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Summary


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This data is from a multi-site, multi-parametric quantitative MRI study of adult (18+ years old) females diagnosed with invasive breast cancer.  Subjects all had a lesion size >1cm in longest dimension and were undergoing neoadjuvant therapy. Participants were scanned prior to any therapy and then 2-3 times after the initiation of neoadjuvant therapy, depending upon their treatment regimen. All data sets were acquired with a research-only protocol, including: DWI (SE EPI), OGSE, qMT, B0 map, multi-flip T1 map, Bloch-Siegert B1 map, DCE, and a T1-weighted anatomical image.

This dataset is an extension of the original QIN-BREAST collection, with updated scan protocols and data collected at both Vanderbilt University Medical Center and the University of Chicago to demonstrate reproducible results at multiple sites (both using Philips 3T MR scanners).  


Acknowledgements

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

  • Thomas E. Yankeelov,  Ph.D. (University of Texas at Austin),
  • Gregory S. Karczmar Ph.D. (University of Chicago),
  • Richard G. Abramson, M.D. and Lori Arlinghaus, Ph.D. (Vanderbilt University Medical Center)

Data Access

When you have a TCIA account, please email to help@cancerimagingarchive.net to request access to these data.

Data TypeDownload all or Query/FilterLicense
Images (DICOM, 3.9 GB)

   

(Download requires the NBIA Data Retriever)

 

TCIA restricted

Clinical Data (XLSX, 17 kB)

 


CC BY 3.0

Acquisition Scan Parameters (XLSX, 50 kB) 

 

CC BY 3.0


Click the Versions tab for more info about data releases.

Detailed Description

Image Statistics


Modalities

MR

Number of Patients

13

Number of Studies

34

Number of Series

235

Number of Images

31,790

Images Size (GB)3.9

Not all participants completed all rounds of imaging. Clinical spreadsheets are available. Acquisition scan parameter tables are available.


Citations & Data Usage Policy

Users must abide by the TCIA Data Usage Policy and Restrictions. Attribution should include references to the following citations:

Please be sure to acknowledge both this data set and TCIA in publications by including the following citations in your work:

Data Citation

Yankeelov TE, Karczmar GS, Abramson RG. (2019) Data from QIN-BREAST-02[Dataset]. The Cancer Imaging Archive. doi: 10.7937/TCIA.2019.4cfm06rr

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. The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository, Journal of Digital Imaging, Volume 26, Number 6, December, 2013, pp 1045-1057. DOI: 10.1007/s10278-013-9622-7

Additional Publication Resources

The Collection authors suggest the below will give context to this dataset:

  1. Williams, J. M., Rani, S. D., Li, X., Arlinghaus, L. R., Lee, T.-C., MacDonald, L. R., Partridge, S. C., Kang, H., Whisenant, J. G., Abramson, R. G., Linden, H. M., Kinahan, P. E., & Yankeelov, T. E. (2015). Comparison of prone versus supine 18F-FDG-PET of locally advanced breast cancer: Phantom and preliminary clinical studies. In Medical Physics (Vol. 42, Issue 7, pp. 3801–3813). Wiley. https://doi.org/10.1118/1.4921363
  2. Li, X., Abramson, R. G., Arlinghaus, L. R., Chakravarthy, A. B., Abramson, V., Mayer, I., Farley, J., Delbeke, D., & Yankeelov, T. E. (2012). An algorithm for longitudinal registration of PET/CT images acquired during neoadjuvant chemotherapy in breast cancer: preliminary results. In EJNMMI Research (Vol. 2, Issue 1). Springer Science and Business Media LLC. https://doi.org/10.1186/2191-219x-2-62
  3. Yankeelov, T. E., Peterson, T. E., Abramson, R. G., Garcia-Izquierdo, D., Arlinghaus, L. R., Li, X., Atuegwu, N. C., Catana, C., Manning, H. C., Fayad, Z. A., & Gore, J. C. (2012). Simultaneous PET–MRI in oncology: a solution looking for a problem? In Magnetic Resonance Imaging (Vol. 30, Issue 9, pp. 1342–1356). Elsevier BV. https://doi.org/10.1016/j.mri.2012.06.001

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 TCIA's Helpdesk.

Update 2020/02/12: Clinical data table has one code revision, text/numeric values have not changed.

Version 1 (Current): Updated 2019/07/10

Data TypeDownload all or Query/Filter
Images (DICOM, 4 GB)

     

(Download requires the NBIA Data Retriever)

Clinical Data (XLSX)

 

Acquisition Scan Parameters (XLSX) 

 

Added new subjects, 10/22/2019 corrected error in clinicaldata spreadsheet.






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