4D flow MRI-based computational analysis of blood flow in patient-specific aortic dissection

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Title: 4D flow MRI-based computational analysis of blood flow in patient-specific aortic dissection
Authors: Pirola, S
Guo, B
Menichini, C
Saitta, S
Fu, W
Dong, Z
Xu, XY
Item Type: Journal Article
Abstract: OBJECTIVE: Computational hemodynamics studies of aortic dissections usually combine patient-specific geometries with idealized or generic boundary conditions. In this study we present a comprehensive methodology for simulations of hemodynamics in type B aortic dissection (TBAD) based on fully patient-specific BCs. METHODS: Pre-operative 4D flow magnetic resonance imaging (MRI) and Doppler-wire pressure measurements (pre- and post-operative) were acquired from a TBAD patient. These data were used to derive boundary conditions for computational modelling of flow before and after thoracic endovascular repair (TEVAR). Validations of the computational results were performed by comparing predicted flow patterns with pre-TEVAR 4D flow MRI, as well as pressures with in vivo measurements. RESULTS AND CONCLUSION: Comparison of instantaneous velocity streamlines showed a good qualitative agreement with 4D flow MRI. Quantitative comparison of predicted pressures with pressure measurements revealed a maximum difference of 11 mmHg (-9.7%). Furthermore, our model correctly predicted the reduction of true lumen pressure from 74/115 mmHg pre-TEVAR to 64/107 mmHg post-TEVAR (diastolic/systolic pressures at entry tear level), compared to the corresponding measurements of 72/118 mmHg and 64/114 mmHg. This demonstrates that pre-TEVAR 4D flow MRI can be used to tune boundary conditions for post-TEVAR hemodynamic analyses.
Issue Date: 1-Dec-2019
Date of Acceptance: 5-Mar-2019
DOI: 10.1109/TBME.2019.2904885
ISSN: 0018-9294
Publisher: Institute of Electrical and Electronics Engineers
Start Page: 3411
End Page: 3419
Journal / Book Title: IEEE Transactions on Biomedical Engineering
Volume: 66
Issue: 12
Copyright Statement: © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor/Funder: The Royal Society
The Royal Society
Funder's Grant Number: IE161052
Keywords: 0903 Biomedical Engineering
0906 Electrical and Electronic Engineering
0801 Artificial Intelligence and Image Processing
Biomedical Engineering
Publication Status: Published
Conference Place: United States
Online Publication Date: 2019-03-13
Appears in Collections:Faculty of Engineering
Chemical Engineering

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