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Definition of project

The goal of this project is to create a survey of Publicly Available InVivo Medical Imaging Archives and the underlying software capabilities. It is generally agreed that there is a need for public medical imaging archives to provide the biomedical research community, industry, and academia with access to images that support:

  • Lesion detection and classification
  • Accelerated diagnostic imaging decision
  • Quantitative imaging assessment of drug response

The purpose of this project is to provide a practical guide for the community which allows them to:

  1. to assess existing software and instantiations that are appropriate to their research or clinical needs.
  2. to locate relevant  publicly available data for research

We encourage any feedback from the wider community that may help improve this information or correct any misconceptions stated below. The survey is divided into two sections:

  1. Publicly hosted biomedical imaging archives which are populated with actual data which researchers, teachers, industry, etc may wish to utilize
  2. Image archive software solutions which one could download and use to host their own DICOM image data sets

Please contact Justin Kirby (kirbyju@mail.nih.gov) or John Freymann (freymanj@mail.nih.gov) with any questions, error reports, updates, additions, etc. 

Acknowledgements

We would like to thank the following people for volunteering their time and effort in helping us populate this survey.

  • Dan Marcus (WUSTL)
  • Brian Hughes (Terpsys)
  • Dan Hall (NIH)
  • Patrick Reynolds (Kitware)
  • Julien Jomier (Kitware)
  • Ivo Dinov (UCLA)
  • Matthew McAuliffe (NIH)
  • David Keator (UCI)

Publicly Hosted Biomedical Imaging Archives

The following table attempts to summarize publicly accessible DICOM based biomedical image archives.  This survey originally initiated in August of 2010.  Information in the tables are being updated periodically.  

NOTE: Due to the large size of this table you may need to use the horizontal scroll bar at the bottom of the table to view some of the archives listed furthest to the right.

 

The Cancer Imaging Archive (TCIA)

NBIA

NIAMS

XNAT Central

Image Data Archive

Function BIRN Data Repository

Give A Scan

Optical Society of America (OSA)

Insight Journal (MIDAS)

National Database for Autism Research (NDAR)

Pediatric MRI Data RepositoryFITBIR

Supporting Institution(s)

Cancer Imaging Program

Cancer Imaging Program, caBIG

NIAMS, caBIG

WUSTL, BIRN

Lab of NeuroImaging UCLA (LONI)

FBIRN Institutions

Lung Cancer Alliance, Kitware

Optical Society of America, Kitware

Kitware, Insight Software Consortium

NIH, NIMH, NINDS, NICHD, NIEHS

NIH, NIMH, NICHD, NIDA, NINDSNINDS, DoD

Content Type

In Vivo Cancer Imaging, phantom imaging and related metada (see full Collection list)

In Vivo Cancer Imaging (see full collection list)

Osteoarthritis

Biomedical images, meta data, other phenotypic data (behavioral, clinical, etc)

ADNI (Alzheimers),
CRYO (histology),
ICBM (Brain mapping),
AIBL (Autralian Aging)

FMRI/MRI images, behavioral data, and clinical data from schizophrenics and healthy volunteers.  Willing to accept data on other neurological disorders.

 

Patient-contributed Lung Cancer Medical scans

Optical, digital holography, 2D/3D modalities, etc

Biomedical images, meta data, and journal articles

Autism - standard phenotypic data, imaging and genomic/pedigree data related to human subjects

Normal brain development

 

TBI related data: imaging, phenotypic and some genomics; human but expanding to preclinical models

Archive Software

NBIA, AIM Data Service (XML image metadata), and a Clinical Data relational database

NBIA

NBIA

XNAT

Image Data Archive

Human Imaging Database (HID)

MIDAS

MIDAS

MIDAS

customSame as NDAR (custom)Biomedical Research Informatics Computing System (BRICS) NIH developed – custom

Login account required

Yes.  Accounts are free and available to anyone. Click here to register.

For advanced site features or limited access data sets, but is not required for accessing public data. Click here to register.

Yes. Click here to register.

For accessing limited access data sets, but not for public data

Yes, via web https://ida.loni.ucla.edu/login.jsp.

No (email requested)

No

For accessing limited access data sets, but not for public data

Only for submitting data.

Yes

YesYes

Explicit data sharing policy

Yes, with options for uploading fully open or limited access data sets

Yes, with options for uploading fully open or limited access data sets

Yes, found here

No, data is made public or restricted as specified by the user who uploads it.

Yes, found here

All data is made publicly accessible.

All data is made publicly accessible.

Yes, found here.

All data is made publicly accessible (varying licenses)

Yes, found here

Similar to NDAR but there is no explicit policyYes, https://fitbir.nih.gov/jsp/about/policy.jsp

Number of Registered Users (or NA)

2,607

2,712

46

~1,000

>1,000

N/A

N/A

 

2,657

60 for data access
100-200 for data submission

~30

15 – just starting

Accepting new data

Yes, proposals are accepted via email and reviewed monthly by the TCIA Advisory Committee. Acceptance criteria is summarized here: Requesting Permission to Upload your Data.

Yes, with approval from NCI CBIIT

More data is being added as part of the official initiative, but external proposals are not being accepted.

Yes, users can register accounts and upload data

Yes, see section 9 in the Appendix of the LONI Policies & Procedures

Yes, https://www.birncommunity.org/about/contact/

Yes, through Lung Cancer Alliance. Learn more here.

Yes, new data may be added as part of future Optical Society of America publications are released.

Yes, users can register accounts and upload data.

Yes, learn more here

NoYes, FITBIR has established a two-tiered submission strategy to ensure high quality and to provide maximum benefit to investigators.  See the Data Submission Procedures for more information.

Central curation/review

Yes, a multiple tiered de-identification and QC process is utilized involving both human review and systematic analysis.  The process is summarized in detail on the TCIA De-Identification Knowledge Base and What to Expect as an Image Provider.

Yes, performed by CBIIT staff

Yes, performed by NIAMS staff.

No

Collaborators strip all personal info from data prior to submission to LONI. Then LONI auto filters again, to ensure that there are no PHI in the files (especially if the data is binary) and stores the data in quarantine, until it’s approved for posting to the web interface.

PHI must be removed by the submitting institution prior to giving the data to the FBIRN.

FBIRN also performs a review to make sure there aren't any de-identification problems.

Yes, performed by Lung Cancer Alliance

Yes, performed by the Optical Society of America

Yes, some QC performed by Kitware staff and peer reviews.  Most data is de-identified by the submitter prior to upload.

Sites do their own de-identification any way they prefer, so long as it meets their IRB's approval. 

Pre-validation is performed to ensure all data conforms/harmonizes to the autism data dictionary. QA is also performed by NDAR staff to check for identifiable information.

Archived project, no longer receiving new data.Yes, pre-validation is performed to ensure all data conforms to the NINDS CDEs. QA is also performed by staff to check for personal identifiable information.

Availability/Uptime

~99%, hosted on a redundant production system at WUSTL

~99%, hosted on a redundant production system at NCI CBIIT

~99%, hosted on a redundant production system at NCI CBIIT

~99%

Continuous (no exact % specified)

Continuous (no exact % specified)

~99.9%, hosted on a production server at Kitware

~99.9%, hosted on a production server at OSA

~99%, hosted on a production server at Kitware

~99%, imaging data hosted on Amazon and metadata hosted by NIH.

~99%, hosted by NIH.~99%, hosted by NIH.

Project- or Collection- based groupings?

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

NoYes

Size of Current Volume

TCIA: 1.8 TB
NLST-LSS: 6.5 TB
NLST-ACRIN: 4.8 TB

Total: 13.1 TB

~2TB

~7.5TB

1 TB

0.7 PB

~2TB

33GB

~50GB

~60GB

~2TB

~2TB0.5TB

Number of patients/subjects with imaging

TCIA: 3,685
NLST-LSS: 17,043
NLST-ACRIN: 9,211

Total: 29,939

4,920

4,796

3,494

> 120,000

~300

37

N/A

> 200, plus some non-patient data

2500 NDAR

 

550 (migrated into NDAR)200

Number of DICOM Tags query-able

~90 via NBIA

~90

~90

~50

50

0

22 (imaging parameters in query interface)

N/A

22 (imaging parameters in query interface)

9, with full listing from data dictionary. (4 NDAR, 5 Pediatric MRI)

9, with full listing from data dictionary. (4 NDAR, 5 Pediatric MRI)10
Metadata AvailabilityWide variety of clinical, genetic, and image segmentation/annotation available is available for various data sets.  Full summary can be viewed here in the "Supporting Data Available" column.Some limited metadata available for specific collectionsNone

Various clinical and other metadata

Biospecimen, clinical, pathological, neuropsychiatric, and demographic.Yes, extensive behavioral data and clinical data. 

Some unstructured clinical data such as patient age, cancer stage, recurrence, and treatment information.

Associated articles, figures, publication-specific metadata, etcUnstructured clinical data as well as publication-specific metadata

NDAR contains all human subjects data related to autism research funded by the NIH and others.  Outside of the NDAR data dictionary, Metadata supporting project definition and research results are provided (see data from papers). 

 

 

Yes, all metadata is collected using NINDS CDEs

Data submission/download methods

Submission via DICOM or HTTPS protocols using CTP. Download via Java Webstart client. A REST API is in development with an expected public release in the summer of 2013.

Submission via DICOM or HTTPS protocols using CTP. Download via Web (zip), FTP, Java Webstart client

Submission via DICOM or HTTPS protocols using CTP. Download via Web (zip), FTP, Java Webstart client

Submission via Web UI or DICOM protocol.  Download via Web (zip) or Java applet.

Secure web upload

Downloads via Web UI, Submissions via https://www.birncommunity.org/about/contact/

Submission via Web UI,
Download via Web (zip).

Submission via Web UI,
Download via Web (zip).

Submission via Web UI, DICOM push, MIDASDesktop.


Download via Web (zip), MIDASDesktop

A custom Java Webstart application allows SFTP/Amazon S3 transfers.  MIPAV is offered as an optional method for de-identification.  Submission is harmonized to the autism data standard using custom data validation software. 

Download methods include multithreaded download from the Amazon Cloud or push to cloud computational pipeline.

Not applicable.They can use MIPAV for submitting images. Submissions must conform to FITBIR Data Dictionary (NINDS CDEs). A custom Java Webstart application allows SFTP transfers.

Helpdesk Support

Yes, the TCIA Helpdesk supports both end users and submitters. They provide phone and email support during regular business hours Mon-Fri.

Yes, CBIIT Application Support

Yes, CBIIT Application Support

Via XNAT discussion group

dba@loni.ucla.edu

Yes, via https://www.birncommunity.org/about/contact/

Technical issues can be sent to midas@public.kitware.com or click here for  Administrative support and other questions.

Contact infobase@osa.org.

Contact midas@public.kitware.com

Yes, available at ndarhelp@mail.nih.gov.

Yes, pedsmri@mail.nih.gov.Yes, FITBIR-help@mail.nih.gov

Affiliation with Journal

No

No

No

No

Yes, NeuroImage

No

No

Yes, Optics Info Base

Yes, Insight Journal

No

NoNo

Intended Audience(s)

Cancer researchers, engineers and developers, professors

Cancer researchers and anyone interested in testing the functionality of the NBIA software.

Osteoarthritis researchers

All imaging research

Neuroimaging and genetics research

Neuroimaging research

Lung cancer researchers

Optical Society of America subscribers

All imaging research

Autism researchers (clinical/phenotype/genomic), both those receiving autism related NIH grants and other investigators sponsored by an NIH recognized institution with a current federal-wide assurance.

Neuroscientists interested in normative brain study of child development.TBI researchers


Image archive software solutions

Below is a list of image archive solutions that can be deployed by interested parties wishing to build their own DICOM based biomedical image archive. This list omits some of the archives above in cases where we could not find any information about how one might download and deploy their own instance of the software.

Software Name and Web Site

NBIA

XNAT

MIDAS

Interface/GUI

Web

Web

Web/Desktop Application

Query types/flexibility

Simple (9 parameters), Advanced (10 more parameters), Dynamic (boolean query of up to 90 DICOM tags)

Limited subset of DICOM tags out of the box but is highly configurable for adding the ability to query on just about any kind of meta data you wish to provide

Customizable, search by any tags registered in the system

Role Based Security

Yes

Yes

Yes

Public access option (no login req)

Yes

Yes

Yes

Active Development

Yes, NCI CBIIT

Yes, WUSTL Neuroinformatics Research Group

Yes, Kitware

License

Open source - NBIA License Agreement Details

Non-restrictive (BSD) open-source license - XNAT License Agreement Details

non-restrictive (BSD) open-source license

Supports Federated Implementation

Yes, can discover other nodes on the caGrid

Not currently, but there are plans to add this functionality eventually

No

API available

Yes, caGrid

Yes, REST

Yes, REST, OAI-PMH

Supported image formats

DICOM

Automated import of DICOM and ECAT. Custom importers can be implemented for other formats.  Any file type can be uploaded through the API and web interface.

DICOM and other ITK-based format

Supported metadata formats

XML, Zip

XML

XML

Transfer protocols (import/export)

DICOM, HTTPS

DICOM, HTTPS

DICOM, HTTPS

Controlled Vocabulary

Follows caBIG standards (caDSR/EVS)

XNAT Schema

NIH Mesh and Dublin Core

Deployment Support

Yes, CBIIT Application Support or via NBIA User Listserv

XNAT Google Discussion group, monthly developer tcons, biannual user conference

Yes, MIDAS mailing list

Support Operating Systems

Linux, Windows, Mac

Linux, Windows, Mac

Linux, Windows, Mac

Data submission options

Submission to NBIA is performed by a java tool called CTP developed by John Perry at the RSNA.  CTP has options to import data from a hard drive or directly from a PACS or DICOM Workstation.

Direct upload is available through the web UI, direct DICOM transfer, scripts using REST API.

Direct upload via web UI, direct DICOM transfer via push, MIDASDesktop transfer (includes command line tools), WebDAV support.

Standard of De-Identification

Incorporates DICOM de-identification standards from The Attribute Confidentiality Profile (DICOM PS 3.15: Appendix E) via CTP.

Built-in de-identification language based on DICOM Browser can be configured to comply with DICOM PS 3.15: Appendix E and other standards.

No, but pre-storage filters can be run automatically

Support for multi-site submissions

Yes

Yes

Yes

 

 

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