3D Visualization and Quantitative Analysis of Myocardial Fiber Architecture Using Diffusion Tensor Imaging (DTI) in Humans

Project Abstract

This study presents a comprehensive investigation into the three-dimensional visualization and quantitative characterization of myocardial fiber architecture in humans using Diffusion Tensor Imaging (DTI) at high spatial resolution and advanced post-processing pipelines. By leveraging state-of-the-art diffusion-weighted imaging sequences and robust tensor estimation, we extracted voxel-wise diffusion metrics including fractional anisotropy (FA), mean diffusivity (MD), and eigenvectors to reconstruct myocardial fiber orientation and helix angle distribution across the left and right ventricles. We integrated drift correction, motion compensation, and cardiac gating to minimize physiological and scanner-induced artifacts, enabling precise mapping of intramyocardial fiber tracts in healthy volunteers and patients with ischemic cardiomyopathy. A novel multi-scale framework was developed to fuse DTI-derived fiber maps with anatomical MRI, enabling accurate segmentation of myocardial layers (subendocardial, midmyocardial, subepicardial) and within-voxel orientation dispersion analyses. Quantitative analyses encompassed global and regional metrics of fiber coherence, orientation dispersion, and helix-to-sheet angle transitions, with particular emphasis on the systolic-diastolic cycle and its impact on fiber contractile alignment. We conducted tractography-based reconstruction of myocardial fibers to quantify connectivity patterns and to identify region-specific deviations associated with pathological remodeling. The study also explores the relationship between diffusion metrics and functional outcomes derived from concurrent cine MRI and strain analyses, investigating how microstructural integrity relates to wall thickening, ejection fraction, and regional myocardial strain. To validate the DTI-derived fiber architecture, we performed phantom studies and comparisons with histological references from ex vivo hearts, as well as cross-validation against diffusion spectrum imaging (DSI) in a subset of samples. Reproducibility assessments demonstrated high intra- and inter-scan reliability for FA and principal eigenvector orientation in both healthy and diseased cohorts. We present a statistically powered analysis of differences in fiber architecture between normal myocardium and regions affected by scar, edema, or fibrotic remodeling, highlighting alterations in helix angle distribution, increased angular dispersion, and disrupted anisotropy in infarcted zones. The results indicate that DTI-derived microstructural metrics can serve as sensitive biomarkers of myocardial integrity, capable of detecting early remodeling before overt functional impairment. Finally, we discuss translational implications for personalized diagnostics, surgical planning, and rehabilitation, proposing a streamlined workflow for integrating DTI-based fiber maps into clinical decision-support systems. Potential limitations include partial volume effects, susceptibility-induced distortions near the papillary muscles, and the need for standardized acquisition protocols to enable multicenter comparisons. Overall, the study advances the quantitative understanding of human myocardial microstructure and provides a reproducible framework for leveraging DTI in cardiovascular research and clinical practice.

Project Overview

What This Project Is About

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This project explores how we can create 3D pictures of the heart’s muscle fibers and measure their properties using a special scan called diffusion tensor imaging (DTI). It aims to show how fibers run through the heart and how their arrangement changes in health and disease.

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The Problem It Addresses

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Understanding the exact pathways of heart muscle fibers is tough with traditional imaging. Without a clear map, diagnosing certain heart diseases or planning surgeries can be harder. This project fills that gap by providing a clearer, quantitative view of fiber directions.

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Objectives of the Project

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1. Learn the basics of heart anatomy and what diffusion imaging measures.
2. Develop a workflow to process DTI scans of the heart.
3. Visualize 3D fiber networks and extract simple metrics about fiber direction and organization.
4. Assess how fiber patterns differ between healthy and simulated or sample diseased hearts.
5. Evaluate the reliability of the measurements with basic repeatability checks.

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What You Will Do Step by Step

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1. Study introductory materials on heart anatomy and diffusion imaging.
2. Collect or access a small dataset of heart DTI scans (with appropriate consent and ethics if needed).
3. Preprocess the data to correct artifacts and align images.
4. Compute diffusion tensors and derive fiber direction maps.
5. Create 3D visualizations of fiber networks in the heart.
6. Quantify basic fiber metrics and compare across cases.
7. Draft a simple report describing methods and findings.

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Expected Outcome

Students will produce a clear, beginner-friendly explanation of how heart fiber architecture is visualized with DTI, plus a basic set of 3D visualizations and simple fiber metrics. The project should demonstrate a reproducible workflow and offer insights into how fiber patterns relate to heart health.