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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
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.
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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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