TY - JOUR
T1 - Validation and Comparison of Radiograph-Based Organ Dose Reconstruction Approaches for Wilms Tumor Radiation Treatment Plans
AU - Wang, Ziyuan
AU - Virgolin, Marco
AU - Balgobind, Brian V.
AU - van Dijk, Irma W. E. M.
AU - Smith, Susan A.
AU - Howell, Rebecca M.
AU - Mille, Matthew M.
AU - Lee, Choonsik
AU - Lee, Choonik
AU - Ronckers, Cécile M.
AU - Bosman, Peter A. N.
AU - Bel, Arjan
AU - Alderliesten, Tanja
N1 - Funding Information: Sources of support: Financial support of this work was provided by Stichting Kinderen Kankervrij (KiKa; project no. 187). Dr Cécile Ronckers was supported by a grant from Dutch Cancer Society (#UVA2012-5517). Funding Information: The authors thank Dr Petra S. Kroon and Dr Geert O. Janssens (Department of Radiation Oncology, University Medical Center Utrecht, Princess Màxima Center for Pediatric Oncology, Utrecht, the Netherlands), Prof.dr. Marcel B. van Herk (Manchester Cancer Research Centre, Division of Cancer Sciences, University of Manchester, United Kingdom), Prof. David C. Hodgson (Department of Radiation Oncology, Princess Margaret Cancer Centre, Canada), and Dr Lorna Zadravec Zaletel (Department of Radiation Oncology, Institute of Oncology Ljubljana, Slovenia) for sharing (anonymized) data (CTs and patient features) of patients treated at their departments for use in the development of the 2 ML based approaches. The authors thank the Maurits en Anna de Kock Stichting for financing a high-performance computing system and Elekta for providing the research software ADMIRE for automatic segmentation for data preparation for the 2 ML-based approaches. Dr Matthew M. Mille and Dr Choonsik Lee performed their portions of this study using the computational resources of the NIH high-performance computing Biowulf cluster (http://hpc.nih.gov). Sources of support: Financial support of this work was provided by Stichting Kinderen Kankervrij (KiKa; project no. 187). Dr Cécile Ronckers was supported by a grant from Dutch Cancer Society (#UVA2012-5517). Disclosures: Dr Alderliesten, Dr Bel, and Prof. dr. Peter A.N. Bosman are involved in projects supported by Elekta. Dr Bel is involved in projects supported by Varian. KiKa, Elekta, and Varian were not involved in the study design, in the collation, analysis or interpretation of data, in the writing of the manuscript, or in the decision to submit the manuscript for publication. Publisher Copyright: © 2022 The Authors
PY - 2022/11/1
Y1 - 2022/11/1
N2 - Purpose: Our purpose was to validate and compare the performance of 4 organ dose reconstruction approaches for historical radiation treatment planning based on 2-dimensional radiographs. Methods and Materials: We considered 10 patients with Wilms tumor with planning computed tomography images for whom we developed typical historic Wilms tumor radiation treatment plans, using anteroposterior and posteroanterior parallel-opposed 6 MV flank fields, normalized to 14.4 Gy. Two plans were created for each patient, with and without corner blocking. Regions of interest (lungs, heart, nipples, liver, spleen, contralateral kidney, and spinal cord) were delineated, and dose-volume metrics including organ mean and minimum dose (Dmean and Dmin) were computed as the reference baseline for comparison. Dosimetry for the 20 plans was then independently reconstructed using 4 different approaches. Three approaches involved surrogate anatomy, among which 2 used demographic-matching criteria for phantom selection/building, and 1 used machine learning. The fourth approach was also machine learning-based, but used no surrogate anatomies. Absolute differences in organ dose-volume metrics between the reconstructed and the reference values were calculated. Results: For Dmean and Dmin (average and minimum point dose) all 4 dose reconstruction approaches performed within 10% of the prescribed dose (≤1.4 Gy). The machine learning-based approaches showed a slight advantage for several of the considered regions of interest. For Dmax (maximum point dose), the absolute differences were much higher, that is, exceeding 14% (2 Gy), with the poorest agreement observed for near-beam and out-of-beam organs for all approaches. Conclusions: The studied approaches give comparable dose reconstruction results, and the choice of approach for cohort dosimetry for late effects studies should still be largely driven by the available resources (data, time, expertise, and funding).
AB - Purpose: Our purpose was to validate and compare the performance of 4 organ dose reconstruction approaches for historical radiation treatment planning based on 2-dimensional radiographs. Methods and Materials: We considered 10 patients with Wilms tumor with planning computed tomography images for whom we developed typical historic Wilms tumor radiation treatment plans, using anteroposterior and posteroanterior parallel-opposed 6 MV flank fields, normalized to 14.4 Gy. Two plans were created for each patient, with and without corner blocking. Regions of interest (lungs, heart, nipples, liver, spleen, contralateral kidney, and spinal cord) were delineated, and dose-volume metrics including organ mean and minimum dose (Dmean and Dmin) were computed as the reference baseline for comparison. Dosimetry for the 20 plans was then independently reconstructed using 4 different approaches. Three approaches involved surrogate anatomy, among which 2 used demographic-matching criteria for phantom selection/building, and 1 used machine learning. The fourth approach was also machine learning-based, but used no surrogate anatomies. Absolute differences in organ dose-volume metrics between the reconstructed and the reference values were calculated. Results: For Dmean and Dmin (average and minimum point dose) all 4 dose reconstruction approaches performed within 10% of the prescribed dose (≤1.4 Gy). The machine learning-based approaches showed a slight advantage for several of the considered regions of interest. For Dmax (maximum point dose), the absolute differences were much higher, that is, exceeding 14% (2 Gy), with the poorest agreement observed for near-beam and out-of-beam organs for all approaches. Conclusions: The studied approaches give comparable dose reconstruction results, and the choice of approach for cohort dosimetry for late effects studies should still be largely driven by the available resources (data, time, expertise, and funding).
UR - http://www.scopus.com/inward/record.url?scp=85136473082&partnerID=8YFLogxK
U2 - https://doi.org/10.1016/j.adro.2022.101015
DO - https://doi.org/10.1016/j.adro.2022.101015
M3 - Article
C2 - 36060631
SN - 2452-1094
VL - 7
JO - Advances in Radiation Oncology
JF - Advances in Radiation Oncology
IS - 6
M1 - 101015
ER -