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Dataset results
22 results for “free-breathing”
Free-Breathing Self-Gated 4D-Lung MRI using wave-CAIPI
<p>MRI raw data set of a volunteer examination for the project "Free-Breathing Self-Gated 4D-Lung MRI using wave-CAIPI". The upload includes the measured k-space for 8 different breathing phases, the respective image reconstructions and the coil sensitivity maps required for the Conjugate Gradient SENSE reconstruction.</p> <p>C++ source code for image reconstruction can be downloaded at <a href="https://github.com/expRad/4d_lung">https://github.com/expRad/4d_lung</a>.</p> <p> </p>
Cine and real-time free-breathing CMR at rest and under exercise stress of healthy volunteers
<p>The dataset consists of cine and real-time images from 15 healthy volunteers (7 males; 8 females). All images were acquired in supine position using a 32-channel cardiac surface receiver coil at 3 T (Skyra, Siemens Healthineers, Germany).</p> <p>Conventional imaging at rest included a balanced steady-state free precession (bSSFP) ECG-gated cine sequence to create a short-axis stack covering the entire heart including both ventricles and atria. Real-time CMR data acquisition was performed during free-breathing and without ECG-synchronization at rest and under two different levels of exercise stress.</p> <p>The dataset includes automatically created contours (comDL) using Medis (version 4.0.56.4, QMass® 8.1, Medical Imaging Systems, Leiden, Netherlands) for all images, as well as manually corrected (mc) contours based on the comDL contours for all cine and real-time measurements at rest and under exercise stress for end-diastolic (ED) and end-systolic phases (ES).</p> <p>The dataset also includes segmentation masks in NIfTI format for cine and real-time CMR at rest and under exercise stress created with nnU-Net (DOI:10.1038/s41592-020-01008-z) with freely available weights based trained on the dataset of the cardiac segmentation challenge "Automated Cardiac Segmentation Challenge" (ACDC) (DOI:10.1109/TMI.2018.2837502).</p> <p>To minimize the influence of respiratory motion on clinical measures, images in the ED and ES phase of the cardiac cycle during end-expiration were manually selected for each slice. The dataset includes indices for these images for real-time CMR measurements at rest and under exercise stress. For intra-observer variability, manually corrected contours for the derivation of the clinical measures were created three to six months after the initial segmentation. For inter-observer variability, manually corrected contours for the derivation of the clinical parameters were created for the first five volunteers by a second reader with experience in cardiac segmentation. Single images in the ED and ES phase during end-expiration were once again chosen from each slice.</p> <p>Image data is provided in a file format used by the BART toolbox. <br>DOI:10.5281/zenodo.7110562</p>
A normative database of free-breathing pediatric thoracic 4D dynamic MRI images
<p>In pediatric patients with respiratory abnormalities, it is important to understand the alterations in regional dynamics of the lungs and other thoracoabdominal components, which in turn requires a quantitative understanding of what is considered as normal in healthy children. Currently, such a normative database of regional respiratory structure and function in healthy children does not exist. The shared open-source normative database is from our ongoing virtual growing child (VGC) project, which includes 4D dynamic magnetic resonance imaging (dMRI) images during one breathing cycle for each normal child and also 10 object segmentations at end expiration (EE) and end inspiration (EI) phases of the respiratory cycle in the 4D image. The lung volumes at EE and EI as well as the excursion volumes of chest wall and diaphragm from EE to EI, left and right separately, are also reported. The database has 2,820 3D segmentations from 141 healthy children, which to our knowledge is the largest dMRI dataset of healthy children to date. The database is unique and provides dMRI images, object segmentations, and quantitative regional respiratory measurement parameters of volumes for healthy children. The database can serve as a reference standard to quantify regional respiratory abnormalities in young patients with various respiratory conditions and facilitate treatment planning and response assessment. The database can be useful to advance future AI-based research on image-based object segmentation and analysis.</p>
Data for: Free-Breathing Myocardial T1 Mapping using Inversion-Recovery Radial FLASH and Motion-Resolved Model-Based Reconstruction (Part 1/2)
<p>Magnetic Resonance Imaging measurement data used in our paper about "Free-Breathing Myocardial T1 Mapping using Inversion-Recovery Radial FLASH and Motion-Resolved Model-Based Reconstruction". The data is provided in a file format used by the BART toolbox (DOI: <a href="http://doi.org/10.5281/zenodo.592960">10.5281/zenodo.592960</a>)</p>
A normative database of free-breathing pediatric thoracic 4D dynamic MRI images
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Data for: Free-Breathing Water, Fat, R2∗ and B0 Field Mapping of the Liver Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction (MERLOT)
<p>Data for our manuscript with title "Free-Breathing Water, Fat, R2∗ and B0 Field Mapping of the Liver Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction (MERLOT)"</p>
The free-breathing motion-corrected phase sensitive inversion recovery sequence provides improved myocardial fibrosis evaluation while significantly shortening acquisition time upon comparison to conventional gradient echo sequences: a tripartite comparison of phase-sensitive inversion recovery sequences.
<p>This article includes original research performed at a US Academic Center related to comparison of three separate Phase-Sensitive Inversion Recovery (PSIR) pulse sequences (Breath-hold Single-Shot SFFP, Breath-hold TurboFLASH, and Free-breathing Motion-Corrected SSFP) evaluating the ability of each PSIR sequence to demonstrate myocardial hyperenhancement. All three PSIR sequences were performed as a part of a cardiac MRI performed on a patient clinically referred for cardiac MRI with and without contrast. A total of 28 patients were examined with the three PSIR sequences. All three PSIR sequences were performed in the short axis 10 – 25 minutes after intravenous injection of a Gadolinium-based contrast agent. </p> <p>Evaluation of the PSIR sequences ability to detect myocardial late gadolinium enhancement (LGE) was performed by a retrospective review by two blinded, experienced cardiovascular imagers. The review was a qualitative inspection that included grading by a 5-point Likert scale for the sequence’s ability to resist motion artifact, image resolution, ability to visualize hyperenhancement, and overall satisfaction. The number of myocardial segments demonstrating LGE was also quantitated, and the acquisition time of each PSIR sequence was performed.</p> <p>To our knowledge this is the first study that compares the 3 available PSIR LGE sequences with a specific attention to acquisition time (TA). Given our initial study resulted in the conclusion that the motion-corrected SSFP PSIR sequence was superior the the TurboFLASH Gradient Echo PSIR sequence in regards to evaluator grading and acquisition time efficiency.</p>
The Free-Breathing Motion-Corrected Phase Sensitive Inversion Recovery Sequence Provides Improved Myocardial Fibrosis Evaluation while Significantly Shortening Acquisition Time Compared to Conventional Gradient Echo Sequences.
<p>This article includes original research performed at a US Academic Center related to comparison of three separate Phase-Sensitive Inversion Recovery (PSIR) pulse sequences (Breath-hold Single-Shot SFFP, Breath-hold TurboFLASH, and Free-breathing Motion-Corrected SSFP) evaluating the ability of each PSIR sequence to demonstrate myocardial hyperenhancement. All three PSIR sequences were performed as a part of a cardiac MRI performed on a patient clinically referred for cardiac MRI with and without contrast. A total of 28 patients were examined with the three PSIR sequences. All three PSIR sequences were performed in the short axis 10 – 25 minutes after intravenous injection of a Gadolinium-based contrast agent. </p> <p>Evaluation of the PSIR sequences ability to detect myocardial late gadolinium enhancement (LGE) was performed by a retrospective review by two blinded, experienced cardiovascular imagers. The review was a qualitative inspection that included grading by a 5-point Likert scale for the sequence’s ability to resist motion artifact, image resolution, ability to visualize hyperenhancement, and overall satisfaction. The number of myocardial segments demonstrating LGE was also quantitated, and the acquisition time of each PSIR sequence was performed.</p> <p>To our knowledge this is the first study that compares the 3 available PSIR LGE sequences with a specific attention to acquisition time (TA). Given our initial study resulted in the conclusion that the motion-corrected SSFP PSIR sequence was superior the the TurboFLASH Gradient Echo PSIR sequence in regards to evaluator grading and acquisition time efficiency.</p>
Breast cancer: CT and Structures. Free-breathing vs DIBH technique
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Raw k-space data for free-breathing diffusion weighted sequence
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Data for: Free-Breathing Myocardial T1 Mapping using Inversion-Recovery Radial FLASH and Motion-Resolved Model-Based Reconstruction (Part 2/2)
<p>Magnetic Resonance Imaging measurement data used in our paper about "Free-Breathing Myocardial T1 Mapping using Inversion-Recovery Radial FLASH and Motion-Resolved Model-Based Reconstruction". The data is provided in a file format used by the BART toolbox (DOI: <a href="http://doi.org/10.5281/zenodo.592960">10.5281/zenodo.592960</a>)</p>
Evaluation of a Free-breathing Cardiac Cine-MRI Sequence With Image Reconstructions by Deep-Learning in Ischemic Heart Disease
ClinicalTrials.gov study NCT05105984. IPD Sharing: NO. Countries: 1. Publications: 1.
Data for: Free-Breathing Liver Fat, R2* and B0 Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction (Part 4/5)
<p>This data set consists of MRI measurement data for liver scans acquired with a 3D stack-of-stars multi-echo FLASH sequence during free breathing as described in:</p> <p>Zhengguo Tan, Christina Unterberg-Buchwald, Moritz Blumenthal, Nick Scholand, Philip Schaten, Christian Holme, Xiaoqing Wang, Dirk Raddatz, Martin Uecker. <a href="https://doi.org/10.1109/TMI.2022.3228075">Free-Breathing Liver Fat, R2* and B0 Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction.</a> IEEE Transactions on Medical Imaging 42:1374-1387 (2023) </p> <p>The data stored in the format of the BART toolbox (DOI: 10.5281/zenodo.592960).</p>
Data for: Free-Breathing Liver Fat, R2* and B0 Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction (Part 5/5)
<p>This data set consists of MRI measurement data for liver scans acquired with a 3D stack-of-stars multi-echo FLASH sequence during free breathing as described in:</p> <p>Zhengguo Tan, Christina Unterberg-Buchwald, Moritz Blumenthal, Nick Scholand, Philip Schaten, Christian Holme, Xiaoqing Wang, Dirk Raddatz, Martin Uecker. <a href="https://doi.org/10.1109/TMI.2022.3228075">Free-Breathing Liver Fat, R2* and B0 Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction.</a> IEEE Transactions on Medical Imaging 42:1374-1387 (2023) </p> <p>The data stored in the format of the BART toolbox (DOI: 10.5281/zenodo.592960).</p>
Data for: Free-Breathing Liver Fat, R2* and B0 Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction (Part 3/5)
<p>This data set consists of MRI measurement data for liver scans acquired with a 3D stack-of-stars multi-echo FLASH sequence during free breathing as described in:</p> <p>Zhengguo Tan, Christina Unterberg-Buchwald, Moritz Blumenthal, Nick Scholand, Philip Schaten, Christian Holme, Xiaoqing Wang, Dirk Raddatz, Martin Uecker. <a href="https://doi.org/10.1109/TMI.2022.3228075">Free-Breathing Liver Fat, R2* and B0 Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction.</a> IEEE Transactions on Medical Imaging 42:1374-1387 (2023) </p> <p>The data stored in the format of the BART toolbox (DOI: 10.5281/zenodo.592960).</p>
Data for: Free-Breathing Liver Fat, R2* and B0 Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction (Part 1/5)
<p>This data set consists of MRI measurement data for liver scans acquired with a 3D stack-of-stars multi-echo FLASH sequence during free breathing as described in:</p> <p>Zhengguo Tan, Christina Unterberg-Buchwald, Moritz Blumenthal, Nick Scholand, Philip Schaten, Christian Holme, Xiaoqing Wang, Dirk Raddatz, Martin Uecker. <a href="https://doi.org/10.1109/TMI.2022.3228075">Free-Breathing Liver Fat, R2* and B0 Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction.</a> IEEE Transactions on Medical Imaging 42:1374-1387 (2023) </p> <p>The data stored in the format of the BART toolbox (DOI: 10.5281/zenodo.592960).</p>
Data for: Free-Breathing Liver Fat, R2* and B0 Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction (Part 2/5)
<p>This data set consists of MRI measurement data for liver scans acquired with a 3D stack-of-stars multi-echo FLASH sequence during free breathing as described in:</p> <p>Zhengguo Tan, Christina Unterberg-Buchwald, Moritz Blumenthal, Nick Scholand, Philip Schaten, Christian Holme, Xiaoqing Wang, Dirk Raddatz, Martin Uecker. <a href="https://doi.org/10.1109/TMI.2022.3228075">Free-Breathing Liver Fat, R2* and B0 Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-based Reconstruction.</a> IEEE Transactions on Medical Imaging 42:1374-1387 (2023) </p> <p>The data stored in the format of the BART toolbox (DOI: 10.5281/zenodo.592960).</p>
Pilot Tone-guided focused navigation (PT-fNAV) for free-breathing whole-liver fat-water quantification
<p>This repository contains <em>in vivo</em> MRI data acquired on a 1.5T clinical system (MAGNETOM Sola, Siemens Healthcare, Erlangen, Germany) using a commercially available 12-channel body coil equipped with an integrated Pilot Tone navigator.<br>All data provided was collected on human volunteers according to local institutional rules (Ethics Committee, Lausanne, Switzerland), within the frame of a research study titled "<strong>Pilot Tone guided focused navigation for free-breathing whole-liver fat-water quantification</strong>" by Mackowiak et al. (2023).</p> <p>******************************************************************************************************************************************************</p> <p>******************************************************************************************************************************************************</p> <p>Please cite the following work when using data from this repository:</p> <p>Link to pre-print: <a href="https://arxiv.org/abs/2312.04908">https://arxiv.org/abs/2312.04908</a></p> <p>******************************************************************************************************************************************************</p> <p>******************************************************************************************************************************************************</p> <p>For each volunteer, the contents of the repository are as follows:</p> <p>1) a .dat file containing the raw data from the 3D radial free-breathing acquisition at 1.5T</p> <p>2) a "PhysioInfo.mat" file containing the extracted Pilot Tone signals and the reconstructed respiratory trace, as well as their associated time stamps</p> <p>3) a "ReferenceImages.mat" file containing anonymized images obtained with reference Cartesian multi-echo scans (a 3D 8-echo breath-held scan and a 2D 2-echo Dixon VIBE sequence) and reconstructed at the scanner with built-in vendor software.</p>
Quantifying Body Composition and Liver Disease in Children Using Free-Breathing MRI and MRE
ClinicalTrials.gov study NCT04591106. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Clinical Feasibility of Full Free-Breathing Cardiac Magnetic Resonance Imaging
ClinicalTrials.gov study NCT07395843. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
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