Summary
As of 6/15/21:The collection of cases was acquired at Stony Brook University from patients who tested positive for COVID-19. The collection includes images from different modalities and organ sites (chest radiographs, chest CTs, brain MRIs, etc). Radiology imaging data is extremely important in COVID-19 from both a diagnostic and a monitoring perspective, given the crucial nature of COVID-19 pulmonary disease and its rapid phenotypic changes.
The datasets are available for non-commercial use by research communities for building AI systems for diagnostic and prognostic modeling. (KG & JK, should this be part of the Summary or is covered in the Licensing Agreement on the Citation Tab?)
Data collection was enabled by the Renaissance School of Medicine at Stony Brook University’s “COVID-19 Data Commons and Analytic Environment”, a data quality initiative instituted by the Office of the Dean, and supported by the Department of Biomedical Informatics. (KG & JK, this seems more like an Acknowledgement. What do you think? We can check with the site.)
Original Summary:
We have curated clinical and imaging data for covid19-positive patients admitted to the SBU hospital. The dataset consists of de-identified Radiology imaging data along with linked clinical data for each patient. The clinical data consists of diagnoses, procedures, lab tests, covid19 specific data values (e.g., intubation status, symptoms at admission) and a set of derived data elements, which were used in analyses of this data. The clinical data is stored as a set of csv files which comply with OMOP Common Data Model data elements.
Additional questions site was asked to address:
Please address the following items in your revision:
- Add something similar to: "this collection of cases represents the entire Stony Brook COVID 19 experience over a period of several months there are quite a number of scanners with a number of DICOM tags relating to settings."
- Update the abstract summarizing what body parts were imaged with each modality. E.g. "COVID 19 impacts many organ sites. This dataset includes all imaging studies carried out on the patient population during their hospitalization including CT's of the lung, MRI's of the brain, ..."
- Update the abstract with a sentence along the lines of "This collection provides all scans carried out during the hospitalization of each Covid 19 positive patient admitted during the targeted time period, giving researchers a valuable opportunity to study disease progression."
Acknowledgements
We would like to acknowledge the individuals and institutions that have provided data for this collection:
Hospital/Institution Name city, state, country - Special thanks to First Last Names, degree PhD, MD, etc from the Department of xxxxxx, Additional Names from same location.
- Continue with any names from additional submitting sites if collection consists of more that one.
Data Access
Data Type | Download all or Query/Filter |
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Images (DICOM, XX.X GB) | (Download requires the NBIA Data Retriever) |
Clinical data (CSV) | |
Other (format) |
Click the Versions tab for more info about data releases.
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Detailed Description
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<< Add any additional information as needed below. Likely would be something from site. >>
Citations & Data Usage Policy
Data Citation
DOI goes here. Create using Datacite with information from Collection Approval form
Publication Citation
We ask on the proposal form if they have ONE traditional publication they'd like users to cite.
Acknowledgement
Only if they ask for special acknowledgments like funding sources, grant numbers, etc in their proposal.
TCIA Citation
Clark K, Vendt B, Smith K, Freymann J, Kirby J, Koppel P, Moore S, Phillips S, Maffitt D, Pringle M, Tarbox L, Prior F. The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository, Journal of Digital Imaging, Volume 26, Number 6, December, 2013, pp 1045-1057. DOI: 10.1007/s10278-013-9622-7
Other Publications Using This Data
TCIA maintains a list of publications which leverage TCIA data. If you have a manuscript you'd like to add please contact the TCIA Helpdesk.
Version X (Current): Updated yyyy/mm/dd
Data Type | Download all or Query/Filter |
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Images (DICOM, xx.x GB) | (Requires NBIA Data Retriever.) |
Clinical Data (CSV) | Link |
Other (format) |
<< One or two sentences about what you changed since last version. No note required for version 1. >>