Just download and put somewhere. DUSTER is written in MATLAB, so it should be platform independent. Tested on Ubuntu 18.04 with MATLAB 2018-19.
Edit /Code/DCE/DCE_Main.m : Provide the .nii file names:
- main DCE run
- T1 map
- [optionally] B1+ map.
The files should be already coregistered and aligned/motion corrected.\
Also needed:
- TimeBetweenDCEVols in secons.
- TR in ms.
- FA in degrees.
We normally acquire ~60 volumes at a temporal resolution of ~6 seconds, with TR ~5ms, and FA ~20o.
The program includes 2 UIs for manual inspection/intervention during the analsys:
- Arterial voxels selection UI. Several voxels with significant arterial content should be chosed, preferably from the artery feeding the tumor. The system is robust to inaccurate selection.
- AIF parameters UI.
And finally, a UI for exploring the results.
Also included is code for T1 mapping calculation from VFA-SPGR data, using the nominal FAs, and estimation of the real FAs produced by the system, detailed in [8].
In case the termporal resolution is good enough (i.e. volume every < 3 seconds), the 2-compartments-exchange-model may be used, providing additional flow information. Code for the analysis, based on [7], is provided here. If you're interested, please contact us.
The code includes stuff from:
SPM8 from https://www.fil.ion.ucl.ac.uk/spm/software/spm8/
NIFTI-Tools from https://www.mathworks.com/matlabcentral/fileexchange/8797-tools-for-nifti-and-analyze-image
MRIcron from https://people.cas.sc.edu/rorden/mricron/index.html
Some optional calls to FSL https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/
[1] DUSTER: Dynamic contrast enhance up-sampled temporal resolution analysis method, Magnetic Resonance Imaging, DOI: 10.1016/j.mri.2015.12.014
[2] Optimization of DCE-MRI protocol for the assessment of patients with brain tumors, Magnetic Resonance Imaging, DOI: 10.1016/j.mri.2016.07.003
[3] Differentiation between Treatment-Related Changes and Progressive Disease in Patients with High Grade Brain Tumors using Support Vector Machine Classification based on DCE MRI, Journal of Neuro-Oncology, DOI: 10.1007/s11060-016-2055-7
[4] Human cerebral blood volume measurements using dynamic contrast enhancement in comparison to dynamic susceptibility contrast MRI, Neuroradiology, DOI: 10.1007/s00234-015-1518-4
[5] Classification of tumor area using combined DCE and DSC MRI in patients with glioblastoma, Journal of Neuro-Oncology, 34(4): 442–450. DOI: 10.1007/s11060-014-1639-3
[6] Differentiation between vasogenic-edema versus tumor-infiltrative area in patients with glioblastoma during bevacizumab therapy: A longitudinal MRI study, European Journal of Radiology, DOI: 10.1016/j.ejrad.2014.03.026
[7] Optimization of two-compartment-exchange-model analysis for dynamic contrast-enhanced mri incorporating bolus arrival time, Journal of Magnetic Resonance Imaging, DOI: 10.1002/jmri.25362
[8] T1 Mapping using Variable Flip Angle SPGR Data with Flip Angle Correction, Journal of Magnetic Resonance Imaging, DOI: 10.1002/jmri.24373