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Updated: Oct 27, 2025

Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression
Published on: January 15, 2022
Adoption of a new automated optical coherence tomography software to obtain a lipid plaque spread-out plot
Francesco Isidori1, Eugenio Lella1, Valeria Marco1
1Centro per la Lotta Contro L'Infarto - CLI Foundation, Rome, Italy.
Purpose:
Near infrared spectroscopy-Intravascular ultrasound (NIRS-IVUS) provide a fully automated Lipid Core Burden Index (LCBI). Optical coherence tomography (OCT) is potentially capable of measuring lipid longitudinal extension in a dedicated two-dimensional LCBI spread-out plot. The present study has been designed to validate an automated approach to assess OCT images, able of providing a dedicated LCBI spread-out plot.
Methods:
We compared results obtained with conventional (manual) OCT, with those obtained with a novel automated OCT algorithm and with NIRS-IVUS in consecutive 40 patients. Our goal was to calculate the lipid core longitudinal extension in a dedicated two-dimensional LCBI spread-out plot. Three groups were identified according to the studied lesions: (1) culprit lesions in ACS patients (n = 16), (2) non-culprit lesions in ACS patients (n = 12) and (3) lesions in stable patients (n = 12). OCT (either manual and automated) and NIRS-IVUS assessment showed for culprit ACS plaques a more complex anatomy.
Results:
A strong trend for increased LCBI was found in the culprit ACS group, regardless of the adopted imaging modality (either NIRS-IVUS or automated OCT). A fair correlation was obtained for the maximum 4 mm LCBI measured by NIRS-IVUS and automated OCT (r = 0.75). The sensitivity and specificity of automated OCT to detect significant LCBI (> 400) were 90.5 and 84.2 respectively.
Conclusion:
We developed an OCT automated approach that can provide a dedicated lipid plaque spread-out plot to address plaque vulnerability. The automated OCT software can promote and improve OCT clinical applications for the identification of patients at risk of hard events.

