I Martínez-Rovira1, C Jouvie1, S Jan1. 1. Service Hospitalier Frédéric Joliot, Commissariat à l'énergie atomique et aux énergies alternatives (CEA/DSV/I2BM/SHFJ), 4 place du général Leclerc, 91401 Orsay Cedex, France.
Abstract
PURPOSE: The imaging of positron emitting isotopes produced during patient irradiation is the only in vivo method used for hadrontherapy dose monitoring in clinics nowadays. However, the accuracy of this method is limited by the loss of signal due to the metabolic decay processes (biological washout). In this work, a generic modeling of washout was incorporated into the GATE simulation platform. Additionally, the influence of the washout on the β(+) activity distributions in terms of absolute quantification and spatial distribution was studied. METHODS: First, the irradiation of a human head phantom with a (12)C beam, so that a homogeneous dose distribution was achieved in the tumor, was simulated. The generated (11)C and (15)O distribution maps were used as β(+) sources in a second simulation, where the PET scanner was modeled following a detailed Monte Carlo approach. The activity distributions obtained in the presence and absence of washout processes for several clinical situations were compared. RESULTS: Results show that activity values are highly reduced (by a factor of 2) in the presence of washout. These processes have a significant influence on the shape of the PET distributions. Differences in the distal activity falloff position of 4 mm are observed for a tumor dose deposition of 1 Gy (Tini = 0 min). However, in the case of high doses (3 Gy), the washout processes do not have a large effect on the position of the distal activity falloff (differences lower than 1 mm). The important role of the tumor washout parameters on the activity quantification was also evaluated. CONCLUSIONS: With this implementation, GATE/GEANT4 is the only open-source code able to simulate the full chain from the hadrontherapy irradiation to the PET dose monitoring including biological effects. Results show the strong impact of the washout processes, indicating that the development of better models and measurement of biological washout data are essential.
PURPOSE: The imaging of positron emitting isotopes produced during patient irradiation is the only in vivo method used for hadrontherapy dose monitoring in clinics nowadays. However, the accuracy of this method is limited by the loss of signal due to the metabolic decay processes (biological washout). In this work, a generic modeling of washout was incorporated into the GATE simulation platform. Additionally, the influence of the washout on the β(+) activity distributions in terms of absolute quantification and spatial distribution was studied. METHODS: First, the irradiation of a human head phantom with a (12)C beam, so that a homogeneous dose distribution was achieved in the tumor, was simulated. The generated (11)C and (15)O distribution maps were used as β(+) sources in a second simulation, where the PET scanner was modeled following a detailed Monte Carlo approach. The activity distributions obtained in the presence and absence of washout processes for several clinical situations were compared. RESULTS: Results show that activity values are highly reduced (by a factor of 2) in the presence of washout. These processes have a significant influence on the shape of the PET distributions. Differences in the distal activity falloff position of 4 mm are observed for a tumor dose deposition of 1 Gy (Tini = 0 min). However, in the case of high doses (3 Gy), the washout processes do not have a large effect on the position of the distal activity falloff (differences lower than 1 mm). The important role of the tumor washout parameters on the activity quantification was also evaluated. CONCLUSIONS: With this implementation, GATE/GEANT4 is the only open-source code able to simulate the full chain from the hadrontherapy irradiation to the PET dose monitoring including biological effects. Results show the strong impact of the washout processes, indicating that the development of better models and measurement of biological washout data are essential.