Data collection

Study design

Twenty healthy adults (mean age 36 years, age range 29-46 y.o.(SD = 4.7), 4 men and 16 women) were scan at the Centre Hospitalier Universitaire of Sherbrooke (CHUS) using a clinical 3T MRI scanner (Ingenia, Philips Healthcare, Best, Netherlands) with a 32-channel head coil. Each MRI session was repeated 5 times over 5 months and a 4-week interval (+/- 1 week). For each participant, images were acquired at approximately the same time of day to avoid potential diurnal effects (i.e., a morning participant had all sessions in the morning, with a tolerated 2–3-hour variation).

Study design - 20 healthy subjects

All MRI data acquisitions were aligned on the anterior commissure-posterior commissure plan (AC-PC) and each MRI session include :

• Anatomical 3D T1-weighted (3DT1)

• Multi-shell diffusion-weighted images (DWI)

• Reverse phase encoding B0 (revb0)

• inhomogeneous magnetization transfer (ihMT)

MRI acquisition parameters

Parameters / Sequences	T1	DWI	Reverse B0	ihMT	T1 ihMT
Phase-encoding direcion*	RL	PA	AP	RL	RL
Technique - Fast imaging method	FFE - TFE	SE - EPI	SE - EPI	FFE - EPI	FFE - EPI
Total scan duration	4 min 20s	9 min 20s	14s	6 min 04 s	13 s
Repetition time (TR, ms)	7.9	4800	4800	112	20
Echo Time (TE, ms)	3.5	92	92	3.6 (Δ = 6)	3.6 (Δ = 6)
Inversion Time (TI, ms)	950
Flip Angle (degree)	8	90	90	15	30
Field of View (FOV, mm)	224 x 224	224 x 224	224 x 224	224 x 224	224 x 224
Slices (n)	150	66	66	65	65
Voxel size (mm)	1 x 1 x 1	2 x 2 x 2	2 x 2 x 2	2 x 2 x 2	2 x 2 x 2
n b0, b-value (n directions)		7, 300 (8), 1000 (32), 2000 (60)
MT stauration pulse				10 Hann pulses of. 0.9 ms duration with 1.5 ms interval
Frequency offset of +/-				7000 Hz
n Echoes - Echo spacing					3 - 6 ms

*The directions are specified in the standard way i.e. in coordinates of the patient (LPH).

An example of bvec and bval file can be downloaded here:

bval bvec files

Data conversion: DICOM to BIDS

To convert data we use BIDS standard. An example of the data structure for one subject is shown below:

data-subject
├── dataset_description.json
├── participants.json
├── participants.tsv
├── sub-001_ses-01
├── sub-001_ses-02
├── sub-001_ses-03
├── sub-001_ses-04
├── sub-001_ses-04
├── sub-002_ses-01
├── ...
├── sub-003_ses-01
    │
    ├── anat
    │   ├── sub-003-01_T1w.json
    │   ├── sub-003-01_T1w.nii.gz
    │   ├── sub-003-01_acq-pos_ihmt.json
    │   ├── sub-003-01_acq-pos_ihmt.nii.gz
    │   ├── sub-003-01_acq-neg_ihmt.json
    │   ├── sub-003-01_acq-neg_ihmt.nii.gz
    │   ├── sub-003-01_acq-altnp_ihmt.json
    │   ├── sub-003-01_acq-altnp_ihmt.nii.gz
    │   ├── sub-003-01_acq-altpn_ihmt.json
    │   ├── sub-003-01_acq-altpn_ihmt.nii.gz
    │   ├── sub-003-01_acq-T1w_ihmt.json
    │   └── sub-003-01_acq-T1w_ihmt.nii.gz
    │
    └── dwi
        ├── sub-003-01_dwi.bval
        ├── sub-003-01_dwi.bvec
        ├── sub-003-01_dwi.json
        ├── sub-003-01_dwi.nii.gz
        ├── sub-003-01_b0.json
        ├── sub-003-01_b0.nii.gz
        ├── sub-003-01_rev-b0.json
        └── sub-003-01_rev-b0.nii.gz

To convert our DICOM data folder to the compatible BIDS structure, we used dcm2bids.

dcm2bids -d DICOM_folder -p id_subject -c config.txt -o sub-id

Quality Control raw data

Quality control of raw data was performed using DMRIQC flow DMRIQC flow.

Example of datasets for one subject

• Anatonimal image

3D-T1w

• Diffusion images

DWI - b0	DWI - b value = 300	DWI - b value = 1000	DWI - b value = 2000	DWI - Reverse B0

• ihMT images

MT-Off	Positive (pos)	Negative (neg)	Alternative pos-neg	Alternative neg-pos	T1w ihMT