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    The Potential for Quantifying Regional Distributions of Radial and Shear Strain in the Thoracic and Abdominal Aortic Wall Using Spiral Cine DENSE Magnetic Resonance Imaging

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    Date
    2021
    Author
    Jones, Patrick A.
    Wilson, John S.
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    Abstract
    Aortic displacement encoding with stimulated echoes (DENSE) magnetic resonance imaging (MRI) was recently developed to assess heterogeneities in aortic wall circumferential strain (CS). However, previous studies neglected potential radial and shear strain (RSS) distributions. Herein, we present an improved aortic DENSE MRI postprocessing method to assess the feasibility of quantifying all components of the two-dimensional (2D) strain tensor. 32 previously acquired 2D DENSE scans from three distinct aortic locations were re-analyzed. Contrasting previous studies, displacements of the inner and outer aortic wall layers were processed separately to preserve RSS. Differences in regional strain between the new and old postprocessing methods were evaluated, along with interobserver, intraobserver, and interscan repeatability for all strain components. The new postprocessing method revealed an overall mean absolute difference in regional CS of 0.01 ± 0.01 compared to the prior method, with minimal impact on CS repeatability. Mean absolute magnitudes of regional RSS increased significantly compared to changes in CS (radial 0.04 ± 0.05, p < 0.001; shear 0.04 ± 0.04, p = 0.02). Most repeatability metrics for RSS were significantly worse than for CS. The unique distributions of RSS for each axial location associated well with local periaortic structures and mean aortic displacement. The new postprocessing method captures heterogeneous distributions of nonzero RSS which may provide new information for improving clinical diagnostics and computational modeling of heterogeneous aortic wall mechanics. However, future studies are required to improve the repeatability of RSS and assess the influence of partial volume effects.
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    http://yetl.yabesh.ir/yetl1/handle/yetl/4276079
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