vfa_t1: Compute a T1 map using Variable Flip AngleΒΆ

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Contents

% This m-file has been automatically generated using qMRgenBatch(vfa_t1)
% Command Line Interface (CLI) is well-suited for automatization
% purposes and Octave.
%
% Please execute this m-file section by section to get familiar with batch
% processing for vfa_t1 on CLI.
%
% Demo files are downloaded into vfa_t1_data folder.
%
% Written by: Agah Karakuzu, 2017
% =========================================================================

I- DESCRIPTION

qMRinfo('vfa_t1'); % Describe the model
Contents of vfa_t1:

vfa_blochsim                   - IR_BLOCHSIM Bloch simulations of the GRE-IR pulse sequence.
vfa_equation                   - S Analytical equations for the longitudinal magnetization of


vfa_t1 is both a directory and a function.

vfa_t1: Compute a T1 map using Variable Flip Angle

Assumptions:

Inputs:
VFAData         spoiled Gradient echo data, 4D volume with different flip angles in time dimension
(B1map)         excitation (B1+) fieldmap. Used to correct flip angles. (optional)
(Mask)          Binary mask to accelerate the fitting (optional)

Outputs:
T1              Longitudinal relaxation time [s]
M0              Equilibrium magnetization

Protocol:
VFAData Array [nbFA x 2]:
[FA1 TR1; FA2 TR2;...]      flip angle [degrees] TR [s]

Options:
None

Example of command line usage:
Model = vfa_t1;  % Create class from model
Model.Prot.VFAData.Mat=[3 0.015; 20 0.015]; %Protocol: 2 different FAs
data = struct;  % Create data structure
data.VFAData = load_nii_data('VFAData.nii.gz');
data.B1map = load_nii_data('B1map.nii.gz');
FitResults = FitData(data,Model); %fit data
FitResultsSave_mat(FitResults);

For more examples: a href="matlab: qMRusage(vfa_t1);"qMRusage(vfa_t1)/a


Author: Ian Gagnon, 2017

References:
Please cite the following if you use this module:
Fram, E.K., Herfkens, R.J., Johnson, G.A., Glover, G.H., Karis, J.P.,
Shimakawa, A., Perkins, T.G., Pelc, N.J., 1987. Rapid calculation of
T1 using variable flip angle gradient refocused imaging. Magn. Reson.
Imaging 5, 201?208
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 vfa_t1


II- MODEL PARAMETERS

a- create object

Model = vfa_t1;

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

         |- vfa_t1 object needs 3 data input(s) to be assigned:
|-   VFAData
|-   B1map
|-   Mask
data = struct();
% VFAData.nii.gz contains [128  128    1    2] data.
data.VFAData=double(load_nii_data('vfa_t1_data/VFAData.nii.gz'));
% B1map.nii.gz contains [128  128] data.
data.B1map=double(load_nii_data('vfa_t1_data/B1map.nii.gz'));
% Mask.nii.gz contains [128  128] data.
data.Mask=double(load_nii_data('vfa_t1_data/Mask.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);
          M0: 2.5567e+03
Model: [11 struct]
Protocol: [11 struct]
T1: 1.3447
Time: 0.0087
Version: [2 0 8]
computed: [128128 double]
fields: {'T1'  'M0'}

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, 'vfa_t1_data/VFAData.nii.gz');
Model.saveObj('vfa_t1_Demo.qmrlab.mat');
Warning: Directory already exists.

V- SIMULATIONS

   |- This section can be executed to run simulations for vfa_t1.

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.