Enhancing Diffusion-Weighted Images (DWI) for Diffusion MRI: Is it Enough without Non-Diffusion-Weighted B=0 Reference?

TL;DR

This paper introduces a novel ratio loss function for diffusion MRI image enhancement, improving the accuracy of diffusion metrics by better preserving the ratio between diffusion-weighted images and b=0 references, which is crucial for clinical diagnostics.

Contribution

The study proposes a new ratio loss that enhances super-resolution of diffusion MRI images by focusing on the ratio between DWI and b=0 images, improving diffusion metric accuracy.

Findings

Incorporating ratio loss reduces ratio mean squared error.

Enhanced DWI images lead to better diffusion metric preservation.

Improved PSNR in generated DWIs.

Abstract

Diffusion MRI (dMRI) is essential for studying brain microstructure, but high-resolution imaging remains challenging due to the inherent trade-offs between acquisition time and signal-to-noise ratio (SNR). Conventional methods often optimize only the diffusion-weighted images (DWIs) without considering their relationship with the non-diffusion-weighted (b=0) reference images. However, calculating diffusion metrics, such as the apparent diffusion coefficient (ADC) and diffusion tensor with its derived metrics like fractional anisotropy (FA) and mean diffusivity (MD), relies on the ratio between each DWI and the b=0 image, which is crucial for clinical observation and diagnostics. In this study, we demonstrate that solely enhancing DWIs using a conventional pixel-wise mean squared error (MSE) loss is insufficient, as the error in ratio between generated DWIs and b=0 diverges. We propose a novel ratio loss, defined as the MSE loss between the predicted and ground-truth log of DWI/b=0 ratios. Our results show that incorporating the ratio loss significantly improves the convergence of this ratio error, achieving lower ratio MSE and slightly enhancing the peak signal-to-noise ratio (PSNR) of generated DWIs. This leads to improved dMRI super-resolution and better preservation of b=0 ratio-based features for the derivation of diffusion metrics.