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15 results for “T2 mapping”
Dataset T2 Mapping from Super-Resolution-Reconstructed Clinical Fast Spin Echo Magnetic Resonance Acquisitions
<p>This dataset provides various acquisitions for T2 mapping of the MnCl2 array of the NIST phantom at 1.5T. Data were acquired on a MAGNETOM Sola (Siemens Healthcare, Erlangen, Germany), with an 18-channel body coil and a 32-channel spine coil (12 elements used). It gathers original acquisitions from Lajous H. et al. (2020) T2 Mapping from Super-Resolution-Reconstructed Clinical Fast Spin Echo Magnetic Resonance Acquisitions. In: Martel A.L. et al. (eds) Medical Image Computing and Computer Assisted Intervention – MICCAI 2020. MICCAI 2020. Lecture Notes in Computer Science, vol 12262. Springer, Cham. https://doi.org/10.1007/978-3-030-59713-9_12.</p> <p>The dataset is composed of DICOM images from:</p> <p>i) Gold-standard single-echo spin echo (SE) sequences acquired at variable TE;</p> <p>ii) Alternative reference multi-echo spin echo (MESE) acquisitions;</p> <p>iii) Half-Fourier Acquisition Single-shot Turbo spin Echo (HASTE) images at variable TE in three orthogonal orientations.</p> <p>The acquisition parameters are further detailed in the ReadMe.txt file provided along with the images.</p> <p>These acquisitions were repeated independently on three different days during the month of January 2020.</p> <p>These data are made publicly available as a support for further reproducibility studies as well as for the validation of new T2 relaxometry strategies.</p> <p>Works using any of these data should cite the following two references:</p> <p>- Lajous H. et al. (2020) T2 Mapping from Super-Resolution-Reconstructed Clinical Fast Spin Echo Magnetic Resonance Acquisitions. In: Martel A.L. et al. (eds) Medical Image Computing and Computer Assisted Intervention – MICCAI 2020. MICCAI 2020. Lecture Notes in Computer Science, vol 12262. Springer, Cham. https://doi.org/10.1007/978-3-030-59713-9_12</p> <p>- Lajous, Hélène, Ledoux, Jean-Baptiste, Hilbert, Tom, van Heeswijk, Ruud B., & Bach Cuadra, Meritxell. (2020). Dataset T2 Mapping from Super-Resolution-Reconstructed Clinical Fast Spin Echo Magnetic Resonance Acquisitions [Data set]. Zenodo. http://doi.org/10.5281/zenodo.3931812</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 From: B1 Field inhomogeneity correction for qDESS T2 mapping: application to rapid bilateral knee imaging
<p><strong>Purpose</strong>: T2 mapping is a powerful tool for studying osteoarthritis (OA) changes and bilateral imaging may be useful in investigating the role of between-knee asymmetry in OA onset and progression. The quantitative double-echo in steady-state (qDESS) can provide fast simultaneous bilateral knee T2 and high-resolution morphometry for cartilage and meniscus.<br> The qDESS uses an analytical signal model to compute T2 relaxometry maps, which require knowledge of the flip angle (FA). <br> In the presence of B1 inhomogeneities, inconsistencies between the nominal and actual FA can affect the accuracy of T2 measurements.<br> We propose a pixel-wise B1 correction method for qDESS T2 mapping exploiting an auxiliary B1 map to compute the actual FA used in the model.<br> <br> <strong>Methods</strong>: The technique was validated in a phantom and in vivo with simultaneous bilateral knee imaging. <br> T2 measurements of femoral cartilage (FC) of both knees of six healthy participants were repeated longitudinally to investigate the association between T2 variation and B1.</p> <p><strong>Results</strong>: The results showed that applying the B1 correction mitigated T2 variations that were driven by B1 inhomogeneities. <br> Specifically, T2 left-right symmetry increased following the B1 correction (rc = 0.74 > rc = 0.69). Without the B1 correction, T2 values showed a linear dependence with B1. The linear coefficient decreased using the B1 correction (from 24.3 <span class="math-tex">\(\pm\)</span> 1.6 ms to 4.1 <span class="math-tex">\(\pm\)</span> 1.8) and the correlation was not statistically significant after the application of the Bonferroni correction (p-value > 0.01).<br> <br> <strong>Conclusion</strong>: the study showed that B1 correction could mitigate variations driven by the sensitivity of the qDESS T2 mapping method to B1, therefore increasing the sensitivity to detect real biological changes. The proposed method may improve the robustness of bilateral qDESS T2 mapping, allowing for an accurate and more efficient evaluation of OA pathways and pathophysiology through longitudinal and cross-sectional studies.</p> <p><strong>This repository contains the raw data for reproducing the results reported in the paper. The data are provided in NIFTI format. The repository also contains the MALTAB scripts used to compute B<sub>1</sub> maps from the NIFTI data.</strong></p>
T2 mapping of the sacroiliac joints in patients with axial spondyloarthritis
<p><strong>Purpose: </strong>To test whether T2 mapping of the sacro-iliac joints (SIJs) might help identifying patients with spondyloarthritis.</p> <p><strong>Method: </strong>This study included 20 biologic-naive patients with axial spondyloarthritis (10 females; mean age: 38 ± 9years; range, 19-47) and 27 controls (16 males; mean age = 39 ± 13years; range = 28-71) who prospectively underwent SIJs MRI at 1.5 T, including a multislice multiecho spin-echo sequence. Standard MRIs were reviewed to assess the SIJs according to the Assessment of SpondyloArthritis International Society (ASAS) criteria and SPondyloArthritis Research Consortium of Canada (SPARCC) MRI index. T2 maps obtained from multiecho sequences were used to draw regions of interests in the cartilaginous part of the SIJs. Disease activity was assessed using BASDAI questionnaire. Bland-Altman method, ROC curve analysis, Chi square, Mann-Whitney U, Pearson's and Spearman's correlation coefficient were used for data analysis.</p> <p><strong>Results: </strong>According to ASAS criteria, MRI was positive for sacroiliitis in 5/20 patients (25 %). Inter-observer reproducibility of T2 values was 87 % (coefficient of repeatability = 7.0; bias = 0.49; p < .001). Mean T2 values of patients (58.5 ± 4.4 ms, range: 52.6-68.2 ms) were significantly higher (p < .001) than those of controls (44.1 ± 6.6 ms, range: 33.6-67.2 ms). A T2 value of 52.51 ms yielded 100 % sensitivity and 91.7 % specificity to differentiate patients from controls. No statistically significant association/correlation was found between T2 values and BASDAI (r=-.026, p = .827), disease duration (r = .024, p = .871), SPARCC (r=-.004, p = .981), ASAS criteria (p = .476), HLA-B27-positivity (p = .139), age (r=-.2.53, p = .891), and gender (p = .404).</p> <p><strong>Conclusions: </strong>T2 relaxation times of the SIJs were significantly higher in patients than in healthy controls, making this tool potentially helpful to early identify patients with spondyloarthritis.</p>
Data from: A Deep Learning Approach for Fast Muscle Water T2 Mapping with Subject Specific Fat T2 Calibration from Multi-Spin-Echo Acquisitions
<p>This repository contains the imaging data (in NIfTI) and analysis code to reproduce the work presented in <em>"A Deep Learning Approach for Fast Muscle Water T2 Mapping with Subject Specific Fat T2 Calibration from Multi-Spin-Echo Acquisitions"</em> by <strong>Marco Barbieri, Melissa T. Hooijmans, Kevin Moulin, Tyler E. Cork, Daniel B. Ennis, Garry E. Gold, Feliks Kogan and Valentina Mazzoli.</strong></p> <p>Citation: "Barbieri, M., Hooijmans, M.T., Moulin, K. <em>et al.</em> A deep learning approach for fast muscle water T2 mapping with subject specific fat T2 calibration from multi-spin-echo acquisitions. <em>Sci Rep</em> 14, 8253 (2024). https://doi.org/10.1038/s41598-024-58812-2"</p> <p>The source code for setting up the Deep Learning application can be found in the GitHub repository https://github.com/barma7/Deep_Learning_for_Muscle_T2_mapping.git</p>
Data and code from: Improving accuracy and reproducibility of cartilage T2 mapping in the OAI dataset through extended phase graph modeling
<p>The repository contains the OAI data used to run the experiments reported in the study "Improving accuracy and reproducibility of cartilage T2 mapping in the OAI dataset through extended phase graph modeling", along with their segmentation and processed T2 maps with the different fitting algorithms.</p> <p>The <em><strong>code_repository</strong></em> folder contains a snapshot of the <a href="https://github.com/barma7/EPGfit_for_cartilage_T2_mapping">GitHub repository</a> at the time of the submission of the manuscript. Please visit the GitHub repository for the latest version. </p>
3D-EPI Blip-Up/Down Acquisition (BUDA) with CAIPI and Joint Hankel Structured Low-Rank Reconstruction for Rapid Distortion-Free High-Resolution T2* Mapping
<p>3D-BUDA data acquired from a 3T Siemens scanner and a 7T Siemens scanner</p>
Anthracycline Induced Cardiotoxicity - Early Detection by Combination of Diastolic Strain and T2-mapping
ClinicalTrials.gov study NCT03940625. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Wrist Cartilage - High Resolution in Vivo MR T2 Mapping- a Feasibility Study
ClinicalTrials.gov study NCT00669201. IPD Sharing: Not stated. Countries: 1. Publications: 3.
T2 orientation anisotropy mapping of articular cartilage using qMRI
<p>Data and codes for publication entitled "T2 orientation anisotropy mapping of articular cartilage using qMRI"</p>
Value of Adding T2 Mapping Routine MRI in Assessment of Knee Articular Cartilage Early Osteoarthritis
ClinicalTrials.gov study NCT07316257. IPD Sharing: Not stated. Countries: 0. Publications: 2.
T2 Heart Mapping in AMI Population for the Prediction of Short Term Major Adverse Cardiovascular Events
ClinicalTrials.gov study NCT01796743. IPD Sharing: Not stated. Countries: 1. Publications: 0.
MRI T2* Mapping of Myocardium, Liver, Pancreas and Pituitary Gland
ClinicalTrials.gov study NCT04835285. IPD Sharing: NO. Countries: 1. Publications: 0.
Diagnostic Performance of 3T MRI T2 Mapping Technique in Chondro-labral Pathology of the Hip, Correlated With Intraoperative Arthroscopic Findings: Interventional Diagnostic Technique Validation Study
ClinicalTrials.gov study NCT06067243. IPD Sharing: NO. Countries: 1. Publications: 0.
Data From: B1 Field inhomogeneity correction for qDESS T2 mapping: application to rapid bilateral knee imaging
<p>T2 mapping is a powerful tool for studying osteoarthritis (OA) changes and bilateral imaging may be useful in investigating the role of between-knee asymmetry in OA onset and progression. The quantitative double-echo in steady-state (qDESS) can provide fast simultaneous bilateral knee T2 and high-resolution morphometry for cartilage and meniscus. The qDESS uses an analytical signal model to compute T2 relaxometry maps, which require knowledge of the flip angle (FA). In the presence of B1 inhomogeneities, inconsistencies between the nominal and actual FA can affect the accuracy of T2 measurements.</p> <p>We propose a pixel-wise B1 correction method for qDESS 2 mapping exploiting an auxiliary B1 map to compute the actual FA used in the model. The technique was validated in a phantom and in vivo with simultaneous bilateral knee imaging. T2 measurements of femoral cartilage (FC) of both knees of a healthy participant were repeated longitudinally to investigate the association between T2 variation and B1. The results showed that applying the B1 correction could mitigate T2 variations that were driven by B1 inhomogeneities. Specifically, T2 left-right symmetry increased following the B1 correction. Without the B1 correction, T2 values showed a significant (p<0.05) moderate Pearson’s correlation with B1 across time points (0.68 <r<0.70 and 0.74<r<0.79, for the left and right knee, respectively). The correlations and slopes decreased using the B1 correction (0.01<r<0.02 and 0.48<r<0.55, for left and right knee, respectively) and were not statistically significant (p > 0.05). In conclusion, the study showed that B1 correction could mitigate variations driven by the sensitivity of the qDESS T2 mapping method to B1, therefore increasing the sensitivity to detect real biological changes.</p> <p>The proposed method may improve the robustness of bilateral qDESS T2 mapping, allowing for an accurate and more efficient evaluation of OA pathways and pathophysiology through longitudinal and cross-sectional studies.</p> <p><strong>This repository contains the raw data for reproducing the results reported in the paper. The data are provided in NIFTI format.</strong></p> <p> </p>
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