Naslov
Global perspective on carotid intima-media thickness and plaque: should the current measurement guidelines be revisited?

Autori
Saba, Luca ; Jamthikar, Ankush ; Gupta, Deep ; Khanna, Narendra N ; Višković, Klaudija ; Suri, Harman S ; Gupta, Ajay ; Mavrogeni, Sophie ; Turk, Monika ; Laird, John R ; Areek, Gyan ; Miner, Martin ; Sfikakis, Petros P ; Protogerou, Athanasios ; Itas, George D ; Viswanathan, Vijay ; Nicolaides, Andrew ; Bhatt, Deepak L ; Suri, Jasjit S

Izvornik
International angiology (0392-9590) 38 (2019), 6; 451-465

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, pregledni rad, znanstveni

Ključne riječi
Ultrasonography ; Carotid arteries ; Cardiovascular diseases ; Stroke

Sažetak
Carotid intima-media thickness (cIMT) and carotid plaque (CP) currently act as risk predictors for CVD/Stroke risk assessment. Over 2000 articles have been published that cover either use cIMT/CP or alterations of cIMT/ CP and additional image- based phenotypes to associate cIMT related markers with CVD/Stroke risk. These articles have shown variable results, which likely reflect a lack of standardization in the tools for measurement, risk stratification, and risk assessment. Guidelines for cIMT/CP measurement are influenced by major factors like the atherosclerosis disease itself, conventional risk factors, 10-year measurement tools, types of CVD/ Stroke risk calculators, incomplete validation of measurement tools, and the fast pace of computer technology advancements. This review discusses the following major points: 1) the American Society of Echocardiography and Mannheim guidelines for cIMT/CP measurements ; 2) forces that influence the guidelines ; and 3) calculators for risk stratification and assessment under the influence of advanced intelligence methods. The review also presents the knowledge- based learning strategies such as machine and deep learning which may play a future role in CVD/stroke risk assessment. We conclude that both machine learning and non-machine learning strategies will flourish for current and 10-year CVD/Stroke risk prediction as long as they integrate image-based phenotypes with conventional risk factors.

Izvorni jezik
Engleski

Znanstvena područja
Kliničke medicinske znanosti

POVEZANOST RADA