Toward Reliable Patient-Specific Aortic Strain Mapping from 4D CTA: Validation, Spectral Structure, and Clinical Potential
Abstract
Objective: To develop and validate a framework for spatially resolved ascending aortic strain estimation from 4D computed tomography angiography (CTA) and characterize reliability across segmentation sources and spatial scales. Methods: We constructed patient-specific aortic strain maps using nnU-Net segmentation, optimized surface remeshing, deformable registration, and mesh-based strain estimation. Finite element (FE)-derived synthetic 4D CT sequences provided controlled reference deformations for registration validation. Strain reliability was characterized across segmentation sources and Laplace-Beltrami (LB) spectral scales. Associations with diameter, aortic height index (AHI), and age were assessed. Results: Registration-derived median strain showed minimal bias relative to FE-reference strain for observer-derived (0.0013) and nnU-Net-derived meshes (0.0056). Median strain exhibited low bias and narrow 95% limits of agreement (LoA) across segmentation sources (interobserver: bias = -0.0045, LoA [-0.0490, 0.0399]; nnU-Net versus observer: bias = -0.0052, LoA [-0.0340, 0.0237]). Differences were greater for 95th-percentile strain, particularly in the interobserver comparison. LB spectral analysis showed preferential preservation of low-frequency strain organization, with k = 5 reconstructions reducing segmentation-related disagreement by 52-56%. The 95th-percentile areal strain was inversely associated with maximum ascending aortic diameter (r = -0.493, p = 0.005), AHI (r = -0.488, p = 0.005), and age (r = -0.479, p = 0.006). Three high-grade AR cases showed heterogeneous regional strain patterns. Conclusion: This framework reproducibly estimates ascending aortic strain from 4D CTA, characterizes its reliability across segmentation sources and spatial scales, and demonstrates its potential for noninvasive assessment of patient-specific aortic mechanics.
Related
- Representation-aware calibration enables statistically reliable protein structure search
- A scalable Zebrafish Platform for genetic validation and functional discovery of stage-specific breast cancer metastasis regulators
- Antioxidant Activity and Anti-Inflammatory Potential of Rhododendron dauricum Flowers via UPLC-Q-TOF-MS/MS Combined with Network Pharmacology and In Vitro Validation
- Functional validation of allele-specific LMNB1 silencing in patient-derived astrocytes as a therapeutic option for Autosomal Dominant Leukodystrophy
- Do Botanical Gardens Pose a Pollen Allergenicity Risk? A Multi-Method Assessment Integrating Species-Specific Values of Potential Allergenicity and Pollen Concentration Monitoring
BibTeX
@misc{lobo2026toward,
title = {{Toward Reliable Patient-Specific Aortic Strain Mapping from 4D CTA: Validation, Spectral Structure, and Clinical Potential}},
author = {Tricia Lobo and Wensi Wu and Harold I. Litt and Nimesh D. Desai and Alison M. Pouch},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.10913},
eprint = {2610.10913},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.10913},
}
RIS
TY - UNPB
TI - Toward Reliable Patient-Specific Aortic Strain Mapping from 4D CTA: Validation, Spectral Structure, and Clinical Potential
AU - Tricia Lobo
AU - Wensi Wu
AU - Harold I. Litt
AU - Nimesh D. Desai
AU - Alison M. Pouch
PY - 2026
DA - 2026/10/07
PB - arXiv
DO - 10.48550/arxiv.2610.10913
UR - https://arxiv.org/abs/2610.10913
AB - Objective: To develop and validate a framework for spatially resolved ascending aortic strain estimation from 4D computed tomography angiography (CTA) and characterize reliability across segmentation sources and spatial scales. Methods: We constructed patient-specific aortic strain maps using nnU-Net segmentation, optimized surface remeshing, deformable registration, and mesh-based strain estimation. Finite element (FE)-derived synthetic 4D CT sequences provided controlled reference deformations for registration validation. Strain reliability was characterized across segmentation sources and Laplace-Beltrami (LB) spectral scales. Associations with diameter, aortic height index (AHI), and age were assessed. Results: Registration-derived median strain showed minimal bias relative to FE-reference strain for observer-derived (0.0013) and nnU-Net-derived meshes (0.0056). Median strain exhibited low bias and narrow 95% limits of agreement (LoA) across segmentation sources (interobserver: bias = -0.0045, LoA [-0.0490, 0.0399]; nnU-Net versus observer: bias = -0.0052, LoA [-0.0340, 0.0237]). Differences were greater for 95th-percentile strain, particularly in the interobserver comparison. LB spectral analysis showed preferential preservation of low-frequency strain organization, with k = 5 reconstructions reducing segmentation-related disagreement by 52-56%. The 95th-percentile areal strain was inversely associated with maximum ascending aortic diameter (r = -0.493, p = 0.005), AHI (r = -0.488, p = 0.005), and age (r = -0.479, p = 0.006). Three high-grade AR cases showed heterogeneous regional strain patterns. Conclusion: This framework reproducibly estimates ascending aortic strain from 4D CTA, characterizes its reliability across segmentation sources and spatial scales, and demonstrates its potential for noninvasive assessment of patient-specific aortic mechanics.
ER -