Algorithms for the optimization of RBE-weighted dose in particle therapy

Dosimetric comparison of robust angles in carbon-ion radiation therapy for prostate cancer

The objective of this study is to compare the plan robustness at various beam angles. Hence, the influence of the beam angles on robustness and linear energy transfer (LET) was evaluated in gantry-based carbon-ion radiation therapy (CIRT) for prostate cancer. 10 patients with prostate cancer were considered, and a total dose of 51.6 Gy (Relative biological effectiveness (RBE) was prescribed for the target volume in 12 fractions. Five beam field plans comprising two opposed fields with different angle pairs were characterized. Further, dose parameters were extracted, and the RBE-weighted dose and LET values for all angle pairs were compared. All plans considering the setup uncertainty satisfied the dose regimen. When a parallel beam pair was used for perturbed scenarios to take into account set-up uncertainty in the anterior direction, the LET clinical treatment volume (CTV) D _95% standard deviation was 1.5 times higher, and the standard deviation of RBE-weighted CTV D _95% was 7.9 times higher compared to an oblique pair. The oblique beam fields were superior in terms of dose sparing for the rectum compared to the dose distribution using two conventional lateral opposed fields for prostate cancer.

Including Volume Effects in Biological Treatment Plan Optimization for Carbon Ion Therapy: Generalized Equivalent Uniform Dose-Based Objective in TRiP98

We describe a way to include biologically based objectives in plan optimization specific for carbon ion therapy, beyond the standard voxel-dose-based criteria already implemented in TRiP98, research planning software for ion beams. The aim is to account for volume effects—tissue architecture-dependent response to damage—in the optimization procedure, using the concept of generalized equivalent uniform dose (gEUD), which is an expression to convert a heterogeneous dose distribution (e.g., in an organ at risk (OAR)) into a uniform dose associated with the same biological effect. Moreover, gEUD is closely related to normal tissue complication probability (NTCP). The multi-field optimization problem here takes also into account the relative biological effectiveness (RBE), which in the case of ion beams is not factorizable and introduces strong non-linearity. We implemented the gEUD-based optimization in TRiP98, allowing us to control the whole dose–volume histogram (DVH) shape of OAR with a single objective by adjusting the prescribed gEUD₀ and the volume effect parameter a, reducing the volume receiving dose levels close to mean dose when a = 1 (large volume effect) while close to maximum dose for a >> 1 (small volume effect), depending on the organ type considered. We studied the role of gEUD₀ and a in the optimization, and we compared voxel-dose-based and gEUD-based optimization in chordoma cases with different anatomies. In particular, for a plan containing multiple OARs, we obtained the same target coverage and similar DVHs for OARs with a small volume effect while decreasing the mean dose received by the proximal parotid, thus reducing its NTCP by a factor of 2.5. Further investigations are done for this plan, considering also the distal parotid gland, obtaining a NTCP reduction by a factor of 1.9 for the proximal and 2.9 for the distal one. In conclusion, this novel optimization method can be applied to different OARs, but it achieves the largest improvement for organs whose volume effect is larger. This allows TRiP98 to perform a double level of biologically driven optimization for ion beams, including at the same time RBE-weighted dose and volume effects in inverse planning. An outlook is presented on the possible extension of this method to the target.

Silicon 3D Microdetectors for Microdosimetry in Hadron Therapy

The present overview describes the evolution of new microdosimeters developed in the National Microelectronics Center in Spain (IMB-CNM, CSIC), ranging from the first ultra-thin 3D diodes (U3DTHINs) to the advanced 3D-cylindrical microdetectors, which have been developed over the last 10 years. In this work, we summarize the design, main manufacture processes, and electrical characterization of these devices. These sensors were specifically customized for use in particle therapy and overcame some of the technological challenges in this domain, namely the low noise capability, well-defined sensitive volume, high spatial resolution, and pile-up robustness. Likewise, both architectures reduce the loss of charge carriers due to trapping effects, the charge collection time, and the voltage required for full depletion compared to planar silicon detectors. In particular, a 3D‒cylindrical architecture with electrodes inserted into the silicon bulk and with a very well‒delimited sensitive volume (SV) mimicked a cell array with shapes and sizes similar to those of mammalian cells for the first time. Experimental tests of the carbon beamlines at the Grand Accélérateur National d’Lourds (GANIL, France) and Centro Nazionale Adroterapia Oncologica (CNAO, Italy) showed the feasibility of the U3DTHINs in hadron therapy beams and the good performance of the 3D‒cylindrical microdetectors for assessing linear energy distributions of clinical beams, with clinical fluence rates of 5 × 10⁷ s⁻¹cm⁻² without saturation. The dose-averaged lineal energies showed a generally good agreement with Monte Carlo simulations. The results indicated that these devices can be used to characterize the microdosimetric properties in hadron therapy, even though the charge collection efficiency (CCE) and electronic noise may pose limitations on their performance, which is studied and discussed herein. In the last 3D‒cylindrical microdetector generation, we considerably improved the CCE due to the microfabrication enhancements, which have led to shallower and steeper dopant profiles. We also summarize the successive microdosimetric characterizations performed with both devices in proton and carbon beamlines.

Radiobiological issues in proton therapy

BACKGROUND

The relative biological effectiveness (RBE) for particle therapy is a complex function of particle type, radiation dose, linear energy transfer (LET), cell type, endpoint, etc. In the clinical practice of proton therapy, the RBE is assumed to have a fixed value of 1.1. This assumption, along with the effects of physical uncertainties, may mean that the biologically effective dose distributions received by the patient may be significantly different from what is seen on treatment plans. This may contribute to unforeseen toxicities and/or failure to control the disease. Variability of Proton RBE: It has been shown experimentally that proton RBE varies significantly along the beam path, especially near the end of the particle range. While there is now an increasing acceptance that proton RBE is variable, there is an ongoing debate about whether to change the current clinical practice. Clinical Evidence: A rationale against the change is the uncertainty in the models of variable RBE. Secondly, so far there is no clear clinical evidence of the harm of assuming proton RBE to be 1.1. It is conceivable, however, that the evidence is masked partially by physical uncertainties. It is, therefore, plausible that reduction in uncertainties and their incorporation in the estimation of dose actually delivered may isolate and reveal the variability of RBE in clinical practice. Nevertheless, clinical evidence of RBE variability is slowly emerging as more patients are treated with protons and their response data are analyzed. Modelling and Incorporation of RBE in the Optimization of Proton Therapy: The improvement in the knowledge of RBE could lead to better understanding of outcomes of proton therapy and in the improvement of models to predict RBE. Prospectively, the incorporation of such models in the optimization of intensity-modulated proton therapy could lead to improvements in the therapeutic ratio of proton therapy.

Kill-painting of hypoxic tumours in charged particle therapy

Solid tumours often present regions with severe oxygen deprivation (hypoxia), which are resistant to both chemotherapy and radiotherapy. Increased radiosensitivity as a function of the oxygen concentration is well described for X-rays. It has also been demonstrated that radioresistance in anoxia is reduced using high-LET radiation rather than conventional X-rays. However, the dependence of the oxygen enhancement ratio (OER) on radiation quality in the regions of intermediate oxygen concentrations, those normally found in tumours, had never been measured and biophysical models were based on extrapolations. Here we present a complete survival dataset of mammalian cells exposed to different ions in oxygen concentration ranging from normoxia (21%) to anoxia (0%). The data were used to generate a model of the dependence of the OER on oxygen concentration and particle energy. The model was implemented in the ion beam treatment planning system to prescribe uniform cell killing across volumes with heterogeneous radiosensitivity. The adaptive treatment plans have been validated in two different accelerator facilities, using a biological phantom where cells can be irradiated simultaneously at three different oxygen concentrations. We thus realized a hypoxia-adapted treatment plan, which will be used for painting by voxel of hypoxic tumours visualized by functional imaging.

4D optimization of scanned ion beam tracking therapy for moving tumors

Motion mitigation strategies are needed to fully realize the theoretical advantages of scanned ion beam therapy for patients with moving tumors. The purpose of this study was to determine whether a new four-dimensional (4D) optimization approach for scanned-ion-beam tracking could reduce dose to avoidance volumes near a moving target while maintaining target dose coverage, compared to an existing 3D-optimized beam tracking approach. We tested these approaches computationally using a simple 4D geometrical phantom and a complex anatomic phantom, that is, a 4D computed tomogram of the thorax of a lung cancer patient. We also validated our findings using measurements of carbon-ion beams with a motorized film phantom. Relative to 3D-optimized beam tracking, 4D-optimized beam tracking reduced the maximum predicted dose to avoidance volumes by 53% in the simple phantom and by 13% in the thorax phantom. 4D-optimized beam tracking provided similar target dose homogeneity in the simple phantom (standard deviation of target dose was 0.4% versus 0.3%) and dramatically superior homogeneity in the thorax phantom (D5-D95 was 1.9% versus 38.7%). Measurements demonstrated that delivery of 4D-optimized beam tracking was technically feasible and confirmed a 42% decrease in maximum film exposure in the avoidance region compared with 3D-optimized beam tracking. In conclusion, we found that 4D-optimized beam tracking can reduce the maximum dose to avoidance volumes near a moving target while maintaining target dose coverage, compared with 3D-optimized beam tracking.

Including oxygen enhancement ratio in ion beam treatment planning: model implementation and experimental verification

We present a method for adapting a biologically optimized treatment planning for particle beams to a spatially inhomogeneous tumor sensitivity due to hypoxia, and detected e.g., by PET functional imaging. The TRiP98 code, established treatment planning system for particles, has been extended for including explicitly the oxygen enhancement ratio (OER) in the biological effect calculation, providing the first set up of a dedicated ion beam treatment planning approach directed to hypoxic tumors, TRiP-OER, here reported together with experimental tests. A simple semi-empirical model for calculating the OER as a function of oxygen concentration and dose averaged linear energy transfer, generating input tables for the program is introduced. The code is then extended in order to import such tables coming from the present or alternative models, accordingly and to perform forward and inverse planning, i.e., predicting the survival response of differently oxygenated areas as well as optimizing the required dose for restoring a uniform survival effect in the whole irradiated target. The multiple field optimization results show how the program selects the best beam components for treating the hypoxic regions. The calculations performed for different ions, provide indications for the possible clinical advantages of a multi-ion treatment. Finally the predictivity of the code is tested through dedicated cell culture experiments on extended targets irradiation using specially designed hypoxic chambers, providing a qualitative agreement, despite some limits in full survival calculations arising from the RBE assessment. The comparison of the predictions resulting by using different model tables are also reported.