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Summary

Background: The functional and biological properties of the tumor microenvironment are fundamentally important determinants of tumor response and therapy outcome in cancer.  Oxygenation status and vascularity are known to influence radiation response, and molecular energy metabolism and proliferation, modulate risk of disease recurrence and metastatic progression.  However, with the current standard clinical diagnostic approaches, such as biopsy or anatomic/morphologic tumor imaging, assessment of the known intra-tumoral heterogeneity of functional and biological tumor properties is limited.  Specifically, the functional characteristics within the microenvironment throughout the entire tumor have been challenging to assess spatially for tumor heterogeneity and temporally for clinical correlation before and during treatment.  While histologic tissue sampling is widely used clinically, sampling of the entire tumor with extensive biopsies, and biopsies at various time points during therapy for intra-treatment assessment are impractical and generally pose unacceptable clinical risk. 

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Localtab Group


Localtab
activetrue
titleData Access

Data Access

Data TypeDownload all or Query/FilterLicense

Images (DICOM, 26.0 GB)


 

Tcia button generator
urlhttps://wiki.cancerimagingarchive.net/download/attachments/112591753/CC-Tumor-Heterogeneity-manifest.tcia?api=v2

https://wiki.cancerimagingarchive.net/download/attachments/112591753/CC-Tumor-Heterogeneity-manifest.tcia?api=v2


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labelSearch
urlhttps://nbia.cancerimagingarchive.net/nbia-search/?MinNumberOfStudiesCriteria=1&CollectionCriteria=CC-Tumor-Heterogeneity


(Download requires NBIA Data Retriever)

CC BY 4.0

Clinical data (XLSX)


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urlhttps://wiki.cancerimagingarchive.net/download/attachments/112591753/TCIA_CCTH_Patient%20data_02.06.23.xlsx?api=v2



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Localtab
titleDetailed Description

Detailed Description

Image Statistics


Modalities

CT,MR,PT,REG,RTSTRUCT

Number of Patients

23

Number of Studies

171

Number of Series

821

Number of Images

131,556

Images Size (GB)

26.0

References 

  1. Bowen SR, Yuh WTC, Hippe DS, et al. Tumor radiomic heterogeneity: Multiparametric functional imaging to characterize variability and predict response following cervical cancer radiation therapy. J Magn Reson Imaging 2018;47(5):1388-96. doi: 10.1002/jmri.25874 [published Online First: 20171016]

  2. Mayr NA, Wang JZ, Zhang D, et al. Longitudinal changes in tumor perfusion pattern during the radiation therapy course and its clinical impact in cervical cancer. Int J Radiat Oncol Biol Phys 2010;77(2):502-8. doi: 10.1016/j.ijrobp.2009.04.084 [published Online First: 20090921]

  3. Mayr NA, Wang JZ, Zhang D, et al. Synergistic effects of hemoglobin and tumor perfusion on tumor control and survival in cervical cancer. Int J Radiat Oncol Biol Phys 2009;74(5):1513-21. doi: 10.1016/j.ijrobp.2008.09.050 [published Online First: 20090313]
  4. Mayr NA, Yuh WT, Jajoura D, et al. Ultra-early predictive assay for treatment failure using functional magnetic resonance imaging and clinical prognostic parameters in cervical cancer. Cancer 2010;116(4):903-12. doi: 10.1002/cncr.24822
  5. Prescott JW, Zhang D, Wang JZ, et al. Temporal analysis of tumor heterogeneity and volume for cervical cancer treatment outcome prediction: preliminary evaluation. J Digit Imaging 2010;23(3):342-57. doi: 10.1007/s10278-009-9179-7 [published Online First: 20090127]
  6. Yuh WT, Mayr NA, Jarjoura D, et al. Predicting control of primary tumor and survival by DCE MRI during early therapy in cervical cancer. Invest Radiol 2009;44(6):343-50. doi: 10.1097/RLI.0b013e3181a64ce9
  7. Huang Z, Mayr NA, Yuh WT, et al. Predicting outcomes in cervical cancer: a kinetic model of tumor regression during radiation therapy. Cancer Res 2010;70(2):463-70. doi: 10.1158/0008-5472.Can-09-2501 [published Online First: 20100112]
  8. Huang Z, Mayr NA, Gao M, et al. Onset time of tumor repopulation for cervical cancer: first evidence from clinical data. Int J Radiat Oncol Biol Phys 2012;84(2):478-84. doi: 10.1016/j.ijrobp.2011.12.037 [published Online First: 20120302]
  9. Mayr NA, Wang JZ, Lo SS, et al. Translating response during therapy into ultimate treatment outcome: a personalized 4-dimensional MRI tumor volumetric regression approach in cervical cancer. Int J Radiat Oncol Biol Phys 2010;76(3):719-27. doi: 10.1016/j.ijrobp.2009.02.036 [published Online First: 20090723]
  10. Wang JZ, Mayr NA, Zhang D, et al. Sequential magnetic resonance imaging of cervical cancer: the predictive value of absolute tumor volume and regression ratio measured before, during, and after radiation therapy. Cancer 2010;116(21):5093-101. doi: 10.1002/cncr.25260


Localtab
titleCitations & Data Usage Policy

Citations & Data Usage Policy

Tcia limited license policy

Info
titleData Citation

Mayr, N., Yuh, W. T. C., Bowen, S., Harkenrider, M., Knopp, M. V., Lee, E. Y.-P., Leung, E., Lo, S. S., Small Jr., W., & Wolfson, A. H. (2023). Cervical Cancer – Tumor Heterogeneity: Serial Functional and Molecular Imaging Across the Radiation Therapy Course in Advanced Cervical Cancer (Version 1) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/ERZ5-QZ59


Info
titlePublication Citation

Bowen, S. R., Yuh, W. T. C., Hippe, D. S., Wu, W., Partridge, S. C., Elias, S., Jia, G., Huang, Z., Sandison, G. A., Nelson, D., Knopp, M. V., Lo, S. S., Kinahan, P. E., & Mayr, N. A. (2017). Tumor radiomic heterogeneity: Multiparametric functional imaging to characterize variability and predict response following cervical cancer radiation therapy. In Journal of Magnetic Resonance Imaging (Vol. 47, Issue 5, pp. 1388–1396). Wiley. https://doi.org/10.1002/jmri.25874


Info
titleTCIA 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

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.


Localtab
titleVersions

Version 2 (Current): 2023/02/23

Data TypeDownload all or Query/FilterLicense
Images (DICOM, 26.0 GB)


Tcia button generator
urlhttps://wiki.cancerimagingarchive.net/download/attachments/112591753/CC-Tumor-Heterogeneity-manifest.tcia?api=v2



Tcia button generator
labelSearch
urlhttps://nbia.cancerimagingarchive.net/nbia-search/?MinNumberOfStudiesCriteria=1&CollectionCriteria=CC-Tumor-Heterogeneity



CC BY 4.0

Clinical data (XLSX)


Tcia button generator
urlhttps://wiki.cancerimagingarchive.net/download/attachments/112591753/TCIA_CCTH_Patient%20data_02.06.23.xlsx?api=v2



Tcia cc by 4

Added 'Time to Distant Metastasis' value for subject CCTH_B-8 in Clinical data

Version 1 Updated: 2023/01/20

Data TypeDownload all or Query/FilterLicense
Images (DICOM, 26.0 GB)


Tcia button generator
urlhttps://wiki.cancerimagingarchive.net/download/attachments/112591753/CC-Tumor-Heterogeneity-manifest.tcia?api=v2



Tcia button generator
labelSearch
urlhttps://nbia.cancerimagingarchive.net/nbia-search/?MinNumberOfStudiesCriteria=1&CollectionCriteria=CC-Tumor-Heterogeneity



CC BY 4.0

Clinical data (XLSX)


Tcia button generator
urlhttps://wiki.cancerimagingarchive.net/download/attachments/112591753/TCIA_CCTH_Patient%20data_1.17.23.xlsx?api=v2



Tcia cc by 4



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