Combined RBE and OER optimization in proton therapy with FLUKA based on EF5-PET

Introduction Tumor hypoxia is associated with poor treatment outcome. Hypoxic regions are more radioresistant than well-oxygenated regions, as quantified by the oxygen enhancement ratio (OER). In optimization of proton therapy, including OER in addition to the relative biological effectiveness (RBE) could therefore be used to adapt to patient-specific radioresistance governed by intrinsic radiosensitivity and hypoxia. Methods A combined RBE and OER weighted dose (ROWD) calculation method was implemented in a FLUKA Monte Carlo (MC) based treatment planning tool. The method is based on the linear quadratic model, with α and β parameters as a function of the OER, and therefore a function of the linear energy transfer (LET) and partial oxygen pressure (pO2). Proton therapy plans for two head and neck cancer (HNC) patients were optimized with pO2 estimated from [18F]-EF5 positron emission tomography (PET) images. For the ROWD calculations, an RBE of 1.1 (RBE1.1,OER) and two variable RBE models, Rørvik (ROR) and McNamara (MCN), were used, alongside a reference plan without incorporation of OER (RBE1.1). Results For the HNC patients, treatment plans in line with the prescription dose and with acceptable target ROWD could be generated with the established tool. The physical dose was the main factor modulated in the ROWD. The impact of incorporating OER during optimization of HNC patients was demonstrated by the substantial difference found between ROWD and physical dose in the hypoxic tumor region. The largest physical dose differences between the ROWD optimized plans and the reference plan was 12.2 Gy. Conclusion The FLUKA MC based tool was able to optimize proton treatment plans taking the tumor pO2 distribution from hypoxia PET images into account. Independent of RBE-model, both elevated LET and physical dose were found in the hypoxic regions, which shows the potential to increase the tumor control compared to a conventional optimization approach.publishedVersio

The FLUKA Monte Carlo code coupled with an OER model for biologically weighted dose calculations in proton therapy of hypoxic tumors

Introduction The increased radioresistance of hypoxic cells compared to well-oxygenated cells is quantified by the oxygen enhancement ratio (OER). In this study we created a FLUKA Monte Carlo based tool for inclusion of both OER and relative biological effectiveness (RBE) in biologically weighted dose (ROWD) calculations in proton therapy and applied this to explore the impact of hypoxia. Methods The RBE-weighted dose was adapted for hypoxia by making RBE model parameters dependent on the OER, in addition to the linear energy transfer (LET). The OER depends on the partial oxygen pressure (pO2) and LET. To demonstrate model performance, calculations were done with spread-out Bragg peaks (SOBP) in water phantoms with pO2 ranging from strongly hypoxic to normoxic (0.01–30 mmHg) and with a head and neck cancer proton plan optimized with an RBE of 1.1 and pO2 estimated voxel-by-voxel using [18F]-EF5 PET. An RBE of 1.1 and the Rørvik RBE model were used for the ROWD calculations. Results The SOBP in water had decreasing ROWD with decreasing pO2. In the plans accounting for oxygenation, the median target doses were approximately a factor 1.1 lower than the corresponding plans which did not consider the OER. Hypoxia adapted target ROWDs were considerably more heterogeneous than the RBE1.1-weighted doses. Conclusion We realized a Monte Carlo based tool for calculating the ROWD. Read-in of patient pO2 and estimation of ROWD with flexibility in choice of RBE model was achieved, giving a tool that may be useful in future clinical applications of hypoxia-guided particle therapy.publishedVersio

High resolution time-course mapping of early transcriptomic, molecular and cellular phenotypes in Huntington\u27s disease CAG knock-in mice across multiple genetic backgrounds.

Huntington\u27s disease is a dominantly inherited neurodegenerative disease caused by the expansion of a CAG repeat in the HTT gene. In addition to the length of the CAG expansion, factors such as genetic background have been shown to contribute to the age at onset of neurological symptoms. A central challenge in understanding the disease progression that leads from the HD mutation to massive cell death in the striatum is the ability to characterize the subtle and early functional consequences of the CAG expansion longitudinally. We used dense time course sampling between 4 and 20 postnatal weeks to characterize early transcriptomic, molecular and cellular phenotypes in the striatum of six distinct knock-in mouse models of the HD mutation. We studied the effects of the HttQ111 allele on the C57BL/6J, CD-1, FVB/NCr1, and 129S2/SvPasCrl genetic backgrounds, and of two additional alleles, HttQ92 and HttQ50, on the C57BL/6J background. We describe the emergence of a transcriptomic signature in HttQ111/+  mice involving hundreds of differentially expressed genes and changes in diverse molecular pathways. We also show that this time course spanned the onset of mutant huntingtin nuclear localization phenotypes and somatic CAG-length instability in the striatum. Genetic background strongly influenced the magnitude and age at onset of these effects. This work provides a foundation for understanding the earliest transcriptional and molecular changes contributing to HD pathogenesis

The FLUKA Monte Carlo code coupled with an OER model for biologically weighted dose calculations in proton therapy of hypoxic tumors

Introduction: The increased radioresistance of hypoxic cells compared to well-oxygenated cells is quantified by the oxygen enhancement ratio (OER). In this study we created a FLUKA Monte Carlo based tool for inclusion of both OER and relative biological effectiveness (RBE) in biologically weighted dose (ROWD) calculations in proton therapy and applied this to explore the impact of hypoxia.Methods: The RBE-weighted dose was adapted for hypoxia by making RBE model parameters dependent on the OER, in addition to the linear energy transfer (LET). The OER depends on the partial oxygen pressure (pO(2)) and LET. To demonstrate model performance, calculations were done with spread-out Bragg peaks (SOBP) in water phantoms with pO(2) ranging from strongly hypoxic to normoxic (0.01-30 mmHg) and with a head and neck cancer proton plan optimized with an RBE of 1.1 and pO(2) estimated voxel-by-voxel using [F-18]-EF5 PET. An RBE of 1.1 and the Rorvik RBE model were used for the ROWD calculations.Results: The SOBP in water had decreasing ROWD with decreasing pO(2). In the plans accounting for oxygenation, the median target doses were approximately a factor 1.1 lower than the corresponding plans which did not consider the OER. Hypoxia adapted target ROWDs were considerably more heterogeneous than the RBE1.1-weighted doses.Conclusion: We realized a Monte Carlo based tool for calculating the ROWD. Read-in of patient pO(2) and estimation of ROWD with flexibility in choice of RBE model was achieved, giving a tool that may be useful in future clinical applications of hypoxia-guided particle therapy.</div

The FLUKA Monte Carlo code coupled with an OER model for biologically weighted dose calculations in proton therapy of hypoxic tumors

Introduction The increased radioresistance of hypoxic cells compared to well-oxygenated cells is quantified by the oxygen enhancement ratio (OER). In this study we created a FLUKA Monte Carlo based tool for inclusion of both OER and relative biological effectiveness (RBE) in biologically weighted dose (ROWD) calculations in proton therapy and applied this to explore the impact of hypoxia. Methods The RBE-weighted dose was adapted for hypoxia by making RBE model parameters dependent on the OER, in addition to the linear energy transfer (LET). The OER depends on the partial oxygen pressure (pO2) and LET. To demonstrate model performance, calculations were done with spread-out Bragg peaks (SOBP) in water phantoms with pO2 ranging from strongly hypoxic to normoxic (0.01–30 mmHg) and with a head and neck cancer proton plan optimized with an RBE of 1.1 and pO2 estimated voxel-by-voxel using [18F]-EF5 PET. An RBE of 1.1 and the Rørvik RBE model were used for the ROWD calculations. Results The SOBP in water had decreasing ROWD with decreasing pO2. In the plans accounting for oxygenation, the median target doses were approximately a factor 1.1 lower than the corresponding plans which did not consider the OER. Hypoxia adapted target ROWDs were considerably more heterogeneous than the RBE1.1-weighted doses. Conclusion We realized a Monte Carlo based tool for calculating the ROWD. Read-in of patient pO2 and estimation of ROWD with flexibility in choice of RBE model was achieved, giving a tool that may be useful in future clinical applications of hypoxia-guided particle therapy