Purpose:To assess the dosimetric impact of interplay between spot-scanning proton beam and respiratory motion in intensity-modulated proton therapy (IMPT) for stage III lung cancer. Methods: Eleven patients were sampled from 112 patients with stage III nonsmall cell lung cancer to well represent the distribution of 112 patients in terms of target size and motion. Clinical target volumes (CTVs) and planning target volumes (PTVs) were defined according to the authors' clinical protocol. Uniform and realistic breathing patterns were considered along with regular-and hypofractionation scenarios. The dose contributed by a spot was fully calculated on the computed tomography (CT) images corresponding to the respiratory phase that the spot is delivered, and then accumulated to the reference phase of the 4DCT to generate the dynamic dose that provides an estimation of what might be delivered under the influence of interplay effect. The dynamic dose distributions at different numbers of fractions were compared with the corresponding 4D composite dose which is the equally weighted average of the doses, respectively, computed on respiratory phases of a 4DCT image set. Results: Under regular fractionation, the average and maximum differences in CTV coverage between the 4D composite and dynamic doses after delivery of all 35 fractions were no more than 0.2% and 0.9%, respectively. The maximum differences between the two dose distributions for the maximum dose to the spinal cord, heart V40, esophagus V55, and lung V20 were 1.2 Gy, 0.1%, 0.8%, and 0.4%, respectively. Although relatively large differences in single fraction, correlated with small CTVs relative to motions, were observed, the authors' biological response calculations suggested that this interfractional dose variation may have limited biological impact. Assuming a hypofractionation scenario, the differences between the 4D composite and dynamic doses were well confined even for single fraction. Conclusions: Despite the presence of interplay effect, the delivered dose may be reliably estimated using the 4D composite dose. In general the interplay effect may not be a primary concern with IMPT for lung cancers for the authors' institution. The described interplay analysis tool may be used to provide additional confidence in treatment delivery.

IMPT's sensitivity to uncertainties can be improved by using robust optimization. They found two possible mechanisms that made improvements possible: (1) a localized single-field uniform dose distribution (LSFUD) mechanism, in which the optimization algorithm attempts to produce a single-field uniform dose distribution while minimizing the patching field as much as possible; and (2) perturbed dose distribution, which follows the change in anatomical geometry. Multiple-instance optimization has more knowledge of the influence matrices; this greater knowledge improves IMPT plans' ability to retain robustness despite the presence of uncertainties.

The purpose of this study was to investigate the feasibility of incorporating linear energy transfer (LET) into the optimization of intensity modulated proton therapy (IMPT) plans. Because increased LET correlates with increased biological effectiveness of protons, high LETs in target volumes and low LETs in critical structures and normal tissues are preferred in an IMPT plan. However, if not explicitly incorporated into the optimization criteria, different IMPT plans may yield similar physical dose distributions but greatly different LET, specifically dose-averaged LET, distributions. Conventionally, the IMPT optimization criteria (or cost function) only includes dose-based objectives in which the relative biological effectiveness (RBE) is assumed to have a constant value of 1.1. In this study, we added LET-based objectives for maximizing LET in target volumes and minimizing LET in critical structures and normal tissues. Due to the fractional programming nature of the resulting model, we used a variable reformulation approach so that the optimization process is computationally equivalent to conventional IMPT optimization. In this study, five brain tumor patients who had been treated with proton therapy at our institution were selected. Two plans were created for each patient based on the proposed LET-incorporated optimization (LETOpt) and the conventional dose-based optimization (DoseOpt). The optimized plans were compared in terms of both dose (assuming a constant RBE of 1.1 as adopted in clinical practice) and LET. Both optimization approaches were able to generate comparable dose distributions. The LET-incorporated optimization achieved not only pronounced reduction of LET values in critical organs, such as brainstem and optic chiasm, but also increased LET in target volumes, compared to the conventional dose-based optimization. However, on occasion, there was a need to tradeoff the acceptability of dose and LET distributions. Our conclusion is that the inclusion of LET-dependent criteria in the IMPT optimization could lead to similar dose distributions as the conventional optimization but superior LET distributions in target volumes and normal tissues. This may have substantial advantages in improving tumor control and reducing normal tissue toxicities.

Purpose The primary aim of this study was to evaluate the impact of interplay effects for intensity-modulated proton therapy (IMPT) plans for lung cancer in the clinical setting. The secondary aim was to explore the technique of iso-layered re-scanning for mitigating these interplay effects. Methods and Materials Single-fraction 4D dynamic dose without considering re-scanning (1FX dynamic dose) was used as a metric to determine the magnitude of dosimetric degradation caused by 4D interplay effects. The 1FX dynamic dose was calculated by simulating the machine delivery processes of proton spot scanning on moving patient described by 4D computed tomography (4DCT) during the IMPT delivery. The dose contributed from an individual spot was fully calculated on the respiratory phase corresponding to the life span of that spot, and the final dose was accumulated to a reference CT phase by using deformable image registration. The 1FX dynamic dose was compared with the 4D composite dose. Seven patients with various tumor volumes and motions were selected. Results The CTV prescription coverage for the 7 patients were 95.04%, 95.38%, 95.39%, 95.24%, 95.65%, 95.90%, and 95.53%, calculated with use of the 4D composite dose, and were 89.30%, 94.70%, 85.47%, 94.09%, 79.69%, 91.20%, and 94.19% with use of the 1FX dynamic dose. For the 7 patients, the CTV coverage, calculated by using single-fraction dynamic dose, were 95.52%, 95.32%, 96.36%, 95.28%, 94.32%, 95.53%, and 95.78%, using maximum MU limit value of 0.005. In other words, by increasing the number of delivered spots in each fraction, the degradation of CTV coverage improved up to 14.6%. Conclusions Single-fraction 4D dynamic dose without re-scanning was validated as a surrogate to evaluate the interplay effects for IMPT for lung cancer in the clinical setting. The interplay effects can be potentially mitigated by increasing the number of iso-layered re-scanning in each fraction delivery.

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.

Uncertainty incorporated BAO may introduce pronounced improvement of IMPT plan quality including dosimetric benefits and robustness over uncertainties, based on the five clinical studies in this paper. In addition, local search algorithms may be more efficient in finding optimal beam angles than global optimization approaches for IMPT BAO.

Intensity-modulated proton therapy (IMPT) is commonly delivered via the spot-scanning technique. To “scan” the target volume, the proton beam is controlled by varying its energy to penetrate the patient’s body at different depths. Although scanning the proton beamlets or spots with the same energy can be as fast as 10–20 m/s, changing from one proton energy to another requires approximately two additional seconds. The total IMPT delivery time thus depends mainly on the number of proton energies used in a treatment. Current treatment planning systems typically use all proton energies that are required for the proton beam to penetrate in a range from the distal edge to the proximal edge of the target. The optimal selection of proton energies has not been well studied. In this study, we sought to determine the feasibility of optimizing and reducing the number of proton energies in IMPT planning. We proposed an iterative mixed-integer programming optimization method to select a subset of all available proton energies while satisfying dosimetric criteria. We applied our proposed method to six patient datasets: four cases of prostate cancer, one case of lung cancer, and one case of mesothelioma. The numbers of energies were reduced by 14.3%–18.9% for the prostate cancer cases, 11.0% for the lung cancer cases, and 26.5% for the mesothelioma case. The results indicate that the number of proton energies used in conventionally designed IMPT plans can be reduced without degrading dosimetric performance. The IMPT delivery efficiency could be improved by energy layer optimization leading to increased throughput for a busy proton center in which a delivery system with slow energy switch is employed.

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