Cancer Imaging Archive Updates: May 2020

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

TCIA Update: May 2020

Stanford's new "DRO Toolkit" collection enables standardization of Radiomic Features by providing sample Digital Reference Objects with varying size, shape, intensity, texture, and margin sharpness values, as well as the soft­ware used to create them: https://doi.org/10.7937/t062-8262

Another very cool use of TCIA data! Can’t wait to hear about the innovative ideas that come out of the Metadata Automation DREAM Challenge - teams are working to help manage diverse annotation requirements of the NCI Commons. TCIA is excited to hear the results and to hopefully be able to  leverage some of the winning solutions in our data curation process.

A new Analysis Results dataset has been published which used the NSCLC-Radiomics collection to create Thoracic Volume and Pleural Effusion Seg­mentations in Diseased Lungs for Benchmarking Chest CT Processing Pipe­lines: https://doi.org/10.7937/tcia.2020.6c7y-gq39

We're excited to see another year of the very popular Brain Tumor Segmen­tation Challenge (BraTS challenge) taking place at MICCAI 2020. Registra­tion and training data leveraging the TCGA-GBM & TCGA-LGG collections from TCIA are now available! https://med.upenn.edu/cbica/brats2020/

The previously restricted-access QIN GBM Treatment Response collection is now publicly available. It contains “double baseline” multi-parametric MRI images (T1, T2, FLAIR, MEMPRAGE, DWI, DCE-MRI) collected on patients with newly diagnosed glioblastoma: https://doi.org/10.7937/K9/ TCIA.2016.nQF4gpn2

TCIA is funded by the NCI Cancer Imaging Program (CIP). Check out this recent editorial by CIP leadership about COVID-19 impact on cancer re­search, as well as plans to post some COVID-19 data on TCIA in the near future! https://pubs.rsna.org/doi/10.1148/rycan.2020204017

50 new CPTAC-AML tumor blood and marrow histopathology images have been posted. Learn more about the CPTAC project at https:// wiki.cancerimagingarchive.net/display/Public/CPTAC+Imaging+Proteomics.

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