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PMID: 35624334 Published · ppublish English Journal Article

Enhanced 4D Flow MRI-Based CFD with Adaptive Mesh Refinement for Flow Dynamics Assessment in Coarctation of the Aorta.

Annals of biomedical engineering ·Vol. 50 ·No. 8 ·2022-08-00 ·页码 1001-1016

Shahid L, Rice J, Berhane H, Rigsby C, Robinson J, Griffin L, Markl M, Roldán-Alzate A

Abstract

4D Flow MRI is a diagnostic tool that can visualize and quantify patient-specific hemodynamics and help interventionalists optimize treatment strategies for repairing coarctation of the aorta (COA). Despite recent developments in 4D Flow MRI, shortcomings include phase-offset errors, limited spatiotemporal resolution, aliasing, inaccuracies due to slow aneurysmal flows, and distortion of images due to metallic artifact from vascular stents. To address these limitations, we developed a framework utilizing Computational Fluid Dynamics (CFD) with Adaptive Mesh Refinement (AMR) that enhances 4D Flow MRI visualization/quantification. We applied this framework to five pediatric patients with COA, providing in-vivo and in-silico datasets, pre- and post-intervention. These two data sets were compared and showed that CFD flow rates were within 9.6% of 4D Flow MRI, which is within a clinically acceptable range. CFD simulated slow aneurysmal flow, which MRI failed to capture due to high relative velocity encoding (Venc). CFD successfully predicted in-stent blood flow, which was not visible in the in-vivo data due to susceptibility artifact. AMR improved spatial resolution by factors of 101 to 103 and temporal resolution four-fold. This computational framework has strong potential to optimize visualization/quantification of aneurysmal and in-stent flows, improve spatiotemporal resolution, and assess hemodynamic efficiency post-COA treatment.

Keywords
4D flow MRI Adaptive mesh refinement Computational fluid dynamics Congenital heart disease Patient-specific
MeSH 主题词
Child Humans Aortic Coarctation/diagnostic imaging Blood Flow Velocity Hemodynamics Hydrodynamics Imaging, Three-Dimensional/methods Magnetic Resonance Imaging/methods Surgical Mesh
作者与单位
共 8 位作者,点击展开单位 / ORCID
Shahid Labib ORCID
Department of Mechanical Engineering, University of Wisconsin-Madison, 1111 Highland Ave, Room 2476 WIMR II, Madison, WI, 53705, USA. [email protected].
Rice James
Department of Mechanical Engineering, University of Wisconsin-Madison, 1111 Highland Ave, Room 2476 WIMR II, Madison, WI, 53705, USA.
Berhane Haben
Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA. | Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, USA.
Rigsby Cynthia
Department of Medical Imaging, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, USA.
Robinson Joshua
Department of Medical Imaging, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, USA.
Griffin Lindsay
Department of Medical Imaging, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, USA.
Markl Michael
Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA. | Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, USA.
Roldán-Alzate Alejandro
Department of Mechanical Engineering, University of Wisconsin-Madison, 1111 Highland Ave, Room 2476 WIMR II, Madison, WI, 53705, USA. | Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, USA. | Department of Radiology, University of Wisconsin-Madison, Madison, WI, USA.
Article Info
Journal
Annals of biomedical engineering
Abbr.
Ann Biomed Eng
ISSN
1573-9686
Corresponding email
Published
2022-08-00
电子出版
2022-00-27
页码
1001-1016
Language
English
Country/Region
United States
NLM ID
0361512
基金资助
American Heart Association-American Stroke Association · 19TPA34850066 · United States
NIDDK NIH HHS · R01 DK126850 · United States
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