Novel atlas of fiber directions built from ex-vivo diffusion tensor images of porcine hearts

Abstract

Cardiac MR image-based predictive models integrating statistical atlases of heart anatomy and fiber orientations can aid in better diagnosis of cardiovascular disease, a major cause of death worldwide. Such atlases have been built from diffusion tensor (DT) images and can be used in anisotropic models for personalized computational electro-mechanical simulations when the fiber directions from DTI are not available. In this paper, we propose a framework for building the first statistical fiber atlas from high-resolution ex-vivo DT images of porcine hearts. A mean geometry that represents the average cardiac morphology of the dataset was first generated via groupwise registration. Then, the associated average cardiac fiber architecture was mapped out by computing the mean of the transformed DT fields of the subjects. To evaluate the stability of the atlas, we performed leave-one-out cross-validation. The resulting tensor statistics indicate that the fiber atlas could accurately describe the fiber architecture of a healthy pig heart.