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Validation of an automated contouring and treatment planning tool for pediatric craniospinal radiation therapy

PURPOSE: Treatment planning for craniospinal irradiation (CSI) is complex and time-consuming, especially for resource-constrained centers. To alleviate demanding workflows, we successfully automated the pediatric CSI planning pipeline in previous work. In this work, we validated our CSI autosegmenta...

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Autores principales: Hernandez, Soleil, Burger, Hester, Nguyen, Callistus, Paulino, Arnold C., Lucas, John T., Faught, Austin M., Duryea, Jack, Netherton, Tucker, Rhee, Dong Joo, Cardenas, Carlos, Howell, Rebecca, Fuentes, David, Pollard-Larkin, Julianne, Court, Laurence, Parkes, Jeannette
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10556471/
https://www.ncbi.nlm.nih.gov/pubmed/37810961
http://dx.doi.org/10.3389/fonc.2023.1221792
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author Hernandez, Soleil
Burger, Hester
Nguyen, Callistus
Paulino, Arnold C.
Lucas, John T.
Faught, Austin M.
Duryea, Jack
Netherton, Tucker
Rhee, Dong Joo
Cardenas, Carlos
Howell, Rebecca
Fuentes, David
Pollard-Larkin, Julianne
Court, Laurence
Parkes, Jeannette
author_facet Hernandez, Soleil
Burger, Hester
Nguyen, Callistus
Paulino, Arnold C.
Lucas, John T.
Faught, Austin M.
Duryea, Jack
Netherton, Tucker
Rhee, Dong Joo
Cardenas, Carlos
Howell, Rebecca
Fuentes, David
Pollard-Larkin, Julianne
Court, Laurence
Parkes, Jeannette
author_sort Hernandez, Soleil
collection PubMed
description PURPOSE: Treatment planning for craniospinal irradiation (CSI) is complex and time-consuming, especially for resource-constrained centers. To alleviate demanding workflows, we successfully automated the pediatric CSI planning pipeline in previous work. In this work, we validated our CSI autosegmentation and autoplanning tool on a large dataset from St. Jude Children’s Research Hospital. METHODS: Sixty-three CSI patient CT scans were involved in the study. Pre-planning scripts were used to automatically verify anatomical compatibility with the autoplanning tool. The autoplanning pipeline generated 15 contours and a composite CSI treatment plan for each of the compatible test patients (n=51). Plan quality was evaluated quantitatively with target coverage and dose to normal tissue metrics and qualitatively with physician review, using a 5-point Likert scale. Three pediatric radiation oncologists from 3 institutions reviewed and scored 15 contours and a corresponding composite CSI plan for the final 51 test patients. One patient was scored by 3 physicians, resulting in 53 plans scored total. RESULTS: The algorithm automatically detected 12 incompatible patients due to insufficient junction spacing or head tilt and removed them from the study. Of the 795 autosegmented contours reviewed, 97% were scored as clinically acceptable, with 92% requiring no edits. Of the 53 plans scored, all 51 brain dose distributions were scored as clinically acceptable. For the spine dose distributions, 92%, 100%, and 68% of single, extended, and multiple-field cases, respectively, were scored as clinically acceptable. In all cases (major or minor edits), the physicians noted that they would rather edit the autoplan than create a new plan. CONCLUSIONS: We successfully validated an autoplanning pipeline on 51 patients from another institution, indicating that our algorithm is robust in its adjustment to differing patient populations. We automatically generated 15 contours and a comprehensive CSI treatment plan for each patient without physician intervention, indicating the potential for increased treatment planning efficiency and global access to high-quality radiation therapy.
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spelling pubmed-105564712023-10-07 Validation of an automated contouring and treatment planning tool for pediatric craniospinal radiation therapy Hernandez, Soleil Burger, Hester Nguyen, Callistus Paulino, Arnold C. Lucas, John T. Faught, Austin M. Duryea, Jack Netherton, Tucker Rhee, Dong Joo Cardenas, Carlos Howell, Rebecca Fuentes, David Pollard-Larkin, Julianne Court, Laurence Parkes, Jeannette Front Oncol Oncology PURPOSE: Treatment planning for craniospinal irradiation (CSI) is complex and time-consuming, especially for resource-constrained centers. To alleviate demanding workflows, we successfully automated the pediatric CSI planning pipeline in previous work. In this work, we validated our CSI autosegmentation and autoplanning tool on a large dataset from St. Jude Children’s Research Hospital. METHODS: Sixty-three CSI patient CT scans were involved in the study. Pre-planning scripts were used to automatically verify anatomical compatibility with the autoplanning tool. The autoplanning pipeline generated 15 contours and a composite CSI treatment plan for each of the compatible test patients (n=51). Plan quality was evaluated quantitatively with target coverage and dose to normal tissue metrics and qualitatively with physician review, using a 5-point Likert scale. Three pediatric radiation oncologists from 3 institutions reviewed and scored 15 contours and a corresponding composite CSI plan for the final 51 test patients. One patient was scored by 3 physicians, resulting in 53 plans scored total. RESULTS: The algorithm automatically detected 12 incompatible patients due to insufficient junction spacing or head tilt and removed them from the study. Of the 795 autosegmented contours reviewed, 97% were scored as clinically acceptable, with 92% requiring no edits. Of the 53 plans scored, all 51 brain dose distributions were scored as clinically acceptable. For the spine dose distributions, 92%, 100%, and 68% of single, extended, and multiple-field cases, respectively, were scored as clinically acceptable. In all cases (major or minor edits), the physicians noted that they would rather edit the autoplan than create a new plan. CONCLUSIONS: We successfully validated an autoplanning pipeline on 51 patients from another institution, indicating that our algorithm is robust in its adjustment to differing patient populations. We automatically generated 15 contours and a comprehensive CSI treatment plan for each patient without physician intervention, indicating the potential for increased treatment planning efficiency and global access to high-quality radiation therapy. Frontiers Media S.A. 2023-09-22 /pmc/articles/PMC10556471/ /pubmed/37810961 http://dx.doi.org/10.3389/fonc.2023.1221792 Text en Copyright © 2023 Hernandez, Burger, Nguyen, Paulino, Lucas, Faught, Duryea, Netherton, Rhee, Cardenas, Howell, Fuentes, Pollard-Larkin, Court and Parkes 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
Hernandez, Soleil
Burger, Hester
Nguyen, Callistus
Paulino, Arnold C.
Lucas, John T.
Faught, Austin M.
Duryea, Jack
Netherton, Tucker
Rhee, Dong Joo
Cardenas, Carlos
Howell, Rebecca
Fuentes, David
Pollard-Larkin, Julianne
Court, Laurence
Parkes, Jeannette
Validation of an automated contouring and treatment planning tool for pediatric craniospinal radiation therapy
title Validation of an automated contouring and treatment planning tool for pediatric craniospinal radiation therapy
title_full Validation of an automated contouring and treatment planning tool for pediatric craniospinal radiation therapy
title_fullStr Validation of an automated contouring and treatment planning tool for pediatric craniospinal radiation therapy
title_full_unstemmed Validation of an automated contouring and treatment planning tool for pediatric craniospinal radiation therapy
title_short Validation of an automated contouring and treatment planning tool for pediatric craniospinal radiation therapy
title_sort validation of an automated contouring and treatment planning tool for pediatric craniospinal radiation therapy
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10556471/
https://www.ncbi.nlm.nih.gov/pubmed/37810961
http://dx.doi.org/10.3389/fonc.2023.1221792
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