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TRUVACE RECORD VERSION
record: TRV-2026-1167
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-09-22T06:53:37.381535Z
status: published
lens: p_space
sector: crime
headline: Radial wall strain for residual risk stratification after percutaneous coronary intervention
dek: 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 (…
gain_title: (none)
problem_title: 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.
trace_subject: (none)
gain_reading: (none)
gain_evidence: (none)
problem_reading: 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.
problem_evidence: (none)
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.
limitation: 
tag: Evidence-backed problem
key_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.
rundown: 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. 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.
sources:
- peer_reviewed | EuroIntervention | https://doi.org/10.4244/eij-d-26-00126 | 2026-09-21
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