TCIA update presented by Christina Vivelo during the January 7, 2019 NCI Imaging Community call

1. The Cancer Imaging Archive - Updates
NCI Imaging Community Call
January 7, 2019
Christina Vivelo

2. 2
TCIA – General Updates
• Text search feature in our data portal allows searching specific DICOM
metadata fields (e.g. "0018,0015:pancreas" would look only at the
BodyPartExamined field for the word “pancreas”)
• Filter collections on our home page by supporting data available for each
data set (image analyses, clinical, genomic, etc.)
• New “Imaging Proteogenomics” and “Imaging Clinical Trials” tabs on the
TCIA website under “Research Activities” menu
• Updated the “Submit your data” menu on TCIA homepage to clarify
submission protocol for novel imaging data sets and analyses of existing
TCIA datasets

3. 3
TCIA – Collections & Publications
• QIN-Prostate-Repeatability Limited Access Collection: On repeatability of
MRI based measurements in the prostate, plan to add additional MRI
series, parametric maps, potential corresponding clinical and pathology data
• Liu, Z., et al. Conventional MR-based Preopertaive Nomograms for
Prediction of IDH/1p19q Subtype in Low-Grade Glioma, Academic
Radiology (Nov 2018): used MRI data sets from TCIA and genetic data from
TCGA, developing a model to provide preoperative prediction of prognosis
and responsiveness to treatment for lower-grade glioma patients
• Li, Z., et al. Multiregional radiomics profiling from multiparametric MRI:
Identifying an imaging predictor of IDH1 mutation status in glioblastoma,
Cancer Med (Dec 2018): used TCIA MRI data sets, how different models,
using multiregional radiomics features, preoperatively predict IDH1 gene
mutation status in glioblastoma patients

4. 4
TCIA – Other Announcements
• NCI Imaging Data Commons – Promoted the RFP
• CPTAC Pathology Data hosted on TCIA – TCIA hosts a large collection of
pathology data, access through CPTAC Pathology Portal
• Test data from the 2018 BraTS competition is now available upon request
from TCIA helpdesk, reviewed in this Nature article: Bakas S., et al.
Advancing The Cancer Genome Atlas glioma MRI collections with expert
segmentation labels and radiomic features
• Follow TCIA on twitter: @TCIA_News, Facebook, and LinkedIn