High-fidelity, accelerated whole-brain submillimeter in vivo diffusion MRI using gSlider-spherical ridgelets (gSlider-SR)

Purpose To develop an accelerated, robust, and accurate diffusion MRI acquisition and reconstruction technique for submillimeter whole human brain in vivo scan on a clinical scanner. Methods We extend the ultra-high resolution diffusion MRI acquisition technique, gSlider, by allowing undersampling in q-space and radiofrequency (RF)-encoding space, thereby dramatically reducing the total acquisition time of conventional gSlider. The novel method, termed gSlider-SR, compensates for the lack of acquired information by exploiting redundancy in the dMRI data using a basis of spherical ridgelets (SR), while simultaneously enhancing the signal-to-noise ratio. Using Monte Carlo simulation with realistic noise levels and several acquisitions of in vivo human brain dMRI data (acquired on a Siemens Prisma 3T scanner), we demonstrate the efficacy of our method using several quantitative metrics. Results For high-resolution dMRI data with realistic noise levels (synthetically added), we show that gSlider-SR can reconstruct high-quality dMRI data at different acceleration factors preserving both signal and angular information. With in vivo data, we demonstrate that gSlider-SR can accurately reconstruct 860 mu m diffusion MRI data (64 diffusion directions at b=2000s/mm2), at comparable quality as that obtained with conventional gSlider with four averages, thereby providing an eight-fold reduction in scan time (from 1 hour 20 to 10 minutes). Conclusions gSlider-SR enables whole-brain high angular resolution dMRI at a submillimeter spatial resolution with a dramatically reduced acquisition time, making it feasible to use the proposed scheme on existing clinical scanners.