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ShareScore release 0.9.0
Dataset results
22 results for “molecular MRI”
Data supporting: "Interaction of MRI Contrast Agent [Gd(DOTA)]− with Lipid Membranes: A Molecular Dynamics Study"
Open the record for dataset details and reuse information.
Data for "Investigating molecular transport in the human brain from MRI with physics-informed neural networks"
<p>Data analyzed in Zapf <em>et al.</em> <a href="https://www.nature.com/articles/s41598-022-19157-w">Investigating molecular transport in the human brain from MRI with physics-informed neural networks</a> (Scientific Reports 2022).</p> <p>The data consists of CSF tracer concentrations in the brain subregions analyzed in the article. The data was pre-processed as described in S1.1 in the supplementarty materials. </p> <p>In Python, load the data as numpy arrays using the nibabel package as</p> <pre><code>import nibabel data = nibabel.load("068/concentrations/24h.mgz").get_fdata() domain_mask = nibabel.load("068/masks/roi.mgz").get_fdata().astype(bool)<br>And view slices of the data as:</code></pre> <div> <div><span>plt</span><span>.</span><span>figure</span><span>()</span></div> <div><span>plt</span><span>.</span><span>imshow</span><span>(</span><span>np</span><span>.take(</span><span>data</span><span>, </span><span>150</span><span>, </span><span>0</span><span>), </span><span>vmax</span><span>=</span><span>0.1</span><span>)</span></div> <div><span>plt</span><span>.</span><span>figure</span><span>()</span></div> <div><span>plt</span><span>.</span><span>imshow</span><span>(</span><span>np</span><span>.take(</span><span>data</span><span>, </span><span>100</span><span>, </span><span>1</span><span>), </span><span>vmax</span><span>=</span><span>0.1</span><span>)</span></div> <div><span>plt</span><span>.</span><span>figure</span><span>()</span></div> <div><span>plt</span><span>.</span><span>imshow</span><span>(</span><span>np</span><span>.take(</span><span>data</span><span>, </span><span>100</span><span>, </span><span>2</span><span>), </span><span>vmax</span><span>=</span><span>0.1</span><span>)</span></div> <div><span>plt</span><span>.</span><span>show</span><span>()</span></div> </div> <pre> </pre>
Breast MRI molecular cancer subtype
<p>This data set is part of the public development data for the <a href="http://auc23.grand-challenge.org/">2023 Automated Universal Classification Challenge</a> (AUC23). The data set concerns the classification of breast cancer molecular subtypes on dynamic contrast-enhanced magnetic resonance imaging (MRI) and was derived from <a href="https://sites.duke.edu/mazurowski/resources/breast-cancer-mri-dataset/">Duke Hospital</a>. The data set is a subset of the data originally introduced and described by <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6134102/">Saha et al. (2018)</a>, with no additional images or patient information. Data was restructured in compliance with the <a href="https://auc23.grand-challenge.org/">AUC23</a> challenge format. The dataset is a single-institutional, retrospective collection of 737 biopsy-confirmed patients from 1 January 2000 to 23 March 2014 with invasive breast cancer and available pre-operative MRI at Duke Hospital.</p> <p>Images are 3D tensors:</p> <ul> <li>0: 3D T1-subtraction dynamic contrast-enhanced MRI</li> </ul> <p>Classification labels:</p> <ul> <li>0: Luminal A, estrogen-receptor (ER) and/or progesterone-receptor (PR) positive<strong>,</strong> human epidermal growth factor receptor 2 (HER2) negative</li> <li>1: Luminal B, ER and/or PR negative, HER2 positive</li> <li>2: HER2, ER and PR negative, HER2 positive</li> <li>3: Triple negative, ER, PR, and HER2 negative</li> </ul> <p>Folder structure:</p> <p>imagesTr (root folder with all patients and studies)<br> ├── Breast_MRI_0001_0000.mha (3D T1-subtraction MRI imaging for study 0001)<br> ├── Breast_MRI_0003_0000.mha (3D T1-subtraction MRI imaging for study 0003)<br> ├── ...</p> <p>Please cite the following article if you are using the <a href="https://wiki.cancerimagingarchive.net/pages/viewpage.action?pageId=70226903">Duke-Breast-Cancer-MRI Dataset</a>:</p> <pre><code>A. Saha, M. R. Harowicz, L. J. Grimm, C. E. Kim, S. V. Ghate, R. Walsh, M. A. Mazurowski, "A machine learning approach to radiogenomics of breast cancer: a study of 922 subjects and 529 DCE-MRI features". Br J Cancer. 2018 Aug;119(4):508-516. doi: 10.1038/s41416-018-0185-8. Epub 2018 Jul 23. PMID: 30033447; PMCID: PMC6134102. </code></pre>
Characterising Metastatic Penile Cancer Using Molecular Imaging - Hybrid MRI-PET [MRI-PET]
ClinicalTrials.gov study NCT02104063. IPD Sharing: Not stated. Countries: 1. Publications: 16.
Comparison of MRI With PET / CT in the Evaluation of Response to Neoadjuvant Therapy Based on the Molecular Subtypes of Breast Cancer
ClinicalTrials.gov study NCT04882371. IPD Sharing: NO. Countries: 1. Publications: 27.
MRI Radiomics Combined With Pathomics on the Prediction of Molecular Classification and Prognosis of Endometrial Cancer
ClinicalTrials.gov study NCT06126393. IPD Sharing: NO. Countries: 1. Publications: 6.
Investigation of Vascular Inflammation in Migraine Using Molecular Nano-imaging and Black Blood Imaging MRI
ClinicalTrials.gov study NCT02549898. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Comparison of MRI and Molecular Breast Imaging in Breast Diagnostic Evaluation
ClinicalTrials.gov study NCT00591864. IPD Sharing: Not stated. Countries: 1. Publications: 0.
MRI-localized biopsies reveal subtype-specific differences in molecular and cellular composition at the margins of glioblastoma
GEO Series GSE59612. Homo sapiens. 92 samples. Type: Expression profiling by high throughput sequencing.
Radiogenomics of glioblastoma: Machine-learning based classification of molecular characteristics using multiparametric and multiregional MRI features
GEO Series GSE85539. Homo sapiens. 152 samples. Type: Methylation profiling by array.
Quantifying Oxygen Utilization of Tumors Using Oxygen-Enhanced Molecular MRI
ClinicalTrials.gov study NCT04460495. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Evaluation of Magnetic Resonance Imaging (MRI) vs Molecular Breast Imaging (Tc-MBI) in Breast Cancer Patients
ClinicalTrials.gov study NCT02024074. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Comparative Performance of Molecular Breast Imaging (MBI) to Magnetic Resonance Imaging (MRI) of the Breast in Identifying and Excluding Breast Carcinoma in Women at High Risk for Breast Cancer
ClinicalTrials.gov study NCT05042687. IPD Sharing: NO. Countries: 1. Publications: 0.
Evaluation of the Correlation Between Molecular Phenotype and Radiological Signature (by PET-scanner and MRI) of Incident WHO II and III Grade Gliomas.
ClinicalTrials.gov study NCT04461002. IPD Sharing: NO. Countries: 1. Publications: 0.
Molecular MRI of the Fibrotic Heart
ClinicalTrials.gov study NCT02012725. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Mapping Molecular Markers of Brain Tumour Activity Using MRI
ClinicalTrials.gov study NCT05140785. IPD Sharing: NO. Countries: 1. Publications: 0.
MRI Functional Imaging Characteristics and Fat Quantification of CT-fat-free Renal Neoplasms: Relationships With Histological Classifications and Molecular Markers
ClinicalTrials.gov study NCT06126159. IPD Sharing: NO. Countries: 1. Publications: 0.
Molecular, Pathologic and MRI Investigation of the Prognostic and Redictive Importance of Extramural Venous Invasion in Rectal Cancer (MARVEL) Trial
ClinicalTrials.gov study NCT01995942. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Prospective Evaluation of Mp-MRI, MR-guided Biopsy, and Molecular Markers for Active Surveillance of Prostate Cancer
ClinicalTrials.gov study NCT03979573. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
FKBP51s: a New Molecular Biomarker for Glioblastoma? Pre- and Post-operative Blood Levels Evaluation of FKBP51s Protein and Correlation With MRI Phenotype
ClinicalTrials.gov study NCT05793021. IPD Sharing: Not stated. Countries: 1. Publications: 0.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.
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.
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.
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.