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Authors

Elizabeth Morris, Elizabeth Burnside, Gary Whitman, Margarita Zuley, Ermelinda Bonaccio, Marie Ganott, Elizabeth Sutton, Jose Net, Kathy Brandt, Chuck Hui Li, Karen Drukker, Chuck Perou, Maryellen L. Giger.

Citations

Coming soon

Description

At the time of our study, 108 cases with breast MRI data were available in the TCGA-BRCA collection. In order to minimize variations in image quality across the multi-institutional cases we included only breast MRI studies acquired on GE 1.5 Tesla magnet strength scanners (GE Medical Systems, Milwaukee,Wisconsin, USA) scanners, yielding a total of 93 cases. We then excluded cases that had missing images in the dynamic sequence (1 patient), or at the time did not have gene expression analysis available in the TCGA Data Portal (8 patients). After these criteria, a dataset of 84 breast cancer patients resulted, with MRIs from four institutions: Memorial Sloan Kettering Cancer Center, the Mayo Clinic, the University of Pittsburgh Medical Center, and the Roswell Park Cancer Institute. The resulting cases contributed by each institution were 9 (date range 1999-2002), 5 (1999-2003), 46 (1999-2004), and 24 (1999-2002), respectively. The dataset of biopsy proven invasive breast cancers included 74 (88%) ductal, 8 (10%) lobular, and 2 (2%) mixed. Of these, 73 (87%) were ER+, 67 (80%) were PR+, and 19 (23%) were HER2+.  Various types of analyses were conducted using the combined imaging, genomic, and clinical data.  Those analyses are described within several manuscripts created by the group (cited above). 

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  • Images
    • DICOMSave/open this file to initiate our Java Web Start download manager to begin your download
  • Radiologist Annotations/Markup
  • Computer-extracted image phentotypes
  • Multi-gene assays including MammaPrint, Ocotype DX, and PAM50
  • TCGA Clinical Data (from TCGA Data Portal, archived in case of subsequent updates made by TCGA)
    • <insert working copy of clinical data file(s)>

Source Shared List

Using Computer-extracted Image Phenotypes from Tumors on Breast MRI to Predict Stage.