ArticleScientific reports2026
Severity and duration-dependent aortic stiffening in a rabbit coarctation model identifies constitutive material parameters as promising regional biomarkers for hypertension progression.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Coarctation of the aorta (CoA) alters hemodynamics and drives regional remodeling, yet the influence of severity and duration on constitutive properties is undefined. We quantified mechanical responses from CoA to identify constitutive parameters capturing stiffening across clinical severities and durations. Mild (≤ 12 mmHg), intermediate (13–20 mmHg), and severe (> 20 mmHg) CoA was created in rabbits for short, long, and prolonged durations (~ 1, 3, or 22 weeks, respectively). Stress–stretch curves from proximal and distal regions were fit with multiple constitutive models (Linear Elastic, Neo-Hookean, Yeoh, Ogden, Mooney–Rivlin, Holzapfel). Model performance was evaluated by normalized RMSE and R², with reproducibility assessed using bootstrap stability of strain energy–parameter coupling. Deterministic models were compared with multi-parameter hyperelastic formulations. Marked stiffening presented proximally for several CoA severities and durations, but was limited to pronounced sustained CoA distally. Yeoh provided reliable coupling between parameters and strain energy, whereas Holzapfel–Isotropic best captured nonlinear stress–stretch behavior. Within physiological ranges, linear elastic and Yeoh fits approximated stiffness effectively. Severity and duration were significant predictors of stiffening, consistent with findings linking these CoA features to hypertension. Yeoh and linear elastic model parameters are suitable as simplified CoA markers of induced proximal stiffening, while complex formulations capture full nonlinear behavior. These parameters align clinically with proximal remodeling and reduced compliance. They may ultimately inform risk stratification including intervention timing thresholds, as well as growth-and-remodeling and AI-based temporal approaches to forecast irreversible stiffening for personalized intervention with CoA patients.
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