Abstract
Objective. As cancer survivorship increases, there is growing interest in minimizing the late effects of radiation therapy such as radiogenic second cancer, which may occur anywhere in the body. Assessing the risk of late effects requires knowledge of the dose distribution throughout the whole body, including regions far from the treatment field, beyond the typical anatomical extent of clinical computed tomography (CT) scans. Approach. A hybrid phantom was developed which consists of in-field patient CT images extracted from ground truth whole-body CT scans, out-of-field mesh phantoms scaled to basic patient measurements, and a blended transition region. Four of these hybrid phantoms were created, representing male and female patients receiving proton therapy treatment in pelvic and cranial sites. To assess the performance of the hybrid approach, we simulated treatments using the hybrid phantoms, the scaled and unscaled mesh phantoms, and the ground truth whole-body CTs. We calculated absorbed dose and equivalent dose in and outside of the treatment field, with a focus on neutrons induced in the patient by proton therapy. Proton and neutron dose was calculated using a general purpose Monte Carlo code. Main results. The hybrid phantom provided equal or superior accuracy in calculated organ dose and equivalent dose values relative to those obtained using the mesh phantoms in 78% in all selected organs and calculated dose quantities. Comparatively the default mesh and scaled mesh were equal or superior to the other phantoms in 21% and 28% of cases respectively. Significance. The proposed methodology for hybrid synthesis provides a tool for whole-body organ dose estimation for individual patients without requiring CT scans of their entire body. Such a capability would be useful for personalized assessment of late effects and risk-optimization of treatment plans.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Physik |
Themengebiete: | 500 Naturwissenschaften und Mathematik > 530 Physik |
ISSN: | 0031-9155 |
Sprache: | Englisch |
Dokumenten ID: | 115219 |
Datum der Veröffentlichung auf Open Access LMU: | 02. Apr. 2024, 08:11 |
Letzte Änderungen: | 02. Apr. 2024, 08:11 |