Feasibility and Implementation of a Deep Learning MR Reconstruction for TSE Sequences in Musculoskeletal Imaging.

Judith Herrmann,Thomas Kuestner,Mariappan Nadar,Sebastian Gassenmaier,Gregor Koerzdoerfer,Mahmoud Mostapha,Dominik Nickel,Ahmed E Othman

doi:10.3390/diagnostics11081484

Abstract

Magnetic Resonance Imaging (MRI) of the musculoskeletal system is one of the most common examinations in clinical routine. The application of Deep Learning (DL) reconstruction for MRI is increasingly gaining attention due to its potential to improve the image quality and reduce the acquisition time simultaneously. However, the technology has not yet been implemented in clinical routine for turbo spin echo (TSE) sequences in musculoskeletal imaging. The aim of this study was therefore to assess the technical feasibility and evaluate the image quality. Sixty examinations of knee, hip, ankle, shoulder, hand, and lumbar spine in healthy volunteers at 3 T were included in this prospective, internal-review-board-approved study. Conventional (TSES) and DL-based TSE sequences (TSEDL) were compared regarding image quality, anatomical structures, and diagnostic confidence. Overall image quality was rated to be excellent, with a significant improvement in edge sharpness and reduced noise compared to TSES (p < 0.001). No difference was found concerning the extent of artifacts, the delineation of anatomical structures, and the diagnostic confidence comparing TSES and TSEDL (p > 0.05). Therefore, DL image reconstruction for TSE sequences in MSK imaging is feasible, enabling a remarkable time saving (up to 75%), whilst maintaining excellent image quality and diagnostic confidence.

Highlights

Introduction published maps and institutional affilMagnetic Resonance Imaging (MRI) has become an important diagnostic tool for the evaluation of the musculoskeletal (MSK) system
One big disadvantage of MRI is the long examination time, which is not tolerated by a substantial proportion of patients and, on the other hand, comes along with other downsides such as decreased image quality due to motion artifacts, increased costs and reduced patient throughput [1]
The acquisition time of MRI is primarily determined by the achievable sampling rate for a given contrast and image quality, which, in turn, is determined by the number of samples needed for the image reconstruction for a given size and resolution

Summary

Introduction

Introduction published maps and institutional affilMagnetic Resonance Imaging (MRI) has become an important diagnostic tool for the evaluation of the musculoskeletal (MSK) system. Different acceleration strategies have been proposed and established such as parallel imaging (PI) and Compressed Sensing (CS) [2,3,4,5,6,7,8,9,10,11,12,13,14].

Objectives

Methods

Results