Abstract
We present a method to leverage the high fidelity of computed tomography (CT) to quantify regional left ventricular function using topography variation of the endocardium as a surrogate measure of strain. 4DCT images of 10 normal and 10 abnormal subjects, acquired with standard clinical protocols, are used. The topography of the endocardium is characterized by its regional values of fractal dimension ( FD ), computed using a box-counting algorithm developed in-house. The average FD in each of the 16 American Heart Association segments is calculated for each subject as a function of time over the cardiac cycle. The normal subjects show a peak systolic percentage change in FD of 5.9% ± 2% in all free-wall segments, whereas the abnormal cohort experiences a change of 2% ± 1.2% ( p < 0.00001 ). Septal segments, being smooth, do not undergo large changes in FD . Additionally, a principal component analysis is performed on the temporal profiles of FD to highlight the possibility for unsupervised classification of normal and abnormal function. The method developed is free from manual contouring and does not require any feature tracking or registration algorithms. The FD values in the free-wall segments correlated well with radial strain and with endocardial regional shortening measurements.