Background and purpose: Dose painting by numbers (DPBN) require a high degree of dose modulation to fulfill the image-based voxel wise dose prescription. The aim of this study was to assess the dosimetric accuracy of 18F-fluoro-2-deoxy-glucose positron emission tomography(18F-FDG-PET)-based DPBN in an anthropomorphic lung phantom using alanine dosimetry.
Materials and methods: A linear dose prescription based on 18F-FDG-PET image intensities within the gross tumor volume (GTV) of a lung cancer patient was employed. One DPBN scheme with low dose modulation (Scheme A; minimum/maximum fraction dose to the GTV 2.92/4.26 Gy) and one with a high modulation (Scheme B; 2.81/4.52 Gy) were generated. The plans were transferred to a computed tomograpy (CT) scan of a thorax phantom based on CT images of the patient. Using volumetric modulated arc therapy (VMAT), DPBN was delivered to the phantom with embedded alanine dosimeters. A plan was also delivered to an intentionally misaligned phantom. Absorbed doses at various points in the phantom were measured by alanine dosimetry.
Results: A pointwise comparison between GTV doses from prescription, treatment plan calculation and VMAT delivery showed high correspondence, with a mean and maximum dose difference of <0.1 Gy and 0.3 Gy, respectively. No difference was found in dosimetric accuracy between scheme A and B. The misalignment caused deviations up to 1 Gy between prescription and delivery.
Conclusion: DPBN can be delivered with high accuracy, showing that the treatment may be applied correctly from a dosimetric perspective. Still, misalignment may cause considerable dosimetric erros, indicating the need for patient immobilization and monitoring.
Keywords: Dose painting by numbers; Dose painting by numbers, DPBN; Electron paramagnetic resonance; Electron paramagnetic resonance, EPR; Imaging for radiotherapy; Radiotherapy; Volumetric modulated arc radiotherapy, VMAT; Volumetric modulated arc therapy.
© 2022 Published by Elsevier B.V. on behalf of European Society of Radiotherapy & Oncology.