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TRUVACE RECORD VERSION
record: TRV-2026-1167
version: 3
kind: revised
reason: Editorial pass: sharper headline; filed as context: no real AI gain or problem (gain activity_only, problem absent).
timestamp: 2026-11-04T09:55:42.272041Z
status: published
lens: general
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: An AI algorithm enables real-time automated radial wall strain assessment from routine angiography, avoiding complex modelling and costly intracoronary imaging, to flag vulnerable plaques.
problem_title: (none)
trace_subject: (none)
gain_reading: An AI algorithm enables real-time automated radial wall strain assessment from routine angiography, avoiding complex modelling and costly intracoronary imaging, to flag vulnerable plaques.
gain_evidence: (none)
problem_reading: (none)
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: Context
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
prev: 974997dc5779126611617af5145db9edd94c312e386ffd113ff64ecc184f3b84

SHA-256 hash

1334fe96099d4ec84b22a95a2370abac192b726e75c464682e7552870b7cd602

Previous version’s hash

974997dc5779126611617af5145db9edd94c312e386ffd113ff64ecc184f3b84