Ramos-Llordén Gabriel, Ning Lipeng, Liao Congyu, Mukhometzianov Rinat, Michailovich Oleg, Setsompop Kawin, Rathi Yogesh
Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Magn Reson Med. 2020 Oct;84(4):1781-1795. doi: 10.1002/mrm.28232. Epub 2020 Mar 3.
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.
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.
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 μm diffusion MRI data (64 diffusion directions at ), 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).
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.
开发一种加速、稳健且准确的扩散磁共振成像(MRI)采集与重建技术,用于在临床扫描仪上对活体全脑进行亚毫米级扫描。
我们通过在q空间和射频(RF)编码空间允许欠采样,扩展了超高分辨率扩散MRI采集技术gSlider,从而显著减少了传统gSlider的总采集时间。这种新方法称为gSlider-SR,它利用球面脊波(SR)基来利用扩散MRI数据中的冗余信息,以补偿采集信息的不足,同时提高信噪比。通过使用具有实际噪声水平的蒙特卡罗模拟以及多次采集活体人脑扩散MRI数据(在西门子Prisma 3T扫描仪上采集),我们使用多种定量指标证明了我们方法的有效性。
对于具有实际噪声水平(合成添加)的高分辨率扩散MRI数据,我们表明gSlider-SR能够在不同加速因子下重建高质量的扩散MRI数据,同时保留信号和角度信息。对于活体数据,我们证明gSlider-SR能够准确重建860μm的扩散MRI数据(在 处有64个扩散方向),其质量与使用传统gSlider并进行四次平均所获得的质量相当,从而将扫描时间减少了八倍(从1小时20分钟减少到10分钟)。
gSlider-SR能够以亚毫米空间分辨率实现全脑高角度分辨率扩散MRI,且采集时间大幅减少,使得在现有临床扫描仪上使用该方案成为可能。