A Boosted Ensemble Algorithm for Determination of Plaque Stability in High-Risk Patients on Coronary CTA.

JACC. Cardiovascular Imaging
Subhi J Al'ArefJames K Min

Abstract

This study sought to identify culprit lesion (CL) precursors among acute coronary syndrome (ACS) patients based on qualitative and quantitative computed tomography-based plaque characteristics. Coronary computed tomography angiography (CTA) has been validated for patient-level prediction of ACS. However, the applicability of coronary CTA to CL assessment is not known. Utilizing the ICONIC (Incident COroNary Syndromes Identified by Computed Tomography) study, a nested case-control study of 468 patients with baseline coronary CTA, the study included ACS patients with invasive coronary angiography-adjudicated CLs that could be aligned to CL precursors on baseline coronary CTA. Separate blinded core laboratories adjudicated CLs and performed atherosclerotic plaque evaluation. Thereafter, the study used a boosted ensemble algorithm (XGBoost) to develop a predictive model of CLs. Data were randomly split into a training set (80%) and a test set (20%). The area under the receiver-operating characteristic curve of this model was compared with that of diameter stenosis (model 1), high-risk plaque features (model 2), and lesion-level features of CL precursors from the ICONIC study (model 3). Thereafter, the machine learning (ML) model wa...Continue Reading

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Citations

Jan 12, 2021·Frontiers in Cardiovascular Medicine·Karthik SeetharamPartho P Sengupta
Mar 30, 2021·Radiology. Cardiothoracic Imaging·Andrew LinDamini Dey
Apr 18, 2021·European Journal of Nuclear Medicine and Molecular Imaging·Riemer H J A SlartAntti Saraste
Jul 20, 2020·JACC. Cardiovascular Imaging·Michelle C Williams, David E Newby

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