Adam Scott Bernstein^{1,2}, Loi V Do^{2}, Nan-kuei Chen^{2}, and Theodore P Trouard^{2}

In this study, we design a unique bootstrapping method to approximate the distributions of diffusion MRI parameters derived from scans that utilize simultaneous multislice techniques compared to the distribution of parameters fit from a single slice EPI sequence. While there are no statistically significant differences between accelerated and non-accelerated datasets, there are some subtle differences that may warrant closer inspection.

**Data Collection:**

A single healthy volunteer was repeatedly scanned on a clinical 3T system in a single session. A multiple-direction, multiple-shell diffusion experiment was designed with 6 b=0 s/mms, 40 b=1000 , 60 b=2000, and 80 b=3000 s/mms images collected. The diffusion directions were determined using a multishell electrostatic repulsion scheme similar to that described in [2]. This experiment was run once with slice acceleration (TR/TE = 3600/115 ms, acceleration factor of 3, FOV shift of ½ ) and once without (TR/TE = 10700/115 ms). An in-plane GRAPPA acceleration of 2, matrix size of 128x128x69, and 2mm isotropic resolution was used for both scans.

**Data Preprocessing:**

The diffusion weighted images were corrected for EPI distortions using
FSL’s TOPUP^{3}, eddy currents using FSL’s eddy^{4}, denoised
using an in house implementation of LPCA denoising^{5}, and corrected
for signal intensity bias using ANTs’ N4 technique^{6}.

**Data Analysis:**

We randomly sampled 2 b=0, 20 b=1000, 30 b=2000,
and 40 b=3000 s/mm2 from both the accelerated and non accelerated
data 50 times to generate 50 unique datasets. Each of these datasets were
processed with in house diffusion tensor analysis to generate FA and MD maps
and with in house MAP MRI analysis to generate propagator anisotropy (PA),
non-gaussianity (NG), return-to-origin probability (RTOP) and return-to-axis probability
(RTAP)^{7}. These parameter maps were used to generate voxel-wise
distributions of parameters for voxel-wise statistical analysis. For each
parameter map, we performed permutation testing and corrected for multiple
comparisons using a single threshold test^{8} to generate voxel-wise
maps of statistical differences in the data generated from standard and
accelerated acquisitions. All statistical analysis was performed using MATLAB
2017a.

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Parameter maps derived from DTI (FA and MD) and MAP-MRI (NG, PA, RTOP, RTAP) from datasets collected without slice acceleration (top) and with 3x acceleration (bottom)

Distributions of several DTI and
MAP-derived parameters selected from a white matter region with crossing fibers
(top), the corpus callosum (middle), and
An area of gray matter (bottom). The
bootstrapped distribution of the parameters from the slice accelerated data is
shown in red, and the bootstrapped
parameter distribution from the data
without slice acceleration is shown in blue.

Parameters
from the accelerated dataset plotted against the same parameters from the non
accelerated dataset.

%-Difference
maps of the standard deviation of the voxelwise bootstrapped parameter maps ((SMS 3x –
SMS 1x) / SMS 1x * 100%) demonstrating that the standard deviation of the
parameters derived from the accelerated dataset is almost always larger than
those derived from the non accelerated dataset except for in the mean
diffusivity map.