A Hybrid Hierarchical Framework for Quantifying Mechanical Markers in Atherosclerotic Disease Progression: A New Approach for Diagnosis and Risk Assessment

ABSTRACT Atherosclerosis is the primary pathological basis for cardiovascular diseases. Despite advances in diagnosis and treatment, current methods primarily focus on late‐stage intervention, missing critical opportunities for early detection. Recently, the dynamic mechanical properties of arterial tissue have been recognized as a novel approach for assessing vascular status, and offer an opportunity to employ the mechanical properties of atherosclerotic lesions for evaluating disease status and monitoring disease progression. Here, we employed a Hybrid Hierarchical theory–Microrheology (HHM) framework to quantify multiscale mechanical markers during lesion progression. The results revealed a two‐stage power‐law rheology, with short‐ and long‐timescale exponents ( α short , α long ) as key mechanical markers of lesion composition and mechanical gradients. We further applied a self‐similar hierarchical framework to capture plaque heterogeneity across cytoplasmic, cellular, and tissue scales, yielding additional mechanical markers (e.g., E 1 , η , E 2 , E 3 ) from subcellular to tissue scales. Based on these markers, we built a multiparametric diagnostic model that outperforms traditional elastic modulus criterion. This model captures stage‐ and region‐specific trajectories, coupling mechanical signatures with histology for improved staging and risk assessment, establishing an operational framework for enhanced prediction and diagnosis of atherosclerosis.

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Publication Details

Journal
Advanced Science
Published
2026-09-30
DOI
https://doi.org/10.1002/advs.77995
Primary Topic
Elasticity and Material Modeling
Type
article
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article

A Hybrid Hierarchical Framework for Quantifying Mechanical Markers in Atherosclerotic Disease Progression: A New Approach for Diagnosis and Risk Assessment

Ruining Peng, Guang‐Kui Xu, Huiyun Xu, Zhuo Chang et al.
Advanced Science
Elasticity and Material Modeling
article

A Hybrid Hierarchical Framework for Quantifying Mechanical Markers in Atherosclerotic Disease Progression: A New Approach for Diagnosis and Risk Assessment

Ruining Peng, Guang‐Kui Xu, Huiyun Xu, Zhuo Chang, Hui Yu Yang, Yu Liu, Sijie Wang, Nu Zhang, Hao Zhang, Yidan Zhou, Zhe Wang, Yuzhi Zhang, Haoyu Xu, Xianjun Wu
article en

Abstract

ABSTRACT Atherosclerosis is the primary pathological basis for cardiovascular diseases. Despite advances in diagnosis and treatment, current methods primarily focus on late‐stage intervention, missing critical opportunities for early detection. Recently, the dynamic mechanical properties of arterial tissue have been recognized as a novel approach for assessing vascular status, and offer an opportunity to employ the mechanical properties of atherosclerotic lesions for evaluating disease status and monitoring disease progression. Here, we employed a Hybrid Hierarchical theory–Microrheology (HHM) framework to quantify multiscale mechanical markers during lesion progression. The results revealed a two‐stage power‐law rheology, with short‐ and long‐timescale exponents ( α short , α long ) as key mechanical markers of lesion composition and mechanical gradients. We further applied a self‐similar hierarchical framework to capture plaque heterogeneity across cytoplasmic, cellular, and tissue scales, yielding additional mechanical markers (e.g., E 1 , η , E 2 , E 3 ) from subcellular to tissue scales. Based on these markers, we built a multiparametric diagnostic model that outperforms traditional elastic modulus criterion. This model captures stage‐ and region‐specific trajectories, coupling mechanical signatures with histology for improved staging and risk assessment, establishing an operational framework for enhanced prediction and diagnosis of atherosclerosis.

Advanced Science
Northwestern Polytechnical University (CN), Nanjing Drum Tower Hospital (CN), Xi'an Jiaotong University (CN)
Good health and well-being
Openalex Percentile: Top 22%
Elasticity and Material Modeling
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