Date(s) - 02/06/2012
11:45 am - 12:35 pm
Coronary artery disease (CAD) afflicts approximately 7.9% of the population in the United States over the age of 20 years, and is the cause of 1 in 6 deaths. Atherosclerotic plaques with thin fibrous caps, large necrotic lipid pools, and high densities of macrophages are more prone to rupture and cause acute coronary syndromes. Optical Coherence Tomography (OCT) provides real-time subsurface imaging of biological tissues with high spatial resolution (on the order of ten micrometers) in three dimensions in vivo. OCT can identify key components related to plaque vulnerability such as lipid pools, macrophages, calcium, and cap thickness. However, OCT may suffer from artifacts and ambiguities that could prevent accurate identification of lipid rich regions. There is a clinical need to make this diagnosis more straightforward, avoid misinterpretation of these features that may occur as a result of artifact, and to automatically discriminate lipid regions of entire pullbacks to facilitate 3D rendering.
In this talk, I will present the use of spectroscopic optical coherence tomography (SOCT) for automated plaque classification through morphological and depth resolved spectroscopic analysis of optical frequency domain images. This method can increase the contrast of OCT intracoronary images and facilitate a rapid comprehensive visualization of OCT datasets, which can potentially improve OCT diagnosis and/or assist in guiding therapeutic procedures.