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Vargas, Alberto; Huang, Erich; Lakhman, Yulia; Ippolito, Joe; Bhosale, Priya; Mellnick, Vincent; Shinagare, Atul; Anello, Maria; Kirby, Justin; Fevrier-Sullivan, Brenda; Freymann, John; Jaffe, Carl; Sala, Evis,. (2016). Imaging Features, and Correlations with Genomic and Clinical Data from the TCGA Ovarian Radiology Research Group. The Cancer Imaging Archive. http://doi.org/ |
Authors
Alberto Vargas, Erich Huang, Yulia Lakhman, Joe Ippolito, Priya Bhosale, Vincent Mellnick, Atul Shinagare, Maria Anello, Justin Kirby, Brenda Fevrier-Sullivan, John Freymann, Carl Jaffe, Evis Sala
Citation
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Description
This study was a multi-reader, multi-institutional, IRB-approved retrospective analysis of 93 HGSOC patients with abdominal and pelvic CT scans prior to primary debulking that were available through The Cancer Imaging Archive (TCIA). Eight radiologists from The Cancer Genome Atlas-Ovarian Cancer (TCGA-OV) Imaging Research Group developed and subsequently independently recorded the following CT features in each patient: primary ovarian mass(es) characteristics (if present), presence and distribution of peritoneal tumor spread, lymphadenopathy, and distant metastases. Inter-observer agreement for the CT features was assessed, as were associations of these features with time-to-disease progression (TTP) and CLOVAR subtypes and abilities of combinations of these features to predict TTP and CLOVAR subtypes. Results of analyzing this data are published in a manuscript
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titled Radiogenomics of High-Grade Serous Ovarian Cancer: Multi- Reader Multi-Institutional Study from The Cancer Genome Atlas-Ovarian Cancer (TCGA-OV) Imaging Research Group.
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| Vargas HA, Huang EP, Lakhman Y, Ippolito JE, Bhosale P, Mellnick V, Shinagare AB, Anello M, Kirby J, Fevrier-Sullivan B, Freymann J, Jaffe CC, Sala E. Radiogenomics of High-Grade Serous Ovarian Cancer: Multireader Multi-Institutional Study from the Cancer Genome Atlas Ovarian Cancer Imaging Research Group. Radiology. 2017 Jun 22:161870. doi: 10.1148/radiol.2017161870. (link) |
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- DICOM Image Data:
- Click the Download button above to save a ".tcia" manifest file to your computer, which you must open with the NBIA Data Retriever.
- Radiologist Assessments of Image Features:
- Clinical Data
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- : ClinicalData101515.csv
- Genomic Data
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