(B-50) Investigating the feasibility of predicting myocardial fiber architecture using cardiac strains

Introduction:: The myocardium is composed of a complex network of contractile myofibers that are organized in such a way as to produce efficient contraction and relaxation of the heart. The myofiber architecture in the myocardium is a key determinant of cardiac motion and the global or organ-level function of the heart. Reports of architectural remodeling in cardiac diseases, such as pulmonary hypertension and myocardial infarction, potentially contributing to cardiac dysfunction call for the inclusion of an architectural marker for an improved assessment of cardiac function. However, the in-vivo quantification of three-dimensional myo-architecture has proven challenging. Despite recent advancements, diffusion tensor-magnetic resonance imaging DT-MRI's [1] use in clinical settings is limited by motion artifacts, low spatial resolution, and accessibility issues. For small animal studies, these limitations are even more severe due to their size and motion constraints. Thus, there is a need to develop methods to quantify the cardiac fiber structure from traditional in-vivo imaging techniques. We have recently introduced an inverse model [2] to estimate the myofiber architecture by using the anatomical strains. We used synthetic fiber orientations as ground truth in finite element (FE) simulations to estimate orientations from cardiac strains. We estimated the myofiber helicity and regional fiber angle using systolic strains as inputs. Thus, here we are hypothesizing that MRI-based strains can be used to estimate the fiber architecture. We propose to use actual MRI strains from murine hearts to estimate fiber orientation and compare them against orientation from histological analysis of cardiac tissues in the same animal.

Materials and Methods:: We investigated the effect of myocardium fiber architecture on cardiac strains by using synthetic fiber structures to simulate the left ventricle (LV) model. Using forward simulations in four mouse-specific hearts models, we predicted the strain data and plotted it against myofiber structure metrics. By doing this, we were able to establish a relationship between strain and fiber architecture as shown in Fig B. Furthermore, we developed an inverse model that aimed to predict myofiber architecture from cardiac strains.


Results, Conclusions, and Discussions:: Results and Discussion: Our results corroborate the idea that the fiber structure is a critical indicator of LV contractile behavior by showing a strong correlation between fiber orientation and LV kinematics. Fig. A shows the results of our inverse model and a successful prediction of the myofiber architecture. Four mice hearts were used to create different random fiber architectures, in terms of fiber range. Different criteria were analyzed including normal strains, shear strains, and torsion (representative correlation is shown in Fig. B). A p-value of < 0.001 is observed for all of the normal strains. Next, strains calculated from MRI slices (representative slices are shown in Fig. C) will be used to estimate orientation. Representative histological for validations in the murine model is shown in Fig. D.

Conclusions: Myocardial fiber architecture plays an important role in defining the kinematics of the left ventricle. Anatomical strains can be used to predict fiber architecture. A good correlation was seen between the strains and fiber architecture. To further solidify the validation, we are further hypothesizing that instead of synthetic fiber architecture, we can use the fiber orientations from the histology data. The histology data of four mice models is shown in Fig. D. The fiber orientation observed in the four mice models is between -30 degrees (for epicardium) and 40 degrees (for endocardium). So, an overall fiber range of 70 degrees is observed. For future studies, we are recommending to also use DT-MRI data to validate the results. Furthermore, extending this study to human heart models is also a very good future research area.


Acknowledgements (Optional): : RA was supported by the NIH, under grant No. R00HL138288.

References (Optional): : [1] Scott et al. Journal of Cardiovascular Magnetic Resonance 20(1), 1–15 (2018) [2] Usman et al. (2023). On the possibility of estimating myocardial fiber architecture from cardiac strains. 10.13140/RG.2.2.10298.06082.