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September 27, 2025Circulation Cardiovascular ImagingOpen Access

Artificial Intelligence-Led Whole Coronary Artery OCT Analysis; Validation and Identification of Drug Efficacy and Higher-Risk Plaques

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Authors

BJBenn JessneyCXChen XuSGSophie Gu

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Overview

Observational analysis improves plaque composition identification in patients, highlighting AI's role in drug efficacy evaluation.

Key Points

  • AutoOCT achieved tissue and plaque classification accuracy of 83%, equivalent to expert clinicians.
  • High-risk plaque features were identified, including minimal lumen area <3.5 mm² and lipid arc >180°.
  • The study validated AutoOCT's performance using ex vivo and core laboratory analyses with multiple patient cohorts.
  • AI-based OCT analysis may enhance clinician capabilities in assessing drug efficacy and detecting high-risk lesions.

Cite This Study

Jessney et al. (2025) studied this question.

synapsesocial.com/papers/68d7b3edeebfec0fc5237236https://doi.org/10.1161/circimaging.125.018133
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Also Consider

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  5. 5A Artifact-corrected artificial intelligence-LED intracoronary OCT analysis identifies plaque progression and vulnerability, drug efficacy and patient events2025 · 1 citations