Literature DB >> 29032716

Prediction of coronary plaque progression using biomechanical factors and vascular characteristics based on computed tomography angiography.

Xiujian Liu1, Guanghui Wu1, Chuangye Xu1, Yuna He1, Lixia Shu1, Yuyang Liu1, Nan Zhang1, Changyan Lin1.   

Abstract

OBJECTIVES: Coronary atherosclerotic plaques progress in a highly individual manner. Accurately predicting plaque progression will promote clinical management of atherosclerosis. The purpose of this study was to investigate the role of local biomechanics factors and vascular characteristics in coronary plaque progression and arterial remodeling.
METHODS: Computed tomography angiography-based three-dimensional reconstruction of the native right coronary artery was performed in vivo in twelve patients with acute coronary syndrome at baseline and 12-month follow-up. The reconstructed arteries were divided into sequential 3-mm-long segments. Wall shear stress (WSS) and von Mises stress (VMS) were computed in all segments at baseline by applying fluid-structure interaction simulations.
RESULTS: In total, 365 segments 3-mm long were analyzed. The decrease in minimal lumen area was independently predicted by low baseline VMS (-0.73 ± 0.13 mm2), increase in plaque burden was independently predicted by small minimal lumen area and low baseline WSS (6.28 ± 0.96%), and decrease in plaque volume was independently predicted by low baseline VMS (-0.99 ± 0.49 mm3). Negative remodeling was more likely to occur in low- (55%) and moderate-VMS (40%) segments, but expansive remodeling was more likely to occur in high-VMS (44%) segments.
CONCLUSIONS: Local von Mises stress, wall shear stress, minimal lumen area, and plaque burden provide independent and additive prediction in identifying coronary plaque progression and arterial remodeling.

Entities:  

Keywords:  Coronary artery disease; computed tomography angiography; fluid-structure interaction; natural history; von Mises stress; wall shear stress

Mesh:

Year:  2017        PMID: 29032716     DOI: 10.1080/24699322.2017.1389407

Source DB:  PubMed          Journal:  Comput Assist Surg (Abingdon)        ISSN: 2469-9322            Impact factor:   1.787


  3 in total

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Journal:  Results Eng       Date:  2021-08-24

Review 2.  Biomechanical Forces and Atherosclerosis: From Mechanism to Diagnosis and Treatment.

Authors:  Vadim V Genkel; Alla S Kuznetcova; Igor I Shaposhnik
Journal:  Curr Cardiol Rev       Date:  2020

3.  Machine Learning Coronary Artery Disease Prediction Based on Imaging and Non-Imaging Data.

Authors:  Vassiliki I Kigka; Eleni Georga; Vassilis Tsakanikas; Savvas Kyriakidis; Panagiota Tsompou; Panagiotis Siogkas; Lampros K Michalis; Katerina K Naka; Danilo Neglia; Silvia Rocchiccioli; Gualtiero Pelosi; Dimitrios I Fotiadis; Antonis Sakellarios
Journal:  Diagnostics (Basel)       Date:  2022-06-14
  3 in total

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