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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 TypeDownload all or Query/Filter

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


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

Users of this data must abide by the TCIA Data Usage Policy and the Creative Commons Attribution-NonCommercial 4.0 International License under which it has been published. Attribution should include references to the following citations:

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. 

Ahmed W. Moawad, MD

David Fuentes, PhD   

Ali Morshid, MD

Ahmed M. Khalaf

Mohab M. Elmohr

Abdelrahman abusaif, MD

John D. Hazle, PhD

Ahmed O. Kaseb, MD

Manal Hassan, MD

Armeen Mahvash, MD

Janio Szklaruk, MD

Aliyya Qayyom, MD

Khaled M. Elsayes, MD

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 TypeDownload all or Query/Filter
Images (DICOM, xx.x GB)

   

(Requires NBIA Data Retriever.)

Clinical Data (CSV)Link
Software/Source Code (web)

 

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