On the R2* Relaxometry in Complex Multi-Peak Multi-Echo Chemical Shift-Based Water-Fat Quantification: Applications to the Neuromuscular Diseases

TL;DR

This paper evaluates advanced R2* relaxometry techniques in MRI for neuromuscular diseases, highlighting the benefits of complex multi-exponential models over simpler approaches, especially in fat-rich tissues.

Contribution

It introduces optimized complex-fitting algorithms for R2* mapping that reduce bias and artifacts, demonstrating improved accuracy in challenging tissue conditions.

Findings

2D complex fitting reduces bias in fat-rich tissues.

Multi-exponential models improve accuracy in iron overload cases.

1D models exhibit significant bias with high fat content.

Abstract

Purpose: Investigation of the feasibility of the R2* mapping techniques by using latest theoretical models corrected for confounding factors and optimized for signal to noise ratio. Theory and Methods: The improvement of the performance of state of the art MRI relaxometry algorithms is challenging because of a non-negligible bias and still unresolved numerical instabilities. Here, R2* mapping reconstructions, including complex-fitting with multi-spectral fat-correction by using single-decay (1D) and double-decay (2D) formulation, are studied in order to identify optimal configuration parameters and minimize numerical artifacts. The effects of echo number, echo spacing, and fat/water relaxation model are evaluated through simulated and in-vivo data. We also explore the stability of such models by analyzing the impact of high percentage of fat infiltrations and local transverse relaxation differences among biological species. Results: The main limits of the MRI relaxometry are the presence of bias and the occurrence of artifacts which affect its accuracy. Chemical-shift complex reconstructions R2*-corrected with 1D formulation exhibit a large bias in presence of a significant difference in the relaxation rates of fat and water and with fat concentration larger than 30%. We find that for fat-dominated tissues or in patients affected by iron overload, MRI reconstructions accounting for multi-exponential relaxation time provide accurate R2* measurements and are less prone to numerical artifacts. Conclusions: Complex fitting 2D formulation outperforms the conventional 1D approximation in various diagnostic scenarios. Although it still lacks of numerical stability which requires model enhancement and support from spectroscopy, it offers promising perspectives for the development of relaxometry as a reliable tool to improve tissue characterization and monitoring of neuromuscular disorders.