A Pilot Study Characterizing Flow Patterns in the Thoracic Aorta of Patients With Connective Tissue Disease: Comparison to Age- and Gender-Matched Controls via Fluid Structure Interaction

Author:

Camarda Joseph A.,Dholakia Ronak J.,Wang Hongfeng,Samyn Margaret M.,Cava Joseph R.,LaDisa John F.

Abstract

Prior computational and imaging studies described changes in flow patterns for patients with Marfan syndrome, but studies are lacking for related populations. This pilot study addresses this void by characterizing wall shear stress (WSS) indices for patients with Loeys-Dietz and undifferentiated connective tissue diseases. Using aortic valve-based velocity profiles from magnetic resonance imaging as input to patient-specific fluid structure interaction (FSI) models, we determined local flow patterns throughout the aorta for four patients with various connective tissue diseases (Loeys-Dietz with the native aorta, connective tissue disease of unclear etiology with native aorta in female and male patients, and an untreated patient with Marfan syndrome, as well as twin patients with Marfan syndrome who underwent valve-sparing root replacement). FSI simulations used physiological boundary conditions and material properties to replicate available measurements. Time-averaged WSS (TAWSS) and oscillatory shear index (OSI) results are presented with localized comparison to age- and gender-matched control participants. Ascending aortic dimensions were greater in almost all patients with connective tissue diseases relative to their respective control. Differences in TAWSS and OSI were driven by local morphological differences and cardiac output. For example, the model for one twin had a more pronounced proximal descending aorta in the vicinity of the ductus ligamentum that impacted WSS indices relative to the other. We are optimistic that the results of this study can serve as a foundation for larger future studies on the connective tissue disorders presented in this article.

Publisher

Frontiers Media SA

Subject

Pediatrics, Perinatology and Child Health

Reference48 articles.

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