Literature DB >> 30989577

Effect of carotid image-based phenotypes on cardiovascular risk calculator: AECRS1.0.

Narendra N Khanna1, Ankush D Jamthikar2, Deep Gupta2, Tadashi Araki3, Matteo Piga4, Luca Saba5, Carlo Carcassi6, Andrew Nicolaides7, John R Laird8, Harman S Suri9, Ajay Gupta10, Sophie Mavrogeni11, Athanasios Protogerou12, Petros Sfikakis13, George D Kitas14, Jasjit S Suri15.   

Abstract

Today, the 10-year cardiovascular risk largely relies on conventional cardiovascular risk factors (CCVRFs) and suffers from the effect of atherosclerotic wall changes. In this study, we present a novel risk calculator AtheroEdge Composite Risk Score (AECRS1.0), designed by fusing CCVRF with ultrasound image-based phenotypes. Ten-year risk was computed using the Framingham Risk Score (FRS), United Kingdom Prospective Diabetes Study 56 (UKPDS56), UKPDS60, Reynolds Risk Score (RRS), and pooled composite risk (PCR) score. AECRS1.0 was computed by measuring the 10-year five carotid phenotypes such as IMT (ave., max., min.), IMT variability, and total plaque area (TPA) by fusing eight CCVRFs and then compositing them. AECRS1.0 was then benchmarked against the five conventional cardiovascular risk calculators by computing the receiver operating characteristics (ROC) and area under curve (AUC) values with a 95% CI. Two hundred four IRB-approved Japanese patients' left/right common carotid arteries (407 ultrasound scans) were collected with a mean age of 69 ± 11 years. The calculators gave the following AUC: FRS, 0.615; UKPDS56, 0.576; UKPDS60, 0.580; RRS, 0.590; PCRS, 0.613; and AECRS1.0, 0.990. When fusing CCVRF, TPA reported the highest AUC of 0.81. The patients were risk-stratified into low, moderate, and high risk using the standardized thresholds. The AECRS1.0 demonstrated the best performance on a Japanese diabetes cohort when compared with five conventional calculators. Graphical abstract AECRS1.0: Carotid ultrasound image phenotype-based 10-year cardiovascular risk calculator. The figure provides brief overview of the proposed carotid image phenotype-based 10-year cardiovascular risk calculator called AECRS1.0. AECRS1.0 was also benchmarked against five conventional cardiovascular risk calculators (Framingham Risk Score (FRS), United Kingdom Prospective Diabetes Study 56 (UKPDS56), UKPDS60, Reynolds Risk Score (RRS), and pooled composite risk (PCR) score).

Entities:  

Keywords:  10-year risk prediction; Atherosclerosis; Carotid intima-media thickness; Composite risk score; Conventional cardiovascular risk; Stroke; Ultrasound

Year:  2019        PMID: 30989577     DOI: 10.1007/s11517-019-01975-2

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN: 0140-0118            Impact factor:   2.602


  14 in total

1.  Wilson disease tissue classification and characterization using seven artificial intelligence models embedded with 3D optimization paradigm on a weak training brain magnetic resonance imaging datasets: a supercomputer application.

Authors:  Mohit Agarwal; Luca Saba; Suneet K Gupta; Amer M Johri; Narendra N Khanna; Sophie Mavrogeni; John R Laird; Gyan Pareek; Martin Miner; Petros P Sfikakis; Athanasios Protogerou; Aditya M Sharma; Vijay Viswanathan; George D Kitas; Andrew Nicolaides; Jasjit S Suri
Journal:  Med Biol Eng Comput       Date:  2021-02-05       Impact factor: 2.602

2.  Multiclass machine learning vs. conventional calculators for stroke/CVD risk assessment using carotid plaque predictors with coronary angiography scores as gold standard: a 500 participants study.

Authors:  Ankush D Jamthikar; Deep Gupta; Laura E Mantella; Luca Saba; John R Laird; Amer M Johri; Jasjit S Suri
Journal:  Int J Cardiovasc Imaging       Date:  2020-11-12       Impact factor: 2.357

3.  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

4.  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

5.  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 6.  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

Review 7.  Carotid plaque imaging and the risk of atherosclerotic cardiovascular disease.

Authors:  Guangming Zhu; Jason Hom; Ying Li; Bin Jiang; Fatima Rodriguez; Dominik Fleischmann; David Saloner; Michele Porcu; Yanrong Zhang; Luca Saba; Max Wintermark
Journal:  Cardiovasc Diagn Ther       Date:  2020-08

8.  A low-cost machine learning-based cardiovascular/stroke risk assessment system: integration of conventional factors with image phenotypes.

Authors:  Ankush Jamthikar; Deep Gupta; Narendra N Khanna; Luca Saba; Tadashi Araki; Klaudija Viskovic; Harman S Suri; Ajay Gupta; Sophie Mavrogeni; Monika Turk; John R Laird; Gyan Pareek; Martin Miner; Petros P Sfikakis; Athanasios Protogerou; George D Kitas; Vijay Viswanathan; Andrew Nicolaides; Deepak L Bhatt; Jasjit S Suri
Journal:  Cardiovasc Diagn Ther       Date:  2019-10

Review 9.  A Review on Joint Carotid Intima-Media Thickness and Plaque Area Measurement in Ultrasound for Cardiovascular/Stroke Risk Monitoring: Artificial Intelligence Framework.

Authors:  Mainak Biswas; Luca Saba; Tomaž Omerzu; Amer M Johri; Narendra N Khanna; Klaudija Viskovic; Sophie Mavrogeni; John R Laird; Gyan Pareek; Martin Miner; Antonella Balestrieri; Petros P Sfikakis; Athanasios Protogerou; Durga Prasanna Misra; Vikas Agarwal; George D Kitas; Raghu Kolluri; Aditya Sharma; Vijay Viswanathan; Zoltan Ruzsa; Andrew Nicolaides; Jasjit S Suri
Journal:  J Digit Imaging       Date:  2021-06-02       Impact factor: 4.903

10.  Cardiovascular/stroke risk prevention: A new machine learning framework integrating carotid ultrasound image-based phenotypes and its harmonics with conventional risk factors.

Authors:  Ankush Jamthikar; Deep Gupta; Narendra N Khanna; Luca Saba; John R Laird; Jasjit S Suri
Journal:  Indian Heart J       Date:  2020-06-18
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