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Dataset results
14 results for “Quantitative susceptibility mapping”
MRI raw data for: A novel phantom with dia- and paramagnetic substructure for quantitative susceptibility mapping and relaxometry
<p>MRI raw data from three different magnetic field strength (1.5 T, 3 T, 7T; 7T data are in separate datasets) for the publication 'A novel phantom with dia- and paramagnetic substructure for quantitative susceptibility mapping and relaxometry', in which a phantom was presented that allows for an experimental evaluation of QSM reconstruction algorithms. The phantom contains susceptibility producing particles with dia- and paramagnetic properties embedded in an MRI visible medium (gelatin and agarose gel) and is suitable to assess the performance of algorithms that attempt to separate isotropic dia- and paramagnetic susceptibility at the sub-voxel level. The dataset additionally contains raw data for a phantom that only contains diamagnetic and paramagnetic particles, respectively, for magnetic field strengths of 1.5 T and 3 T (additional 7 T data are provided in separate datasets).</p>
7T MRI raw data for: A novel phantom with dia- and paramagnetic substructure for quantitative susceptibility mapping and relaxometry
<p>MRI 7 T raw data for the publication 'A novel phantom with dia- and paramagnetic substructure for quantitative susceptibility mapping and relaxometry', in which a phantom was presented that allows for an experimental evaluation of QSM reconstruction algorithms. The phantom contains susceptibility producing particles with dia- and paramagnetic properties embedded in an MRI visible medium (gelatin and agarose gel) and is suitable to assess the performance of algorithms that attempt to separate isotropic dia- and paramagnetic susceptibility at the sub-voxel level. This dataset only contains additional raw data for a phantom that only contains diamagnetic and paramagnetic particles, respectively.</p>
Quantitative susceptibility mapping of articular cartilage: ex vivo findings at multiple orientations and following different degradation treatments
<p>This dataset contains all the raw source data and MATLAB analysis functions that comprise the study:</p> <p><br> Quantitative susceptibility mapping of articular cartilage: Ex vivo findings at multiple orientations and following different degradation treatments</p> <p>Magnetic Resonance in Medicine | DOI: 10.1002/mrm.27216</p> <p>Nykänen Olli(1*), Rieppo Lassi(2,3), Töyräs Juha(1,4), Kolehmainen Ville(1), Saarakkala Simo(2,3,5), Shmueli Karin(6) and Nissi Mikko Johannes(1)</p> <p>(1) Department of Applied Physics, University of Eastern Finland, POB 1627, FI-70211 Kuopio, Finland<br> (2) Research Unit of Medical Imaging, Physics and Technology, University of Oulu, POB 5000, FI-90014 Oulu, Finland<br> (3) Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland<br> (4) Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland<br> (5) Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland<br> (6) Department of Medical Physics & Biomedical Engineering, University College London(UCL), London, United Kingdom</p> <p><br> *Corresponding author:<br> Olli Nykänen<br> Department of Applied Physics,<br> University of Eastern Finland<br> POB 1627<br> FI-70211, Kuopio, Finland<br> olli.nykanen@uef.fi<br> +358-50-5556357</p> <p><br> Keywords: cartilage, collagen matrix, quantitative susceptibility mapping, MRI, osteoarthritis</p> <p><br> Included folders and files are:<br> - article_figures: all figures published in the manuscript<br> - data: all MRI, histological, and PLM data used in this article<br> - matlab_functions: matlab functions used in data analysis with subfolders:<br> - aedes_plugins: plugins for aedes (http://aedes.uef.fi) for calculation of QS- and T2* maps<br> - fitting_functions: functions for fitting relaxation times or TKD-method for QSM, used by the functions in above folder<br> - miscellaneous_functions: small helper functions for a number of small tasks utilized by the other scripts and functions<br> - ReadMe.txt: this file</p> <p><br> Notes for setting up Aedes correctly for this dataset:<br> Run Aedes -> Tools -> Edit VNMR Defaults:<br> - Return: FT + K-space<br> - DC: off<br> - Zeropadding: off<br> - Sorting & fastread: on<br> - Precision: single<br> - Read_fcn: readvnmr<br> - Orient: no</p> <p>See more info in separate readme files included in each folder.</p> <p><br> (Olli Nykänen, Apr 17, 2018)</p>
7 T MRI rawdata for (part 1): A novel phantom with dia- and paramagnetic substructure for quantitative susceptibility mapping and relaxometry
<p>MRI raw data from three different magnetic field strength (1.5 T, 3 T, 7T; 7T data are in separate datasets) for the publication 'A novel phantom with dia- and paramagnetic substructure for quantitative susceptibility mapping and relaxometry', in which a phantom was presented that allows for an experimental evaluation of QSM reconstruction algorithms. The phantom contains susceptibility producing particles with dia- and paramagnetic properties embedded in an MRI visible medium (gelatin and agarose gel) and is suitable to assess the performance of algorithms that attempt to separate isotropic dia- and paramagnetic susceptibility at the sub-voxel level. This dataset additionally contains raw data for a phantom that only contains diamagnetic and paramagnetic particles, respectively, for magnetic field strengths of 7 T.</p>
7 T MRI rawdata for (part 2): A novel phantom with dia- and paramagnetic substructure for quantitative susceptibility mapping and relaxometry
<p>MRI raw data from three different magnetic field strength (1.5 T, 3 T, 7T; 7T data are in separate datasets) for the publication 'A novel phantom with dia- and paramagnetic substructure for quantitative susceptibility mapping and relaxometry', in which a phantom was presented that allows for an experimental evaluation of QSM reconstruction algorithms. The phantom contains susceptibility producing particles with dia- and paramagnetic properties embedded in an MRI visible medium (gelatin and agarose gel) and is suitable to assess the performance of algorithms that attempt to separate isotropic dia- and paramagnetic susceptibility at the sub-voxel level. This dataset additionally contains raw data for a phantom that only contains diamagnetic and paramagnetic particles, respectively, for magnetic field strengths of 7 T.</p>
Recommended Implementation of Quantitative Susceptibility Mapping for Clinical Research in The Brain: A Consensus of the ISMRM Electro-Magnetic Tissue Properties Study Group
<p>Example datasets and code for the recommended implementation of Quantitative Susceptibility Mapping (QSM) in "Recommended Implementation of Quantitative Susceptibility Mapping for Clinical Research in The Brain: A Consensus of the ISMRM Electro-Magnetic Tissue Properties Study Group".</p>
T2* and quantitative susceptibility mapping in an equine model of post-traumatic osteoarthritis: prediction of mechanical and structural properties
<p>Dataset for the manuscript titled "T2* and quantitative susceptibility mapping in an equine model of post-traumatic osteoarthritis: assessment of mechanical and structural properties"</p>
data set related to article Echo-time dependency of quantitative susceptibility mapping reproducibility at different magnetic field strengths
<p>This record contains raw date related to article Echo-time dependency of quantitative susceptibility mapping reproducibility at different magnetic field strengths</p>
Quantitative Susceptibility Mapping (QSM) to Guide Iron Chelating Therapy
ClinicalTrials.gov study NCT04171635. IPD Sharing: NO. Countries: 1. Publications: 0.
Evaluation of the Reproducibility of the Measurement of the QSM Signal (Quantitative Susceptibility Mapping)
ClinicalTrials.gov study NCT04465448. IPD Sharing: NO. Countries: 1. Publications: 0.
Database of publication "Diagnostic accuracy of Quantitative Susceptibility Mapping in Multiple System Atrophy: the impact of echo time and the potential of histogram analysis". NeuroImage: Clinical, 2022, 102989.
<p>The file data_MSA_NICL2022.mat contains the data from Lancione et al., NeuroImage: Clinical 2022.</p> <p>If you use these data, please cite:</p> <p>Lancione, M., et al. Diagnostic accuracy of Quantitative Susceptibility Mapping in Multiple System Atrophy: the impact of echo time and the potential of histogram analysis. NeuroImage: Clinical, 2022, 102989.</p> <p><br> The data are structured as follows:</p> <p>- age: age in years of all 44 subjects<br> - sex: "1": male; "-1": female<br> - diagnosis: "HC": healthy controls; "MSAp": Multiple System Atrophy with Parkinsonian phenotype; "MSAc": Multiple System Atrophy with cerebellar phenotype<br> - roi_name: names of the 20 ROIs; the abbreviations are defined in the original paper<br> - stats_name: names of the 9 histogram features<br> - stats: [9 histogram features x 44 subjects x 20 ROIs x 5 TEs (4 acquired TEs + the average of all TEs)]</p>
Longitudinal Quantitative Susceptibility Mapping (QSM) in Alzheimer 's Disease
ClinicalTrials.gov study NCT02752750. IPD Sharing: NO. Countries: 0. Publications: 0.
Dataset related to "Multi-centre and multi-vendor reproducibility of a standardized protocol for quantitative susceptibility Mapping of the human brain at 3T"
<p>Data supporting the journal article:</p> <p>Lancione, Marta, et al. "Multi-centre and multi-vendor reproducibility of a standardized protocol for quantitative susceptibility Mapping of the human brain at 3T." <em>Physica Medica</em> 103 (2022): 37-45.</p>
Dataset related to "Evaluation of iron overload in nigrosome 1 via quantitative susceptibility mapping as a progression biomarker in prodromal stages of synucleinopathies"
<p>Data supporting the journal article:</p> <p>Lancione, Marta, et al. "Evaluation of iron overload in nigrosome 1 via quantitative susceptibility mapping as a progression biomarker in prodromal stages of synucleinopathies." <em>NeuroImage</em> 260 (2022): 119454.</p>
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