Haipeng Liu1,2, Aleksandra Wingert2, Jian'an Wang3, Jucheng Zhang4, Xinhong Wang5, Jianzhong Sun5, Fei Chen6, Syed Ghufran Khalid1, Jun Jiang3, Dingchang Zheng1. 1. Research Centre for Intelligent Healthcare, Coventry University, Coventry, United Kingdom. 2. Faculty of Health, Education, Medicine, and Social Care, Anglia Ruskin University, Chelmsford, United Kingdom. 3. Department of Cardiology, School of Medicine, The Second Affiliated Hospital, Zhejiang University, Hangzhou, China. 4. Department of Clinical Engineering, School of Medicine, The Second Affiliated Hospital, Zhejiang University, Hangzhou, China. 5. Department of Radiology, School of Medicine, The Second Affiliated Hospital, Zhejiang University, Hangzhou, China. 6. Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China.
Abstract
Background: Atherosclerotic plaques are the major cause of coronary artery disease (CAD). Currently, computed tomography (CT) is the most commonly applied imaging technique in the diagnosis of CAD. However, the accurate extraction of coronary plaque geometry from CT images is still challenging. Summary of Review: In this review, we focused on the methods in recent studies on the CT-based coronary plaque extraction. According to the dimension of plaque extraction method, the studies were categorized into two-dimensional (2D) and three-dimensional (3D) ones. In each category, the studies were analyzed in terms of data, methods, and evaluation. We summarized the merits and limitations of current methods, as well as the future directions for efficient and accurate extraction of coronary plaques using CT imaging. Conclusion: The methodological innovations are important for more accurate CT-based assessment of coronary plaques in clinical applications. The large-scale studies, de-blooming algorithms, more standardized datasets, and more detailed classification of non-calcified plaques could improve the accuracy of coronary plaque extraction from CT images. More multidimensional geometric parameters can be derived from the 3D geometry of coronary plaques. Additionally, machine learning and automatic 3D reconstruction could improve the efficiency of coronary plaque extraction in future studies.
Background: Atherosclerotic plaques are the major cause of coronary artery disease (CAD). Currently, computed tomography (CT) is the most commonly applied imaging technique in the diagnosis of CAD. However, the accurate extraction of coronary plaque geometry from CT images is still challenging. Summary of Review: In this review, we focused on the methods in recent studies on the CT-based coronary plaque extraction. According to the dimension of plaque extraction method, the studies were categorized into two-dimensional (2D) and three-dimensional (3D) ones. In each category, the studies were analyzed in terms of data, methods, and evaluation. We summarized the merits and limitations of current methods, as well as the future directions for efficient and accurate extraction of coronary plaques using CT imaging. Conclusion: The methodological innovations are important for more accurate CT-based assessment of coronary plaques in clinical applications. The large-scale studies, de-blooming algorithms, more standardized datasets, and more detailed classification of non-calcified plaques could improve the accuracy of coronary plaque extraction from CT images. More multidimensional geometric parameters can be derived from the 3D geometry of coronary plaques. Additionally, machine learning and automatic 3D reconstruction could improve the efficiency of coronary plaque extraction in future studies.
Authors: Bálint Szilveszter; Hesham Elzomor; Mihály Károlyi; Márton Kolossváry; Rolf Raaijmakers; Kálmán Benke; Csilla Celeng; Andrea Bartykowszki; Zsolt Bagyura; Árpád Lux; Béla Merkely; Pál Maurovich-Horvat Journal: Int J Cardiovasc Imaging Date: 2015-08-19 Impact factor: 2.357
Authors: Damini Dey; Victor Y Cheng; Piotr J Slomka; Ryo Nakazato; Amit Ramesh; Swaminatha Gurudevan; Guido Germano; Daniel S Berman Journal: J Cardiovasc Comput Tomogr Date: 2009-10-01
Authors: Matthias Renker; John W Nance; U Joseph Schoepf; Terrence X O'Brien; Peter L Zwerner; Mathias Meyer; J Matthias Kerl; Ralf W Bauer; Christian Fink; Thomas J Vogl; Thomas Henzler Journal: Radiology Date: 2011-06-21 Impact factor: 11.105