دورية أكاديمية

Recent Trends in Artificial Intelligence-Assisted Coronary Atherosclerotic Plaque Characterization

التفاصيل البيبلوغرافية
العنوان: Recent Trends in Artificial Intelligence-Assisted Coronary Atherosclerotic Plaque Characterization
المؤلفون: Gudigar, A, Nayak, S, Samanth, J, Raghavendra, U, Ashwal, AJ, Barua, PD, Hasan, N, Ciaccio, EJ, Tan, R-S, Acharya, UR
بيانات النشر: MDPI AG
سنة النشر: 2022
المجموعة: University of Technology Sydney: OPUS - Open Publications of UTS Scholars
مصطلحات موضوعية: Toxicology
الوصف: Coronary artery disease is a major cause of morbidity and mortality worldwide. Its underlying histopathology is the atherosclerotic plaque, which comprises lipid, fibrous and—when chronic—calcium components. Intravascular ultrasound (IVUS) and intravascular optical coherence tomography (IVOCT) performed during invasive coronary angiography are reference standards for characterizing the atherosclerotic plaque. Fine image spatial resolution attainable with contemporary coronary computed tomographic angiography (CCTA) has enabled noninvasive plaque assessment, including identifying features associated with vulnerable plaques known to presage acute coronary events. Manual interpretation of IVUS, IVOCT and CCTA images demands scarce physician expertise and high time cost. This has motivated recent research into and development of artificial intelligence (AI)-assisted methods for image processing, feature extraction, plaque identification and characterization. We performed parallel searches of the medical and technical literature from 1995 to 2021 focusing respectively on human plaque characterization using various imaging modalities and the use of AI-assisted computer aided diagnosis (CAD) to detect and classify atherosclerotic plaques, including their composition and the presence of high-risk features denoting vulnerable plaques. A total of 122 publications were selected for evaluation and the analysis was summarized in terms of data sources, methods—machine versus deep learning—and performance metrics. Trends in AI-assisted plaque characterization are detailed and prospective research challenges discussed. Future directions for the development of accurate and efficient CAD systems to characterize plaque noninvasively using CCTA are proposed.
نوع الوثيقة: article in journal/newspaper
وصف الملف: application/pdf
اللغة: English
تدمد: 1661-7827
1660-4601
العلاقة: International Journal of Environmental Research and Public Health; International Journal of Environmental Research and Public Health, 2021, 18, (19), pp. 10003; http://hdl.handle.net/10453/154586Test
الإتاحة: http://hdl.handle.net/10453/154586Test
حقوق: info:eu-repo/semantics/openAccess
رقم الانضمام: edsbas.E02AE65B
قاعدة البيانات: BASE