MRI Lab

MRI lab heads: Nadège Bault & Matt Roser

Lab overview (new)

Safety and ethics

Safety training

Before being able to access the MRI lab, you will need to complete a safety training. Safety training sessions may be ran monthly or bi-monthly, depending on the needs, in small groups.

Please contact the lab heads (BRIC.MRI-lab.heads@plymouth.ac.uk).

Safety questionnaires must be filled by staff and research participants before they can enter the restricted MRI environment.

safety questionnaire - adults research participants

safety questionnaire - staff (permit to work)

Safety policies

See these documents for details of BRIC MR Safety and Operating rules and policies.

BRIC MRI Local Rules

BRIC Safety and Risk Operational Policy

Developing and testing a new task

This section contains some tools and resources to help develop and test new tasks

Testing

All tasks and sequences should be tested before starting data collection

Sequences

BRIC_CORE

The BRIC_CORE Tree collects sequences that have been used extensively at BRIC, all are available for the 32-channel coil and based on both Siemens stock sequences and the Minnesota CMRR multiband sequences provided under the Siemens Core Competence Partnership (C2P) agreement

All the most commonly used sequence types are available (T1 scout, T1 HiRes, BOLD functional, field map, diffusion, phase-reversed diffusion), all use BIDS sequence labelling to enable upload of data to the correct storage. https://bids.neuroimaging.io/

Stock Siemens-derived and Minn-CMRR-derived sequences are grouped in separate Strategies.

  • If using Minn-CMRR diffusion sequences then use the MOSAIC-enabled versions (see diffusion section) - Sequence parameters for BRIC Core with Diff_MOSAIC (in BIDS) are available as a pdf here link to GitLab repository.

Other bespoke sequences (MR Spectroscopy, McGill-tweaked diffusion) are available from other users. Talk to the MR lab heads or SH about these.

Creating a new sequence

  • Create a new Exam in BRIC-Dev/HP-DevB labelled as BD-DDMMYY

  • Create a new Protocol in your new Exam.

  • Copy/Paste an existing sequence (e.g. from BRIC_CORE) to this new Protocol.

  • Edit and test your new sequence before copying to a Protocol in your own Tree.

Warning

BIDS labelling: Use BIDS labelling to ensure the correct routing of data to storage. Please see here for more information.

Printing sequence parameters and exporting protocol

Although many acquisition parameters will be passed to the JSON file that accompanies your data it is a good idea to print the pdf of the exact sequences that you used in your study for future reference.

  • In Dot Cockpit Explorer right click on any Region, Exam or Program and choose Print to print to pdf.

  • Right click to Export the *.exar1 protocol file that can be opened on another Siemens system, these can be output to H:/MRI_Protocols.

Diffusion

MOSAIC data compression is native for SIEMENS sequences and is now enabled for diffusion on the Minnesota C2P sequences in BRIC_Core with Diff_MOSAIC (in BIDS). Use this to avoid upload delay due to high number of separate files. This adds a single unweighted diffusion volume to the start of the acquisition, which shows as a 0 in your conversion-output Bval/Bvec files (but not in your DVS file).

Bespoke diffusion directions

Generation of single/multiple shell directions can be made with this free online tool. An accompanying paper available here

  • Bvec/val location *.dvs file: /Computer/Med_System C:/Medcom/MriCustomer/seq/DiffusionVectorSets. Also backed up to H:/Diffusion/DiffusionVectorSets.

  • Go to the Diff tab of the sequence. Click the elipsis next to Diffusion mode (Free).

  • Import/Export diffusion vector set (.dvs)

  • Phase-reversed unweighted volumes dwi_acq_mb2_dir-PA (2mm, 3mm Minn-C2P-CMRR) and fmap_dir-PA_acq-diff (Siemens, Note- this is not a field map)

The reverse phase encoding step for the Siemens Sequence needs you to manually plan the reverse encoding each time but the Physicists have developed a technique called the ‘Malek flip’.

  • The Malek flip for P>A: Select R-L, then A>P, enter 180 minus inplane rotation.

  • The reverse phase encoding step is enabled by a setting on the Minnesota-C2P-CMRR sequence.

  • On the Programme card the phase direction is reported as A>P. In fact it is P>A

  • Go to Sequence/Special and mouse over the options to check that RO/PE Polarity is ON.

Tasks

Tasks can be presented to participants whilst in the scanner using the Cambridge Research BOLDScreen 32 MR compatable screen and responses can be detected with optical responses devices. <response buttons>

The experimental computer contains copies of PsychoPy, Presentation, Matlab Psychtoolbox, and OpenSesame for running experiments. For more information and resources see here <mri experimental software>

Tasks trials can be enslaved to the scanner by listening to ‘t’ keyboard inputs, as these are sent by the scanner at the start of each aquistion. For testing enslaved scripts, the following program emulates the scanners triggers and can be used to test through longer scripts before uploading to the experimental computer.

Once your task and sequence has been designed and tested, you should book time in the scanner to run a phantom pilot session before starting data collection.

Template experiments

Below are some experiments that have been made available to use as a template for further development, they are based on common experimental designs

Block design
En-slaved

Data processing

The following section outlines some of the processes used by researchers previously at BRIC, as there is yet to be a internationally recognised processing pipeline for MRI data this page explores various methods by various researchers.

An up-to-date repository of scripts is available here - (link to gitlabs repository).

BIDS formating

The following scripts have been written at BRIC for use in previous experiments, the file paths have been generalised for distribution but still follow BIDS conventions.

Raw data checks

Before starting data processing the first step is to check your raw data.

Check your data for missing files or folders as there is potential for data to be lost during Dicomm/Nifty conversion.

FSLeyes can be used to check the quality of both structural and functional images.

Load the structural image into FSLeyes and visually inspect and explore the image for potental artifacts and image quality.

Load the functional images into FSLeyes and use the movie mode to watch through the volumes, noting image quality and potential artifacts for each volume.

Loading mulitple images

When loading mutliple images into FSLeyes, a potental warning may occur informing you some images loaded are different sizes or oreintations.

FSLeyes will try to correct this and transform the images to match, however in doing so some artifacts may appear. These artifacts will remain in the image even if the other images are removed.

It is therefore recommened to load images individually, and reserve the use of overlaying mutliple images.

Brain extraction

In FSleyes, BET is a automated tool for extracting brains from T1-weighted images.

bet <input file> <output file> <options>

bet /DATA/sub-atto0090/anat/sub-atto0090_T1 /DATA/anat/sub-atto0090/sub-atto0090_T1_brain

bet /DATA/sub-atto0090/anat/sub-atto0090_T1 /DATA/anat/sub-atto0090/sub-atto0090_T1_brain_rob_04 -R -f 0.4

Various examples of bet usage, by default BET will call BET2.

Note

ROB - Using -R in the BET command uses robust brain extraction. By using up-to 10 iterations of BET, this function is better able to estimate the centre of gravity for creating the brain mask.

Fractional intensity - Using -f in the BET command allows you to set the fractional intensity of the extraction, lower numbers will make the extraction more generous potentially including more non-brain matter.

Mask - Using -m creates an additional binary mask output of the brain extraction

Another method for improving the quality of BET extractions is by cropping images to remove non-brain matter, most notably in the neck. The following script is written to take a set of participan T1-weighted structural scans and crop images to a predefined limit.

Link to cropped BET script from gitlab repository

Note

Commands used in this script:

Previous researchers at BRIC have found a common issue with BET not performing optimaly for older participants. The following script take both a T1 and T2-weighted image to improve the accuracy of BET extractions.

Link to T1 T2 bet extraction script from gitlab repository

Note

Commands used in this script:

Brain extraction checks

Brain extractions can be manually checked through FSLeyes in the same way as preliminary data quality checks.

For larger data sets, slicesDIR is able to take a T1 structural image and extracted brain and produce a visual report of 9 ortho slices showing an outline of the extraction. This report is useful for checking mulitple extractions and their overall quality.

Link to slicesdir from gitlab repository

Prep field map

Prep field map for Siemans scanner

Link to prep_fieldmap from gitlab repository

Note

Commands used in this script:

bet

fsl_prep_fieldmap

Diffusion

The following script is a pipeline for processing diffusion data developed at BRIC.

Link to diffusion pipeline script from gitlab repository

Additional scripts

Link to pull number of volumes script from gitlab repository

Link to Diffusion extract values from gitlab repository

To request more information or resources please contact the lab heads