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7
datasets available to search
ShareScore release 0.9.0
Dataset results
7 results for “structural magnetic resonance imaging”
Effects of Tofacitinib (CP-690,550) on Magnetic Resonance Imaging (MRI)- Assessed Joint Structure In Early Rheumatoid Arthritis (RA)
ClinicalTrials.gov study NCT01164579. IPD Sharing: Not stated. Countries: 9. Publications: 14.
Osteoarthritis Structural Changes Assessed by Magnetic Resonance Imaging and Neuropathic Pain in Knee Osteoarthritis
ClinicalTrials.gov study NCT01733277. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Magnetic Resonance Imaging Development for High Resolution Atrial Structural and Functional Characterization
ClinicalTrials.gov study NCT06617624. IPD Sharing: YES. Countries: 0. Publications: 0.
Depression in Adolescents. A Cerebral Structural, Diffusion, and Functional Magnetic Resonance Imaging Study
ClinicalTrials.gov study NCT01857518. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Evaluation of Blood Brain Barrier Integrity and Structural Abnormalities in MPS IIIB Patients Using Multimodal Magnetic Resonance Imaging
ClinicalTrials.gov study NCT02090179. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Data set and 3d model from Emendi M, Sturla F, Ghosh RP, Bianchi M, Piatti F, Pluchinotta FR, Giese D, Lombardi M, Redaelli A, Bluestein D. Patient-Specific Bicuspid Aortic Valve Biomechanics: A Magnetic Resonance Imaging Integrated Fluid-Structure Interaction Approach. Ann Biomed Eng. 2020 Aug 17. doi: 10.1007/s10439-020-02571-4. Epub ahead of print. PMID: 32804291.
<p>Data set and 3d model from Emendi M, Sturla F, Ghosh RP, Bianchi M, Piatti F, Pluchinotta FR, Giese D, Lombardi M, Redaelli A, Bluestein D. Patient-Specific Bicuspid Aortic Valve Biomechanics: A Magnetic Resonance Imaging Integrated Fluid-Structure Interaction Approach. Ann Biomed Eng. 2020 Aug 17. doi: 10.1007/s10439-020-02571-4. Epub ahead of print. PMID: 32804291.</p> <p> </p> <p>This is the abstract:</p> <p>Congenital bicuspid aortic valve (BAV) consists of two fused cusps and represents a major risk factor for calcific valvular stenosis. Herein, a fully coupled fluid-structure interaction (FSI) BAV model was developed from patient-specific magnetic resonance imaging (MRI) and compared against in vivo 4-dimensional flow MRI (4D Flow). FSI simulation compared well with 4D Flow, confirming direction and magnitude of the flow jet impinging onto the aortic wall as well as location and extension of secondary flows and vortices developing at systole: the systolic flow jet originating from an elliptical 1.6 cm<sup>2</sup> orifice reached a peak velocity of 252.2 cm/s, 0.6% lower than 4D Flow, progressively impinging on the ascending aorta convexity. The FSI model predicted a peak flow rate of 22.4 L/min, 6.7% higher than 4D Flow, and provided BAV leaflets mechanical and flow-induced shear stresses, not directly attainable from MRI. At systole, the ventricular side of the non-fused leaflet revealed the highest wall shear stress (WSS) average magnitude, up to 14.6 Pa along the free margin, with WSS progressively decreasing towards the belly. During diastole, the aortic side of the fused leaflet exhibited the highest diastolic maximum principal stress, up to 322 kPa within the attachment region. Systematic comparison with ground-truth non-invasive MRI can improve the computational model ability to reproduce native BAV hemodynamics and biomechanical response more realistically, and shed light on their role in BAV patients' risk for developing complications; this approach may further contribute to the validation of advanced FSI simulations designed to assess BAV biomechanics.</p> <p> </p>
Dataset related to article "Automated Head Tissue Modelling Based on Structural Magnetic Resonance Images for Electroencephalographic Source Reconstruction"
<p><strong>SCORING SEGMENTATIONS</strong></p> <ul> <li>Qualitative segmentation scores by two raters (rater1; rater2).</li> <li>Scale: excellent (4); good (3); doubtful (2) and failed (1).</li> </ul> <p> </p> <p><strong>DATABASES</strong></p> <ul> <li>IXI database, Imperial College of London (<a href="https://brain-development.org/ixi-dataset/">https://brain-development.org/ixi-dataset/</a>)</li> <li>Autism Brain Imaging Data Exchange (ABIDE) database (<a href="http://fcon_1000.projects.nitrc.org">http://fcon_1000.projects.nitrc.org</a>)</li> <li>SchizConnect database (<a href="http://schizconnect.org">http://schizconnect.org</a>)</li> </ul> <p> </p> <p><strong>SEGMENTATION METHODS</strong></p> <ul> <li>MR-TIM (Taberna et al., 2021), green rows</li> <li>WTS (Liu et al., 2017), red rows</li> </ul> <p> </p> <p><strong>TABLES</strong></p> <p><strong>IXI_young </strong></p> <ul> <li>20 MRI from the IXI database, participants 20–35 years old;</li> <li>MR scanners: Philips Intera 3.0T (HH); Philips Gyroscan Intera 1.5T (G)</li> </ul> <p><strong>IXI_older</strong></p> <ul> <li>20 MRI from the IXI database, participants 60–75 years old;</li> <li>MR scanners: Philips Intera 3.0T (HH); Philips Gyroscan Intera 1.5T (G)</li> </ul> <p><strong>ABIDE</strong></p> <ul> <li>10 MRI from the ABIDE database, participants 18-25 years old;</li> <li>MR scanner: Philips Achieva 3.0T</li> </ul> <p><strong>SchizConnect</strong></p> <ul> <li>10 MRI from the SchizConnect database, participants 19-66 years old;</li> <li>MR scanner: Siemens Trio Tim 3.0T</li> </ul> <p> </p> <p><strong>REFERENCES</strong></p> <p>Liu, Q., Farahibozorg, S., Porcaro, C., Wenderoth, N., & Mantini, D. (2017). Detecting large-scale networks in the human brain using high-density electroencephalography. Hum Brain Mapp, 38(9), 4631-4643. doi:10.1002/hbm.23688</p> <p>Taberna, G. A., Samogin, J., & Mantini, D. (2021). Automated Head Tissue Modelling Based on Structural Magnetic Resonance Images for Electroencephalographic Source Reconstruction. Neuroinformatics. doi:10.1007/s12021-020-09504-5</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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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.
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.