Abstract

Background Myocardial fiber structure exhibits a helical geometry, characterized by the helical angle (HA). HA transitions smoothly from a negative helix in the epicardium to a positive helix in the endocardium. HA plays an important role in understanding the electrical and mechanical properties of the heart. Therefore, there exists a need to non-invasively quantify HA which can be determined using diffusion tensor imaging (DTI). The evaluation of HA measured from DTI depends on the accuracy of the diffusion tensors which in turn depend on the number of diffusion-encoding directions (DED) and the signal to noise ratio (SNR, which can be increased by increasing the total number of excitations (NEX)). However, increasing SNR and DED also increases the total acquisition time (TA). The aim of the study is to optimize the acquisition protocol (NEX and DED) to robustly estimate HA in the shortest possible TA.

Highlights

  • Myocardial fiber structure exhibits a helical geometry, characterized by the helical angle (HA)

  • The evaluation of HA measured from diffusion tensor imaging (DTI) depends on the accuracy of the diffusion tensors which in turn depend on the number of diffusion-encoding directions (DED) and the signal to noise ratio (SNR, which can be increased by increasing the total number of excitations (NEX))

  • Line profiles were computed along 16 spaced transmural regions (Figure 1) on the free wall of the left ventricle (LV) to evaluate the optimum acquisition parameter required for a robust estimation of HA

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Summary

Introduction

Myocardial fiber structure exhibits a helical geometry, characterized by the helical angle (HA). HA transitions smoothly from a negative helix in the epicardium to a positive helix in the endocardium. There exists a need to non-invasively quantify HA which can be determined using diffusion tensor imaging (DTI). The evaluation of HA measured from DTI depends on the accuracy of the diffusion tensors which in turn depend on the number of diffusion-encoding directions (DED) and the signal to noise ratio (SNR, which can be increased by increasing the total number of excitations (NEX)). Increasing SNR and DED increases the total acquisition time (TA). The aim of the study is to optimize the acquisition protocol (NEX and DED) to robustly estimate HA in the shortest possible TA

Objectives
Methods
Results

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