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Crime·P Space·Evidence-backed problem·Published 2026-09-22

Radial wall strain for residual risk stratification after percutaneous coronary intervention

Abstract: Background Percutaneous coronary intervention effectively treats flow-limiting stenoses; however, untreated non-target vessels with vulnerable plaques remain a major contributor to future adverse cardiovascular events. Plaque strain is a promising marker of plaque vulnerability but traditionally requires complex modelling and expensive intracoronary imaging. We developed a novel artificial intelligence algorithm for subpixel-level lumen delineation, enabling real-time automated assessment of radial wall strain (…

TRV-2026-1167Peer-reviewedPermanent record — cite & verify
Radial wall strain for residual risk stratification after percutaneous coronary intervention

Reduction of residual stresses and distortion in girth welded pipes by Barnes, Pamela Kay. Public domain

The quick read

Background Percutaneous coronary intervention effectively treats flow-limiting stenoses; however, untreated non-target vessels with vulnerable plaques remain a major contributor to future adverse cardiovascular events. Plaque strain is a promising marker of plaque vulnerability but traditionally requires complex modelling and expensive intracoronary imaging.

We developed a novel artificial intelligence algorithm for subpixel-level lumen delineation, enabling real-time automated assessment of radial wall strain (RWS) from routine angiography. A prespecified cutoff value of maximal RWS (RWS max ) ≥13% was used to define increased plaque vulnerability.

Main points
  • Background Percutaneous coronary intervention effectively treats flow-limiting stenoses; however, untreated non-target vessels with vulnerable plaques remain a major contributor to future adverse cardiovascular events.
  • Plaque strain is a promising marker of plaque vulnerability but traditionally requires complex modelling and expensive intracoronary imaging.
  • We developed a novel artificial intelligence algorithm for subpixel-level lumen delineation, enabling real-time automated assessment of radial wall strain (RWS) from routine angiography.
Problem

Radial wall strain for residual risk stratification after percutaneous coronary intervention: Ongoing and planned prospective, randomised trials are evaluating the role of RWS-guided risk stratification.

The rundown

We developed a novel artificial intelligence algorithm for subpixel-level lumen delineation, enabling real-time automated assessment of radial wall strain (RWS) from routine angiography. Aims This post hoc study sought to determine the prognostic value of RWS for predicting future cardiac events in non-target vessels over 5 years, using the high-quality TARGET All Comers randomised trial.

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