Multimodal and multiscale modeling and simulation of the fiber architecture of the human heart – MOSIFAH

Heart disease remains one of the most serious health problems in the world. According to the World Health Organization estimates in 2011, 17.3 million people around the globe died from this disease in 2008; this represents about 1/3 of all deaths globally. Despite decades of intensive cardiovascular research in basic and clinical sciences, very little information exists on the intrinsically three-dimensional (3D) fiber architecture of the human heart, which is however fundamental for a comprehensive understanding of the interrelations between mechanical function, hemodynamic, and adaptive structural changes in cardiac diseases. The only reason for this situation is that there is currently no means to access such in vivo 3D fiber architecture. Diffusion magnetic resonance imaging (dMRI) including diffusion tensor imaging (DTI) and High Angular Resolution Diffusion Imaging (HARDI), intensively studied for the human brain, appears as the new and perhaps the only way to access the 3D fiber architecture of the in vivo human heart. However, due to the tissue property itself of the myocardium and the motion sensitivity, it is currently not possible to obtain in vivo cardiac fiber architecture. To tackle this problem, we propose here a radically different approach, based on synergy between specialists from different disciplines such as physicians, computer scientists, mathematicians, physicist and clinical doctors. The idea consists in modeling and simulating the ex vivo and in vivo 3D fiber architectures at various scales using multiphysical data from different imaging modalities working at different spatial resolutions. To this end, the myocardium of the human heart will be imaged using respectively Polarized Light Imaging (PLI) and dMRI. Appropriate diffusion models will be explored including second and fourth order DTI models as well as HARDI models such as the single shell Q-Ball Imaging (QBI). These various types of images will be processed within the right Riemannian mathematical framework to provide tensor as well as Ensemble Average Propagator (EAP) and Orientation Distribution Function (ODF) fields. Virtual cardiac fiber structure (VCFS) will then be modeled using myocardial fiber information derived from each of these imaging modalities. Finally, diffusion behavior of water molecules in these VCFSs will be simulated by means of quantum spin theory, which allows computing ex vivo and in vivo virtual diffusion magnetic resonance (MR) images at various scales ranging from a few microns to a few millimeters. From the obtained virtual diffusion MR images, multiscale and probabilistic atlas describing the 3D fiber architecture of the heart ex vivo and in vivo will be constructed. Meanwhile, the simulation involving a large number of water molecules, grid computing will be used to cope with huge computation resource requirement. We expect to construct a complete database containing a very wide range of simulated (noise- and artifact-free) diffusion images that can be used as benchmarks or ground-truth for evaluating or validating diffusion image processing algorithms, create new virtual fiber models allowing mimicking and better understanding the heart muscle structures, pioneer ex vivo and in vivo fiber architecture atlases at various scales featuring statistical properties of the myocardium, establish first-ever gateways between different scales of the fiber architecture, and provide the possibility for researchers and clinical doctors to better explain diffusion anisotropy phenomenon and predict tissue structure of the heart through customizing the models to specific patient hearts. Ultimately, the proposed research can open a completely novel way to approach the whole field of heart diseases including the fundamental understanding of heart physiology and pathology, and new diagnosis, monitoring and treatment of patients.