Diffusion MRI of the prenatal fetal brain: a methodological scoping review

Background: Fetal diffusion-weighted Magnetic Resonance Imaging (dMRI) represents a promising modality for the assessment of white matter fiber organization, microstructure and development during pregnancy. Over the past two decades, research using this technology has significantly increased, but no consensus has yet been established on how to best implement and standardize the use of fetal dMRI across clinical and research settings. Aims: This scoping review aims to synthesize the various methodological approaches for the analysis of fetal dMRI brain data and their applications. Methods: We identified a total of 54 relevant articles and analyzed them across five primary domains: (1) datasets, (2) acquisition protocols, (3) image preprocessing/denoising, (4) image processing/modeling, and (5) brain atlas construction. Results: The review of these articles reveals a predominant reliance on Diffusion Tensor Imaging (DTI) (n = 37) to study fiber properties, and deterministic tractography approaches to investigate fiber organization (n = 23). However, there is an emerging trend towards the adoption of more advanced techniques that address the inherent limitations of fetal dMRI (e.g. maternal and fetal motion, intensity artifacts, fetus's fast and uneven development), particularly through the application of artificial intelligence-based approaches (n = 8). In our view, the results suggest that the potential of fetal brain dMRI is hindered by the methodological heterogeneity of the proposed solutions and the lack of publicly available data and tools. Nevertheless, clinical applications demonstrate its utility in studying brain development in both healthy and pathological conditions.