%% jobSDAT.m % This function describes an Osprey job defined in a MATLAB script. % % A valid Osprey job contains four distinct classes of items: % 1. basic information on the MRS sequence used % 2. several settings for data handling and modeling % 3. a list of MRS (and, optionally, structural imaging) data files % to be loaded % 4. an output folder to store the results and exported files % % The list of MRS and structural imaging files is provided in the form of % cell arrays. They can simply be provided explicitly, or from a more % complex script that automatically determines file names from a given % folder structure. % % Osprey distinguishes between four sets of data: % - metabolite (water-suppressed) data % (MANDATORY) % Defined in cell array "files" % - water reference data acquired with the SAME sequence as the % metabolite data, just without water suppression RF pulses. This % data is used to determine complex coil combination % coefficients, and perform eddy current correction. % (OPTIONAL) % Defined in cell array "files_ref" % - additional water data used for water-scaled quantification, % usually from short-TE acquisitions due to reduced T2-weighting % (OPTIONAL) % Defined in cell array "files_w" % - Structural image data used for co-registration and tissue class % segmentation (usually a T1 MPRAGE). These files need to be % provided in the NIfTI format (*.nii) or, for GE data, as a % folder containing DICOM Files (*.dcm). % (OPTIONAL) % Defined in cell array "files_nii" % - External segmentation results. These files need to be % provided in the NIfTI format (*.nii or *.nii.gz). % (OPTIONAL) % Defined in cell array "files_seg" with 1 x 3 cell for each % subject or 1 x 1 cell if a single 4D NIfTI is supplied. % % Files in the formats % - .7 (GE) % - .SDAT, .DATA/.LIST, .RAW/.SIN/.LAB (Philips) % - .DAT (Siemens) % - .nii, .nii.gz (NIfTI-MRS) % usually contain all of the acquired data in a single file per scan. GE % systems store water reference data in the same .7 file, so there is no % need to specify it separately under files_ref. % % Files in the formats % - .DCM (any) % - .IMA, .RDA (Siemens) % may contain separate files for each average. Instead of providing % individual file names, please specify folders. Metabolite data, water % reference data, and water data need to be located in separate folders. % % In the example script at hand the MATLAB functions strrep and which are % used to generate a relative path, which allows you to run the examples % on your machine directly. To set up your own Osprey job supply the % specific locations as described above. % % AUTHOR: % Dr. Georg Oeltzschner (Johns Hopkins University, 2019-07-15) % goeltzs1@jhmi.edu % % HISTORY: % 2019-07-15: First version of the code. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%% 1. SPECIFY SEQUENCE INFORMATION %%% % Specify sequence type seqType = 'MEGA'; % OPTIONS: - 'unedited' (default) % - 'MEGA' % - 'HERMES' % - 'HERCULES' % Specify editing targets editTarget = {'GABA'}; {'GSH'}, {'Lac'}, {'PE322'}, {'PE398'} % OPTIONS: - {'none'} (default if 'unedited') % - {'GABA'}, {'GSH'}, {'Lac'}, {'PE322'}, {'PE398'} (for 'MEGA') % - {'GABA', 'GSH'}, {'GABA', 'Lac'}, {'NAA', 'NAAG'} (for 'HERMES'and 'HERCULES') % Specify data scenario dataScenario = 'invivo'; % OPTIONS: - 'invivo' (default) % - 'phantom' % - 'PRIAM' % - 'MRSI' %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%% 2. SPECIFY DATA HANDLING AND MODELING OPTIONS %%% % Which spectral registration method should be used? Robust spectral % registration is default, a frequency restricted spectral registration % method is also availaible and is linked to the fit range. opts.SpecReg = 'RobSpecReg'; % OPTIONS: - 'RobSpecReg' (default) Spectral aligment with Water/Lipid removal, using simialrity meric, and weighted averaging % - 'ProbSpecReg' Probabilistic spectral aligment to median target and weighted averaging % - 'RestrSpecReg' Frequency restricted (fit range) spectral aligment, using simialrity meric, and weighted averaging % - 'none' % Which algorithm do you want to align the sub spectra? L2 norm % optimization is the default. This is only used for edited MRS! % Which algorithm do you want to align the sub spectra? L2 norm % optimization is the default. This is only used for edited MRS! %Perform correction on the metabolite data (raw) or metabolite %-nulled data (mm). opts.SubSpecAlignment.mets = 'L2Norm'; % OPTIONS: - 'L2Norm' (default) % - 'L1Norm' % - 'none' opts.UnstableWater = 0; %Perform eddy-current correction on the metabolite data (raw) or metabolite %-nulled data (mm). This can either be done similar for all data sets by %supplying a single value or specified for each dataset individually by supplying % multiple entries (number has to match the number of datasets) e.g. to perform ECC % for the second dataset only: % opts.ECC.raw = [0 1]; % opts.ECC.mm = [0 1]; opts.ECC.raw = 1; % OPTIONS: - '1' (default) opts.ECC.mm = 1; % - '0' (no) % - [] array % Save LCModel-exportable files for each spectrum? opts.saveLCM = 1; % OPTIONS: - 0 (no, default) % - 1 (yes) % Save jMRUI-exportable files for each spectrum? opts.savejMRUI = 1; % OPTIONS: - 0 (no, default) % - 1 (yes) % Save processed spectra in vendor-specific format (SDAT/SPAR, RDA, P)? opts.saveVendor = 0; % OPTIONS: - 0 (no, default) % - 1 (yes) % Save processed spectra in NIfTI-MRS format? opts.saveNII = 1; % OPTIONS: - 0 (no) % - 1 (yes, default) % Save PDF output for all Osprey modules and subjects? opts.savePDF = 0; % OPTIONS: - 0 (no, default) % - 1 (yes) % Save mat file of the compiled fitting parameters? opts.exportParams.flag = 0; % Options: - 0 (no, default) % - 1 (yes) opts.exportParams.path = ''; % Replace with string for the path % to the save directory % Choose the fitting algorithm opts.fit.method = 'Osprey'; % OPTIONS: - 'Osprey' (default) % Select the metabolites to be included in the basis set as a cell array, % with entries separates by commas. % With default Osprey basis sets, you can select the following metabolites: % Ala, Asc, Asp, bHB, bHG, Cit, Cr, Cystat, CrCH2, EtOH, GABA, GPC, GSH, Glc, Gln, % Glu, Gly, H2O, mI, Lac, NAA, NAAG, PCh, PCr, PE, Phenyl, sI, Ser, % Tau, Tyros, MM09, MM12, MM14, MM17, MM20, Lip09, Lip13, Lip20. % If you enter 'default', the basis set will include all of the above % except for Ala, bHB, bHG, Cit, Cystat, EtOH, Glc, Gly, Phenyl, Ser, and Tyros. opts.fit.includeMetabs = {'default'}; % OPTIONS: - {'default'} % - {'full'} % - {custom} % Choose the fitting style for difference-edited datasets (MEGA, HERMES, HERCULES) % (only available for the Osprey fitting method) opts.fit.style = 'Separate'; % OPTIONS: - 'Concatenated' (default) - will fit DIFF and SUM simultaneously) % - 'Separate' - will fit DIFF and OFF separately % Determine fitting range (in ppm) for the metabolite and water spectra opts.fit.range = [0.5 4]; % [ppm] Default: [0.2 4.2] opts.fit.rangeWater = [2.0 7.4]; % [ppm] Default: [2.0 7.4] opts.fit.GAP.A = []; opts.fit.GAP.diff1 = []; % Determine the baseline knot spacing (in ppm) for the metabolite spectra opts.fit.bLineKnotSpace = 0.55; % [ppm] Default: 0.4. % Add macromolecule and lipid basis functions to the fit? opts.fit.fitMM = 1; % OPTIONS: - 0 (no) % - 1 (yes, default) % How do you want to model the co-edited macromolecules at 3 ppm for GABA-edited MRS? opts.fit.coMM3 = '3to2MM'; % OPTIONS: - {'3to2MM'} (default) % - {'3to2MMsoft'} % - {'1to1GABA'} % - {'1to1GABAsoft'} % - {'freeGauss'} % - {'fixedGauss'} % - {'none'} opts.fit.FWHMcoMM3 = 14; % Optional: In case the automatic basisset picker is not working you can manually % select the path to the basis set in the osprey/fit/basis, i.e.: % opts.fit.basisSetFile = 'osprey/fit/basis/3T/philips/mega/press/gaba68/basis_philips_megapress_gaba68.mat'; % Optional: Deface the strucutral images in the Coreg/Seg figures for HIPAA % compliance opts.img.deface = 0; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%% 3. SPECIFY MRS DATA AND STRUCTURAL IMAGING FILES %% % When using single-average Siemens RDA or DICOM files, specify their % folders instead of single files! % Clear existing files % Clear existing files clear files files_ref files_w files_nii files_mm % Data folder in BIDS format % The filparts(which()) comment is needed to find the data on your machine. If you set % up the jobFile for your own data you can set a direct path to your data % folder e.g., data_folder = /Volumes/MyProject/data/' data_folder = 'C:\Users\22404132t\Bureau\osprey\osprey-develop\PROJET\BIDS'; % The following lines perform an automated set-up of the jobFile which % takes advatage of the BIDS foramt. If you are not using BIDS (highly % recommended) you can look at the definitions below the loop to see how to % set up direct path links to your data. subs = dir(data_folder); %subs = variable dans laquelle on stocke le fichier BIDS subs(1:2) = []; %permet de supp les 2 premiers éléments de la liste subs = subs([subs.isdir]); % permet de garder que les sous dossiers subs = subs(contains({subs.name},'sub')); % on garde que les dossiers commençant par sub counter = 1; for kk = 1:35 %length(subs) %boucle pour le nombre de sujet, un seul sujet pour ce script, kk = sujet % Loop over sessions sess = dir([subs(kk).folder filesep subs(kk).name]); %subs = variable dans laquelle on stocke le dossier parent de sub1 sess(1:2) = []; %permet de supp les 2 premiers éléments de la liste sess = sess([sess.isdir]); % permet de garder que les sous dossiers sess = sess(contains({sess.name},'ses')); % on garde que les dossiers commençant par ses for ll = 1:length(sess) % boucle pour le nombre de session, toujours une session % Chemin du sujet chemin_sujet = fullfile(data_folder, subs(kk).name); % Chemins des dossiers MRS et anat chemin_mrs_parent = fullfile(chemin_sujet, sess(ll).name, 'mrs'); chemin_anat = fullfile(chemin_sujet, sess(ll).name, 'anat'); % 1. Cherche le fichier métabolite (.dat) dir_metabolite = dir([chemin_mrs_parent filesep subs(kk).name '_mpress' filesep subs(kk).name '_svs_mpress.dat']); %construit le chemin vers le fichier mrs du sujet 1 files{counter} = [dir_metabolite(1).folder filesep dir_metabolite(1).name]; % sauvegarde le chemin du fichier % 2. Cherche le fichier MRS 2 dir_metabolite2 = dir([chemin_mrs_parent filesep subs(kk).name '_mpress2' filesep subs(kk).name '_svs_mpress2.dat']); %construit le chemin vers le fichier mrs du sujet 1 files_met2{counter} = [dir_metabolite2(1).folder filesep dir_metabolite2(1).name]; % sauvegarde le chemin du fichier % 3. Cherche le fichier référence (W) dir_ref = dir([chemin_mrs_parent filesep subs(kk).name '_mpressW' filesep subs(kk).name '_svs_mpressW.dat']);%construit le chemin vers le fichier ref du sujet 1 files_ref{counter} = [dir_ref(1).folder filesep dir_ref(1).name]; % sauvegarde le chemin du fichier % 4. Cherche le fichier eau (PRESS) dir_water = dir([chemin_mrs_parent filesep subs(kk).name '_SRM_W30' filesep 'meas_*_SRM_W30.dat' ]);%construit le chemin vers le fichier w du sujet 1 files_w{counter} = [dir_water(1).folder filesep dir_water(1).name]; % 4. Chemin pour le fichier anat dir_anat = dir([chemin_anat filesep subs(kk).name '_T1w.nii.gz']); files_nii{counter} = [dir_anat(1).folder filesep dir_anat(1).name]; counter = counter + 1; end end % 5. Fichier stat file_stat = 'C:\Users\22404132t\Bureau\osprey\osprey-develop\PROJET\stat.csv' % 6. Dossier de sortie outputFolder = 'C:\Users\22404132t\Desktop\osprey\osprey-develop\PROJET\finaletest'