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1,152 results for “Magnetic resonance imaging”

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ClinicalTrials.gov36/100

Hyperpolarized Xenon-129 Magnetic Resonance Imaging and Spectroscopy of Brown Fat: Healthy Adult Volunteer Pilot Study

ClinicalTrials.gov study NCT02220426. IPD Sharing: NO. Countries: 1. Publications: 1.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov36/100

Cardiac Magnetic Resonance Imaging in Patients With Non-Hodgkin Lymphoma or Hodgkin Lymphoma Receiving Doxorubicin

ClinicalTrials.gov study NCT00577798. IPD Sharing: Not stated. Countries: 1. Publications: 4.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov36/100

Evaluate Carotid Artery Plaque Composition by Magnetic Resonance Imaging in People Receiving Cholesterol Medication

ClinicalTrials.gov study NCT00715273. IPD Sharing: NO. Countries: 1. Publications: 12.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov36/100

Low-field Magnetic Resonance Imaging of Pediatric COVID-19

ClinicalTrials.gov study NCT04990531. IPD Sharing: YES. Countries: 1. Publications: 8.

controlledIPD-YESFeb 2026View details →
ClinicalTrials.gov36/100

Functional Magnetic Resonance Imaging of Opioid Withdrawal in Healthy Human Volunteers

ClinicalTrials.gov study NCT01006707. IPD Sharing: NO. Countries: 1. Publications: 9.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov36/100

Dose Finding Study of Gadavist in Central Nervous System (CNS) Magnetic Resonance Imaging (MRI)

ClinicalTrials.gov study NCT00862459. IPD Sharing: Not stated. Countries: 4. Publications: 1.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov36/100

Therapeutic Magnetic Resonance Imaging (MRI)-Guided High Intensity Focused Ultrasound (HIFU) Ablation of Uterine Fibroids

ClinicalTrials.gov study NCT00897897. IPD Sharing: Not stated. Countries: 4. Publications: 8.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov36/100

Evaluation of Triple Therapy Using Magnetic Resonance Imaging in Asthma

ClinicalTrials.gov study NCT04651777. IPD Sharing: Not stated. Countries: 1. Publications: 13.

restrictedIPD-UNDECIDEDFeb 2026View details →
dryad32/100

Data from: Headache study: The management of chronic headache with referral from primary care to direct access to Magnetic Resonance Imaging (MRI) compared to Neurology services: an observational prospective study in London

<p><b>Objectives</b>. To evaluate the cost, accessibility and patient satisfaction implications of two clinical pathways used in the management of chronic headache.</p> <p><b>Intervention</b>. Management of chronic headache following referral from Primary Care that differed in the first appointment, either a Neurology appointment or an MRI brain scan.</p> <p><b>Design and setting</b>. A pragmatic, non-randomised, prospective, single-center study at a Central Hospital in London.</p> <p><b>Participants. </b>Adult patients with chronic headache referred from Primary to Secondary Care.</p> <p><b>Primary and secondary outcome measures.</b> Participants' use of health care services and costs were estimated using primary and secondary care databases and questionnaires quarterly up to 12 months post-recruitment. Cost analyses were compared using generalised linear models (GLM). Secondary outcomes assessed: access to care, patient satisfaction, headache burden and self-perceived quality of life using headache-specific (MIDAS, HIT-6) and a generic questionnaire (EQ-5D-5L).</p> <p><b>Results. </b>Mean (SD) cost up to 6 months post-recruitment per participant was £578 (£420) for the Neurology group (n=128) and £245 (£172) for the MRI group (n=95), leading to an estimated mean cost difference of £333 (95% CI £253 to £413, p&lt;0.001). The mean cost difference at 12 months increased to £518 (95% CI £401 to £637, p&lt;0.001). When adjusted for baseline and follow-up imbalances between groups, this remained statistically significant. The utilisation of brain MRI improved access to care compared to the Neurology group (p&lt;0.001). Participants in the Neurology group reported higher levels of satisfaction associated with the pathway and led to greater change in care management.</p> <p><b>Conclusion. </b>Direct referral to brain MRI from Primary Care led to cost-savings and quicker access to care but lower satisfaction levels when compared with referral to Neurology services. Further research into the use of brain MRI for a subset of patient population more likely to be reassured by a negative brain scan should be considered.</p>

opencc-zeroAug 2020View details →
dryad32/100

Data from: The demanding grey zone: sport indices by cardiac magnetic resonance imaging differentiate hypertrophic cardiomyopathy from athlete's heart

Background: We aimed to characterize gender specific left ventricular hypertrophy using a novel, accurate and less time demanding cardiac magnetic resonance (CMR) quantification method to differentiate physiological hypertrophy and hypertrophic cardiomyopathy based on a large population of highly trained athletes and hypertrophic cardiomyopathy patients. Methods and Results: Elite athletes (n=150,&gt;18 training hours/week), HCM patients (n=194) and athletes with hypertrophic cardiomyopathy (n=10) were examined by CMR. CMR based sport indices such as maximal end-diastolic wall thickness to left ventricular end-diastolic volume index ratio (EDWT/LVEDVi) and left ventricular mass to left ventricular end-diastolic volume ratio (LVM/LVEDV) were calculated, established using both conventional and threshold-based quantification method. Whereas 47.5% of male athletes, only 4.1% of female athletes were in the grey zone of hypertrophy (EDWT 13-16mm). EDWT/LVEDVi discriminated between physiological and pathological left ventricular hypertrophy with excellent diagnostic accuracy (AUCCQ:0.998, AUCTQ:0.999). Cut-off value for LVM/LVEDVCQ&lt;0.82 mm×m2/ml and for EDWT/LVEDViTQ&lt;1.27 discriminated between physiological and pathological left ventricular hypertrophy with a sensitivity of 77.8% and 89.2%, a specificity of 86.7% and 91.3%, respectively. LVM/LVEDV evaluated using threshold-based quantification performed significantly better than conventional quantification even in the male subgroup with EDWT between 13-16mm (p&lt;0.001). Conclusions: Almost 50% of male highly trained athletes can reach EDWT of 13 mm. CMR based sport indices provide an important tool to distinguish hypertrophic cardiomyopathy from athlete's heart, especially in highly trained athletes in the grey zone of hypertrophy.

opencc-zeroDec 2018View details →
dryad32/100

Magnetic resonance imaging reveals human brown adipose tissue is rapidly activated in response to cold

<p class="MsoNoSpacing"><b>Context.</b> In rodents, cold exposure induces the activation of brown adipose tissue (BAT) and the induction of intracellular triacylglycerol (TAG) lipolysis. However, in humans, the kinetics of supraclavicular (SCV) BAT activation and the potential importance of TAG stores remain poorly defined.</p> <p class="MsoNoSpacing"><b>Objective.</b> To determine the time course of BAT activation and changes in intracellular TAG using magnetic resonance imaging (MRI) assessment of the SCV (i.e. BAT depot) and fat in the posterior neck region (i.e. non BAT).</p> <p class="MsoNoSpacing"><b>Design.</b> Cross-sectional.</p> <p class="MsoNoSpacing"><b>Setting.</b> Clinical research centre.</p> <p class="MsoNoSpacing"><b>Patients or Other Participants.</b> Twelve healthy male volunteers ages 18-29 years [BMI=24.7±2.8kg/m<sup>2</sup> and body fat percentage = 25.0±7.4% (both mean±SD)].</p> <p class="MsoNoSpacing"><b>Intervention(s).</b> Standardized whole-body cold exposure (180 minutes at 18<span>°</span>C) and immediate re-warming (30 minutes at 32°C).</p> <p class="MsoNoSpacing"><b>Main Outcome Measure(s).</b> Proton density fat fraction (PDFF) and T2* of the SCV and posterior neck fat pads. Acquisitions occurred at 5-15 minute intervals during cooling and subsequent warming.</p> <p class="MsoNoSpacing"><b>Results.</b> SCV PDFF declined significantly after only 10 minutes of cold exposure [-1.6% (standard error (SE) 0.44%), <i>p</i>=0.007) and continued to decline until 35 minutes after which time it remained stable until 180 minutes. A similar time course was also observed for SCV T2*. In the posterior neck fat (non-BAT) there were no cold-induced changes in PDFF or T2*. Re-warming did not result in a change in SCV PDFF or T2*.</p> <p class="MsoNoSpacing"><b>Conclusions.</b> The rapid cold-induced decline in SCV PDFF suggests that in humans, BAT is activated quickly in response to cold and that TAG is a primary substrate.</p>

opencc-zeroOct 2019View details →
zenodo32/100

Dataset of synthetic, maturation-informed magnetic resonance images of the human fetal brain

<p>This dataset gathers synthetic-yet-highly-realistic T2-weighted magnetic resonance images (MRI) of the fetal brain based on the latest development of our prototype Fetal Brain magnetic resonance Acquisition Numerical phantom that now simulates local heterogeneities within white matter tissues throughout maturation (FaBiAN v2.0).<br>This dataset is associated with the following paper:</p> <p><strong>- Lajous H. et al. (2024) A dataset of synthetic, maturation-informed magnetic resonance images of the human fetal brain.</strong> Submitted to Nature Scientific Data, Pre-print available https://doi.org/10.1101/2024.04.08.588566</p> <p>We propose this unique, extensive fetal MRI dataset of simulated standard clinical fast spin echo sequences in both healthy and pathological neurodevelopmental trajectories to address data scarcity in this sensitive population, and therefore support the continuous endeavor of the community to develop advanced post-processing methods as well as cutting-edge artificial intelligence models. Automated brain tissue annotations of the two-dimensional, low-resolution series as well as super-resolution (SR) reconstructions of the fetal brain volumes are also included.</p> <p><strong>Work using any of these data should cite the following references:</strong></p> <ul> <li>Lajous, H. et al. A dataset of synthetic, maturation-informed magnetic resonance images of the human fetal brain. Submitted to Nature Scientific Data (2024), https://doi.org/10.1101/2024.04.08.588566</li> <li>Lajous, H. et al. Dataset of synthetic, maturation-informed magnetic resonance images of the human fetal brain. Zenodo (2024). 10.5281/zenodo.10940427</li> <li>Lajous, H., le Boeuf Fl&oacute;, A., Esteban, O. &amp; Bach Cuadra, M. Medical-Image-Analysis-Laboratory/FaBiAN: FaBiAN v2.0 (2.0). Zenodo (2023), 10.5281/zenodo.5471094</li> </ul> <p>This work was supported by the Swiss National Science Foundation through grant 182602, and by the ProTechno Foundation. We acknowledge access to the facilities and expertise of the CIBM Center for Biomedical Imaging, a Swiss research center of excellence founded and supported by Lausanne University Hospital (CHUV), University of Lausanne (UNIL), Ecole Polytechnique F&eacute;d&eacute;rale de Lausanne (EPFL), University of Geneva (UNIGE) and Geneva University Hospitals (HUG).</p> <p>Medical Image Analysis Laboratory - Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland &amp; CIBM Center for Biomedical Imaging. 2024.</p> <p>Note:&nbsp;<em>Terms of use for the original cohort (</em>Fidon, L., Aertsen, M., Emam, D., et al. Label-set Loss Functions for Partial Supervision: Application to Fetal Brain 3D MRI Parcellation. MICCAI, 2021<em>) are for research and education purposes only.</em></p>

opencc-by-4.0Apr 2024View details →
zenodo32/100

Spinal changes after 5-day dry immersion as shown by magnetic resonance imaging (DI-5-CUFFS)

<p>Supplemental data</p>

opencc-by-4.0Mar 2022View details →
zenodo32/100

Radiomics and Machine Learning Analysis Based on Magnetic Resonance Imaging in the Assessment of Colorectal Liver Metastases Growth Pattern

<p>I upload&nbsp;the images of the manuscript &quot;Radiomics and Machine Learning Analysis Based on Magnetic Resonance Imaging in the Assessment of Colorectal Liver Metastases Growth Pattern&quot;.</p>

opencc-by-4.0Apr 2022View details →
zenodo32/100

Radiomics and machine learning analysis based on magnetic resonance imaging in the assessment of liver mucinous colorectal metastases

<p>I uploaded the images of the manuscript&nbsp;Radiomics and machine learning analysis based on magnetic resonance imaging in the assessment of liver mucinous colorectal metastases.</p>

opencc-by-4.0May 2022View details →
zenodo32/100

Risk Assessment and Radiomics Analysis in Magnetic Resonance Imaging of Pancreatic Intraductal Papillary Mucinous Neoplasms (IPMN)

<p>I uploaded the original images of the manuscript "Risk Assessment and Radiomics Analysis in Magnetic Resonance Imaging of Pancreatic Intraductal Papillary Mucinous Neoplasms (IPMN)" accepted for pubblication on Cancer Control.</p>

opencc-by-4.0Jun 2024View details →
zenodo32/100

Fig. 2. A in Microstructural Impact of Ischemia and Bone Marrow-Derived Cell Therapy Revealed With Diffusion Tensor Magnetic Resonance Imaging Tractography of the Heart In Vivo

Fig. 2. A picture of four male - female pairs of Amblyomma variegatum attached on a cow examined during this survey. © Anne Laudisoit.

opennotspecifiedDec 2014View details →
zenodo32/100

Fig. 1 in Microstructural Impact of Ischemia and Bone Marrow-Derived Cell Therapy Revealed With Diffusion Tensor Magnetic Resonance Imaging Tractography of the Heart In Vivo

Fig. 1. Map of Kisangani and Major transhumance routes from probable departure location to Kisangani city, DR Congo.

opennotspecifiedDec 2014View details →
zenodo32/100

A comprehensive dataset of magnetic resonance enterography images with bowel segment annotations

<p>Inflammatory bowel disease (IBD) is a recurrent bowel disease that usually requires magnetic resonance enterography (MRE) for diagnosis and monitoring. However, recognition of bowel segments from MRE images by a radiologist is challenging and time-consuming. Deep learning-based medical image segmentation has shown the potential to reduce manual effort and provide automated tools to assist in disease management; however, it requires a large-scale fine<span>-</span>annotated dataset for training. To address this gap, we collected MRE data, including HASTE(half-Fourier acquisition single-shot turbo spin-echo) sequences with coronal orientation, from 114 patients&nbsp;with IBD. The bowel images per patient were contoured and annotated into ten segments (stomach, duodenum, small intestine, appendix, cecum, ascending colon, transverse colon, descending colon, sigmoid colon, and rectum), with fine pixel-level annotations labeled by experienced radiologists. Furthermore, we <span>validated</span> the efficiency of several state-of-the-art segmentation methods&nbsp;using this dataset. This study established a high-quality, publicly available whole-bowel segment MR dataset with benchmark results and laid the groundwork for AI research&nbsp;on IBD.</p>

opencc-by-4.0Sep 2024View details →
zenodo32/100

Magnetic resonance imaging in the assessment of pancreatic cancer with quantitative parameter extraction by means of dynamic contrast-enhanced magnetic resonance imaging, diffusion kurtosis imaging and intravoxel incoherent motion diffusion-weighted imaging

<p>We uploaded&nbsp;IVIM and DKI parameters values of&nbsp;included patients in the manuscript:&nbsp;Fusco, Roberta, Adele Piccirillo, Mario Sansone, Vincenza Granata, Paolo Vallone, Maria L. Barretta, Teresa Petrosino, Claudio Siani, Raimondo Di Giacomo, Maurizio Di Bonito, Gerardo Botti, and Antonella Petrillo. 2021. &quot;Radiomic and Artificial Intelligence Analysis with Textural Metrics, Morphological and Dynamic Perfusion Features Extracted by Dynamic Contrast-Enhanced Magnetic Resonance Imaging in the Classification of Breast Lesions&quot; Applied Sciences 11, no. 4: 1880. https://doi.org/10.3390/app11041880</p>

opencc-by-4.0May 2020View details →

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Allen Brain Atlas

Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

Annotated Behaviour and Observability Dataset (ABODe)

ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

DANDI Archive for NWB datasets

DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

OpenNeuro

OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record