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Diffusion MRI acqusition

Introduction

Currently there is no consensus on the "optimal" btable setting to acquire diffusion MRI for "beyond-DTI" analysis. 

10 years ago, the trend in the field was "high angular resolution diffusion imaging" (HARDI), which acquires hundreds of sampling at one b-value (typically 3000 or more), but then HARDI was gradually replaced by multishell acquisition, which acquired diffusion MRI using at least two different b-values. This trend was motivated by studies confirming the benefit of combining data from multiple b-values. 

Nonetheless, the multishell acquisition has optimization problems. For example, the human connectome project acquired 90-90-90 directions at b-values of 1000, 2000, and 3000.  These 90 sampling directions are not homogeneously distributed on each shell. Some directions have higher sampling density, whereas others have lower. Moreover, the 90 directions at lower b-value could be over-sampling, whereas the 90 directions at high b-value could be under-sampling. This is evident if we calculate the correlation between any two DWI in each shell, the correlation is much higher in the low b shell, suggesting greater data redundancy.

My personal recommendation is "grid-258" sampling, which acquires, not just two or three b-values, but 23 different b-values ranging from b=0 to b=4000 at a total of 258 directions. Using a multi-band sequence with an MB factor of 3, the 2-mm dMRI acquisition can be done in 15 to 20 minutes.

The grid sampling has several benefits:

  1. It has uniformly distributed density in the diffusion encoding space (i.e. q-space). This avoids over-sampling at low b-values or under-sampling at high b-values. It does not have the sampling homogeneity problem in the shell acquisitions.
  2. It can be reconstructed by DTI, ball-and-sticks model, NODDI, GQI...etc.
  3. It captures a continuous range of diffusion patterns from none-restricted diffusion to restricted diffusion. For clinical studies, the grid scheme can capture all possible diffusion change due to edematous tissue or cell infiltration. in comparison, multi-shell only acquires 2 or 3 b-values and may miss diffusion patterns that are only sensitive to values in between.

There are limitations with the grid sampling scheme:
  1. It's Eddy current artifact cannot be corrected using FSL eddy, and the bipolar pulse is often needed to handle eddy current at the sequence level
  2. Methods using spherical harmonics cannot use grid schemes because there is no shell structure for estimating spherical harmonics.

The following steps will help you set up the grid-258 sampling scheme on your MRI scanner. The following steps are verified on Siemens scanners, and a similar protocol may  be implemented in other manufacturers.

STEP1: Download the b-table

If you are using a Siemens Scanner, you may download the vector table here: https://pitt.box.com/v/GRID258SIEMENS
If you are using other Scanners, you may need to convert the b-table to its compatible format: https://pitt.box.com/v/GRID258

STEP2: Install a multi-band EPI sequence

The MRI scanner needs to have a multi-band diffusion sequence installed. For example, the CMRR multi-band sequence: http://www.cmrr.umn.edu/multiband/ or you may use any multi-band sequence provided by the MRI vendor. There could be a licensing fee with the multi-band sequence.

*Make sure that the sequence allows for loading an external b-table (e.g. the "Free" mode)

STEP3: Setup parameters


Set up the parameters for the sequence in the following steps:

1. In-plane resolution: 2.0 mm, slice thickness: 2.0 mm (if your SNR is not good enough, increase them to 2.4 mm.)
2. Matrix size: 104x104
3. Slice number: 72 (can be reduced if ignoring the cerebellum), no gap
4. Multi-band acceleration factor: 3 or 4
5. In the diffusion tab, load the vector table obtained from STEP1 by "Free" mode.
6. b-value1=0 and b-value2=4000
7. "Bipolar" diffusion scheme (for eliminating eddy current). Some may prefer "Monopolar" and correct Eddy current using FSL's eddy. This only works on shell acquisition, and I do not recommend this approach for grid scheme.
8. Minimum TE and TR
9. Pixel bandwidth: ~1700
10. Make a copy of the sequence and invert its phase encoding direction. This means two GRID258 data sets will be acquired, one with A-P phase encoding direction and another with P-A (LR and RL also work). The two data sets with opposite phase encoding directions will be used by FSL's TOPUP to correct for gradient distortion.

STEP4: Quality Check

1. Make sure that you can still see the brain contour in the DWI with b=4000. If not, consider lowering the b-value to 3000.
2. Create SRC files from the diffusion MRI data. Run DSI Studio and use [Tool: Batch Processing][SRC Quality control] to select a folder that contains the SRC file. It will compute "Neighboring DWI correlation". The one with a low correlation value may indicate a problem in data acquisition.


*Please feel free to send me your grid258 data for a quality check. I will compare the results with the data I have to make sure that you have achieved the same quality.

What if I only have the default DTI protocol? 

The good news is that you can use scanner's built-in DTI protocol to acquire "multishell" and still enjoy the benefit of "beyond-DTI" methods such as GQI, QSDR, RDI...etc.

Here's a working setting on a SIEMENS 3T Scanner:

1. acquire one 32-direction DTI at b=1500 and another 60-direction DTI at b=3000 (built-in ep2d_mddw protocol)
2. In-plane resolution: 2mm, slice thickness: 2mm
3. Matrix size: 104x104
4. Slice number: 72 (can be reduced if ignoring the cerebellum), no gap
5. Minimum TE and TR, but the TE for the b=1500 DTI should be the same as the TE of the b=3000 DTI.
6. Make a copy of the sequence and invert its phase encoding direction (acquire AP and PA for phase distortion correction)

In the analysis, copy the DICOM files from these two DTI acquisitions together.

This acquisition will require FSL's eddy to correct for the eddy correct artifact.


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Download		   8k v. 2 Mar 23, 2015, 2:19 PM Fang-Cheng Yeh
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Download		 Run this program to generate SIEMENS Free Model vector table  330k v. 3 Mar 23, 2015, 2:18 PM Fang-Cheng Yeh
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