Non-Invasive Prediction of Site-Specific Coronary Atherosclerotic Plaque Progression Using Lipidomics, Blood Flow, and LDL Transport Modeling

Non-Invasive Prediction of Site-Specific Coronary Atherosclerotic Plaque Progression Using Lipidomics, Blood Flow, and LDL Transport Modeling

Background: coronary computed tomography angiography (CCTA) is a first line non-invasive imaging modality for detection of coronary atherosclerosis. Computational modeling with lipidomics analysis can be used for prediction of coronary atherosclerotic plaque progression. Methods: 187 patients (480 v...

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Bibliographic Details
Main Authors: Antonis I. Sakellarios, Panagiota Tsompou, Vassiliki Kigka, Panagiotis Siogkas, Savvas Kyriakidis, Nikolaos Tachos, Georgia Karanasiou, Arthur Scholte, Alberto Clemente, Danilo Neglia, Oberdan Parodi, Juhani Knuuti, Lampros K. Michalis, Gualtiero Pelosi, Silvia Rocchiccioli, Dimitrios I. Fotiadis
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Applied Sciences
Subjects:
prediction of plaque progression
computational modeling
endothelial shear stress
LDL transport
non-invasive FFR
Online Access:https://www.mdpi.com/2076-3417/11/5/1976

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https://www.mdpi.com/2076-3417/11/5/1976

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