanced nitroglycerin (NTG)-assisted whole-heart coronary magnetic resonance angiography (MRA) employing Dixon water-fat separation and compressed SENSE (CS-SENSE) acceleration is a promising method for diagnosing coronary artery disease (CAD). PURPOSE To evaluate the diagnostic performance of this technique for detecting clinically-relevant (≥50% diameter reducing) CAD and to evaluate the difference in NTG-induced coronary vasodilation between patients with and without clinically-relevant CAD. STUDY TYPE Prospective. POPULATION Sixty-six patients with suspected CAD. FIELD STRENGTH/SEQUENCE 3.0 T; CSSENSE, Dixon water-fat separation, three-dimensional segmented turbo field gradient-echo sequence for whole-heart coronary MRA. ASSESSMENT Overall image quality of coronary MRA was calculated on the basis of all visible coronary segments. The diagnostic performance of coronary MRA for detecting a ≥50% reduction in coronary artery diameter with and without NTG was compared using X-ray coronary angiography (CAG) as the reference. According to CAG, patients were divided into a non-clinically-relevant CAD group and clinically-relevant CAD group, and the difference in NTG-induced vasodilation between the groups was evaluated. STATISTICAL TESTS Unpaired/paired Student's t-test, Mann-Whitney U test, paired Wilcoxon signed-rank test, χ2 test, McNemar test. A two-tailed P value <0.05 was considered significant. RESULTS Overall image quality was increased significantly in the coronary MRA images after NTG. The diagnostic performance of the non-NTG vs. NTG-assisted coronary MRA was as follows on a per-patient basis: sensitivity 94.3% vs. 94.3%, specificity 64.5% vs. 83.9%, positive predictive value 75.0% vs. 86.8%, negative predictive value 90.9% vs. 92.9%, and accuracy 80.3% vs. 89.4%, respectively. NTG-induced vasodilation was significantly lower in the clinically-relevant CAD group than in the non-clinically-relevant CAD group (13.7 ± 8.1% vs. 24.1 ± 16.3%). DATA CONCLUSION Non-contrast Dixon water-fat separation CS-SENSE coronary MRA at 3.0 T can noninvasively detect clinically-relevant CAD and sublingual NTG improved performance. Combining pre- and post-NTG coronary MRA may provide a simple noninvasive and nonionizing test to evaluate coronary vasodilation function. LEVEL OF EVIDENCE 1 TECHNICAL EFFICACY STAGE: 2.
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Affiliation(s)
- Hongfei Lu
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Medical Imaging, Shanghai, China.,Department of Medical Imaging, Shanghai Medical School, Fudan University, Shanghai, China
| | - Shihai Zhao
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Medical Imaging, Shanghai, China.,Department of Medical Imaging, Shanghai Medical School, Fudan University, Shanghai, China
| | - Di Tian
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Medical Imaging, Shanghai, China.,Department of Medical Imaging, Shanghai Medical School, Fudan University, Shanghai, China
| | - Shan Yang
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Medical Imaging, Shanghai, China.,Department of Medical Imaging, Shanghai Medical School, Fudan University, Shanghai, China
| | - Jianying Ma
- Department of Cardiology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yinyin Chen
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Medical Imaging, Shanghai, China.,Department of Medical Imaging, Shanghai Medical School, Fudan University, Shanghai, China
| | - Meiying Ge
- Department of Radiology, The Fifth People's Hospital of Shanghai, Fudan University, Shanghai, China
| | - Mengsu Zeng
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Medical Imaging, Shanghai, China.,Department of Medical Imaging, Shanghai Medical School, Fudan University, Shanghai, China
| | - Hang Jin
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Medical Imaging, Shanghai, China.,Department of Medical Imaging, Shanghai Medical School, Fudan University, Shanghai, China
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