Dataset: In-vivo characterization of magnetic inclusions in the subcortex from non-exponential transverse relaxation decay
<p>This repository includes the data used to compile the results presented in the scientific publication: "In-vivo characterization of magnetic inclusions in the subcortex from non-exponential transverse relaxation decay".</p>
<p>Rita Oliveira, Antoine Lutti<br>Laboratory for Research in Neuroimaging (LREN)<br>Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne<br>Mont-Paisible 16, CH-1011 Lausanne, Switzerland<br><br>Classically, the MRI transverse relaxation decay is analyzed by fitting the signal decay over echo time voxel-wise with a monoexponential function (Exp), for which a decay rate R<sub>2</sub><sup>∗</sup> is estimated. However, the presence of magnetic material within the tissue, such as iron-loaded cells, myelin, or blood vessels, introduces variations in the magnetic field, which can modify the exponential behaviour of the decay (1,2). In such inhomogeneous magnetic fields, the theory predicts a transient regime starting with a Gaussian behaviour at short echo times and approaching a monoexponential relaxation at long echo times (1,3–6).<br>We highlight three different analytical descriptions of the signal decay that account for the transient regime of the transverse relaxation decay: i) the Anderson and Weiss, 1953 model (AW); ii) the Jensen and Chandra, 2000 model/Sukstanskii and Yablonskiy, 2003 model (SY; in the article is called JC); iii) and following a Padé approximation (Padé) of the transition from Gaussian to exponential decay.<br>This repository includes transverse relaxation decay data that enables the observation of the non-exponential MRI transverse relaxation. The data was acquired from 5 healthy volunteers at 3T. AW, SY, Padé, and Exp are the different methods that we used to fit the data with. Here we focus on the analysis of subcortical brain regions: Substantia Nigra, Pallidum, Putamen, Caudate, and Thalamus.</p>
<p><strong>Data Description</strong><br>The necessary files to compile the results presented in the scientific publication can be found in the ‘<em>multiecho</em>’ folder. There are three different folders corresponding to three repetitions of the acquisition (‘rep1’ to ‘rep3’). The data consists of:<br>• resc_den_ subject_name_N.nii: magnitude image file corresponding to echo N. These files were previously denoised and rescaled (resc_den). The description field of the header of the images contains the corresponding TE at which the image was acquired, which will be needed in the fitting routine. Since we focus on the analysis of subcortical brain regions (Substantia Nigra, Pallidum, Putamen, Caudate, and Thalamus), the multi-echo data is masked within this region.<br>• nf: value of the noise floor level. Corresponds to the noncentrality parameter of a Rician distribution fitted to the background signal.</p>
<p>In the ‘<em>anat</em>’ folder the user has access to:<br>• MT: Magnetization Transfer map (MTsat) that serves as a reference anatomical image.<br>• ROI folder: contains masks of each of the 5 regions of interest analyzed in the scientific paper: Substantia Nigra, Pallidum, Putamen, Caudate, and Thalamus.</p>
<p><br>The ‘<em>modelfits</em>’ folder contains pre-computed results for each subject analyzed. If the user uses the analysis code that comes along with this dataset (<a href="https://github.com/LREN-physics/TransverseRelaxation">https://github.com/LREN-physics/TransverseRelaxation</a>), this folder will be overwritten with the new results. For each method (‘AW’, ‘SY’, ‘Pade’, ‘Exp’) there is a folder containing the corresponding resulting maps. These maps are:<br>• R2s.nii: map of R<sub>2,micro</sub><sup>∗</sup> [ms<sup>-1</sup>] for ‘AW’, ‘SY’, and ‘Pade’ options. Map of R<sub>2</sub><sup>∗</sup> [ms<sup>-1</sup>] for ‘Exp’ fit.<br>• OmegaSq.nii: map of γ\(\Omega^2\) [rad<sup>2</sup> ms<sup>-2</sup>]. Not available for ‘Exp’ fit.<br>• TE0signal.nii: map of the initial signal amplitude S<sub>0</sub>.<br>• T2mol.nii: map of the inverse of effective transverse relaxation rate resulting from processes on the nanoscale [ms]<br>• AIC.nii: map of Akaike information criterion regarding the fitting procedure.<br>• MSE.nii: maps of the mean square error of the fitting procedure.<br>• DataMatrix.mat: matrix containing the data used for the fitting procedure.<br>• VoxelIndices.mat: vector containing the indices of the voxels corresponding to the analyzed data, which is restricted to the subcortical regions.<br>• Params.mat: structure containing the parameters used for the analysis.<br>Inside ‘modelfits’ there are also two folders corresponding to two different regimes that can describe the transverse relaxation decay: static dephasing regime (‘SDR’) or diffusion narrowing regime (‘DNR’). Under the assumption of SDR, we computed:<br>• ki_ppm.nii: maps of π₯π, which is the difference in susceptibility of the magnetic inclusions to the surrounding tissue [addimentional, in ppm and in SI units]<br>• zeta.nii: maps of π, which is the volume fraction of the magnetic inclusions [addimentional]<br>Under the assumption of DNR, we computed:<br>• alpha.nii: πΌ=πγ\(\sqrt{\Omega^2}\)γ [addimentional]<br>• tau_ms.nii: maps of π, which is the time scale for water molecules to diffuse away from magnetic inclusions [ms]<br>Please refer to the corresponding article for a complete description of the methods and corresponding estimated parameters.</p>
openSep 2023View details β
