The Cardiac Atlas Project: Rationale, Design and Procedures

  • Carissa G. Fonseca
  • Michael Backhaus
  • Jae Do Chung
  • Wenchao Tao
  • Pau Medrano-Gracia
  • Brett R. Cowan
  • Peter J. Hunter
  • J. Paul Finn
  • Kalyanam Shivkumar
  • Joao A. C. Lima
  • David A. Bluemke
  • Alan H. Kadish
  • Daniel C. Lee
  • Alistair A. Young
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6364)

Abstract

The Cardiac Atlas Project (CAP) is a NIH sponsored international collaboration to establish a web-accessible structural and functional atlas of the normal and pathological heart as a resource for the clinical, research and educational communities. An initial goal of the atlas is to facilitate statistical analysis of regional heart shape and wall motion characteristics, and characterization of remodeling, between and within population groups. The two main early contributing studies are the Multi Ethnic Study of Atherosclerosis (MESA) and the Defibrillators to Reduce Risk by Magnetic Resonance Imaging Evaluation (DETERMINE) clinical trial. De-identified image and text data from 2864 asymptomatic volunteers from MESA, and 470 myocardial infarction cases from DETERMINE, are currently available in the CAP database. DICOM images were de-identified using HIPAA compliant software based on tools provided by the Center for Computational Biology at UCLA. Only those cases with informed consent and IRB approval compatible with the CAP were included. Researchers requesting permission to access CAP data can apply through the CAP website (www.cardiacatlas.org). All proposals for data access must be approved by the data contributors, and applicants must sign a data transfer agreement with each study from which data is requested. Software to visualize cardiac images and create 3D mathematical models, developed in the CAP, is available open-source from the website.

Keywords

Computational Atlas Database Cardiac Mapping 

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References

  1. 1.
    ABI Physiome Home Page, http://www.physiome.org.nz/
  2. 2.
    International Consortium for Brain Mapping, http://www.loni.ucla.edu/ICBM
  3. 3.
    Informatics for Integrating Biology and Bedside Home Page, http://www.i2b2.org/
  4. 4.
    Integrative Biology Project Home Page, http://www.integrativebiology.ox.ac.uk/
  5. 5.
    Center for Computational Biology Home Page, http://www.loni.ucla.edu/ccb
  6. 6.
    Cardiovascular Research Grid Home Page, http://www.cvrgrid.org/
  7. 7.
    Cancer Biomedical Informatics Grid Home Page, http://cabig.nci.nih.gov
  8. 8.
    Biomedical Informatics Resarch Network Home Page, http://www.nbirn.net/
  9. 9.
    Bild, D.E., Bluemke, D.A., Burke, G.L., Detrano, R., Diez Roux, A.V., Folsom, A.R., Greenland, P., Jacob Jr., D.R., Kronmal, R., Liu, K., Nelson, J.C., O’Leary, D., Saad, M.F., Shea, S., Szklo, M., Tracy, R.P.: Multi-ethnic study of atherosclerosis: objectives and design. Am. J. Epidemiol. 156, 871–881 (2002)CrossRefGoogle Scholar
  10. 10.
    Kadish, A.H., Bello, D., Finn, J.P., Bonow, R.O., Schaechter, A., Subacius, H., Albert, C., Daubert, J.P., Fonseca, C.G., Goldberger, J.: Rationale and design for the Defibrillators to Reduce Risk by Magnetic Resonance Imaging Evaluation (DETERMINE) trial. J. Cardiovasc. Electro-physiol. 20, 982–987 (2009)CrossRefGoogle Scholar
  11. 11.
    LONI De-identification Debabelet, http://www.loni.ucla.edu/Software/DiD
  12. 12.
  13. 13.
    Backhaus, M., Britten, R., Chung, J.D., Cowan, B.R., Fonseca, C.G., Medrano-Gracia, P., Tao, W., Young, A.A.: The Cardiac Atlas Project: Development of a Framework Integrating Cardiac Images and Models. In: MICCAI 2010, Workshop on Statistical Atlases and Computational Models of the Heart: Mapping Structure and Function plus a Cardiac Electrophysiological Simulation Challenge (STACOM-CESC 2010), Beijing, China. LNCS (2010) (in press)Google Scholar
  14. 14.
    Young, A.A., Frangi, A.: Computational cardiac atlases: from patient to population and back. Experimental Physiology 94(5), 578 (2009)CrossRefGoogle Scholar
  15. 15.
    OWL Web Ontology Language, http://www.w3.org/TR/owl-features/
  16. 16.
  17. 17.
    Foundational Model of Anatomy Home Page, http://sig.biostr.washington.edu/projects/fm/AboutFM.html
  18. 18.
    Ryan, A.: Towards semantic interoperability in healthcare: ontology mapping from SNOMED-CT to HL7 version 3. Australian Computer Society, Inc., Hobart (2006)Google Scholar
  19. 19.

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Carissa G. Fonseca
    • 1
  • Michael Backhaus
    • 2
  • Jae Do Chung
    • 2
  • Wenchao Tao
    • 1
  • Pau Medrano-Gracia
    • 2
  • Brett R. Cowan
    • 2
  • Peter J. Hunter
    • 2
  • J. Paul Finn
    • 1
  • Kalyanam Shivkumar
    • 3
  • Joao A. C. Lima
    • 4
  • David A. Bluemke
    • 4
  • Alan H. Kadish
    • 5
  • Daniel C. Lee
    • 5
  • Alistair A. Young
    • 2
  1. 1.Diagnostic CardioVascular Imaging, UCLA, Suite 3371Los AngelesUSA
  2. 2.Auckland Bioengineering InstituteUniversity of AucklandAucklandNew Zealand
  3. 3.UCLA Cardiac Arrhythmia Center, BH-307 CHSLos AngelesUSA
  4. 4.Department of RadiologyJohns Hopkins HospitalBaltimoreUSA
  5. 5.Bluhm Cardiovascular InstituteNorthwestern Memorial InstituteChicagoUSA

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