Localtab |
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active | true |
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title | Data Access |
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| Data AccessClick the Download button to save to your local storage. Click the Search button to open our Data Portal, where you can browse the data collection and/or download a subset of its contents.
Data Type | Download all or Query/Filter |
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Images (DICOM, XX.X GB) | Tcia button generator |
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label | Search |
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url | https://nbia.cancerimagingarchive.net/nbia-search/?CollectionCriteria=Duke-Breast-Cancer-MRI |
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(Requires NBIA Data Retriever .) | Clinical and Other Features (XLSX, 582 kB) | | Annotation Boxes (XLSX, 49 kB) | | Imaging features (XLSX, 6.44 MB) | |
Click the Versions tab for more info about data releases. |
Localtab |
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title | Detailed Description |
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| Detailed Description
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Modalities | MR | Number of Participants | 922 | Number of Studies | 922 | Number of Series | 5,304 | Number of Images | 773,126 | Images Size (GB) | 351.3 | Users please note this caveat about DICOM tag (0020,0052) Frame Of Reference UID: This DICOM tag was lost during deidentification and curation, and has been replaced with a Dummy value per study that may not be reliable for image alignment. |
Localtab |
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title | Citations & Data Usage Policy |
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| Citations & Data Usage PolicyAdd any special restrictions in here. Tcia license 4 noncommercial |
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Info |
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| Saha, A., Harowicz, M. R., Grimm, L. J., Weng, J., Cain, E. H., Kim, C. E., Ghate, S. V., Walsh, R., & Mazurowski, M. A. (2020) Dynamic contrast-enhanced magnetic resonance images of breast cancer patients with tumor locations [Dataset]. The Cancer Imaging Archive. https://doi.org/ < Dataset DOI coming soon> (no other authors seem to have an ORCiD) Saha https://orcid.org/0000-0002-7650-1720 (Abstract for DOI) Breast MRI is a common image modality to assess extent of disease in breast cancer patients. Recent studies show that MRI has a potential in prognosis of patient sort and long term outcomes as well as predicting pathological and genomic features of the tumors. However, large, well annotated datasets are needed to make further progress in the field. We share such a dataset here. In this dataset, we share MRI imaging and other data for 922 patients with invasive breast cancer. Their prone position axial breast MRI images were acquired by 1.5T or 3T scanners. Following MRI sequences are shared: a non-fat saturated T1-weighted sequence, a fat-saturated gradient echo T1-weighted pre-contrast sequence, and mostly three to four post-contrast sequences. The images are associated with a variety of metadata. Specifically, we are sharing: Demographic, clinical, pathology, treatment, outcomes, and genomic data. This data has been collected from a variety of sources including clinical notes and has served as a source for multiple published papers on radiogenomics, outcomes prediction, and other.529 imaging features which represent a variety of imaging characteristics including size, shape, texture, and enhancement of both the tumor and the surrounding tissue, which is combined of features commonly published in the literature, as well as the features developed in our lab. These features were used in our previous paper (https://doi.org/10. 10167937/ j.eswa.2017.06.029)Annotation boxes provided by radiologists that indicate locations of the lesions in the images.TCIA.e3sv-re93 |
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| Saha, A., Harowicz, M. R., Grimm, L. J., Kim, C. E., Ghate, S. V., Walsh, R., & Mazurowski, M. A. (2018). A machine learning approach to radiogenomics of breast cancer: a study of 922 subjects and 529 DCE-MRI features. British journal of cancer, 119(4), 508-516. DOI: https://doi.org/10.1038/s41416-018-0185-8
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| 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: https://doi.org/10.1007/s10278-013-9622-7 |
Other Publications Using This DataTCIA maintains a list of publications which leverage TCIA data. If you have a manuscript you'd like to add please contact the TCIA Helpdesk. |
Localtab |
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| Version 1 (Current): Updated 2020/12/03
Data Type | Download all or Query/Filter |
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Images (DICOM, xx.x GB) | Tcia button generator |
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label | Search |
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url | https://nbia.cancerimagingarchive.net/nbia-search/?CollectionCriteria=Duke-Breast-Cancer-MRI |
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(Requires NBIA Data Retriever .) | Clinical and Other Features (XLSX, 582 kB) | | Annotation Boxes (XLSX, 49 kB) | | Imaging features (XLSX, 6.44 MB) | |
Added new subjects. |
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