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B-MODE-AND-CEUS-LIVER

B-mode-and-CEUS-Liver | Ultrasound data of a variety of liver masses

DOI: 10.7937/TCIA.2021.v4z7-tc39 | Data Citation Required | Image Collection

Location Species Subjects Data Types Cancer Types Size Supporting Data Status Updated
Liver Human 120 US Liver Cancer 272.16GB Clinical Public, Complete 2022/02/18

Summary

Data were generated as part of two ongoing clinical trials investigating the use of contrast-enhanced ultrasound to a) characterize indeterminate liver lesions and b) monitor treatment response to loco regional therapy. Ultrasound data was obtained on a variety of state of the art ultrasound scanners with curvilinear probes. Gain, dynamic range, focus position and depth were optimized for image quality by the performing sonographer. Images of the mass in both sagittal and transverse planes were obtained and saved in DICOM format. Full cine-loops of the contrast enhanced ultrasound are also saved in DICOM format. The reference standard used for lesion characterization included tissue pathology and contrast-enhanced cross-sectional imaging within 1 month of the ultrasound exam. The initial treatment response to transarterial chemoembolization is also available for many hepatocellular carcinoma (HCC) cases and uses pathology, retreatment angiography, or longer-term tumor response on cross-sectional imaging as a reference standard.

We expect these images can be used in a wide variety of image processing application. We are currently exploring a variety of automated intelligence algorithms for AI-based lesion characterization. Algorithms for object detection and segmentation may also be of interest. As the studies that have generated this data are also ongoing, it is expected that we can add volumetric data, contrast-enhanced ultrasound cine loops, and longer-term treatment response data to this data set in the future.

Data Access

Version 2: Updated 2022/02/18

Added 45 new participants and a new spreadsheet version.

Title Data Type Format Access Points Subjects Studies Series Images License
Images US DICOM
Download requires NBIA Data Retriever
 120 120 120 1,859 CC BY 4.0
Clinical data XLSX CC BY 4.0

Additional Resources for this Dataset

The NCI Cancer Research Data Commons (CRDC) provides access to additional data and a cloud-based data science infrastructure that connects data sets with analytics tools to allow users to share, integrate, analyze, and visualize cancer research data.

  • Imaging Data Commons (IDC) (Imaging Data)

    • Citations & Data Usage Policy

    Data Citation Required: Users must abide by the TCIA Data Usage Policy and Restrictions. Attribution must include the following citation, including the Digital Object Identifier:

    Data Citation

    Eisenbrey, J., Lyshchik, A., & Wessner, C. (2021). Ultrasound data of a variety of liver masses [Data set]. The Cancer Imaging Archive.  DOI: https://doi.org/10.7937/TCIA.2021.v4z7-tc39

    Acknowledgements

    We would like to acknowledge the individuals and institutions that have provided data for this collection:

    • Thomas Jefferson University, Philadelphia, PA, USA - Special thanks to John Eisenbrey, PhD from the Department of Radiology, Andrej Lyshchik, MD, PhD from the Department of Radiology, Corinne Wessner, MBA from the Department of Radiology

    • This work was supported in whole or in part under R01 CA194307 ; R01 CA215520 .

    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.

    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. In Journal of Digital Imaging (Vol. 26, Issue 6, pp. 1045–1057). Springer Science and Business Media LLC. https://doi.org/10.1007/s10278-013-9622-7

    Previous Versions

    Version 1: Updated 2021/08/04

    7/28/21 Added new participants.
    8/4/21 Added spreadsheet.

    Title Data Type Format Access Points Studies Series Images License
    Images DICOM
    Clinical data XLSX