An Example Data Set and How to Read It

Overview

The 2024 MRSI Data Processing and Quantitation Challenge will test the ability of data processing and spectral analysis pipelines to create accurate metabolite maps from a group of FID-MRSI data sets simulated using in vivo experimental data. The Challenge contains two sub-challenges:

  • Sub-Challenge 1: Perform nuisance signal removal and spectral quantification on (x,t)-space MRSI data contaminated by noise, baseline signals, spectral distortions, residual water signals, and unsuppressed lipid signals.
  • Sub-Challenge 2: Perform spectral quantification on (x,t)-space MRSI data contaminated by noise, baseline signals, and spectral distortions.

Interested groups are encouraged to participate in either or both of the challenges.

Note. You do NOT have to be attending the ISMRM MRS Workshop in October to participate in this challenge.

What are We Offering Here

Using the link below, you can download one example data set similar to the ones that will be provided in the 2024 MRSI Data Processing and Quantitation Challenge. This gives you a chance to understand what the scale and complexity of the data processing and analysis might look like. The example dataset consists of contaminated FID-MRSI data, anatomical structural image, and B0 inhomogeneity map along with the ground truth of the metabolite concentration maps, metabolite signals (after removal of macromolecular signals) and nuisance signals (residual water and unsuppressed lipid signals). More specifically, the FID-MRSI data was produced as follows:

  • The metabolite signals were created using spectral basis functions obtained by quantum mechanics simulation for an FID-MRSI acquisition at 3T. Macromolecular signals generated from in vivo measurement were also included.
  • The water signals were created using Bloch equation simulation to simulate residual water signals after WET water suppression with one frequency-selective saturation pulse (50 Hz bandwidth).
  • The lipid signals were created using high-resolution lipid signals acquired from in vivo experiments without any suppression pulses.
  • The spatial distribution of metabolite, water, and lipid signals was simulated based on anatomical structural images and B0 inhomogeneity maps from in vivo experiments at 3T as well as literature values.

Note that the water and lipid signals involved in this challenge were simulated to mimic situations in an in vivo FID-MRSI scan with short TR and TE for improved data acquisition efficiency and thus might appear stronger than a normal MRSI experiment.

Example Data Set Description

Use this link to access the Example Data Box folder hosted by Dr. Soher at Duke. The folder has MRI and SI data files in NIfTI and NIfTI-MRS data formats, respectively. These data are also available in a MATLAB .mat file.

Notes: Files that begin with prefix mri_ are in NIfTI image file format, and those that begin with mrs_ are in NIfTI-MRS file format. All filenames are in lower case to make sorting easier across Windows/Linux machines :)

Subdirectory example_data - Image data files provided in NIfTI format, (nx, ny, nz) array:

  • mri_t1w_mpr.nii.gz - T1w image stack
  • mri_b0_map.nii.gz - B0 map (in Hz) image stack
  • mri_brain_mask.nii.gz - Brain mask image stack
  • Metabolite area ground truth maps (x18, one for each metabolite basis set)
    • mrs_metab_result_naa.nii.gz
    • mrs_metab_result_tcho.nii.gz
    • mrs_metab_result_tcr.nii.gz
    • mrs_metab_result_lac.nii.gz
    • etc.

Subdirectory example_data - Spectral data files provided in NIfTI-MRS format array:

  • mrs_fids_si_data.nii.gz - (x,t)-space data for FID-MRSI data acquisition with the following parameters:
    • matrix = 64,64,32,384 (nx,ny,nz,nt)
    • TR/TE = 450ms/1ms
    • dwell time = 0.83ms
    • center frequency = 127.7 MHz
    • All data formats are co-registered
  • mrs_fids_metabolites.nii.gz - (x,t)-space data of ideal fitted metabolite signals
  • mrs_fids_nuisance.nii.gz - (x,t)-space data of ‘nuisance’ signals

Subdirectory basis_metab_3T - High-Resolution metabolite basis files in NIfTI-MRS format

  • matrix = 1,1,1,32768 (nx,ny,nz,nt)
  • dwell_time = 8.0389e-05 sec
  • one file for each metabolite (so 18 files with metabolite abbreviation in filename)
    • mrs_basis_naa.nii.gz
    • mrs_basis_tcr.nii.gz
    • mrs_basis_glu.nii.gz
    • etc.
  • *Note: Some metabolites have been ‘split’ into two parts for resonance groups at or above 3.9 ppm (Lac, PE, Cr) that may be affected by water suppression.
  • *Note: These bases signals need to be re-processed to the actual FID-MRSI acquisition sampling (dwell_time = 0.83 msec, TE = 1 ms)

Subdirectory basis_macromol_3T - High-Resolution macromolecule basis files in NIfTI-MRS format

  • matrix = 1,1,1,32768 (nx,ny,nz,nt)
  • dwell_time = 8.0389e-05 sec
  • one file for each macromolecular signal contribution (so 9 files with filenames that indicate the PPM location of that peak)
    • mrs_mm_0_9.nii
    • mrs_mm_1_21.nii
    • mrs_mm_1_43.nii
    • etc.
  • *Note: These macromolecular bases signals need to be re-processed to the actual FID-SI acquisition sampling (dwell_time = 0.83 msec, TE = 1 ms)

Code Examples for Accessing the Data

The code_examples_for_accessing_data subdirectory contains the Matlab and Python example code. As mentioned before, we are using NIfTI and NIfTI-MRS data formats to store our MRI and FID-SI data files, respectively. The NIfTI formatted files are just image arrays saved at the FID-SI spatial dimensions and can be accessed by typical NIfTI code methods. Our examples are mainly meant to inform about the newer NIfTI-MRS format.

Subdirectory matlab_general_example contains a file that show how to load NIfTI-MRS data. The ‘load_nifti_mrs.m’ file will display the spectrum for the central k-space data in the ‘~example_data\mrs_fids_si_data.nii.gz’ file.

Subdirectory python_general_example contains two files that show how to load/save NIfTI-MRS data. The ‘load_nifti_mrs.py’ file will display the spectrum for the central k-space data in the ‘~example_data\mrs_fids_si_data.nii.gz’ file.

To help out folks unfamiliar with the NIfTI-MRS formats, we have included example Python and Matlab code that show how to access the FID-SI (NIfTI-MRS) data. And, here is a link to the main reference site for NIfTI-MRS format.

The load_nifti_mrs.py file contain comments to explain the method. It requires the following library to use: https://nipy.org/nibabel/

The load_nifti_mrs.m file contain comments to explain the method. It requires the following library to use: https://github.com/xiangruili/dicm2nii

If you have trouble accessing the data, or other questions, please email us at fittingchallenge2024@gmail.com