This study was performed to characterize coronary plaque types by optical coherence tomography (OCT) and intravascular ultrasound (IVUS) radiofrequency (RF) data analysis, and to investigate the possibility of error reduction by combining these techniques. Intracoronary imaging methods have greatly enhanced the diagnostic capabilities for the detection of high-risk atherosclerotic plaques. IVUS RF data analysis and OCT are two techniques focusing on plaque morphology and composition. Regions of interest were selected and imaged with OCT and IVUS in 50 sections, from 14 human coronary arteries, sectioned post-mortem from 14 hearts of patients dying of non-cardiovascular causes. Plaques were classified based on IVUS RF data analysis (VH-IVUSTM), OCT and the combination of those. Histology was the benchmark. Imaging with both modalities and coregistered histology was successful in 36 sections. OCT correctly classified 24; VH-IVUS 25, and VH-IVUS/OCT combined, 27 out of 36 cross-sections. Systematic misclassifications in OCT were intimal thickening classified as fibroatheroma in 8 cross-sections. Misclassifications in VH-IVUS were mainly fibroatheroma as intimal thickening in 5 cross-sections. Typical image artifacts were found to affect the interpretation of OCT data, misclassifying intimal thickening as fibroatheroma or thin-cap fibroatheroma. Adding VH-IVUS to OCT reduced the error rate in this study.

Optical coherence tomography (OCT) is rapidly becoming the method of choice for assessing arterial wall pathology in vivo. Atherosclerotic plaques can be diagnosed with high accuracy, including measurement of the thickness of fibrous caps, enabling an assessment of the risk of rupture. While the OCT image presents morphological information in highly resolved detail, it relies on interpretation of the images by trained readers for the identification of vessel wall components and tissue type. We present a framework to enable systematic and automatic classification of atherosclerotic plaque constituents, based on the optical attenuation coefficient mu(t) of the tissue. OCT images of 65 coronary artery segments in vitro, obtained from 14 vessels harvested at autopsy, are analyzed and correlated with histology. Vessel wall components can be distinguished based on their optical properties: necrotic core and macrophage infiltration exhibit strong attenuation, mu(t)>or=10 mm(-1), while calcific and fibrous tissue have a lower mu(t) approximately 2-5mm(-1). The algorithm is successfully applied to OCT patient data, demonstrating that the analysis can be used in a clinical setting and assist diagnostics of vessel wall pathology.