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A real-time contouring feedback tool for consensus-based contour training
PURPOSE: Variability 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, the...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10525705/ https://www.ncbi.nlm.nih.gov/pubmed/37771435 http://dx.doi.org/10.3389/fonc.2023.1204323 |
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author | Nelson, Christopher L. Nguyen, Callistus Fang, Raymond Court, Laurence E. Cardenas, Carlos E. Rhee, Dong Joo Netherton, Tucker J. Mumme, Raymond P. Gay, Skylar Gay, Casey Marquez, Barbara El Basha, Mohammad D. Zhao, Yao Gronberg, Mary Hernandez, Soleil Nealon, Kelly A. Martel, Mary K. Yang, Jinzhong |
author_facet | Nelson, Christopher L. Nguyen, Callistus Fang, Raymond Court, Laurence E. Cardenas, Carlos E. Rhee, Dong Joo Netherton, Tucker J. Mumme, Raymond P. Gay, Skylar Gay, Casey Marquez, Barbara El Basha, Mohammad D. Zhao, Yao Gronberg, Mary Hernandez, Soleil Nealon, Kelly A. Martel, Mary K. Yang, Jinzhong |
author_sort | Nelson, Christopher L. |
collection | PubMed |
description | PURPOSE: Variability 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. METHODS: We 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. RESULTS: For 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. CONCLUSIONS: A 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. |
format | Online Article Text |
id | pubmed-10525705 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-105257052023-09-28 A real-time contouring feedback tool for consensus-based contour training Nelson, Christopher L. Nguyen, Callistus Fang, Raymond Court, Laurence E. Cardenas, Carlos E. Rhee, Dong Joo Netherton, Tucker J. Mumme, Raymond P. Gay, Skylar Gay, Casey Marquez, Barbara El Basha, Mohammad D. Zhao, Yao Gronberg, Mary Hernandez, Soleil Nealon, Kelly A. Martel, Mary K. Yang, Jinzhong Front Oncol Oncology PURPOSE: Variability 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. METHODS: We 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. RESULTS: For 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. CONCLUSIONS: A 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. Frontiers Media S.A. 2023-09-13 /pmc/articles/PMC10525705/ /pubmed/37771435 http://dx.doi.org/10.3389/fonc.2023.1204323 Text en Copyright © 2023 Nelson, Nguyen, Fang, Court, Cardenas, Rhee, Netherton, Mumme, Gay, Gay, Marquez, El Basha, Zhao, Gronberg, Hernandez, Nealon, Martel and Yang https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Nelson, Christopher L. Nguyen, Callistus Fang, Raymond Court, Laurence E. Cardenas, Carlos E. Rhee, Dong Joo Netherton, Tucker J. Mumme, Raymond P. Gay, Skylar Gay, Casey Marquez, Barbara El Basha, Mohammad D. Zhao, Yao Gronberg, Mary Hernandez, Soleil Nealon, Kelly A. Martel, Mary K. Yang, Jinzhong A real-time contouring feedback tool for consensus-based contour training |
title | A real-time contouring feedback tool for consensus-based contour training |
title_full | A real-time contouring feedback tool for consensus-based contour training |
title_fullStr | A real-time contouring feedback tool for consensus-based contour training |
title_full_unstemmed | A real-time contouring feedback tool for consensus-based contour training |
title_short | A real-time contouring feedback tool for consensus-based contour training |
title_sort | real-time contouring feedback tool for consensus-based contour training |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10525705/ https://www.ncbi.nlm.nih.gov/pubmed/37771435 http://dx.doi.org/10.3389/fonc.2023.1204323 |
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