Accelerating Cardiac Diffusion Tensor Imaging With a U-Net Based Model: Toward Single Breath-Hold.

ABSTRACT:

Background

In vivo cardiac diffusion tensor imaging (cDTI) characterizes myocardial microstructure. Despite its potential clinical impact, considerable technical challenges exist due to the inherent low signal-to-noise ratio.

Purpose

To reduce scan time toward one breath-hold by reconstructing diffusion tensors for in vivo cDTI with a fitting-free deep learning approach.

Study type

Retrospective.

Population

A total of 197 healthy controls, 547 cardiac patients.

Field strength/sequence

A 3 T, diffusion-weighted stimulated echo acquisition mode single-shot echo-planar imaging sequence.

Assessment

A U-Net was trained to reconstruct the diffusion tensor elements of the reference results from reduced datasets that could be acquired in 5, 3 or 1 breath-

SUBMITTER: Ferreira PF 

PROVIDER: S-EPMC9790699 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature