  The limitations of conventional imaging techniques have hitherto precluded a
thorough and formal investigation of the complex morphology of the left
ventricular (LV) endocardial surface and its relation to the severity of
Coronary Artery Disease (CAD). Recent developments in high-resolution
Multirow-Detector Computed Tomography (MDCT) scanner technology have enabled
the imaging of LV endocardial surface morphology in a single heart beat.
Analysis of high-resolution Computed Tomography (CT) images from a 320-MDCT
scanner allows the study of the relationship between percent Diameter Stenosis
(DS) of the major coronary arteries and localization of the cardiac segments
affected by coronary arterial stenosis. In this paper a novel approach for the
analysis using a combination of rigid transformation-invariant shape
descriptors and a more generalized isometry-invariant Bag-of-Features (BoF)
descriptor, is proposed and implemented. The proposed approach is shown to be
successful in identifying, localizing and quantifying the incidence and extent
of CAD and thus, is seen to have a potentially significant clinical impact.
Specifically, the association between the incidence and extent of CAD,
determined via the percent DS measurements of the major coronary arteries, and
the alterations in the endocardial surface morphology is formally quantified. A
multivariate regression test performed on a strict leave-one-out basis are
shown to exhibit a distinct pattern in terms of the correlation coefficient
within the cardiac segments where the incidence of coronary arterial stenosis
is localized.
