mt_sat : Correction of Magnetization transfer for RF inhomogeneities and T1ΒΆ

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Contents

% This m-file has been automatically generated using qMRgenBatch(mt_sat)
% Command Line Interface (CLI) is well-suited for automatization
% purposes and Octave.
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% Please execute this m-file section by section to get familiar with batch
% processing for mt_sat on CLI.
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% Demo files are downloaded into mt_sat_data folder.
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% Written by: Agah Karakuzu, 2017
% =========================================================================

I- DESCRIPTION

qMRinfo('mt_sat'); % Describe the model
  mt_sat :  Correction of Magnetization transfer for RF inhomogeneities and T1

Assumptions:
MTsat is a semi-quantitative method. MTsat values depend on protocol parameters.

Inputs:
MTw     3D MT-weighted data. Spoiled Gradient Echo (or FLASH) with MT
pulse
T1w     3D T1-weighted data. Spoiled Gradient Echo (or FLASH)
PDw     3D PD-weighted data. Spoiled Gradient Echo (or FLASH)
(B1map)  B1+ map. B1map = 1 : perfectly accurate flip angle. Optional.
(Mask)   Binary mask. DOES NOT ACCELERATE FITTING. Just for visualisation

Outputs:
MTSAT         MT saturation map (%), T1-corrected
T1            T1 map (s)

Options:
B1 correction factor     Correction factor (empirical) for the transmit RF. Only
corrects MTSAT, not T1.
Weiskopf, N., Suckling, J., Williams, G., CorreiaM.M., Inkster, B., Tait, R., Ooi, C., Bullmore, E.T., Lutti, A., 2013. Quantitative multi-parameter mapping of R1, PD(*), MT, and R2(*) at 3T: a multi-center validation. Front. Neurosci. 7, 95.

Protocol:
MTw    [FA  TR  Offset]  flip angle [deg], TR [s], Offset Frequency [Hz]
T1w    [FA  TR]          flip angle [deg], TR [s]
PDw    [FA  TR]          flip angle [deg], TR [s]

Example of command line usage:
Model = mt_sat;  % Create class from model
Model.Prot.MTw.Mat = txt2mat('MT.txt');  % Load protocol
Model.Prot.T1w.Mat = txt2mat('T1.txt');
Model.Prot.PDw.Mat = txt2mat('PD.txt');
data = struct;  % Create data structure
data.MTw = load_nii_data('MTw.nii.gz');
data.T1w = load_nii_data('T1w.nii.gz');
data.PDw = load_nii_data('PDw.nii.gz');  % Load data
FitResults = FitData(data,Model); %fit data
FitResultsSave_nii(FitResults,'MTw.nii.gz'); % Save in local folder: FitResults/

For more examples: a href="matlab: qMRusage(mt_sat);"qMRusage(mt_sat)/a

Author: Pascale Beliveau (pascale.beliveau@polymtl.ca)

References:
Please cite the following if you use this module:
Helms, G., Dathe, H., Kallenberg, K., Dechent, P., 2008. High-resolution maps of magnetization transfer with inherent correction for RF inhomogeneity and T1 relaxation obtained from 3D FLASH MRI. Magn. Reson. Med. 60, 1396?1407.
In addition to citing the package:
Cabana J-F, Gu Y, Boudreau M, Levesque IR, Atchia Y, Sled JG, Narayanan S, Arnold DL, Pike GB, Cohen-Adad J, Duval T, Vuong M-T and Stikov N. (2016), Quantitative magnetization transfer imaging made easy with qMTLab: Software for data simulation, analysis, and visualization. Concepts Magn. Reson.. doi: 10.1002/cmr.a.21357

Reference page in Doc Center
doc mt_sat


II- MODEL PARAMETERS

a- create object

Model = mt_sat;

b- modify options

         |- This section will pop-up the options GUI. Close window to continue.
|- Octave is not GUI compatible. Modify Model.options directly.
Model = Custom_OptionsGUI(Model); % You need to close GUI to move on.

III- FIT EXPERIMENTAL DATASET

a- load experimental data

         |- mt_sat object needs 5 data input(s) to be assigned:
|-   MTw
|-   T1w
|-   PDw
|-   B1map
|-   Mask
data = struct();
% MTw.nii.gz contains [128  128   96] data.
data.MTw=double(load_nii_data('mt_sat_data/MTw.nii.gz'));
% T1w.nii.gz contains [128  128   96] data.
data.T1w=double(load_nii_data('mt_sat_data/T1w.nii.gz'));
% PDw.nii.gz contains [128  128   96] data.
data.PDw=double(load_nii_data('mt_sat_data/PDw.nii.gz'));

b- fit dataset

           |- This section will fit data.
FitResults = FitData(data,Model,0);
...done

c- show fitting results

         |- Output map will be displayed.
|- If available, a graph will be displayed to show fitting in a voxel.
|- To make documentation generation and our CI tests faster for this model,
we used a subportion of the data (40X40X40) in our testing environment.
|- Therefore, this example will use FitResults that comes with OSF data for display purposes.
|- Users will get the whole dataset (384X336X224) and the script that uses it for demo
via qMRgenBatch(qsm_sb) command.
FitResults_old = load('FitResults/FitResults.mat');
qMRshowOutput(FitResults_old,data,Model);

d- Save results

         |-  qMR maps are saved in NIFTI and in a structure FitResults.mat
that can be loaded in qMRLab graphical user interface
|-  Model object stores all the options and protocol.
It can be easily shared with collaborators to fit their
own data or can be used for simulation.
FitResultsSave_nii(FitResults, 'mt_sat_data/MTw.nii.gz');
Model.saveObj('mt_sat_Demo.qmrlab.mat');
Warning: Directory already exists.

V- SIMULATIONS

   |- This section can be executed to run simulations for mt_sat.

a- Single Voxel Curve

         |- Simulates Single Voxel curves:
(1) use equation to generate synthetic MRI data
(2) add rician noise
(3) fit and plot curve
% Not available for the current model.

b- Sensitivity Analysis

         |-    Simulates sensitivity to fitted parameters:
(1) vary fitting parameters from lower (lb) to upper (ub) bound.
(2) run Sim_Single_Voxel_Curve Nofruns times
(3) Compute mean and std across runs
% Not available for the current model.