Skip to main content

QIN-BREAST-02

The Cancer Imaging Archive

QIN-BREAST-02 | QIN-BREAST-02

DOI: 10.7937/TCIA.2019.4cfm06rr | Data Citation Required | 169 Views | 4 Citations | Image Collection

Location Species Subjects Data Types Cancer Types Size Supporting Data Status Updated
Breast Human 13 MR, Demographic, Diagnosis, Molecular Test, Treatment, Follow-Up, Protocol Breast Cancer 4.19GB Clinical Limited, Complete 2019/07/10

Summary

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).

Data Access

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

Version 1: Updated 2019/07/10

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

Title Data Type Format Access Points Subjects Studies Series Images License
Images MR DICOM
Download requires NBIA Data Retriever
 13 34 235 31,790 TCIA Limited (contact Support)
Clinical Data Demographic, Diagnosis, Molecular Test, Treatment, Follow-Up XLSX CC BY 3.0
Acquisition Scan Parameters Protocol XLSX CC BY 3.0
Related Datasets
No related Analysis Results found: Submit your proposal! No related Collections found
Legend: Analysis Results| Collections

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

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

Detailed Description

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

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)

Related Publications

Publications by the Dataset Authors

The authors recommended the following as the best source of additional information about this dataset:

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

Research Community Publications

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.

TCIA maintains a list of publications that leveraged this dataset. If you have a manuscript you’d like to add please contact TCIA’s Helpdesk.

Additional Publications Related to this Work

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.