Advanced microstructure imaging at high b-values and high resolution combining ultra-high performance gradient diffusion imaging and model-based deep learning demonstrated using 3D multi-slab acquisition.

Purpose: To demonstrate the extended capabilities of 3D multi-slab diffusion-weighted acquisition (3D-msDWI) on high-performance gradients (HPG) to support advanced microstructure modeling for in-vivo human studies at high resolutions.

Methods: Despite optimal SNR-efficiency, the application of 3D-msDWI has been limited by the long volume acquisition times (VAT) required for encoding the 3D k-space using multi-shot approaches. Substantial reduction of VAT is possible by employing optimized 3D k-space under-sampling methods. We demonstrate that with reduced VAT, 3D-msDWI can be successfully utilized for advanced brain microstructure modeling at high resolution. HPG systems (e.g.,  mT/m,  T/m/s) enable further optimization through shorter echo times at high b-values. We evaluated the accelerated 3D-msDWI method's ability to support diffusion studies at 1mm isotropic resolution using data collected across three shells, with b-values extended up to 6000  , and employing compartment models. The reconstruction employed a navigator-based, motion-compensated approach using a regularized, iterative model-based algorithm.

Results: The accelerated 3D-msDWI framework enabled the generation of whole-brain parametric maps of a three-compartment model, at 1mm isotropic resolution, using a 3-shell, 66-direction acquisition completed in 15 min. The intra-axonal diffusivities (in ) and volume fractions reported from the method are as follows: 2.27 0.14; 0.6 0.04 in corpus-callosum, 2.17 0.09; 0.66 0.03 in anterior limb of internal capsule, 2.18 0.08; 0.68 0.04 in posterior limb of internal capsule, 2.07 0.06; 0.62 0.04 in corona radiata, 2.25 0.08; 0.68 0.04 in cortico-spinal tract, 2.12 0.04; 0.63 0.05 in superior longitudinal fasciculus, with a coefficient of variation % across subjects for all regions studied. The quantified values were validated using standard single-diffusion and multi-dimensional q-trajectory encoding acquisitions.

Conclusion: The inherent optimal SNR-efficiency of the 3D-msDWI framework can be harnessed for whole-brain high-resolution advanced microstructure modeling for in-vivo human studies, using advanced hardware and reconstruction.