Skip to main content
eScholarship
Open Access Publications from the University of California

UC Irvine

UC Irvine Previously Published Works bannerUC Irvine

Macrophages and Intravascular OCT Bright Spots A Quantitative Study

Abstract

Objectives

This study hypothesized that bright spots in intravascular optical coherence tomography (IVOCT) images may originate by colocalization of plaque materials of differing indexes of refraction. To quantitatively identify bright spots, we developed an algorithm that accounts for factors including tissue depth, distance from light source, and signal-to-noise ratio. We used this algorithm to perform a bright spot analysis of IVOCT images and compared these results with histological examination of matching tissue sections.

Background

Bright spots are thought to represent macrophages in IVOCT images, and studies of alternative etiologies have not been reported.

Methods

Fresh human coronary arteries (n = 14 from 10 hearts) were imaged with IVOCT in a mock catheterization laboratory and then processed for histological analysis. The quantitative bright spot algorithm was applied to all images.

Results

Results are reported for 1,599 IVOCT images co-registered with histology. Macrophages alone were responsible for only 23% of the bright spot-positive regions, although they were present in 57% of bright spot-positive regions (as determined by histology). Additional etiologies for bright spots included cellular fibrous tissue (8%), interfaces between calcium and fibrous tissue (10%), calcium and lipids (5%), and fibrous cap and lipid pool (3%). Additionally, we showed that large pools of macrophages in CD68(+) histology sections corresponded to dark regions in comparative IVOCT images; this is due to the fact that a pool of lipid-rich macrophages will have the same index of refraction as a pool of lipid and thus will not cause bright spots.

Conclusions

Bright spots in IVOCT images were correlated with a variety of plaque components that cause sharp changes in the index of refraction. Algorithms that incorporate these correlations may be developed to improve the identification of some types of vulnerable plaque and allow standardization of IVOCT image interpretation.

Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies. Let us know how this access is important for you.

Main Content
For improved accessibility of PDF content, download the file to your device.
Current View