Submillimeter diffusion MRI using an in-plane segmented 3D multi-slab acquisition and denoiser-regularized reconstruction

Journal article

Diffusion MRI (dMRI) enables brain connectivity mapping but is constrained by spatial resolution. Previous post-mortem studies have demonstrated the potential of submillimeter dMRI in enabling more precise delineations of curved and crossing white matter pathways. However, achieving such resolution in-vivo poses significant challenges due to the intrinsically low signal-to-noise ratio (SNR). Furthermore, for echo-planar imaging (EPI), large matrix sizes often require long echo spacing, readout duration, and echo times (TE), leading to significant image distortion, T2* blurring, and T2 signal decay. Here, we propose an acquisition and reconstruction framework to overcome these challenges. Based on numerical simulations, we employ in-plane segmented 3D multi-slab EPI that leverages the optimal SNR efficiency of 3D multi-slab imaging while reducing echo spacing, readout durations, and TE using in-plane segmentation. This approach minimizes distortion, improves image sharpness, and enhances SNR. Additionally, we develop a denoiser-regularized reconstruction to suppress noise while maintaining data fidelity, which reconstructs highSNR images without introducing substantial blurring or bias. At 3T, we present 0.53-0.65 mm in-vivo data that reveal finer fiber architectures, reduced gyral bias, and improved Ufiber mapping compared to 1.22 mm data. At 7T, we acquire 0.61 mm data that show excellent agreement with high-resolution post-mortem dMRI, demonstrating robustness and high SNR at an ultra-high field. Our method is implemented using the open-source, scanneragnostic framework Pulseq to facilitate broader adoption across scanner platforms to benefit a wider range of applications. These results establish our approach as a promising tool for high-resolution dMRI, advancing neuroanatomical investigations of white matter architecture.

Authors: Li, Z; Zhu, S; Miller, K; Wu, W

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Elsevier
• Journal: Medical Image Analysis
• Volume: 107
• Issue: Part B
• Article number: 103834
• Publication date: 2025-10-09
• Acceptance date: 2025-10-05
• DOI: 10.1016/j.media.2025.103834
• EISSN: 1361-8423
• ISSN: 1361-8415
• Language: English
• Keywords: white matter; 3D diffusion MRI; high-resolution; tractography; gyral bias; U-fiber