Resolution and b value dependent Structural Connectome in ex vivo Mouse Brain

Abstract

Diffusion magnetic resonance imaging has been widely used in both clinical and preclinical studies to characterize tissue microstructure and structural connectivity. The diffusion MRI protocol for the Human Connectome Project (HCP) has been developed and optimized to obtain high-quality, high-resolution diffusion MRI (dMRI) datasets. However, such efforts have not been fully explored in preclinical studies, especially for rodents. In this study, high quality dMRI datasets of mouse brains were acquired at 9.4T system from two vendors. In particular, we acquired a high-spatial resolution dMRI dataset (25 um isotropic with 126 diffusion encoding directions), which we believe to be the highest spatial resolution yet obtained; and a high-angular resolution dMRI dataset (50 um isotropic with 384 diffusion encoding directions), which we believe to be the highest angular resolution compared to the dMRI datasets at the microscopic resolution. We systematically investigated the effects of three important parameters that affect the final outcome of the connectome: b value (1000 s/mm2 to 8000 s/mm2), angular resolution (10 to 126), and spatial resolution (25 um to 200 um). The stability of tractography and connectome increase with the angular resolution, where more than 50 angles are necessary to achieve consistent results. The connectome and quantitative parameters derived from graph theory exhibit a linear relationship to the b value (R2 > 0.99); a single-shell acquisition with b value of 3000 s/mm2 shows comparable results to the multi-shell high angular resolution dataset. The dice coefficient decreases and both false positive rate and false negative rate gradually increase with coarser spatial resolution. Our study provides guidelines and foundations for exploration of tradeoffs among acquisition parameters for the structural connectome in ex vivo mouse brain.

Age-dependent microstructure alterations in 5xFAD mice by high-resolution diffusion tensor imaging

“…A high-sensitivity cryogenic RF surface receiveonly coil was used for signal reception (Bruker CryoProbe). A multi-shot 3D EPI pulse sequence was used with the following parameters: matrix size = 180 × 128 × 76, FOV = 18.0 mm × 12.8 mm × 7.6 mm, 100 µm isotropic spatial resolution, TE = 22.3 ms, TR = 100 ms, 61 unique diffusion directions with b-value of 3000 s/mm 2 and six non-diffusionweighted (b0) measurements (Crater et al, 2022). The gradient separation time was 4.4 ms and the diffusion gradient duration time was 9.8 ms.…”

HiDiver: A Suite of Methods to Merge Magnetic Resonance Histology, Light Sheet Microscopy, and Complete Brain Delineations

“…comparison of figure S9B (at 126 angles) with figure S9C (at 61 angles) is not as obvious yet it results in a reduction of scan time by ~1/2. Recent work has demonstrated an inflection point at ~61 angles when comparing connectome metrics vs angular sampling [69]. Denoising.…”

“…The primary ways to further reduce scan times are to: 1. decrease spatial resolution, 2. decrease angular resolution, 3. increase the compression factor, or 4. decrease the repetition rate. We chose to fix the b values-that is the magnitude of diffusion weighting-for all acquisitions at 3000 s/mm 2 based on previous experiments (Methods) [32]. This imposes a limit on TR-dependence on the thermal load to the gradients.…”