Skip to main content
Log in

Creating and Curating a Terminology for Radiology: Ontology Modeling and Analysis

  • Published:
Journal of Digital Imaging Aims and scope Submit manuscript

Abstract

The radiology community has recognized the need to create a standard terminology to improve the clarity of reports, to reduce radiologist variation, to enable access to imaging information, and to improve the quality of practice. This need has recently led to the development of RadLex, a controlled terminology for radiology. The creation of RadLex has proved challenging in several respects: It has been difficult for users to peruse the large RadLex taxonomies and for curators to navigate the complex terminology structure to check it for errors and omissions. In this work, we demonstrate that the RadLex terminology can be translated into an ontology, a representation of terminologies that is both human-browsable and machine-processable. We also show that creating this ontology permits computational analysis of RadLex and enables its use in a variety of computer applications. We believe that adopting an ontology representation of RadLex will permit more widespread use of the terminology and make it easier to collect feedback from the community that will ultimately lead to improving RadLex.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig 1.
Fig 2.
Fig 3.
Fig 4.

Similar content being viewed by others

Notes

  1. See http://www.xml.com/2002/11/06/Ontology_Editor_Survey.html for a recent large survey of ontology editing tools.

References

  1. Andriole KP, et al: Addressing the coming radiology crisis-the Society for Computer Applications in Radiology transforming the radiological interpretation process (TRIP) initiative. J Digit Imaging 17:235–243, 2004

    Article  PubMed  Google Scholar 

  2. Langlotz CP, Caldwell SA: The completeness of existing lexicons for representing radiology report information. J Digit Imaging 15(Suppl 1):201–205, 2002

    Article  PubMed  Google Scholar 

  3. Sinha U, et al.: Evaluation of SNOMED3.5 in representing concepts in chest radiology reports: integration of a SNOMED mapper with a radiology reporting workstation. Proc AMIA Symp:799–803, 2000

  4. Starren J, Johnson SM: Expressiveness of the Breast Imaging Reporting and Database System (BI-RADS). Proc AMIA Annu Fall Symp:655–659, 1997

  5. Reiner BI, Knight N, Siegel EL: Radiology reporting, past, present, and future: the radiologist’s perspective. J Am Coll Radiol 4:313–319, 2007

    Article  PubMed  Google Scholar 

  6. Alberdi E, Taylor P, Lee R, Fox J, Sordo M, Todd-Pokropek A: Cadmium II: acquisition and representation of radiological knowledge for computerized decision support in mammography. Proc AMIA Symp:7–11, 2000

  7. Langlotz CP: RadLex: a new method for indexing online educational materials. Radiographics 26:1595–1597, 2006

    Article  PubMed  Google Scholar 

  8. RadLex Steering Subcommittee: RadLex: A lexicon for uniform indexing and retrieval of radiology information resources. http://www.rsna.org/radlex/

  9. Musen MA, Fergerson RW, Noy NF, Crubezy M: Protege-2000: A plug-in architecture to support knowledge acquisition, knowledge visualization, and the semantic Web. J Am Med Inform Assoc:1079–1079, 2001

  10. Noy NF, Fergerson RW, Musen MA: The knowledge model of Protege-2000: combining interoperability and flexibility. Lect Notes Artif Int 1937:17–32, 2000

    Google Scholar 

  11. Dameron O: JOT: a scripting environment for creating and managing ontologies. Proc. 7th International Protégé Conference, Stanford, CA

  12. Lambrix P, Habbouche M, Perez M: Evaluation of ontology development tools for bioinformatics. Bioinformatics 19:1564–1571, 2003

    Article  PubMed  CAS  Google Scholar 

  13. Cimino JJ: Review paper: coding systems in health care. Methods Inf Med 35:273–284, 1996

    PubMed  CAS  Google Scholar 

  14. Web ontology language (OWL) reference version 1.0. http://www.w3.org/tr/owl-guide/

  15. Knublauch H, Fergerson RW, Noy NF, Musen MA: The Protege OWL Plugin: an open development environment for Semantic Web applications. Semantic Web—Iswc 2004 Proceedings 3298:229–243, 2004

    Google Scholar 

  16. Berners-Lee T, Hendler J, Lassila O: The Semantic Web: Scientific American. New York: Scientific American, 2001

    Google Scholar 

  17. Harris MA, et al.: The gene ontology (GO) database and informatics resource. Nucleic Acids Res 32:D258–D261, 2004

    Article  PubMed  CAS  Google Scholar 

  18. OBO: Open Biological Ontologies. http://obo.sourceforge.net

  19. ACR BI-RADS breast imaging and reporting data system: Breast imaging atlas. Reston, VA: American College of Radiology, 2003

    Google Scholar 

  20. Kahn CE, Jr., Channin DS, Rubin DL: An ontology for PACS integration. J Digit Imaging 19:316–327, 2006

    Article  PubMed  Google Scholar 

Download references

Acknowledgment

We wish to thank Curtis P. Langlotz, MD, PhD, and Beverly Collins, PhD, for their assistance and support with RadLex and for their outstanding efforts in creating this rich resource.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Daniel L. Rubin.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Rubin, D.L. Creating and Curating a Terminology for Radiology: Ontology Modeling and Analysis. J Digit Imaging 21, 355–362 (2008). https://doi.org/10.1007/s10278-007-9073-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10278-007-9073-0

Key words

Navigation