1. Impact and implications of mixed plaque class in automated characterization of complex atherosclerotic lesions

    Impact and implications of mixed plaque class in automated characterization of complex atherosclerotic lesions

    Atherosclerosis is a complex disease altering vasculature morphology, and subsequently flow, with progressive plaque formation, mural disruption, and lumen occlusion. Determination of clinically-relevant plaque components—particularly calcium, lipid, and fibrous tissue—has driven automated image-based tissue characterization. Atherosclerotic tissue of mixed composition type arises when these principal components interdigitate and combine during the course of progressive atherosclerosis. Nevertheless, such mixed plaque is treated non-uniformly, and often neglected, as a distinct class in image analysis. We therefore quantitatively investigate frameworks to characterize mixed and other plaque tissue types, and examine their implications. Convolutional neural networks operated on labeled intravascular optical coherence ...

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