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Updated: May 14, 2026

Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression
Published on: January 15, 2022
Polarization-sensitive optical coherence tomography-based fully-automated volumetric coronary fibrous cap
Georgia L Jones1,2, Kenichiro Otsuka3, Laurens van Zandvoort4
1Wellman Center for Photomedicine, Massachusetts General Hospital, Boston, MA 02139, USA.
Aims:
Accurate characterization of fibrous caps in coronary arteries allows more precise estimations of coronary plaque rupture risk. While intravascular imaging techniques offer high-resolution imaging, limitations in contrast and reliance on manual interpretation hinder large-scale, volumetric assessments of cap morphology. In this study, we present CapSeg, a fully automated computational pipeline for in vivo fibrous cap segmentation and thickness measurement, leveraging intravascular polarization-sensitive OCT (IV-PS-OCT). By incorporating reflectance, birefringence, and depolarization metrics, CapSeg differentiates fibrous caps from lipid-rich cores, enabling automated extraction of minimum cap thickness and polarization properties across entire vessel segments.
Methods And Results:
Using a dataset of 200 cross-sectional coronary IV-PS-OCT images, CapSeg's minimum cap thickness measurements were validated against manual annotations from two expert observers. Automated cap thickness measurements showed strong agreement with manual assessments (mean ± SD: CapSeg 131 ± 80 µm; Observer 1: 137 ± 84 µm; Observer 2: 144 ± 83 µm) demonstrating comparable limits of agreement relative to the inter-observer variability. The pipeline was applied to volumetric IV-PS-OCT data of 38 coronary lesions from patients with acute coronary syndrome (ACS, n = 23) or chronic coronary syndrome (n = 15). This analysis revealed decreased birefringence (3.7·10-4 vs. 4.5·10-4) and increased depolarization (9.6·10-2 vs. 8.6·10-2) in the fibrous caps of patients with acute disease.
Conclusion:
Overall, CapSeg enables fast, reproducible, and fully automated fibrous cap evaluation, laying the foundation for large-scale clinical studies and real-time intravascular imaging applications.
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