TY - JOUR
T1 - Validation of an automated contouring and treatment planning tool for pediatric craniospinal radiation therapy
AU - Hernandez, Soleil
AU - Burger, Hester
AU - Nguyen, Callistus
AU - Paulino, Arnold C.
AU - Lucas, John T.
AU - Faught, Austin M.
AU - Duryea, Jack
AU - Netherton, Tucker
AU - Rhee, Dong Joo
AU - Cardenas, Carlos
AU - Howell, Rebecca
AU - Fuentes, David
AU - Pollard-Larkin, Julianne
AU - Court, Laurence
AU - Parkes, Jeannette
N1 - Publisher Copyright:
Copyright © 2023 Hernandez, Burger, Nguyen, Paulino, Lucas, Faught, Duryea, Netherton, Rhee, Cardenas, Howell, Fuentes, Pollard-Larkin, Court and Parkes.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - autocontouring
KW - autoplanning
KW - global health
KW - pediatrics
KW - radiation oncology
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U2 - 10.3389/fonc.2023.1221792
DO - 10.3389/fonc.2023.1221792
M3 - Article
C2 - 37810961
AN - SCOPUS:85173762104
SN - 2234-943X
VL - 13
JO - Frontiers in Oncology
JF - Frontiers in Oncology
M1 - 1221792
ER -