A Computational Framework for the Statistical Analysis of Cardiac Diffusion Tensors: Application to a Small Database of Canine Hearts

We propose a unified computational framework to build a statistical atlas of the cardiac fiber architecture from diffusion tensor magnetic resonance images (DT-MRIs). We apply this framework to a small database of nine ex vivo canine hearts. An average cardiac fiber architecture and a measure of its variability are computed using most recent advances in diffusion tensor statistics. This statistical analysis confirms the already established good stability of the fiber orientations and a higher variability of the laminar sheet orientations within a given species. The statistical comparison between the canine atlas and a standard human cardiac DT-MRI shows a better stability of the fiber orientations than their laminar sheet orientations between the two species. The proposed computational framework can be applied to larger databases of cardiac DT-MRIs from various species to better establish intraspecies and interspecies statistics on the anatomical structure of cardiac fibers. This information will be useful to guide the adjustment of average fiber models onto specific patients from in vivo anatomical imaging modalities.

I. Introduction

Cardiac fiber architecture, a complex arrangement of myofibers bounded to each other to form laminar sheets [1], plays an essential role in defining the electrical and mechanical behavior of the heart [2], [3]. Mathematical modeling of the cardiac fiber architecture and its variability is important to better understand physiological principles and to construct computational models of the heart [4], [5]. However, the in vivo imaging of the cardiac fiber architecture at high resolution is still considered to be infeasible in the near term because of heart motion and limitations in current imaging techniques [6], [7]. Therefore, modeling of the cardiac fiber architecture and its variability on ex vivo data is particularly important. For instance, the fiber architecture model can be used to simulate the electrical and mechanical functions of the heart for planning patient-specific therapies [8], [9].