End-diastolic segmentation of intravascular ultrasound images enables more reproducible volumetric analysis of atheroma burden.

Emrah ErdoğanXingru HuangJackie CooperAjay JainAnantharaman RamasamyRetesh BajajRyo ToriiJames MoonAndrew DeanerChristos CostaHector M Garcia-GarciaVincenzo TufaroPatrick W J C SerruysFrancesca PuglieseAnthony MathurJouke DijkstraAndreas BaumbachQianni ZhangChristos V Bourantas

Published in: Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions (2021)

ED IVUS segmentation enables more reproducible volumetric analysis and quantification of TAV and PAV that are established end points in longitudinal studies assessing the efficacy of novel pharmacotherapies. Therefore, it should be preferred over conventional IVUS analysis as its higher reproducibility is expected to have an impact on the sample size calculation for the primary end point.

Keyphrases

deep learning
convolutional neural network
emergency department
magnetic resonance imaging
blood pressure
coronary artery
left ventricular
machine learning