Polarization-Sensitive Optical Coherence Tomography based Fully-Automated Volumetric Coronary Fibrous Cap Characterization

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 (CCS, 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. Conclusions 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.