Study on the Mathematical Relationship between Cerebral Vascular Stent Structural Parameters and Flexibility

Vascular stents play a crucial role in managing vascular pathologies with high mortality and disability rates. New opportunities for cerebrovascular stent design are offered by biodegradable materials. However, current design methodologies rely heavily on empirical trial-and-error. A systematic theoretical framework is still lacking. A closed-form analytical mathematical model, which differs from existing models by targeting the specific flexibility requirement of tortuous cerebrovascular anatomies, is presented in this study. The model is established based on cantilever beam theory, energy conservation and Castigliano's theorem. The model is built to correlate stent structural parameters with mechanical flexibility. Numerical calculation is performed with MATLAB. Validation is conducted via finite element analysis (FEA), with a coefficient of determination R 2 =0.997 for the core parameter strut width (w) and an overall average R 2 of 0.917 for all structural parameters after dimensionless normalization. Key findings are revealed: stent flexibility is inversely proportional to the cube of strut width (w) and thickness (t). A more significant effect on flexibility is exerted by w than t. The transition of cerebrovascular stent design from empirical-driven approaches to theory-guided reasoning is realized by this work.

Authors

Institutions

Publication Details

Journal
International Journal of Applied Mechanics
Published
2026-05-29
DOI
https://doi.org/10.1142/s1758825126500560
Primary Topic
Coronary Interventions and Diagnostics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Study on the Mathematical Relationship between Cerebral Vascular Stent Structural Parameters and Flexibility

Weiliang Shi, Ling Shi, Jiang Wang, Haijun Zhang
International Journal of Applied Mechanics
Coronary Interventions and Diagnostics
article

Study on the Mathematical Relationship between Cerebral Vascular Stent Structural Parameters and Flexibility

Weiliang Shi, Ling Shi, Jiang Wang, Haijun Zhang
article en

Abstract

Vascular stents play a crucial role in managing vascular pathologies with high mortality and disability rates. New opportunities for cerebrovascular stent design are offered by biodegradable materials. However, current design methodologies rely heavily on empirical trial-and-error. A systematic theoretical framework is still lacking. A closed-form analytical mathematical model, which differs from existing models by targeting the specific flexibility requirement of tortuous cerebrovascular anatomies, is presented in this study. The model is established based on cantilever beam theory, energy conservation and Castigliano's theorem. The model is built to correlate stent structural parameters with mechanical flexibility. Numerical calculation is performed with MATLAB. Validation is conducted via finite element analysis (FEA), with a coefficient of determination R 2 =0.997 for the core parameter strut width (w) and an overall average R 2 of 0.917 for all structural parameters after dimensionless normalization. Key findings are revealed: stent flexibility is inversely proportional to the cube of strut width (w) and thickness (t). A more significant effect on flexibility is exerted by w than t. The transition of cerebrovascular stent design from empirical-driven approaches to theory-guided reasoning is realized by this work.

International Journal of Applied Mechanics
Twitter (United States) (US)
Life in Land
Openalex Percentile: Top 6%
Coronary Interventions and Diagnostics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.