Reduce in Variation and Improve Efficiency of Target Volume Delineation by a Computer-Assisted System Using a Deformable Image Registration Approach

K. S.Clifford Chao, Shreerang Bhide, Hansen Chen, Joshua Asper, Steven Bush, Gregg Franklin, Vivek Kavadi, Vichaivood Liengswangwong, William Gordon, Adam Raben, Jon Strasser, Christopher Koprowski, Steven Frank, Gregory Chronowski, Anesa Ahamad, Robert Malyapa, Lifei Zhang, Lei Dong

Research output: Contribution to journalArticlepeer-review

94 Scopus citations

Abstract

Purpose: To determine whether a computer-assisted target volume delineation (CAT) system using a deformable image registration approach can reduce the variation of target delineation among physicians with different head and neck (HN) IMRT experiences and reduce the time spent on the contouring process. Materials and Methods: We developed a deformable image registration method for mapping contours from a template case to a patient case with a similar tumor manifestation but different body configuration. Eight radiation oncologists with varying levels of clinical experience in HN IMRT performed target delineation on two HN cases, one with base-of-tongue (BOT) cancer and another with nasopharyngeal cancer (NPC), by first contouring from scratch and then by modifying the contours deformed by the CAT system. The gross target volumes were provided. Regions of interest for comparison included the clinical target volumes (CTVs) and normal organs. The volumetric and geometric variation of these regions of interest and the time spent on contouring were analyzed. Results: We found that the variation in delineating CTVs from scratch among the physicians was significant, and that using the CAT system reduced volumetric variation and improved geometric consistency in both BOT and NPC cases. The average timesaving when using the CAT system was 26% to 29% for more experienced physicians and 38% to 47% for the less experienced ones. Conclusions: A computer-assisted target volume delineation approach, using a deformable image-registration method with template contours, was able to reduce the variation among physicians with different experiences in HN IMRT while saving contouring time.

Original languageEnglish (US)
Pages (from-to)1512-1521
Number of pages10
JournalInternational Journal of Radiation Oncology Biology Physics
Volume68
Issue number5
DOIs
StatePublished - Aug 1 2007
Externally publishedYes

Keywords

  • Auto-segmentation
  • Computer-assisted
  • Contour variations
  • Deformable image registration
  • Target delineation

ASJC Scopus subject areas

  • Radiation
  • Oncology
  • Radiology Nuclear Medicine and imaging
  • Cancer Research

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