Artificial Intelligence in Cardiovascular Atherosclerosis Imaging

被引:17
作者
Zhang, Jia [1 ]
Han, Ruijuan [2 ]
Shao, Guo [3 ]
Lv, Bin [4 ]
Sun, Kai [3 ]
机构
[1] Hohhot Hlth Comm, Hohhot 010000, Peoples R China
[2] Peoples Hosp Longgang Dist, Shenzhen 518172, Peoples R China
[3] Third Peoples Hosp Longgang Dist, Shenzhen 518100, Peoples R China
[4] Fuwai Hosp, Natl Ctr Cardiovasc Dis, Beijing 100037, Peoples R China
关键词
artificial intelligence; atherosclerosis; plaque characterization; CORONARY-ARTERY-DISEASE; OPTICAL COHERENCE TOMOGRAPHY; FRACTIONAL FLOW RESERVE; WALL SHEAR-STRESS; HIGH-RISK; AUTOMATIC CLASSIFICATION; PLAQUE CHARACTERIZATION; VULNERABLE PLAQUE; ANGIOGRAPHY; ULTRASOUND;
D O I
10.3390/jpm12030420
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
At present, artificial intelligence (AI) has already been applied in cardiovascular imaging (e.g., image segmentation, automated measurements, and eventually, automated diagnosis) and it has been propelled to the forefront of cardiovascular medical imaging research. In this review, we presented the current status of artificial intelligence applied to image analysis of coronary atherosclerotic plaques, covering multiple areas from plaque component analysis (e.g., identification of plaque properties, identification of vulnerable plaque, detection of myocardial function, and risk prediction) to risk prediction. Additionally, we discuss the current evidence, strengths, limitations, and future directions for AI in cardiac imaging of atherosclerotic plaques, as well as lessons that can be learned from other areas. The continuous development of computer science and technology may further promote the development of this field.
引用
收藏
页数:14
相关论文
共 78 条
[1]   Automated plaque classification using computed tomography angiography and Gabor transformations [J].
Acharya, U. Rajendra ;
Meiburger, Kristen M. ;
Koh, Joel En Wei ;
Vicnesh, Jahmunah ;
Ciaccio, Edward J. ;
Lih, Oh Shu ;
Tan, Sock Keow ;
Aman, Raja Rizal Azman Raja ;
Molinari, Filippo ;
Ng, Kwan Hoong .
ARTIFICIAL INTELLIGENCE IN MEDICINE, 2019, 100
[2]   Clinical applications of machine learning in cardiovascular disease and its relevance to cardiac imaging [J].
Al'Aref, Subhi J. ;
Anchouche, Khalil ;
Singh, Gurpreet ;
Slomka, Piotr J. ;
Kolli, Kranthi K. ;
Kumar, Amit ;
Pandey, Mohit ;
Maliakal, Gabriel ;
van Rosendael, Alexander R. ;
Beecy, Ashley N. ;
Berman, Daniel S. ;
Leipsic, Jonathan ;
Nieman, Koen ;
Andreini, Daniele ;
Pontone, Gianluca ;
Schoepf, U. Joseph ;
Shaw, Leslee J. ;
Chang, Hyuk-Jae ;
Narula, Jagat ;
Bax, Jeroen J. ;
Guan, Yuanfang ;
Min, James K. .
EUROPEAN HEART JOURNAL, 2019, 40 (24) :1975-+
[3]  
[Anonymous], 2017, LANCET, V390, P2739, DOI 10.1016/S0140-6736(17)31540-4
[4]   PCA-based polling strategy in machine learning framework for coronary artery disease risk assessment in intravascular ultrasound: A link between carotid and coronary grayscale plaque morphology [J].
Araki, Tadashi ;
Ikeda, Nobutaka ;
Shukla, Devarshi ;
Jain, Pankaj K. ;
Londhe, Narendra D. ;
Shrivastava, Vimal K. ;
Banchhor, Sumit K. ;
Saba, Luca ;
Nicolaides, Andrew ;
Shafique, Shoaib ;
Laird, John R. ;
Suri, Jasjit S. .
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2016, 128 :137-158
[5]   A new method for IVUS-based coronary artery disease risk stratification: A link between coronary & carotid ultrasound plaque burdens [J].
Araki, Tadashi ;
Ikeda, Nobutaka ;
Shukla, Devarshi ;
Londhe, Narendra D. ;
Shrivastava, Vimal K. ;
Banchhor, Sumit K. ;
Saba, Luca ;
Nicolaides, Andrew ;
Shafique, Shoaib ;
Laird, John R. ;
Suri, Jasjit S. .
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2016, 124 :161-179
[6]  
Athanasiou LS, 2011, IEEE ENG MED BIO, P4485, DOI 10.1109/IEMBS.2011.6091112
[7]   Wall-based measurement features provides an improved IVUS coronary artery risk assessment when fused with plaque texture-based features during machine learning paradigm [J].
Banchhor, Sumit K. ;
Londhe, Narendra D. ;
Araki, Tadashi ;
Saba, Luca ;
Radeva, Petia ;
Laird, John R. ;
Suri, Jasjit S. .
COMPUTERS IN BIOLOGY AND MEDICINE, 2017, 91 :198-212
[8]   Mechanisms of Plaque Formation and Rupture [J].
Bentzon, Jacob Fog ;
Otsuka, Fumiyuki ;
Virmani, Renu ;
Falk, Erling .
CIRCULATION RESEARCH, 2014, 114 (12) :1852-1866
[9]   Next-Generation Machine Learning for Biological Networks [J].
Camacho, Diogo M. ;
Collins, Katherine M. ;
Powers, Rani K. ;
Costello, James C. ;
Collins, James J. .
CELL, 2018, 173 (07) :1581-1592
[10]  
Cao YK, 2020, COMPUT MED IMAG GRAP, V81, DOI [10.1016/j.compmedimag.2020.101711, 10.1016/j.compmedimg.2020.101711]