Radial Wall Strain as an Angiography-Derived Biomarker for Plaque Vulnerability Assessment: Pathophysiology, Clinical Applications, and Prognostic Implications
Authors:
- Lisa SimioniLSLisa Simioni
- Wesley BennarWBWesley Bennar
- Giulia S BerettaGBGiulia S Beretta
- Thaïs PittetTPThaïs Pittet
- Matteo ChalMCMatteo Chal
- Julius JelisejevasJJJulius Jelisejevas
- Giacomo Maria CioffiGCGiacomo Maria Cioffi
- Pascal MeierPMPascal Meier
- Mariama AkodadMAMariama Akodad
- Thomas HovasseTHThomas Hovasse
- Philippe GarotPGPhilippe Garot
- Lorenzo FargioneLFLorenzo Fargione
Open Access
- 9 July 2026
- journal article
- review article
- Published by MDPI AG in Journal of Clinical Medicine
- Vol. 15 (14) , 5389
Abstract
Radial wall strain (RWS) is an angiography-derived biomechanical index that quantifies plaque deformability from routine coronary angiography, offering a novel approach to assess plaque vulnerability beyond conventional anatomical and physiological parameters. This narrative review synthesizes current evidence on the pathophysiological basis, clinical applications, and prognostic implications of RWS in coronary artery disease. Recent studies have demonstrated that elevated RWS values are associated with established markers of plaque vulnerability, including thin-cap fibroatheromas and large lipid cores, as well as increased risk of major adverse cardiovascular events. Furthermore, RWS has emerged as a promising tool for identifying vulnerable plaques in non-flow-limiting lesions and predicting in-stent restenosis, demonstrating incremental prognostic value when combined with angiography-derived physiological indices such as the quantitative flow ratio. By integrating biomechanical assessment with conventional physiological and morphological characterization, RWS may enhance risk stratification and guide clinical decision-making in percutaneous coronary intervention. While current evidence is encouraging, prospective randomized trials are needed to validate RWS-guided management strategies and establish optimal cutoff values for clinical implementation.Keywords
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