AI-powered optical coherence tomography shows similar performance to intravascular ultrasound for plaque burden quantification: head-to-head benchmark study against histopathology of native coronary arteries.
7 affiliations
- 1Biomedical Instrument Institute, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, China.
- 2School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, Guangdong, China.
- 3Division of Cardiology, Department of Medicine, Verona University Hospital, Verona 37126, Italy.
- 4Department of Histopathology, University Hospital Galway and University of Galway, Galway H91 YR71, Ireland.
- 5Department of Radiology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
- 6The Lambe Institute for Translational Medicine, Smart Sensors Laboratory and Curam, University of Galway, H91 TK33 Galway, Ireland.
- 7Department of Cardiology, Erasmus University Medical Center, Rotterdam 3015 GD, the Netherlands.
Abstract
Aims
Optical coherence tomography (OCT) provides excellent resolution at the cost of shallow penetration, limiting its ability for plaque burden (PB) assessment. A deep learning (DL) algorithm was therefore developed to provide fully automated assessment of PB and vessel size from OCT. We aimed to perform a head-to-head comparison of AI-powered OCT vs. intravascular ultrasound (IVUS) for PB quantification, using histopathology as the reference standard.Methods and results
Ten post-mortem human hearts were harvested. All 29 major epicardial coronary arteries were perfused and underwent OCT and IVUS pullbacks. After imaging, the arteries were serially sectioned at 1-mm intervals for histopathology. Lumen and vessel contours were derived fully automatically from OCT using the DL algorithm and semi-automatically from IVUS. Histopathological measurements were obtained by experienced analysts. Statistical analyses accounted for within-patient clustering. A total of 852 paired OCT-IVUS histopathology cross-sections were obtained. AI-powered OCT showed strong correlations with histopathology for the assessment of lumen area (r = 0.89 [95% CI: 0.88-0.91]), vessel area (r = 0.85 [95% CI: 0.83-0.87]), and PB (r = 0.76 [95% CI: 0.73-0.79]). The corresponding correlations between IVUS and histopathology were 0.90 (95% CI: 0.89-0.92), 0.86 (95% CI: 0.84-0.88), and 0.79 (95% CI: 0.76-0.81), respectively. Comparisons of the OCT-histopathology and IVUS-histopathology correlation coefficients yielded P = 0.336 for lumen area, P = 0.444 for vessel area, and P = 0.161 for PB. Both OCT and IVUS showed good diagnostic performance in identifying PB > 65%, with the area under the receiver operating characteristic curve being 0.92 (95% CI: 0.90-0.94) and 0.92 (95% CI: 0.88-0.95), respectively.Conclusion
In this histopathology validation study of 10 post-mortem human hearts, AI-powered OCT enabled fully automated plaque burden quantification and correlated strongly with histopathology, with no statistically significant difference between the OCT-histopathology and IVUS-histopathology correlations.
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BibTeX
@article{huang2026aipowered,
title = {{AI-powered optical coherence tomography shows similar performance to intravascular ultrasound for plaque burden quantification: head-to-head benchmark study against histopathology of native coronary arteries.}},
author = {Jiayue Huang and Ruobing Dai and Xu Yu and Miao Chu and Su Zhang and Simone Fezzi and Sean Hynes and Yining Wang and William Wijns and Shengxian Tu},
journal = {European heart journal. Digital health},
year = {2026},
month = oct,
doi = {10.1093/ehjdh/ztag163},
url = {https://europepmc.org/article/MED/42927271},
note = {CC BY},
}
RIS
TY - JOUR
TI - AI-powered optical coherence tomography shows similar performance to intravascular ultrasound for plaque burden quantification: head-to-head benchmark study against histopathology of native coronary arteries.
AU - Jiayue Huang
AU - Ruobing Dai
AU - Xu Yu
AU - Miao Chu
AU - Su Zhang
AU - Simone Fezzi
AU - Sean Hynes
AU - Yining Wang
AU - William Wijns
AU - Shengxian Tu
PY - 2026
DA - 2026/10/12
JO - European heart journal. Digital health
DO - 10.1093/ehjdh/ztag163
UR - https://europepmc.org/article/MED/42927271
AB - Aims Optical coherence tomography (OCT) provides excellent resolution at the cost of shallow penetration, limiting its ability for plaque burden (PB) assessment. A deep learning (DL) algorithm was therefore developed to provide fully automated assessment of PB and vessel size from OCT. We aimed to perform a head-to-head comparison of AI-powered OCT vs. intravascular ultrasound (IVUS) for PB quantification, using histopathology as the reference standard.Methods and results Ten post-mortem human hearts were harvested. All 29 major epicardial coronary arteries were perfused and underwent OCT and IVUS pullbacks. After imaging, the arteries were serially sectioned at 1-mm intervals for histopathology. Lumen and vessel contours were derived fully automatically from OCT using the DL algorithm and semi-automatically from IVUS. Histopathological measurements were obtained by experienced analysts. Statistical analyses accounted for within-patient clustering. A total of 852 paired OCT-IVUS histopathology cross-sections were obtained. AI-powered OCT showed strong correlations with histopathology for the assessment of lumen area (r = 0.89 [95% CI: 0.88-0.91]), vessel area (r = 0.85 [95% CI: 0.83-0.87]), and PB (r = 0.76 [95% CI: 0.73-0.79]). The corresponding correlations between IVUS and histopathology were 0.90 (95% CI: 0.89-0.92), 0.86 (95% CI: 0.84-0.88), and 0.79 (95% CI: 0.76-0.81), respectively. Comparisons of the OCT-histopathology and IVUS-histopathology correlation coefficients yielded P = 0.336 for lumen area, P = 0.444 for vessel area, and P = 0.161 for PB. Both OCT and IVUS showed good diagnostic performance in identifying PB > 65%, with the area under the receiver operating characteristic curve being 0.92 (95% CI: 0.90-0.94) and 0.92 (95% CI: 0.88-0.95), respectively.Conclusion In this histopathology validation study of 10 post-mortem human hearts, AI-powered OCT enabled fully automated plaque burden quantification and correlated strongly with histopathology, with no statistically significant difference between the OCT-histopathology and IVUS-histopathology correlations.
SN - 2634-3916
ER -