![]() ![]() In addition, they found better stability in the statistical comparison of fiber orientations than the laminar sheet orientations between the computed canine atlas and a standard human cardiac DT-MRI. They also extracted diffusion tensor statistics characterizing cardiac fiber and laminar sheet orientations. presented a detailed computational framework for building a statistical atlas and applied said framework on a dataset of 9 ex-vivo canine hearts. They also compared their results against previous studies on mammals and found that they yielded concurring conclusions. ![]() In their study, they calculated the fiber orientation dispersion across the population. Their dataset consisted of 10 ex-vivo healthy hearts. Thus, an average atlas could be used instead of individual fiber directions.Ī statistical atlas of the human cardiac fiber architecture was first built by Lombaert et al. 9, 10 However, such information is difficult to obtain in-vivo due to lengthy MR imaging times. 2- 6 Thus, a remodeling of fiber orientations profoundly impacts the conduction properties of the heart, which is often impaired in CVD.įiber directions in healthy state can be determined via DT MRI and then integrated into predictive image-based heart models 7, 8 and statistical atlases. The organization of parallel myofibers into bundles helps coordinate the propagation of action potential electrical wave, leading to a synchronous depolarization and contraction of left and right ventricles. The cardiac muscle structure is characterized by a high degree of anisotropy. 1 Image-based models and statistical atlases of the cardiac anatomy and physiology can aid in better diagnosis and treatment-planning of CVD. The registration step eliminates the need for landmarks, while the tensor reorientation strategy enables the transformation of the diffusion tensors and preserves the diffusion tensor orientations.Ĭardiovascular disease (CVD) is the leading cause of mortality, accounting annually for 17 million deaths, or around 30% of all deaths worldwide. Our framework involves normalizing the cardiac geometries, reorienting local directional information on diffusion, and computing the average diffusion tensor field. In this work, we present a simple and computationally efficient pipeline for constructing a novel statistical cardiac atlas from ex-vivo high resolution DT images of porcine hearts. However, this information is not available due to limitations of cardiac in-vivo DTI thus, an average atlas could be used instead of individual fiber directions. Fiber directions can be obtained using diffusion tensor (DT) MR imaging and further integrated into computational heart models for accurate predictions of activation times and contraction. The local arrangement of cardiac fibers provides insight into the electrical and mechanical functions of the heart. ![]()
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