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PMID: 39129987 Published · epublish English

Multiphysiologic State Computational Fluid Dynamics Modeling for Planning Fontan With Interrupted Inferior Vena Cava.

JACC. Advances ·Vol. 3 ·No. 7 ·2024-07-00

Hoganson DM, Govindarajan V, Schulz NE, Eickhoff ER, Breitbart RE, Marx GR, Del Nido PJ, Hammer PE

Abstract

Single ventricle (SV) patients with interrupted inferior vena cava (iIVC) and azygos continuation are at high risk for unbalanced hepatic venous flow (HVF) distribution to the lungs after Fontan completion and subsequent pulmonary arteriovenous malformations (AVMs) formation. The aim of the study was to utilize computational fluid dynamics (CFD) analysis to avoid maldistribution of HVF to the lungs after Fontan surgery. Four SV subjects with iIVC were prospectively studied with a 3-dimensional (3D) modeling workflow with digital 3D models created from segmented magnetic resonance images or computer tomography scans, virtual surgery, and CFD analysis over multiple physiologic states for the evaluation of operative plans to achieve balanced HVF to both lungs. Three of the patients were Fontan revision candidates with existing AVMs. All patients underwent Fontan completion or revision surgery. CFD predicted that existing or proposed Fontan completion in all patients would result in 100% of HVF to one lung. Improved HVF balance was achieved with CFD analysis of alternative surgical approaches resulting in the average distribution of HVF to the right/left pulmonary arteries of 37%/63% ± 10.4%. A hepatoazygos shunt was required in all patients and additional creation of an innominate vein in one. CFD analysis was validated by the comparison of pre-operative predicted and postoperative MRI-measured total right/left pulmonary flow (51%/49% ± 5.4% vs 49%/51% ± 8.5%). A 3D modeling workflow with CFD simulation for SV patients with iIVC may avoid HVF maldistribution and development of AVMs after Fontan completion.

Keywords
3D model Fontan flow modeling single ventricle virtual surgery
Article Info
Journal
JACC. Advances
Abbr.
JACC Adv
ISSN
2772-963X
Published
2024-07-00
Language
English
Country/Region
United States
NLM ID
9918419284106676
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