Purpose Quantitative assessment of myocardial deformation is increasingly important in clinical cardiology, yet conventional two-dimensional (2D) echocardiography and standard three-dimensional (3D) approaches remain limited by out-of-plane motion and incomplete characterization of transmural mechanics. To address these limitations, we introduce a physics-informed framework for 3D echocardiography that reconstructs the full finite strain tensor across the entire myocardial wall. As an initial methodological study, we demonstrate the framework and validate it against cardiac magnetic resonance in a small cohort. Methods Endocardial and epicardial surfaces were segmented from 3D echocardiographic datasets and tracked throughout the cardiac cycle using speckle-tracking techniques. An optimization framework with a soft volumetric penalty was implemented, permitting volume change at finite cost while maintaining tracking fidelity and geometric smoothness. The resulting deformation field enabled reconstruction of the complete 3D strain tensor. Global strain measurements derived from the method were validated against cardiac magnetic resonance (CMR) measurements obtained in two subjects. Results Global longitudinal and circumferential strain values obtained from the proposed framework showed strong agreement with CMR measurements. The optimization procedure also demonstrated robustness to segmentation variability and reduced errors associated with epicardial tracking. Beyond conventional strain indices, the method enabled reconstruction of spatially resolved principal strain fields throughout the ventricular wall, revealing physiologically consistent transmural gradients and contraction patterns. Conclusion Physics-informed integration of speckle tracking with biomechanical constraints enables robust reconstruction of 3D myocardial deformation from echocardiography. This framework provides a comprehensive and physically consistent characterization of myocardial mechanics from widely available 3D echocardiographic data. These initial results support the feasibility of the proposed framework and motivate future evaluation in larger, more diverse patient cohorts to establish its clinical reliability.
Satyaki Pradhan, Arash Yavari, Issac D. Lindley et al.· Annals of Biomedical Enginee...· 0 citations
Recent updates to the diagnostic criteria of multiple sclerosis (MS) require whole‐brain T2*‐weighted (T2*w) imaging with submillimeter resolution to detect novel diagnostic biomarkers such as the central vein sign. However, to achieve the needed submillimeter spatial resolution, conventional T2*w 3D gradient‐echo scans sequences are limited by prohibitively long scan times for clinical use. Here, we evaluated a different approach based on a segmented 3D echo planar imaging (3D‐EPI) sequence, accelerated with 2D Controlled Aliasing in Parallel Imaging Results in Higher Acceleration (CAIPIRINHA) undersampling and denoised with a deep learning‐based network.
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