Abstract 3821: Isotropic Wavelet Analysis for Identification of Coronary Atherosclerotic Plaque Components from Computed Tomography
Background: The capability of wavelet transforms to separate signals into frequency bands is the basis for its use in image compression and storage, data management and transmission, and, recently, extraction of latent images of tissue components from noisy medical images. Recent studies have shown that analyzing temporal variations of radiofrequency intravascular ultrasound backscatter with one-dimensional wavelets can detect lipid-laden plaque in human coronary arteries with a sensitivity and specificity of >80%. The current study presents the development and micro-CT testing of a novel, 3-D, isotropic, multiresolutional wavelet analysis for non-invasive discrimination between components of coronary atherosclerotic plaques.
Methods: Eighteen coronary artery segments (5–15 mm) of individuals with coronary artery disease were excised at necropsy. Specimens were imaged using a GE RS-9 micro-CT scanner and processed for histological correlation. Novel isotropic wavelets were applied to the CT data to distinguish tissue textures of varying scales and intensities. Voxels were classified and plaque characterization achieved by comparing the relative magnitude of these wavelet constituents to that of several reference plaque tissue components.
Results: Processing of micro-CT images via these wavelet algorithms permitted 3-D, color-coded, high resolution, digital discrimination between lumen, calcific deposits, lipid core, and fibromuscular tissue providing detail not possible with conventional thresholding based on Hounsfield intensity units. Lipid pools were identified with 83% sensitivity and >90% specificity. Calcific deposits as small as 50 microns and lipid pools beyond the resolution of 64-slice MDCT in its current configuration were also extracted.
Conclusions: Configuration of this micro-CT tested technology to the clinical, multi-detector scanners should be the next step toward realizing the capability of non-invasive high resolution identification of atherosclerotic plaque components, plaques prone to rupture (vulnerable plaques), and non-invasive monitoring of the effects of risk factor and/or treatment modification on the incidence of major acute coronary events.