Skip to main content
Log in

Visual Interpretation with Three-Dimensional Annotations (VITA): Three-Dimensional Image Interpretation Tool for Radiological Reporting

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

Abstract

This paper introduces a software framework called Visual Interpretation with Three-Dimensional Annotations (VITA) that is able to automatically generate three-dimensional (3D) visual summaries based on radiological annotations made during routine exam reporting. VITA summaries are in the form of rotating 3D volumes where radiological annotations are highlighted to place important clinical observations into a 3D context. The rendered volume is produced as a Digital Imaging and Communications in Medicine (DICOM) object and is automatically added to the study for archival in Picture Archiving and Communication System (PACS). In addition, a video summary (e.g., MPEG4) can be generated for sharing with patients and for situations where DICOM viewers are not readily available to referring physicians. The current version of VITA is compatible with ClearCanvas; however, VITA can work with any PACS workstation that has a structured annotation implementation (e.g., Extendible Markup Language, Health Level 7, Annotation and Image Markup) and is able to seamlessly integrate into the existing reporting workflow. In a survey with referring physicians, the vast majority strongly agreed that 3D visual summaries improve the communication of the radiologists' reports and aid communication with patients.

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

Access this article

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

References

  1. Fan SF, Zhe X, He HQ, Ding JR, Teng GJ: The role of key image notes in CT imaging study interpretation. J Digit Imaging 24(2):366–372, 2011

    Article  PubMed Central  PubMed  Google Scholar 

  2. Armato SG: Computerized lung nodule detection: effect of image annotation schemes for conveying results to radiologists. Proc SPIE 5032:854–859, 2003

    Article  Google Scholar 

  3. Reiner B, Siegel E: Radiology reporting: returning to our image-centric roots. AJR Am J Roentgenol 187:1151–1155, 2006

    Article  PubMed  Google Scholar 

  4. Rubin GD: Data explosion: the challenge of multi-detector-row CT. Eur J Radiol 36(2):74–80, 2000

    Article  CAS  PubMed  Google Scholar 

  5. Lawrence HS, David MP, Alexandra RB, Yuelin L, Hedvig H: Improving communication of diagnostic radiology findings through structured reporting. Radiology 260:174–181, 2011

    Article  Google Scholar 

  6. Bosmans JML, Weyler JJ, Schepper AMD, Parizel PM: The radiology report as seen by radiologists and referring clinicians: results of the COVER and ROVER surveys. Radiology 259:184–195, 2011

    Article  PubMed  Google Scholar 

  7. Armato III, SG, McLennan G, Bidaut L, et al: The lung image database consortium (LIDC) and image database resource initiative (IDRI): a completed reference database of lung nodules on CT scans. Med Phys 38:915–931, 2011

    Article  PubMed  Google Scholar 

  8. Choplin RH, Johannes M, Boehme JM, Maynard CC: Picture archiving and communication systems: an overview. RadioGraphics 12:127–129, 1992

    Article  CAS  PubMed  Google Scholar 

  9. Digital Imaging and Communications in Medicine (DICOM) Standard. Available at http://medical.nema.org/. Accessed 20 January 2011

  10. Annotation Imaging Markup (AIM) Standard. Available at https://cabig.nci.nih.gov/tools/AIM/. Accessed 15 February 2011

  11. Channin DS, Mongkolwat P, Kleper V, Rubin DL: The annotation and image mark-up project. Radiology 253(3):590–592, 2009

    Article  PubMed  Google Scholar 

  12. Channin DS, Mongkolwat P, Kelper V, Sepukar K, Rubin DL: The caBIG annotation and image markup project. J Digit Imaging 23(2):217–225, 2010

    Article  PubMed Central  PubMed  Google Scholar 

  13. ClearCanvas RIS/PACS and DICOM viewing software solution. Available at http://www.clearcanvas.ca/. Accessed 23 December 2010

  14. Rosset A, Spadola L, Ratib O: Osirix: an open-source software for navigating in multidimensional DICOM images. J Digit Imaging 17(3):205–216, 2004

    Article  PubMed Central  PubMed  Google Scholar 

  15. Rubin DL: Rodriguez C, Shah P. Beaulieu C: iPad: semantic annotation and markup of radiological images. AMIA Annu Symp Proc(626–630), 2008

  16. Zimmerman SL, Kim W, Boonn WW: Informatics in radiology: automated structured reporting of imaging findings using the AIM standard and XML. RadioGraphics 31:881–887, 2011

    Article  PubMed  Google Scholar 

  17. Nokia Qt Application and UI framework. Available at http:/qt.nokia.com/. Accessed 15 August 2010

  18. NVIDIA Cg Toolkit. Available at http://developer.nvidia.com/cg-toolkit/. Accessed 23 November 2010

  19. Insight Segmentation and Registration Toolkit (ITK). Available at http://www.itk.org/. Accessed 21 August 2010

  20. DICOM Offis Toolkit (DCMTK). Available at http://dicom.offiss.de/. Accessed 26 January 2011

  21. Hall FM: The radiology report of the future. Radiology 251:313–316, 2009

    Article  PubMed  Google Scholar 

  22. Chiaramonte D: Who's afraid of the empowered patient? JAMA 300:1393–1394, 2004

    Article  Google Scholar 

  23. Berlin L: Communicating results of all outpatient radiologic examinations directly to patients: the time has come. AJR Am J Roentgenol 192:571–573, 2009

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

The authors acknowledge the National Cancer Institute and the Foundation for the National Institutes of Health and their critical role in the creation of the free publicly available LIDC/IDRI Database used in this study [7].

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sharmili Roy.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Roy, S., Brown, M.S. & Shih, G.L. Visual Interpretation with Three-Dimensional Annotations (VITA): Three-Dimensional Image Interpretation Tool for Radiological Reporting. J Digit Imaging 27, 49–57 (2014). https://doi.org/10.1007/s10278-013-9624-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10278-013-9624-5

Keywords

Navigation