The Cancer Imaging Archive (TCIA) Public Access

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  • I-SPY 2 Breast Dynamic Contrast Enhanced MRI Trial (ISPY2)

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Summary

I-SPY 2 (Investigation of Serial studies to Predict Your Therapeutic Response with Imaging And moLecular analysis 2) is an ongoing, multi-center trial designed to quickly identify new agents for breast cancer. Patients with high-risk disease are adaptively-randomized to either standard neoadjuvant chemotherapy (NAC) or one of several concurrent experimental arms. I-SPY 2 utilizes change in tumor volume by DCE-MRI at serial time-points during chemotherapy to adjust the randomization schema as the trial proceeds, preferentially assigning patients to receive agents showing an increasing likelihood of efficacy against their breast cancer subtype. I-SPY 2 opened in March 2010 at 20 clinical sites and is ongoing.

This collection includes DCE MRI data (original acquired and derived), and outcomes for 990 patients adaptively randomized to one of several different investigational regimens or control therapy between March 2010 and November 2016 with histopathologic outcome data.  Breast MRI data in this collection was acquired prospectively at over 20 clinical centers using a standardized image acquisition protocol. Patients underwent 4 MRI exams over treatment and over 95% of imaging data met acceptance criteria for analysis of functional tumor volume (FTV), a demonstrated quantitative imaging marker of breast cancer response to NAC. This is a comprehensive, highly curated imaging data set with histopathologic outcome that can be used to develop, test and compare imaging metrics and prediction models for breast cancer response to treatment.

Acknowledgements

The I-SPY2 Breast MRI Collection is supported by NIH grants U01 CA225427, R01 CA132870 and P01 CA210961. The I-SPY 2 TRIAL is supported by the Quantum Leap Healthcare Collaborative. The authors gratefully acknowledge and thank the patients who have volunteered to participate in the I-SPY2 TRIAL, as well as the extensive network of investigators, patient advocates and study coordinators. We especially thank the site radiology teams that have contributed substantially to the value of this archive.

Data Access

Data TypeDownload all or Query/Filter

Images (DICOM, XX.X GB)


   

(Download requires the NBIA Data Retriever)

Clinical data (CSV)


 

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


Number of Patients

987

Number of Studies

3758

Number of Series


Number of Images


Images Size (GB)

Citations & Data Usage Policy

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

Data Citation

Wen Li, David C. Newitt, Jessica Gibbs, Lisa J. Wilmes, Ella F. Jones, Vignesh A. Arasu, Fredrik Strand, Natsuko Onishi, Alex Anh-Tu Nguyen, John Kornak, Bonnie N. Joe, Elissa R. Price, Haydee Ojeda-Fournier, Mohammad Eghtedari, Kathryn W. Zamora, Stefanie A. Woodard, Heidi Umphrey, Wanda Bernreuter, Michael Nelson, An Ly Church, Patrick Bolan, Theresa Kuritz, Kathleen Ward, Kevin Morley, Dulcy Wolverton, Kelly Fountain, Dan Lopez Paniagua, Lara Hardesty, Kathy Brandt, Elizabeth S. McDonald, Mark Rosen, Despina Kontos, Hiroyuki Abe, Deepa Sheth, Erin Crane, Charlotte Dillis, Pulin Sheth, Linda Hovanessian-Larsen, Dae Hee Bang, Bruce Porter, Karen Y. Oh, Neda Jafarian, Alina Tudorica, Bethany Niell, Jennifer Drukteinis, Mary S. Newell, Michael A. Cohen, Marina Giurescu & Elisa Berman (2021). 10.7937/tcia.d8z0-9t85

Publication Citation

Li W, et al., Predicting breast cancer response to neoadjuvant treatment using multi-feature MRI: results from the I-SPY 2 TRIAL, in press NPJ Breast Cancer

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 1 (Current): Updated yyyy/mm/dd

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


   

(Requires NBIA Data Retriever.)

Note: When DICOM data are downloaded with the NBIA Data Retriever, the app uses "Series Description" values to construct descriptive directory names. In some series for this Collection, characters that are not allowed in directory names are present. So the workaround is to select the “Classic Directory Name” option, which is located above “Select Directory For Downloaded Files.” 

Clinical Data (CSV)Link
Other (format)


 



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