Summary
This dataset was retrospectively acquired from University of Texas - MD Anderson cancer center, after its IRB approval. It contains patients treated at MD Anderson with hepatocellular carcinoma from November 2002 to June 2012. The inclusion criteria were TACE as the sole first-line or initial bridging therapy and availability of multiphasic contrast material–enhanced CT images obtained at baseline with no image artifacts (eg, surgical clips). On average, baseline CT was performed 3 weeks before the first session of TACE (range, 1–12 weeks).Segmentation (liver, tumor, vessels) were created with semiautomated software in NIfTI and converted to DICOM SEG format.
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.
Harmonization of the components of this dataset, including into standard DICOM representation, was supported in part by the NCI Imaging Data Commons consortium. NCI Imaging Data Commons consortium is supported by the contract number 19X037Q from Leidos Biomedical Research under Task Order HHSN26100071 from NCI.
Data Access
Data Type | Download all or Query/Filter |
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Images and Segmentations (DICOM, XX.X GB) | (Download requires the NBIA Data Retriever) |
Clinical data with description (XLSX) | |
Software/Source Code (External weblink to github) |
Click the Versions tab for more info about data releases.
Please contact help@cancerimagingarchive.net with any questions regarding usage.
Detailed Description
Image Statistics | |
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Modalities | CT, SEG |
Number of Patients | 105 |
Number of Studies | 214 |
Number of Series | 677 |
Number of Images | 51,968 |
Images Size (GB) | 26.6 |
These SEG were originally created as NIfTI format files (Amira Software, ThermoFisher 2019) , and converted to DICOM.
Github link for the NN code: https://github.com/fuentesdt/livermask
Note - the mask on Patient ID HCC_001 (SEG file Series UID 1.2.276.0.7230010.3.1.3.8323329.719.1600928570.399942) has a slightly different dimension than the CT (Series UI 1.3.6.1.4.1.14519.5.2.1.1706.8374.302065206690360709343725942120) . This difference is is far from the interesting features and the masks, so clinical interpretation should be unaffected by this discrepancy.
Citations & Data Usage Policy
Data Citation
DOI goes here. Create using Datacite with information from Collection Approval form
Moawad A, Fuentes D, Elsayes K. Multimodality annotated HCC cases with and without advanced imaging segmentation.
Publication Citation
Morshid, A., Elsayes, K. M., Khalaf, A. M., Elmohr, M. M., Yu, J., Kaseb, A. O., Hassan, M., Mahvash, A., Wang, Z., Hazle, J. D., & Fuentes, D. (2019). A Machine Learning Model to Predict Hepatocellular Carcinoma Response to Transcatheter Arterial Chemoembolization. Radiology: Artificial Intelligence, 1(5), e180021. https://doi.org/10.1148/ryai.2019180021
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. (2013). The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository. Journal of Digital Imaging, 26(6), 1045–1057. https://doi.org/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 |
Software/Source Code (web) |
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