Skip to main content

VICTRE

The Cancer Imaging Archive

VICTRE | The VICTRE Trial: Open-Source, In-Silico Clinical Trial For Evaluating Digital Breast Tomosynthesis

DOI: 10.7937/TCIA.2019.ho23nxaw | Data Citation Required | Image Collection

Location Species Subjects Data Types Cancer Types Size Supporting Data Status Updated
Breast Human 2,994 MG Breast Cancer 1.03TB Software/Source Code Public, Complete 2019/03/08

Summary

Expensive and lengthy clinical trials delay regulatory evaluation of innovative medical technologies affecting patient access to high-quality medical products. Sophisticated simulation tools are increasingly being used in device development, but are rarely used in regulatory applications. We investigate a new paradigm for evaluating digital breast tomosynthesis (DBT) as a replacement for digital mammography (DM), using exclusively in-silico methods.

A total of 2986 subjects, with breast sizes and radiographic densities representative of a screening population and compressed thicknesses from 3.5 to 6 cm, were simulated and imaged on in-silico versions of DM and DBT systems using fast Monte Carlo x-ray transport. Images were interpreted by a computational reader detecting the presence of lesions. The in-silico trial (VICTRE) was designed to replicate a comparative trial from a previous regulatory submission. The endpoint was the difference in area under the receiver-operating-characteristic curve between modalities (delta-AUC) for lesion detection. Using a fully-crossed design, VICTRE was sized for a standard error (SE) of 0.01 in delta-AUC, half the uncertainty seen in the comparative trial. A 1-hour summary presentation of the project and findings was given at the FDA Grand Rounds on 3/14/2019 and can be found here.

A systematic exploration of the trial parameters including lesion types and sizes is also possible and greatly facilitated by the availability of open-source, free software tools available at https://github.com/DIDSR/VICTRE.

Data Access

Version 1: Updated

Title Data Type Format Access Points Subjects Studies Series Images License
Images MG DICOM
Download requires NBIA Data Retriever
2,994 8,749 8,749 217,913 CC BY 3.0

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.

The following external resources have been made available by the data submitters.  These are not hosted or supported by TCIA, but may be useful to the researchers utilizing this collection:

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

Badano A, Graff CG, Badal A, Sharma D, Zeng R, Samuelson FW, Glick S, Myers KJ. The VICTRE Trial: Open-Source, In-Silico Clinical Trial for Evaluating Digital Breast Tomosynthesis. 2018. DOI:  10.7937/TCIA.2019.ho23nxaw .

Other Publications Using this Data

TCIA maintains a list of publications which leverage our data. If you have a  publication  you’d like to add please  contact the TCIA Helpdesk .

Publication Citation

Badano A, Graff CG, Badal A, Sharma D , Zeng R, Samuelson FW, Glick SJ, Myers KJ. Evaluation of Digital Breast Tomosynthesis as Replacement of Full-Field Digital Mammography Using an In Silico Imaging Trial. JAMA Netw Open. 2018;1(7):e185474. DOI: 10.1001/jamanetworkopen.2018.5474.

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