Frontiers in Oncology (Sep 2023)

A real-time contouring feedback tool for consensus-based contour training

  • Christopher L. Nelson,
  • Callistus Nguyen,
  • Raymond Fang,
  • Laurence E. Court,
  • Carlos E. Cardenas,
  • Dong Joo Rhee,
  • Tucker J. Netherton,
  • Raymond P. Mumme,
  • Skylar Gay,
  • Casey Gay,
  • Barbara Marquez,
  • Mohammad D. El Basha,
  • Yao Zhao,
  • Mary Gronberg,
  • Soleil Hernandez,
  • Kelly A. Nealon,
  • Mary K. Martel,
  • Jinzhong Yang

DOI
https://doi.org/10.3389/fonc.2023.1204323
Journal volume & issue
Vol. 13

Abstract

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PurposeVariability in contouring structures of interest for radiotherapy continues to be challenging. Although training can reduce such variability, having radiation oncologists provide feedback can be impractical. We developed a contour training tool to provide real-time feedback to trainees, thereby reducing variability in contouring.MethodsWe developed a novel metric termed localized signed square distance (LSSD) to provide feedback to the trainee on how their contour compares with a reference contour, which is generated real-time by combining trainee contour and multiple expert radiation oncologist contours. Nine trainees performed contour training by using six randomly assigned training cases that included one test case of the heart and left ventricle (LV). The test case was repeated 30 days later to assess retention. The distribution of LSSD maps of the initial contour for the training cases was combined and compared with the distribution of LSSD maps of the final contours for all training cases. The difference in standard deviations from the initial to final LSSD maps, ΔLSSD, was computed both on a per-case basis and for the entire group.ResultsFor every training case, statistically significant ΔLSSD were observed for both the heart and LV. When all initial and final LSSD maps were aggregated for the training cases, before training, the mean LSSD ([range], standard deviation) was –0.8 mm ([–37.9, 34.9], 4.2) and 0.3 mm ([–25.1, 32.7], 4.8) for heart and LV, respectively. These were reduced to –0.1 mm ([–16.2, 7.3], 0.8) and 0.1 mm ([–6.6, 8.3], 0.7) for the final LSSD maps during the contour training sessions. For the retention case, the initial and final LSSD maps of the retention case were aggregated and were –1.5 mm ([–22.9, 19.9], 3.4) and –0.2 mm ([–4.5, 1.5], 0.7) for the heart and 1.8 mm ([–16.7, 34.5], 5.1) and 0.2 mm ([-3.9, 1.6],0.7) for the LV.ConclusionsA tool that uses real-time contouring feedback was developed and successfully used for contour training of nine trainees. In all cases, the utility was able to guide the trainee and ultimately reduce the variability of the trainee’s contouring.

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