Literature DB >> 31782286

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

Luca Saba1, Ankush Jamthikar2, Deep Gupta2, Narendra N Khanna3, Klaudija Viskovic4, Harman S Suri5, Ajay Gupta6, Sophie Mavrogeni7, Monika Turk8, John R Laird9, Gyan Pareek10, Martin Miner11, Petros P Sfikakis12, Athanasios Protogerou13, George D Kitas14, Vijay Viswanathan15, Andrew Nicolaides16, Deepak L Bhatt17, Jasjit S Suri18.   

Abstract

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.

Entities:  

Mesh:

Year:  2019        PMID: 31782286     DOI: 10.23736/S0392-9590.19.04267-6

Source DB:  PubMed          Journal:  Int Angiol        ISSN: 0392-9590            Impact factor:   2.789


  16 in total

1.  Role of artificial intelligence in cardiovascular risk prediction and outcomes: comparison of machine-learning and conventional statistical approaches for the analysis of carotid ultrasound features and intra-plaque neovascularization.

Authors:  Amer M Johri; Laura E Mantella; Ankush D Jamthikar; Luca Saba; John R Laird; Jasjit S Suri
Journal:  Int J Cardiovasc Imaging       Date:  2021-05-29       Impact factor: 2.357

2.  Cardiovascular/stroke risk predictive calculators: a comparison between statistical and machine learning models.

Authors:  Ankush Jamthikar; Deep Gupta; Luca Saba; Narendra N Khanna; Tadashi Araki; Klaudija Viskovic; Sophie Mavrogeni; John R Laird; Gyan Pareek; Martin Miner; Petros P Sfikakis; Athanasios Protogerou; Vijay Viswanathan; Aditya Sharma; Andrew Nicolaides; George D Kitas; Jasjit S Suri
Journal:  Cardiovasc Diagn Ther       Date:  2020-08

3.  Ultrasound-based stroke/cardiovascular risk stratification using Framingham Risk Score and ASCVD Risk Score based on "Integrated Vascular Age" instead of "Chronological Age": a multi-ethnic study of Asian Indian, Caucasian, and Japanese cohorts.

Authors:  Ankush Jamthikar; Deep Gupta; Elisa Cuadrado-Godia; Anudeep Puvvula; Narendra N Khanna; Luca Saba; Klaudija Viskovic; Sophie Mavrogeni; Monika Turk; John R Laird; Gyan Pareek; Martin Miner; Petros P Sfikakis; Athanasios Protogerou; George D Kitas; Chithra Shankar; Andrew Nicolaides; Vijay Viswanathan; Aditya Sharma; Jasjit S Suri
Journal:  Cardiovasc Diagn Ther       Date:  2020-08

4.  Cardiovascular disease detection using machine learning and carotid/femoral arterial imaging frameworks in rheumatoid arthritis patients.

Authors:  George Konstantonis; Krishna V Singh; Petros P Sfikakis; Ankush D Jamthikar; George D Kitas; Suneet K Gupta; Luca Saba; Kleio Verrou; Narendra N Khanna; Zoltan Ruzsa; Aditya M Sharma; John R Laird; Amer M Johri; Manudeep Kalra; Athanasios Protogerou; Jasjit S Suri
Journal:  Rheumatol Int       Date:  2022-01-11       Impact factor: 2.631

Review 5.  Cardiovascular Risk Stratification in Diabetic Retinopathy via Atherosclerotic Pathway in COVID-19/Non-COVID-19 Frameworks Using Artificial Intelligence Paradigm: A Narrative Review.

Authors:  Smiksha Munjral; Mahesh Maindarkar; Puneet Ahluwalia; Anudeep Puvvula; Ankush Jamthikar; Tanay Jujaray; Neha Suri; Sudip Paul; Rajesh Pathak; Luca Saba; Renoh Johnson Chalakkal; Suneet Gupta; Gavino Faa; Inder M Singh; Paramjit S Chadha; Monika Turk; Amer M Johri; Narendra N Khanna; Klaudija Viskovic; Sophie Mavrogeni; John R Laird; Gyan Pareek; Martin Miner; David W Sobel; Antonella Balestrieri; Petros P Sfikakis; George Tsoulfas; Athanasios Protogerou; Durga Prasanna Misra; Vikas Agarwal; George D Kitas; Raghu Kolluri; Jagjit Teji; Mustafa Al-Maini; Surinder K Dhanjil; Meyypan Sockalingam; Ajit Saxena; Aditya Sharma; Vijay Rathore; Mostafa Fatemi; Azra Alizad; Vijay Viswanathan; Padukode R Krishnan; Tomaz Omerzu; Subbaram Naidu; Andrew Nicolaides; Mostafa M Fouda; Jasjit S Suri
Journal:  Diagnostics (Basel)       Date:  2022-05-14

6.  H2 FPEF score predicts atherosclerosis presence in patients with systemic connective tissue disease.

Authors:  Vladimir Vasilev; Dejana Popovic; Gorica G Ristic; Ross Arena; Goran Radunovic; Arsen Ristic
Journal:  Clin Cardiol       Date:  2021-06-02       Impact factor: 2.882

Review 7.  Cardiovascular risk assessment in patients with rheumatoid arthritis using carotid ultrasound B-mode imaging.

Authors:  Ankush D Jamthikar; Deep Gupta; Anudeep Puvvula; Amer M Johri; Narendra N Khanna; Luca Saba; Sophie Mavrogeni; John R Laird; Gyan Pareek; Martin Miner; Petros P Sfikakis; Athanasios Protogerou; George D Kitas; Raghu Kolluri; Aditya M Sharma; Vijay Viswanathan; Vijay S Rathore; Jasjit S Suri
Journal:  Rheumatol Int       Date:  2020-08-28       Impact factor: 2.631

8.  Comparison of carotid artery ultrasound and Framingham risk score for discriminating coronary artery disease in patients with psoriatic arthritis.

Authors:  Isaac T Cheng; Ka Tak Wong; Edmund K Li; Priscilla C H Wong; Billy T Lai; Isaac C Yim; Shirley K Ying; Kitty Y Kwok; Martin Li; Tena K Li; Jack J Lee; Alex P Lee; Lai-Shan Tam
Journal:  RMD Open       Date:  2020-09

9.  LPA Genotypes and Haplotypes Are Associated with Lipoprotein(a) Levels but Not Arterial Wall Properties in Stable Post-Coronary Event Patients with Very High Lipoprotein(a) Levels.

Authors:  Andreja Rehberger Likozar; Aleš Blinc; Katarina Trebušak Podkrajšek; Miran Šebeštjen
Journal:  J Cardiovasc Dev Dis       Date:  2021-12-13

10.  Unseen Artificial Intelligence-Deep Learning Paradigm for Segmentation of Low Atherosclerotic Plaque in Carotid Ultrasound: A Multicenter Cardiovascular Study.

Authors:  Pankaj K Jain; Neeraj Sharma; Luca Saba; Kosmas I Paraskevas; Mandeep K Kalra; Amer Johri; John R Laird; Andrew N Nicolaides; Jasjit S Suri
Journal:  Diagnostics (Basel)       Date:  2021-12-02
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.