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Assessing Lipid Core Burden Index with Depolarization-Sensitive Optical Frequency Domain Imaging

Jones, G.; Otsuka, K.; Fujisawa, N.; Yamaura, H.; Matsumoto, K.; Okamoto, A.; Yamaguchi, T.; Shimada, T.; Kagawa, S.; Yamazaki, T.; Akasaka, T.; Bouma, B. E.; Villiger, M.; Fukuda, D.

2026-06-01 cardiovascular medicine
10.64898/2026.05.22.26353889 medRxiv
Show abstract

Background: Quantitative lipid assessment is central to identifying rupture-prone coronary plaques and represents a therapeutic target for lipid-lowering therapy. Near-infrared spectroscopy (NIRS)-derived lipid core burden index (LCBI) is well validated and widely used for detecting lipid-rich lesions. Optical frequency domain imaging (OFDI) is increasingly adopted for guiding percutaneous coronary intervention (PCI) due to its high-resolution structural imaging capabilities. Depolarization-sensitive OFDI (depOFDI) provides intrinsic lipid contrast and may enable combined structural and compositional plaque characterization within a single OFDI-based platform. Objective: To define an OFDI-derived lipid metric and evaluate its agreement with NIRS-derived LCBI. Methods: Thirty-three patients underwent both polarization-sensitive OFDI and NIRS-intravascular ultrasound imaging during PCI. After exclusion of 4 datasets, 29 co-registered pullbacks were analyzed. A signal-to-noise-corrected depolarization metric was used to identify lipid-rich regions and generate depOFDI chemograms. maxLCBI4mm value and location, as well as total LCBI, were computed and compared with NIRS. Results: depOFDI demonstrated strong agreement with NIRS, showing high correlation for maxLCBI4mm (r^2 = 0.862) and total LCBI (r^2 = 0.867), along with strong spatial concordance for the location of the maxLCBI4mm (r^2 = 0.900). Bland-Altman analysis of LCBI4mm showed minimal bias (10.7) with 95% limits of agreement of [81.4 to 102.8]. Conclusions: depOFDI enables accurate quantification of lipid burden alongside the high-resolution structural information inherently provided by OFDI. Because depolarization metrics can be derived from polarization-diverse detection available in many commercial OFDI systems, this approach provides a practical pathway toward comprehensive plaque characterization within existing PCI workflows, without the need for additional imaging modalities.

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