1.
Justin Kirby1, Lawrence Tarbox2, John Freymann1, Carl Jaffe3, Fred Prior2
1 Leidos Biomedical Research, Frederick National Laboratory for Cancer Research, Frederick, MD,
2 Washington University School of Medicine, St. Louis, MO,
3 Boston University School of Medicine, Boston, MA

2. The current publishing landscape
Rewards publishing early and often
Leads to experimental studies - “further testing with larger population is required”
Reduced emphasis on validation studies

3. Need for enhanced reproducibility
2012 Amgen study unable to reproduce 47 of 53 “landmark” publications from top journals and reputable labs
NIH and major journals encouraging authors to provide more raw data with their papers

4. Need for enhanced reproducibility

5. Radiomics/radiogenomics analyses
Usually implies:
Large patient cohorts
Large numbers of feature variables
Can lead to an increased risk of spurious correlations not driven by biology

6. Radiomics/radiogenomics analyses
Who thinks per capita consumption of cheese actually drives the number of doctorates awarded? Sometimes data presents us with spurious correlations so it’s important to use open science methods to clearly document your process and see if it can be repeated by others or with other data sets.

7. Barriers to reproducibility
De-identification and hosting of imaging data is a high risk, non-trivial process
Limited availability of public databases to support sharing of imaging data
Limited incentive for individual researchers to spend time addressing these issues

8. The Cancer Imaging Archive (TCIA)
Collections of freely accessible DICOM images and supplementary data to foster re-use and reproducibility within the cancer imaging research community

9. TCIA Services Relieves PI of majority of data sharing burden/risks
Data hosting with >99% uptime
De-identification using pre-configured RSNA’s Clinical Trials Processor (CTP) and DICOM PS 3.15 Annex E standards
Multi-tiered QC process inspects both DICOM headers and pixels for PHI and integrity of data set
Phone/ support available for end users and submitters
Extensive documentation throughout the site
Exposure to a large community of researchers
Increase visibility of your work, get more citations!

10. TCIA Software Features
Collection/project-based organization of raw DICOM data
Wiki to support summary of data sets and research initiatives, non-image supporting data
Multiple search mechanisms to query across Collections
Simple
Free text
Advanced
Digital Object Identifiers (DOIs) to easily share data associated with publications
Programmatic interface (API) to integrate TCIA data into other applications
Notifications via or social media about new data additions and related news

11. Digital Object Identifiers (DOIs)
DOI’s provide permanent links to subsets of TCIA data used to reach the conclusions in a publication.

12. DOI Example
The DOI can be included in your paper as a permanent URL, making it easy for readers to quickly download and/or cite the data from TCIA.

13. TCIA Collections
Patients
Patients
56 Purpose-built data sets

14. TCGA Data Portal
The Cancer Genome Atlas -
Extensive genomics, digital pathology and clinical demographics/treatments/outcomes
21 of the 34 different cancer types have DICOM images in TCIA

15. TCGA Collections

16. TCGA Publication Policy
Mirrors TCGA publication policies
Image source sites (ISS) given first right to publish
Embargo lifted upon releasing a marker paper or 1 year after 100 cases are accrued then anyone can publish

17. Additional Radiogenomics Data Sets
NSCLC-Radiogenomics
26 subjects from Stanford University and the Veterans Administration Palo Alto Health Care System with PET/CT lung imaging and microarray data
NSCLC-Radiomics-Genomics
89 subjects from Maastro Clinic with lung CT imaging, gene expression and clinical data

18. Site usage and publications
Approximately 3,000 users visit the site monthly.
Nearly 200 manuscripts based on data in TCIA
Journals beginning to encourage data DOIs

19. Acknowledgements Washington University in St. Louis (PI: Fred Prior)
NCI - Paula Jacobs
Frederick National Laboratory for Cancer Research
John Freymann
Justin Kirby
Brenda Fevrier-Sullivan
Consultant - Carl Jaffe
Emory University – Ashish Sharma

20. Funding
This project has been funded in whole or in part with federal funds from the National Cancer Institute, National Institutes of Health, under Contract No. HHSN E. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government.

21. Questions?