Cancer Imaging Archive Updates: September 2019

[Tacconelli, Michelle (NIH/NCI) [C]]

TCIA Update September 2019

Clinical data for all 10 CPTAC cancer types are now availa­ble! You can access these data via download links on the Collection pages (see screenshot) or developers can lever­age the full set of API capabilities to build custom CPTAC applications: https://clinicalapi-cptac.esacinc.com/api/tcia/ . pic.twitter.com/wSw70G32x4

The new SLN-Breast collection enables an objective com­parison of breast cancer metastases detection algorithms. It consists of 130 H&E stained axillary lymph node specimens from 78 patients. Metastatic breast carcinoma is present in 27 of the patients: https://doi.org/10.7937/ tcia.2019.3xbn2jcc … pic.twitter.com/xpVfwZ7bA5

Our next #CPTAC Imaging SIG webinar is Monday, Sep 9 at noon. We'll have two speakers who will discuss their work linking imaging with genomics/proteomics from CPTAC pa­tients. Recording/slides from last week's presentation are also available: https://wiki.cancerimagingarchive.net/display/ Public/CPTAC+SIG+Webinars … @NCI_CSSI

CALLING ALL SCIENTISTS!!! THE #CPTAC SCIENTIFIC SYMPOSIUM IS HERE!!! Join us to learn about all our ad­vances in cancer #proteogenomics! Space is limited so sign up now! https://events.cancer.gov/cssi/occpr  @theNCI #CancerResearch #PrecisionMedicine #Collaborate4Cures pic.twitter.com/4qV0D4LsZi

We've updated our search capabilities to enable filtering for "phantoms" and "3rd party analyses". Learn more at https:// wiki.cancerimagingarchive.net/display/NBIA/What%27s+New+TCIA+7.2

Writing a paper about TCIA data?www.cancerimagingarchive.net/publications/ is a great place to begin your literature search. You can search by titles/ authors and filter on key word tags. You can even download an Endnote XML file to import everything into most citation management tools. pic.twitter.com/VGogYRDKsK

New data release! The CC-Radiomics-Phantom-3 collection scanned a physical phantom using 3 protocols on 100    scanners, enabling researchers to quantify inter-scanner        variability and determine whether quantitative imaging signa­tures are robust:https://doi.org/10.7937/tcia.2019.j71i4fah

The QIN-Breast-02 collection is now available on TCIA (limited-access). This was a multi-parametric quantitative MRI study of adult females diagnosed with invasive breast cancer collected at 2 different medical centers to demonstrate repro­ducible results. pic.twitter.com/BHLbEvVVLS

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