Journal of Digital Imaging

, Volume 27, Issue 1, pp 108–119

Development of a Software for Quantitative Evaluation Radiotherapy Target and Organ-at-Risk Segmentation Comparison

Authors

  • Jayashree Kalpathy-Cramer
    • Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Department of Radiology and NeuroscienceMassachusetts General Hospital
  • Musaddiq Awan
    • Head and Neck Section, Division of Radiation Oncology, Department of Radiation OncologyThe University of Texas MD Anderson Cancer Center
  • Steven Bedrick
    • Department of Medical Informatics & Clinical EpidemiologyOregon Health & Science University
  • Coen R. N. Rasch
    • Department of RadiotherapyAcademic Medical Center
  • David I. Rosenthal
    • Head and Neck Section, Division of Radiation Oncology, Department of Radiation OncologyThe University of Texas MD Anderson Cancer Center
    • Head and Neck Section, Division of Radiation Oncology, Department of Radiation OncologyThe University of Texas MD Anderson Cancer Center
Article

DOI: 10.1007/s10278-013-9633-4

Cite this article as:
Kalpathy-Cramer, J., Awan, M., Bedrick, S. et al. J Digit Imaging (2014) 27: 108. doi:10.1007/s10278-013-9633-4

Abstract

Modern radiotherapy requires accurate region of interest (ROI) inputs for plan optimization and delivery. Target delineation, however, remains operator-dependent and potentially serves as a major source of treatment delivery error. In order to optimize this critical, yet observer-driven process, a flexible web-based platform for individual and cooperative target delineation analysis and instruction was developed in order to meet the following unmet needs: (1) an open-source/open-access platform for automated/semiautomated quantitative interobserver and intraobserver ROI analysis and comparison, (2) a real-time interface for radiation oncology trainee online self-education in ROI definition, and (3) a source for pilot data to develop and validate quality metrics for institutional and cooperative group quality assurance efforts. The resultant software, Target Contour Testing/Instructional Computer Software (TaCTICS), developed using Ruby on Rails, has since been implemented and proven flexible, feasible, and useful in several distinct analytical and research applications.

Keywords

SegmentationImaging informaticsImage segmentationRadiation oncologyAlgorithmsTeaching

Copyright information

© Society for Imaging Informatics in Medicine 2013