Advances in acquisition and post-processing optimization of IVIM MRI for brain imaging: A systematic review

Purpose: Diffusion-weighted MRI is widely used to probe brain microstructure, but its signal reflects both diffusion and perfusion effects. Intravoxel Incoherent Motion (IVIM) MRI enables non-contrast separation of these components, offering potential clinical value in neuroimaging. However, clinical translation remains limited due to variability in acquisition and post-processing methods. This systematic review evaluates optimization strategies aimed at improving the accuracy, reproducibility, and clinical utility of IVIM parameters in brain. Methods: Registered in PROSPERO and conducted according to PRISMA guidelines, a systematic search across five databases was performed. Original peer-reviewed studies focusing on optimization of IVIM acquisition or post-processing in human brain imaging were included, while reviews and studies lacking methodological detail were excluded. Study quality was assessed using a customized QUADAS-2 tool. Due to methodological heterogeneity, an effect direction plot was applied instead of meta-analysis. Results: Out of 1,668 identified records, 14 studies were included. Acquisition strategies such as optimised b-value sampling, cardiac gating, and advanced sequences reduced parameter variability by up to 40 %. Post-processing methods, including Bayesian fitting, deep learning–based models, and advanced denoising, improved parameter accuracy by up to 99 % and precision by up to 95 %. Effect direction analysis demonstrated significant positive effects on accuracy and clinical utility (p < 0.001) and repeatability (p < 0.05), while scan-time reduction showed no significant benefit (p > 0.05). No study reported gold-standard validation. Conclusion: Optimization of IVIM acquisition and post-processing enhances parameter robustness and reproducibility in brain MRI, though protocol heterogeneity remains a major obstacle to standardization and clinical adoption.