Effect of a consistent reconstruction algorithm on inter‐scanner reproducibility in diffusion MRI

作者：Qiang Liu, Ante Zhu, Xiaoqing Wang, Deniz Erdoğmuş, Carl‐Fredrik Westin, Lauren J. O’Donnell, Berkin Bilgiç, Lipeng Ning, Yogesh Rathi · 发表于：Medical Physics · 年份：2025 · DOI：10.1002/mp.70096 · 被引用次数：1 · 研究领域：Advanced Neuroimaging Techniques and Applications、Functional Brain Connectivity Studies、Fetal and Pediatric Neurological Disorders

BACKGROUND: Diffusion MRI (dMRI) enables non-invasive characterization of brain microstructure and connectivity. However, multi-center studies face reproducibility challenges due to inter-scanner variability, which arises from differences in hardware, acquisition protocols, and image reconstruction algorithms. While prior harmonization efforts have focused on standardizing protocols and post-processing methods, the impact of using a consistent reconstruction algorithm across scanners on inter-scanner reproducibility remains unexplored. PURPOSE: To evaluate the impact of consistent reconstruction algorithms on cross-vendor, inter-scanner reproducibility in diffusion MRI (dMRI) microstructure and tractography-derived measures. METHODS: Identical single-shell dMRI protocols were used on two clinical 3T scanners (Siemens Prisma and GE Premier) using simultaneous multi-slice (SMS) EPI sequences. Five healthy volunteers were scanned twice for capturing within-scanner variability and also on both scanners for computing cross-scanner variability (total of 20 scans). Three MRI image reconstruction methods were assessed: vendor-provided online reconstruction (Product), offline Split slice-GRAPPA (Split-GRAPPA), and offline L1-wavelet regularized SENSE (L1-ESPIRiT). Microstructure measures that were estimated included fiber-specific fractional anisotropy (FA) and mean diffusivity (MD) (from a multi-tensor UKF tractography model) and FA and MD (from a diffusion tensor imaging (DTI) model...