Validation and Comparison of Radiograph-Based Organ Dose Reconstruction Approaches for Wilms Tumor Radiation Treatment Plans.

Autor: Wang Z; Department of Radiation Oncology, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands., Virgolin M; Life Sciences and Health Research Group, Centrum Wiskunde & Informatica (CWI), Science Park 123, 1098 XG, Amsterdam, the Netherlands., Balgobind BV; Department of Radiation Oncology, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands., van Dijk IWEM; Department of Radiation Oncology, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands., Smith SA; Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas., Howell RM; Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas., Mille MM; Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland., Lee C; Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland., Lee C; Division of Radiation Oncology, University of Michigan, Ann Arbor, Michigan., Ronckers CM; Princess Máxima Center for Paediatric Oncology, Utrecht, the Netherlands.; Institute of Biostatistics and Registry Research, Brandenburg Medical School, Neuruppin, Germany., Bosman PAN; Life Sciences and Health Research Group, Centrum Wiskunde & Informatica (CWI), Science Park 123, 1098 XG, Amsterdam, the Netherlands., Bel A; Department of Radiation Oncology, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands., Alderliesten T; Department of Radiation Oncology, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands.; Department of Radiation Oncology, Leiden University Medical Center, Albinusdreef 2, 2333 ZA, Leiden, the Netherlands.
Jazyk: angličtina
Zdroj: Advances in radiation oncology [Adv Radiat Oncol] 2022 Jul 04; Vol. 7 (6), pp. 101015. Date of Electronic Publication: 2022 Jul 04 (Print Publication: 2022).
DOI: 10.1016/j.adro.2022.101015
Abstrakt: 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 (D mean and D min ) 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 D mean and D min (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 D max (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).
(© 2022 The Authors.)
Databáze: MEDLINE
Externí odkaz: