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MTE_SANDI.m
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clear all
close all
clc
% This code estimates relaxation-unbiased signal fractions and compartmental T2 values using the MTE-SANDI approach, introduced in: Ting Gong, CM Tax, Matteo Mancini, Derek K Jones, Hui Zhang, Marco Palombo, "Multi-TE SANDI: Quantifying compartmental T2 relaxation times in the grey matter", 2023 International Society of Magnetic Resonance in Medicine annual meeting & exhibition, abstract: #766 (https://archive.ismrm.org/2023/0766.html).
% Author:
% Dr. Marco Palombo
% Cardiff University Brain Research Imaging Centre (CUBRIC)
% Cardiff University, UK
% Jan 2025
% Email: [email protected]
% TO BE EDITED BY THE USER %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
TE = []; % Vector containing the TE values acquired, in milliseconds
Delta = ; % diffusion gradients separation, Delta, in milliseconds
smalldelta = ; % diffusion grdients duration, smalldelta, in milliseconds
MainDataFolder = ''; % ProjectMainFolder full path
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% First run SANDI Matlab Toolbox for each TE individually
%Before running the code, all the data should have been arranged into
%folders named: "Data_TEXXX", where XXX is the corresponding TE value in
% milliseconds. The structure of the "Data_TEXXX" is like the structure of
% the "ProjectMainFolder" expected by the SANDI MAtlab Toolbox, i.e.:
% - ProjectMainFolder
% - Data_TE54
% |-> - derivatives
% |--> - preprocessed
% |---> - sub-01
% |----> - ses-01
% |-----> sub-<>_ses-<>_acq-<>_run-<>_desc-preproc_dwi.nii.gz
% |-----> sub-<>_ses-<>_acq-<>_run-<>_desc-preproc_dwi.bval
% |-----> sub-<>_ses-<>_acq-<>_run-<>_desc-preproc_dwi.bvec
% |-----> sub-<>_ses-<>_acq-<>_run-<>_desc-preproc_mask.nii.gz
% |-----> sub-<>_ses-<>_acq-<>_run-<>_desc-preproc_noisemap.nii.gz
% ...
% |----> - ses-n
% |-----> sub-<>_ses-<>_acq-<>_run-<>_desc-preproc_dwi.nii.gz
% |-----> sub-<>_ses-<>_acq-<>_run-<>_desc-preproc_dwi.bval
% |-----> sub-<>_ses-<>_acq-<>_run-<>_desc-preproc_dwi.bvec
% |-----> sub-<>_ses-<>_acq-<>_run-<>_desc-preproc_mask.nii.gz
% |-----> sub-<>_ses-<>_acq-<>_run-<>_desc-preproc_noisemap.nii.gz
% ...
% |---> - sub-n
% |----> - ses-01
% |-----> sub-<>_ses-<>_acq-<>_run-<>_desc-preproc_dwi.nii.gz
% |-----> sub-<>_ses-<>_acq-<>_run-<>_desc-preproc_dwi.bval
% |-----> sub-<>_ses-<>_acq-<>_run-<>_desc-preproc_dwi.bvec
% |-----> sub-<>_ses-<>_acq-<>_run-<>_desc-preproc_mask.nii.gz
% |-----> sub-<>_ses-<>_acq-<>_run-<>_desc-preproc_noisemap.nii.gz
% ...
% |----> - ses-n
% |-----> sub-<>_ses-<>_acq-<>_run-<>_desc-preproc_dwi.nii.gz
% |-----> sub-<>_ses-<>_acq-<>_run-<>_desc-preproc_dwi.bval
% |-----> sub-<>_ses-<>_acq-<>_run-<>_desc-preproc_dwi.bvec
% |-----> sub-<>_ses-<>_acq-<>_run-<>_desc-preproc_mask.nii.gz
% |-----> sub-<>_ses-<>_acq-<>_run-<>_desc-preproc_noisemap.nii.gz
disp('Step 1 - Fitting SANDI to data at each TE independently ... ')
for i=1:numel(TE)
ProjectMainFolder = fullfile(MainDataFolder, ['Data_TE' num2str(TE(i))]);
SNR = [];
SANDIinput = SANDI_batch_analysis(ProjectMainFolder, Delta, smalldelta, SNR); % Run the SANDI analysis for each TE individually
end
%% Then estimate relaxation-unbiased signal fractions and compartmental T2 values
disp('Step 2 - Estimating compartmental T2 relaxation times and relaxation unbiased signal fractions ... ')
fn = [];
fs = [];
fe = [];
Din = [];
De = [];
Rsoma = [];
% Load the SANDI estimated signal fractions for each of the TE values
for i=1:numel(TE)
MainSANDIfolder = fullfile(MainDataFolder, ['Data_TE' num2str(TE(i))], 'derivatives\SANDI_analysis\sub-01\ses-01\SANDI_Output');
tmp = load_untouch_nii(fullfile(MainSANDIfolder, 'SANDI-fit_fneurite.nii.gz'));
fn(:,:,:,i) = double(tmp.img(:,:,:));
tmp = load_untouch_nii(fullfile(MainSANDIfolder, 'SANDI-fit_fsoma.nii.gz'));
fs(:,:,:,i) = double(tmp.img(:,:,:));
tmp = load_untouch_nii(fullfile(MainSANDIfolder, 'SANDI-fit_fextra.nii.gz'));
fe(:,:,:,i) = double(tmp.img(:,:,:));
tmp = load_untouch_nii(fullfile(MainSANDIfolder, 'SANDI-fit_Din.nii.gz'));
Din(:,:,:,i) = double(tmp.img(:,:,:));
tmp = load_untouch_nii(fullfile(MainSANDIfolder, 'SANDI-fit_De.nii.gz'));
De(:,:,:,i) = double(tmp.img(:,:,:));
tmp = load_untouch_nii(fullfile(MainSANDIfolder, 'SANDI-fit_Rsoma.nii.gz'));
Rsoma(:,:,:,i) = double(tmp.img(:,:,:));
end
% Load the b=0 images for each TE
b0 = [];
for i=1:numel(TE)
datafolder = fullfile(MainDataFolder, ['Data_TE' num2str(TE(i))], 'derivatives', 'preprocessed', 'sub-01', 'ses-01');
tmp = dir(fullfile(datafolder, '*_dwi.nii.gz'));
datafile = fullfile(tmp.folder, tmp.name);
tmp = dir(fullfile(datafolder, '*_dwi.bval'));
bvalfile = fullfile(tmp.folder, tmp.name);
tmp = load_untouch_nii(datafile);
dwi = double(tmp.img(:,:,:,:));
bval = importdata(bvalfile);
b0(:,:,:,i) = nanmean(dwi(:,:,:,bval==0), 4);
end
fn = reshape(fn, [size(fn,1)*size(fn,2)*size(fn,3), size(fn,4)]);
fs = reshape(fs, [size(fs,1)*size(fs,2)*size(fs,3), size(fs,4)]);
fe = reshape(fe, [size(fe,1)*size(fe,2)*size(fe,3), size(fe,4)]);
S0 = reshape(b0, [size(b0,1)*size(b0,2)*size(b0,3), size(b0,4)]);
Y = log( fn.*S0 );
X = [TE', ones(size(TE'))];
cc = linsolve(X,Y');
T2n = -1./cc(1,:);
S0n = exp(cc(2,:));
Y = log( fs.*S0 );
X = [TE', ones(size(TE'))];
cc = linsolve(X,Y');
T2s = -1./cc(1,:);
S0s = exp(cc(2,:));
Y = log( fe.*S0 );
X = [TE', ones(size(TE'))];
cc = linsolve(X,Y');
T2e = -1./cc(1,:);
S0e = exp(cc(2,:));
fn0 = S0n./(S0n + S0s + S0e);
fs0 = S0s./(S0n + S0s + S0e);
fe0 = S0e./(S0n + S0s + S0e);
T2n_map = reshape(T2n, [size(b0,1), size(b0,2) size(b0,3)]);
T2s_map = reshape(T2s, [size(b0,1), size(b0,2) size(b0,3)]);
T2e_map = reshape(T2e, [size(b0,1), size(b0,2) size(b0,3)]);
fn0_map = reshape(fn0, [size(b0,1), size(b0,2) size(b0,3)]);
fs0_map = reshape(fs0, [size(b0,1), size(b0,2) size(b0,3)]);
fe0_map = reshape(fe0, [size(b0,1), size(b0,2) size(b0,3)]);
%% Save the output maps within a new folder 'MTE-SANDI_maps'
disp('Saving the MTE-SANDI parametric maps ... ')
tmp = load_untouch_nii(fullfile(MainSANDIfolder, 'SANDI-fit_fneurite.nii.gz')); % Load representative NIFTI
outputfolder = fullfile(MainDataFolder, 'MTE-SANDI_analysis');
mkdir(outputfolder);
tmp.img = T2n_map;
save_untouch_nii(tmp, fullfile(outputfolder, 'MTE-SANDI-fit_T2neurite.nii.gz'));
tmp.img = T2s_map;
save_untouch_nii(tmp, fullfile(outputfolder, 'MTE-SANDI-fit_T2soma.nii.gz'));
tmp.img = T2e_map;
save_untouch_nii(tmp, fullfile(outputfolder, 'MTE-SANDI-fit_T2extra.nii.gz'));
tmp.img = fn0_map;
save_untouch_nii(tmp, fullfile(outputfolder, 'MTE-SANDI-fit_fneurite0.nii.gz'));
tmp.img = fs0_map;
save_untouch_nii(tmp, fullfile(outputfolder, 'MTE-SANDI-fit_fsoma0.nii.gz'));
tmp.img = fe0_map;
save_untouch_nii(tmp, fullfile(outputfolder, 'MTE-SANDI-fit_fextra0.nii.gz'));
tmp.img = mean(Din,4);
save_untouch_nii(tmp, fullfile(outputfolder, 'MTE-SANDI-fit_MeanDin.nii.gz'));
tmp.img = mean(De, 4);
save_untouch_nii(tmp, fullfile(outputfolder, 'MTE-SANDI-fit_MeanDe.nii.gz'));
tmp.img = mean(Rsoma, 4);
save_untouch_nii(tmp, fullfile(outputfolder, 'MTE-SANDI-fit_MeanRsoma.nii.gz'));
tmp = load_untouch_nii(datafile);
tmp.img = Din;
tmp.hdr.dime.dim(5) = size(tmp.img, 4);
save_untouch_nii(tmp, fullfile(outputfolder, 'MTE-SANDI-fit_MTE-Din.nii.gz'));
tmp.img = De;
tmp.hdr.dime.dim(5) = size(tmp.img, 4);
save_untouch_nii(tmp, fullfile(outputfolder, 'MTE-SANDI-fit_MTE-De.nii.gz'));
tmp.img = Rsoma;
tmp.hdr.dime.dim(5) = size(tmp.img, 4);
save_untouch_nii(tmp, fullfile(outputfolder, 'MTE-SANDI-fit_MTE-Rsoma.nii.gz'));