Search

Purpose: Arguably, intensity-modulated radiotherapy (IMRT) is one of the most important contributions by physicists in medicine to the treatment of cancer. It enabled the achievement of dose distributions that allowed treatment of targets to high doses and yet spared normal tissues to degrees previously considered virtually impossible. The concept underlying IMRT for photons, originally called "inverse planning," was introduced by Anders Brahme in the early 1980s. Since then, many physicists have been conducting research to advance the state of the art, to overcome obstacles discovered and to develop tools and techniques to translate it clinically. IMRT was first implemented clinically the early 1990's. Soon thereafter, it was also incorporated into intensity modulated particle therapy (IMPT), initially for protons and eventually for ions heavier than protons., Methods: In IMRT, intensities of small segments or beamlets of multiple incident beams are optimized to produce the best approximation of desired dose distributions that deliver the requisite tumor dose and maximally spare normal tissues. Such dose distributions are delivered using dynamic multi-leaf collimators whose leaves move continuously while the radiation is on or in a step-and-shoot fashion. For IMPT, there is an extra degree of freedom, that of energies of particle beamlets, which are part of the optimization process. IMPT dose distributions allow substantial additional sparing of normal tissues. They are delivered using scanning beams., Results: IMRT and IMPT represents a true paradigm shift in the way cancer patients are treated. Their evolution, especially that of IMPT, is still ongoing, with new advancements being added continually. With the improving understanding of the immunomodulatory effects of radiotherapy, it is quite plausible that a combination of IMPT and immunotherapy will mature into one of the most effective ways of treating not just localized cancers but also systemic disease., (© 2022 American Association of Physicists in Medicine.)

Background: Successful generation of biomechanical-model-based deformable image registration (BM-DIR) relies on user-defined parameters that dictate surface mesh quality. The trial-and-error process to determine the optimal parameters can be labor-intensive and hinder DIR efficiency and clinical workflow., Purpose: To identify optimal parameters in surface mesh generation as boundary conditions for a BM-DIR in longitudinal liver and lung CT images to facilitate streamlined image registration processes., Methods: Contrast-enhanced CT images of 29 colorectal liver cancer patients and end-exhale four-dimensional CT images of 26 locally advanced non-small cell lung cancer patients were collected. Different combinations of parameters that determine the triangle mesh quality (voxel side length and triangle edge length) were investigated. The quality of DIRs generated using these parameters was evaluated with metrics for geometric accuracy, robustness, and efficiency. Metrics for geometric accuracy included target registration error (TRE) of internal vessel bifurcations, dice similar coefficient (DSC), mean distance to agreement (MDA), Hausdorff distance (HD) for organ contours, and number of vertices in the triangle mesh. American Association of Physicists in Medicine Task Group 132 was used to ensure parameters met TRE, DSC, MDA recommendations before the comparison among the parameters. Robustness was evaluated as the success rate of DIR generation, and efficiency was evaluated as the total time to generate boundary conditions and compute finite element analysis., Results: Voxel side length of 0.2 cm and triangle edge length of 3 were found to be the optimal parameters for both liver and lung, with success rate of 1.00 and 0.98 and average DIR computation time of 100 and 143 s, respectively. For this combination, the average TRE, DSC, MDA, and HD were 0.38-0.40, 0.96-0.97, 0.09-0.12, and 0.87-1.17 mm, respectively., Conclusion: The optimal parameters were found for the analyzed patients. The decision-making process described in this study serves as a recommendation for BM-DIR algorithms to be used for liver and lung. These parameters can facilitate consistence in the evaluation of published studies and more widespread utilization of BM-DIR in clinical practice., (© 2022 American Association of Physicists in Medicine.)

Background: Radiation with high dose rate (FLASH) has shown to reduce toxicities to normal tissues around the target and maintain tumor control with the same amount of dose compared to conventional radiation. This phenomenon has been widely studied in electron therapy, which is often used for shallow tumor treatment. Proton therapy is considered a more suitable treatment modality for deep-seated tumors. The feasibility of FLASH proton therapy has recently been demonstrated by a series of pre- and clinical trials. One of the challenges is to efficiently generate wide enough dose distributions in both lateral and longitudinal directions to cover the entire tumor volume. The goal of this paper is to introduce a set of automatic FLASH proton beam optimization algorithms developed recently., Purpose: To develop a fast and efficient optimizer for the design of a passive scattering proton FLASH radiotherapy delivery at The University of Texas MD Anderson Proton Therapy Center, based on the fast dose calculator (FDC)., Methods: A track-repeating algorithm, FDC, was validated versus Geant4 simulations and applied to calculate dose distributions in various beamline setups. The design of the components was optimized to deliver homogeneous fields with well-defined diameters between 11.0 and 20.5 mm, as well as a spread-out Bragg peak (SOBP) with modulations between 8.5 and 39.0 mm. A ridge filter, a high-Z material scatterer, and a collimator with range compensator were inserted in the beam path, and their shapes and sizes were optimized to spread out the Bragg peak, widen the beam, and reduce the penumbra. The optimizer was developed and tested using two proton energies (87.0 and 159.5 MeV) in a variety of beamline arrangements. Dose rates of the optimized beams were estimated by scaling their doses to those of unmodified beams., Results: The optimized 87.0-MeV beams, with a distance from the beam pipe window to the phantom surface (window-to-surface distance [WSD]) of 550 mm, produced an 8.5-mm-wide SOBP (proximal 90% to distal 90% of the maximum dose); 14.5, 12.0, and 11.0-mm lateral widths at the 50%, 80%, and 90% dose location, respectively; and a 2.5-mm penumbra from 80% to 20% in the lateral profile. The 159.5-MeV beam had an SOBP of 39.0 mm and lateral widths of 20.5, 15.0, and 12.5 mm at 50%, 80%, and 90% dose location, respectively, when the WSD was 550 mm. Wider lateral widths were obtained with increased WSD. The SOBP modulations changed when the ridge filters with different characteristics were inserted. Dose rates on the beam central axis for all optimized beams (other than the 87.0-MeV beam with 2000-mm WSD) were above that needed for the FLASH effect threshold (40 Gy/s) except at the very end of the depth dose profile scaling with a dose rate of 1400 Gy/s at the Bragg peak in the unmodified beams. The optimizer was able to instantly design the individual beamline components for each of the beamline setups, without the need of time intensive iterative simulations., Conclusion: An efficient system, consisting of an optimizer and an FDC have been developed and validated in a variety of beamline setups, comprising two proton energies, several WSDs, and SOBPs. The set of automatic optimization algorithms produces beam shaping element designs efficiently and with excellent quality., (© 2022 American Association of Physicists in Medicine.)

Purpose: Recent studies have shown that severe depletion of the absolute lymphocyte count (ALC) induced by radiation therapy (RT) has been associated with poor overall survival of patients with many solid tumors. In this paper, we aimed to predict radiation-induced lymphocyte depletion in esophageal cancer patients during the course of RT based on patient characteristics and dosimetric features., Methods: We proposed a hybrid deep learning model in a stacked structure to predict a trend toward ALC depletion based on the clinical information before or at the early stages of RT treatment. The proposed model consisted of four channels, one channel based on long short-term memory (LSTM) network and three channels based on neural networks, to process four categories of features followed by a dense layer to integrate the outputs of four channels and predict the weekly ALC values. Moreover, a discriminative kernel was developed to extract temporal features and assign different weights to each part of the input sequence that enabled the model to focus on the most relevant parts. The proposed model was trained and tested on a dataset of 860 esophageal cancer patients who received concurrent chemoradiotherapy., Results: The performance of the proposed model was evaluated based on several important prediction metrics and compared to other commonly used prediction models. The results showed that the proposed model outperformed off-the-shelf prediction methods with at least a 30% reduction in the mean squared error (MSE) of weekly ALC predictions based on pretreatment data. Moreover, using an extended model based on augmented first-week treatment, data reduced the MSE of predictions by 70% compared to the model based on the pretreatment data., Conclusions: In conclusion, our model performed well in predicting radiation-induced lymphocyte depletion for RT treatment planning. The ability to predict ALC will enable physicians to evaluate individual RT treatment plans for lymphopenia risk and to identify patients at high risk who would benefit from modified treatment approaches., (© 2022 American Association of Physicists in Medicine.)

Purpose: Proton beam therapy has been found to have enhanced biological effectiveness in targets that contain the boron isotope 11 B, with the alpha particles resulting from the p + 11 B → 3α reaction being hypothesized as the mechanism; in this study, we aimed to elucidate the causes of the enhanced biological effectiveness of proton-boron fusion therapy by performing a detailed Monte Carlo study of the p + 11 B → 3α reaction in a phantom geometry., Methods: We utilized the Geant4 toolkit to create Monte Carlo particle physics simulations. These simulations consisted of a proton beam with a range 30 mm, creating a Spread-Out Bragg Peak with a modulation width of 10 mm, directed into a water phantom containing a region of boron material. Energy deposition, particle energy, and particle fluence were scored along the path of the beam and grouped by particle species. The scoring was performed using a series of cylindrical volumes with a radius of 2.5 mm and depth of 0.1 mm, constructed such that the depth was parallel to the proton beam. Root was then used to perform the data analysis., Results: Our simulations showed that the dose delivered by alpha particles produced by p + 11 B → 3α was several orders of magnitude lower than the dose delivered directly by protons, even when the boron uptake region was comprised entirely of natural boron or pure 11 B., Conclusions: Our findings do not support the theory that an alpha particle-based mechanism is responsible for the enhanced biological effectiveness of proton-boron fusion therapy. We conclude that any enhanced biological effect seen in experimental studies was not caused by fusion reactions between protons and 11 B nuclei. However, it is necessary to reproduce the past experiments that indicated significant dose enhancement., (© 2021 American Association of Physicists in Medicine.)

Purpose: The main purpose of this work was to generate and validate the dosimetric accuracy of proton beams of dimensions that are appropriate for in vivo small animal and in vitro ultrahigh dose rate (FLASH) radiotherapy experiments using a synchrotron-based treatment delivery system. This study was performed to enable future investigations of the relevance of a spread-out Bragg peak (SOBP) under FLASH conditions., Methods: The spill characteristics of the small field fixed horizontal beam line were modified to deliver accelerated protons in times as short as 2 ms and to control the dose delivered. A Gaussian-like transverse beam profile was transformed into a square uniform one at FLASH dose rates, while avoiding low-dose regions, a crucial requirement to protect normal tissue during FLASH irradiation. Novel beam-shaping devices were designed using Monte Carlo techniques to produce up to about 6 cm 3 of uniform dose in SOBPs while maximizing the dose rate. These included a scattering foil, a conical flattening filter to maximize the flux of protons into the region of interest, energy filters, range compensators, and collimators. The shapes, sizes, and positions of the components were varied to provide the required field sizes and SOBPs., Results: The designed and fabricated devices were used to produce 10-, 15-, and 20-mm diameter, circular field sizes and 10-, 15-, and 20-mm SOBP modulation widths at uniform physical dose rates of up to 375 Gy/s at the center of the SOBP and a minimum dose rate of about 255 Gy/s at the entrance, respectively, in cylindrical volumes. The flatness of lateral dose profiles at the center could be adjusted to within ±1.5% at the center of the SOBP. Assessment of systematic uncertainties, such as impact of misalignments and positioning uncertainties, was performed using simulations, and the results were used to provide appropriate adjustments to ensure high-accuracy FLASH beam delivery for both in vitro and in vivo preclinical experiments., Conclusions: It is feasible to use synchrotron-generated proton beams of sufficient dimensions for FLASH radiobiology experiments. We expect to use the system we developed to acquire in vitro and in vivo small animal FLASH radiobiology data as a function of dose, dose rate, oxygen content, and linear energy transfer to help us understand the underlying mechanisms of the FLASH phenomenon., (© 2021 American Association of Physicists in Medicine.)

Introduction: The exact dependence of biological effect on dose and linear energy transfer (LET) in human tissue when delivering proton therapy is unknown. In this study, we propose a framework for measuring this dependency using multi-modal image-based assays with deformable registrations within imaging sessions and across time., Materials and Methods: 3T MRI scans were prospectively collected from 6 pediatric brain cancer patients before they underwent proton therapy treatment, and every 3 months for a year after treatment. Scans included T1-weighted with contrast enhancement (T1), T2-FLAIR (T2) and fractional anisotropy (FA) images. In addition, the planning CT, dose distributions and Monte Carlo-calculated LET distributions were collected. A multi-modal deformable image registration framework was used to create a dataset of dose, LET and imaging intensities at baseline and follow-up on a voxel-by-voxel basis. We modelled the biological effect of dose and LET from proton therapy using imaging changes over time as a surrogate for biological effect. We investigated various models to show the feasibility of the framework to model imaging changes. To account for interpatient and intrapatient variations, we used a nested generalized linear mixed regression model. The models were applied to predict imaging changes over time as a function of dose and LET for each modality., Results: Using the nested models to predict imaging changes, we saw a decrease in the FA signal as a function of dose; however, the signal increased with increasing LET. Similarly, we saw an increase in T2 signal as a function of dose, but a decrease in signal with LET. We saw no changes in T1 voxel values as a function of either dose or LET., Conclusions: The imaging changes could successfully model biological effect as a function of dose and LET using our proposed framework. Due to the low number of patients, the imaging changes observed for FA and T2 scans were not marked enough to draw any firm conclusions., (© 2021 American Association of Physicists in Medicine.)

Purpose: We present a first-principles molecular dynamics (MD) simulation and expound upon a mechanism of oxygen depletion hypothesis to explain the mitigation of normal tissue injury observed in ultra-high-dose-rate (UHDR) FLASH radiotherapy., Methods: We simulated damage to a segment of DNA (also representing other biomolecules such as RNA and proteins) in a simulation box filled with H 2 O and O 2 molecules. Attoseconds physical interactions (ionizations, electronic, and vibrational excitations) were simulated by using the Monte Carlo track structure code Geant4-DNA. Immediately after ionization, ab initio Car-Parrinello molecular dynamics (CPMD) simulation was used to identify which H 2 O and O 2 molecules surrounding the DNA molecule were converted into reactive oxygen species (ROS). Subsequently, the femto- to nanosecond reactions of ROS were simulated by using MD with reactive force field (ReaxFF), to illustrate ROS merging into new types of non-reactive oxygen species (NROS) due to strong coupling among ROS. A coarse-grained model was constructed to describe the relevant collective phenomenon at the macroscopic level on ROS aggregation and formation of NROS agglomerates consistent with the underlying microscopic pathways obtained from MD simulations., Results: Time-dependent molecular simulations revealed the formation of metastable and transient spaghetti-like complexes among ROS generated at UHDR. At the higher ROS densities produced under UHDR, stranded chains (i.e., NROS) are produced, mediated through attractive electric polarity forces, hydrogen bonds, and magnetic dipole-dipole interactions among hydroxyl ( . OH ) radicals. NROS tend to be less mobile than cellular biomolecules as opposed to the isolated and sparsely dense ROS generated at conventional dose rates (CDR). We attribute this effect to the suppression of biomolecular damage induced per particle track. At a given oxygen level, as the dose rate increases, the size and number of NROS chains increase, and correspondingly the population of toxic ROS components decreases. Similarly, at a given high dose rate, as the oxygen level increases, so do the size and number of NROS chains until an optimum level of oxygen is reached. Beyond that level, the amount of oxygen present may be sufficient to saturate the production of NROS chains, thereby reversing the sparing effects of UHDRs., Conclusions: We showed that oxygen depletion, hypothesized to lead to lower normal-tissue toxicity at FLASH dose rates, takes place within femto- to nanoseconds after irradiation. The mechanism is governed by the slow dynamics of chains of ROS complexes (NROS). Under physoxic (≈ 4-5% oxygen) conditions (i.e., in normal tissues), NROS are more abundant than in hypoxic conditions (e.g., <0.3% in parts of tumors), suggesting that biomolecular damage would be reduced in an environment with physoxic oxygen levels. Hence irradiation at UHDRs would be more effective for sparing physoxic normal tissues but not tumors containing regions of hypoxia. At much higher levels of oxygen (e.g., >10-15%), oxygen depletion by UHDRs may not be sufficient for tissue sparing., (© 2020 American Association of Physicists in Medicine.)

Purpose: Linear energy transfer (LET)-guided methods have been applied to intensity-modulated proton therapy (IMPT) to improve its biological effect. However, using LET as a surrogate for biological effect ignores the topological relationship of the scanning spot to different structures of interest. In this study, we developed an optimization method that takes advantage of the continuing increase in LET beyond the physical dose Bragg peak. This method avoids placing high biological effect values in critical structures and increases biological effect in the tumor area without compromising target coverage., Methods: We selected the cases of two patients with brain tumors and two patients with head and neck tumors who had been treated with proton therapy at our institution. Three plans were created for each case: a plan based on conventional dose-based optimization (DoseOpt), one based on LET-incorporating optimization (LETOpt), and one based on the proposed distal-edge avoidance-guided optimization method (DEAOpt). In DEAOpt, an L 1 -norm sparsity term, in which the penalty of each scanning spot was set according to the topological relationship between the organ positions and the location of the peak scaled LET-weighted dose (c LETxD) was added to a conventional dose-based optimization objective function. All plans were normalized to give the same target dose coverage. Dose (assuming a constant relative biological effectiveness value of 1.1, as in clinical practice), biological effect (c LETxD), and computing time consumption were evaluated and compared among the three optimization approaches for each patient case., Results: For all four cases, all three optimization methods generated comparable dose coverage in both target and critical structures. The LETOpt plans and DEAOpt plans reduced biological effect hot spots in critical structures and increased biological effect in the target volumes to a similar extent. For the target, the c LETxD 98% and c LETxD 2% in the DEAOpt plans were on average 7.2% and 11.74% higher than in the DoseOpt plans, respectively. For the brainstem, the c LETxD mean in the DEAOpt plans was on average 33.38% lower than in the DoseOpt plans. In addition, the DEAOpt method saved 30.37% of the computation cost over the LETOpt method., Conclusions: DEAOpt is an alternative IMPT optimization approach that correlates the location of scanning spots with biological effect distribution. IMPT could benefit from the use of DEAOpt because this method not only delivers comparable biological effects to LETOpt plans, but also is faster., (© 2020 American Association of Physicists in Medicine.)

Introduction: To revisit the formulation of the mean chord length in microdosimetry and replace it by the particle mean free path appropriate for modelings in radiobiology., Methods: We perform a collision-by-collision followed by event-by-event Geant4 Monte Carlo simulation and calculate double-averaged stepping length, 〈〈l〉〉, for a range of target sizes from mm down to μm and depth in water. We consider 〈〈l〉〉 to represent the particle mean free path., Results: We show that 〈〈l〉〉 continuously drops as a function of depth and asymptotically saturates to a minimum value in low energies, where it exhibits a universal scaling behavior, independent of particle nominal beam energy. We correlate 〈〈l〉〉 to linear density of DNA damage, complexities of initial lethal lesions and illustrate a relative difference between predictive RBEs in model calculations using mean chord length vs the proposed mean free path. We demonstrate consistency between rapid increase in RBE within and beyond the Bragg peak and 〈〈l〉〉, a decreasing function of depth., Discussion and Conclusion: An interplay between localities in imparted energy at nanometer scale and subsequent physio-chemical processes, causalities and pathways in DNA damage requires substitution of geometrical chord length of cell nuclei by mean-free path of proton and charged particles to account for a mean distance among sequential collisions in DNA materials. To this end, the event averaging over cell volume in the current microdosimetry formalism must be superseded by the collision averaging scored within the volume. The former, is fundamentally a global attribute of the cell nuclei surfaces and boundaries and is characterized by their membrane diameters, hence such global indices are not appropriate to quantitatively represent the radiobiological strength of the particles and their RBE variabilities that is associated with the sensitivities to local structure of the collisions and their spatio-temporal collective patterns in DNA materials., (© 2020 American Association of Physicists in Medicine.)

Purpose: To develop a first principle and multiscale model for normal tissue complication probability (NTCP) as a function of dose and LET for proton and in general for particle therapy with a goal of incorporating nanoscale radio-chemical to macroscale cell biological pathways, spanning from initial DNA damage to tissue late effects., Methods: The method is a combination of analytical and multiscale computational steps including (a) derivation of functional dependencies of NTCP on DNA-driven cell lethality in nanometer and mapping to dose and LET in millimeter, and (b) three-dimensional-surface fitting to Monte Carlo data set generated based on postradiation image change and gathered for a cohort of 14 pediatric patients treated by scanning beam of protons for ependymoma. We categorize voxel-based dose and LET associated with development of necrosis in NTCP., Result: Our model fits well the clinical data, generated for postradiation tissue toxicity and necrosis. The fitting procedure results in extraction of in vivo radio-biological α-β indices and their numerical values., Discussion and Conclusion: The NTCP model, explored in this work, allows to correlate the tissue toxicities to DNA initial damage, cell lethality and the properties and qualities of radiation, dose, and LET., (© 2020 American Association of Physicists in Medicine.)

The biological effectiveness of proton beams relative to photon beams in radiation therapy has been taken to be 1.1 throughout the history of proton therapy. While potentially appropriate as an average value, actual relative biological effectiveness (RBE) values may differ. This Task Group report outlines the basic concepts of RBE as well as the biophysical interpretation and mathematical concepts. The current knowledge on RBE variations is reviewed and discussed in the context of the current clinical use of RBE and the clinical relevance of RBE variations (with respect to physical as well as biological parameters). The following task group aims were designed to guide the current clinical practice: Assess whether the current clinical practice of using a constant RBE for protons should be revised or maintained. Identifying sites and treatment strategies where variable RBE might be utilized for a clinical benefit. Assess the potential clinical consequences of delivering biologically weighted proton doses based on variable RBE and/or LET models implemented in treatment planning systems. Recommend experiments needed to improve our current understanding of the relationships among in vitro, in vivo, and clinical RBE, and the research required to develop models. Develop recommendations to minimize the effects of uncertainties associated with proton RBE for well-defined tumor types and critical structures., (© 2019 American Association of Physicists in Medicine.)

Purpose: Accurate modeling of the relative biological effectiveness (RBE) of particle beams requires increased systematic in vitro studies with human cell lines with care towards minimizing uncertainties in biologic assays as well as physical parameters. In this study, we describe a novel high-throughput experimental setup and an optimized parameterization of the Monte Carlo (MC) simulation technique that is universally applicable for accurate determination of RBE of clinical ion beams. Clonogenic cell-survival measurements on a human lung cancer cell line (H460) are presented using proton irradiation., Methods: Experiments were performed at the Heidelberg Ion Therapy Center (HIT) with support from the Deutsches Krebsforschungszentrum (DKFZ) in Heidelberg, Germany using a mono-energetic horizontal proton beam. A custom-made variable range selector was designed for the horizontal beam line using the Geant4 MC toolkit. This unique setup enabled a high-throughput clonogenic assay investigation of multiple, well defined dose and linear energy transfer (LETs) per irradiation for human lung cancer cells (H460) cultured in a 96-well plate. Sensitivity studies based on application of different physics lists in conjunction with different electromagnetic constructors and production threshold values to the MC simulations were undertaken for accurate assessment of the calculated dose and the dose-averaged LET (LET d ). These studies were extended to helium and carbon ion beams., Results: Sensitivity analysis of the MC parameterization revealed substantial dependence of the dose and LET d values on both the choice of physics list and the production threshold values. While the dose and LET d calculations using FTFP&#95;BERT&#95;LIV, FTFP&#95;BERT&#95;EMZ, FTFP&#95;BERT&#95;PEN and QGSP&#95;BIC&#95;EMY physics lists agree well with each other for all three ions, they show large differences when compared to the FTFP&#95;BERT physics list with the default electromagnetic constructor. For carbon ions, the dose corresponding to the largest LET d value is observed to differ by as much as 78% between FTFP&#95;BERT and FTFP&#95;BERT&#95;LIV. Furthermore, between the production threshold of 700 μm and 5 μm, proton dose varies by as much as 19% corresponding to the largest LET d value sampled in the current investigation. Based on the sensitivity studies, the FTFP&#95;BERT physics list with the low energy Livermore electromagnetic constructor and a production threshold of 5 μm was employed for determining accurate dose and LET d . The optimized MC parameterization results in a different LET d dependence of the RBE curve for 10% SF of the H460 cell line irradiated with proton beam when compared with the results from a previous study using the same cell line. When the MC parameters are kept consistent between the studies, the proton RBE results agree well with each other within the experimental uncertainties., Conclusions: A custom high-throughput, high-accuracy experimental design for accurate in vitro cell survival measurements was employed at a horizontal beam line. High sensitivity of the physics-based optimization establishes the importance of accurate MC parameterization and hence the conditioning of the MC system on a case-by-case basis. The proton RBE results from current investigations are observed to agree with a previous measurement made under different experimental conditions. This establishes the consistency of our experimental findings across different experiments and institutions., (© 2017 American Association of Physicists in Medicine.)

With the recent clinical implementation of real-time MRI-guided x-ray beam therapy (MRXT), attention is turning to the concept of combining real-time MRI guidance with proton beam therapy; MRI-guided proton beam therapy (MRPT). MRI guidance for proton beam therapy is expected to offer a compelling improvement to the current treatment workflow which is warranted arguably more than for x-ray beam therapy. This argument is born out of the fact that proton therapy toxicity outcomes are similar to that of the most advanced IMRT treatments, despite being a fundamentally superior particle for cancer treatment. In this Future of Medical Physics article, we describe the various software and hardware aspects of potential MRPT systems and the corresponding treatment workflow. Significant software developments, particularly focused around adaptive MRI-based planning will be required. The magnetic interaction between the MRI and the proton beamline components will be a key area of focus. For example, the modeling and potential redesign of a magnetically compatible gantry to allow for beam delivery from multiple angles towards a patient located within the bore of an MRI scanner. Further to this, the accuracy of pencil beam scanning and beam monitoring in the presence of an MRI fringe field will require modeling, testing, and potential further development to ensure that the highly targeted radiotherapy is maintained. Looking forward we envisage a clear and accelerated path for hardware development, leveraging from lessons learnt from MRXT development. Within few years, simple prototype systems will likely exist, and in a decade, we could envisage coupled systems with integrated gantries. Such milestones will be key in the development of a more efficient, more accurate, and more successful form of proton beam therapy for many common cancer sites., (© 2017 American Association of Physicists in Medicine.)

Purpose: (3)He ions may hold great potential for clinical therapy because of both their physical and biological properties. In this study, the authors investigated the physical properties, i.e., the depth-dose curves from primary and secondary particles, and the energy distributions of helium ((3)He) ions. A relative biological effectiveness (RBE) model was applied to assess the biological effectiveness on survival of multiple cell lines., Methods: In light of the lack of experimental measurements and cross sections, the authors used Monte Carlo methods to study the energy deposition of (3)He ions. The transport of (3)He ions in water was simulated by using three Monte Carlo codes-FLUKA, GEANT4, and MCNPX-for incident beams with Gaussian energy distributions with average energies of 527 and 699 MeV and a full width at half maximum of 3.3 MeV in both cases. The RBE of each was evaluated by using the repair-misrepair-fixation model. In all of the simulations with each of the three Monte Carlo codes, the same geometry and primary beam parameters were used., Results: Energy deposition as a function of depth and energy spectra with high resolution was calculated on the central axis of the beam. Secondary proton dose from the primary (3)He beams was predicted quite differently by the three Monte Carlo systems. The predictions differed by as much as a factor of 2. Microdosimetric parameters such as dose mean lineal energy (y(D)), frequency mean lineal energy (y(F)), and frequency mean specific energy (z(F)) were used to characterize the radiation beam quality at four depths of the Bragg curve. Calculated RBE values were close to 1 at the entrance, reached on average 1.8 and 1.6 for prostate and head and neck cancer cell lines at the Bragg peak for both energies, but showed some variations between the different Monte Carlo codes., Conclusions: Although the Monte Carlo codes provided different results in energy deposition and especially in secondary particle production (most of the differences between the three codes were observed close to the Bragg peak, where the energy spectrum broadens), the results in terms of RBE were generally similar.

Purpose: The motivation of this study was to find and eliminate the cause of errors in dose-averaged linear energy transfer (LET) calculations from therapeutic protons in small targets, such as biological cell layers, calculated using the geant 4 Monte Carlo code. Furthermore, the purpose was also to provide a recommendation to select an appropriate LET quantity from geant 4 simulations to correlate with biological effectiveness of therapeutic protons., Methods: The authors developed a particle tracking step based strategy to calculate the average LET quantities (track-averaged LET, LETt and dose-averaged LET, LETd) using geant 4 for different tracking step size limits. A step size limit refers to the maximally allowable tracking step length. The authors investigated how the tracking step size limit influenced the calculated LETt and LETd of protons with six different step limits ranging from 1 to 500 μm in a water phantom irradiated by a 79.7-MeV clinical proton beam. In addition, the authors analyzed the detailed stochastic energy deposition information including fluence spectra and dose spectra of the energy-deposition-per-step of protons. As a reference, the authors also calculated the averaged LET and analyzed the LET spectra combining the Monte Carlo method and the deterministic method. Relative biological effectiveness (RBE) calculations were performed to illustrate the impact of different LET calculation methods on the RBE-weighted dose., Results: Simulation results showed that the step limit effect was small for LETt but significant for LETd. This resulted from differences in the energy-deposition-per-step between the fluence spectra and dose spectra at different depths in the phantom. Using the Monte Carlo particle tracking method in geant 4 can result in incorrect LETd calculation results in the dose plateau region for small step limits. The erroneous LETd results can be attributed to the algorithm to determine fluctuations in energy deposition along the tracking step in geant 4. The incorrect LETd values lead to substantial differences in the calculated RBE., Conclusions: When the geant 4 particle tracking method is used to calculate the average LET values within targets with a small step limit, such as smaller than 500 μm, the authors recommend the use of LETt in the dose plateau region and LETd around the Bragg peak. For a large step limit, i.e., 500 μm, LETd is recommended along the whole Bragg curve. The transition point depends on beam parameters and can be found by determining the location where the gradient of the ratio of LETd and LETt becomes positive.

Purpose: The purpose of the work reported here was to investigate the influence of sub-millimeter size heterogeneities on the degradation of the distal edges of proton beams and to validate Monte Carlo (MC) methods' ability to correctly predict such degradation., Methods: A custom-designed high-resolution plastic phantom approximating highly heterogeneous, lung-like structures was employed in measurements and in Monte Carlo simulations to evaluate the degradation of proton Bragg curves penetrating heterogeneous media., Results: Significant differences in distal falloff widths and in peak dose values were observed in the measured and the Monte Carlo simulated curves compared to pristine proton Bragg curves. Furthermore, differences between simulations of beams penetrating CT images of the phantom did not agree well with the corresponding experimental differences. The distal falloff widths in CT image-based geometries were underestimated by up to 0.2 cm in water (corresponding to 0.8-1.4 cm in lung tissue), and the peak dose values of pristine proton beams were overestimated by as much as ˜35% compared to measured curves or depth-dose curves simulated on the basis of true geometry. The authors demonstrate that these discrepancies were caused by the limited spatial resolution of CT images that served as a basis for dose calculations and lead to underestimation of the impact of the fine structure of tissue heterogeneities. A convolution model was successfully applied to mitigate the underestimation., Conclusions: The results of this study justify further development of models to better represent heterogeneity effects in soft-tissue geometries, such as lung, and to correct systematic underestimation of the degradation of the distal edge of proton doses.

Purpose: This paper investigates, via magnetic modeling and Monte Carlo simulation, the ability to deliver proton beams to the treatment zone inside a split-bore MRI-guided proton therapy system., Methods: Field maps from a split-bore 1 T MRI-Linac system are used as input to geant4 Monte Carlo simulations which model the trajectory of proton beams during their paths to the isocenter of the treatment area. Both inline (along the MRI bore) and perpendicular (through the split-bore gap) orientations are simulated. Monoenergetic parallel and diverging beams of energy 90, 195, and 300 MeV starting from 1.5 and 5 m above isocenter are modeled. A phase space file detailing a 2D calibration pattern is used to set the particle starting positions, and their spatial location as they cross isocenter is recorded. No beam scattering, collimation, or modulation of the proton beams is modeled., Results: In the inline orientation, the radial symmetry of the solenoidal style fringe field acts to rotate the protons around the beam's central axis. For protons starting at 1.5 m from isocenter, this rotation is 19° (90 MeV) and 9.8° (300 MeV). A minor focusing toward the beam's central axis is also seen, but only significant, i.e., 2 mm shift at 150 mm off-axis, for 90 MeV protons. For the perpendicular orientation, the main MRI field and near fringe field act as the strongest to deflect the protons in a consistent direction. When starting from 1.5 m above isocenter shifts of 135 mm (90 MeV) and 65 mm (300 MeV) were observed. Further to this, off-axis protons are slightly deflected toward or away from the central axis in the direction perpendicular to the main deflection direction. This leads to a distortion of the phase space pattern, not just a shift. This distortion increases from zero at the central axis to 10 mm (90 MeV) and 5 mm (300 MeV) for a proton 150 mm off-axis. In both orientations, there is a small but subtle difference in the deflection and distortion pattern between protons fired parallel to the beam axis and those fired from a point source. This is indicative of the 3D spatially variant nature of the MRI fringe field., Conclusions: For the first time, accurate magnetic and Monte Carlo modeling have been used to assess the transport of generic proton beams toward a 1 T split-bore MRI. Significant rotation is observed in the inline orientation, while more complex deflection and distortion are seen in the perpendicular orientation. The results of this study suggest that due to the complexity and energy-dependent nature of the magnetic deflection and distortion, the pencil beam scanning method will be the only choice for delivering a therapeutic proton beam inside a potential MRI-guided proton therapy system in either the inline or perpendicular orientation. Further to this, significant correction strategies will be required to account for the MRI fringe fields.

Purpose: Spot-scanning proton therapy (SSPT) using multifield optimization (MFO) can generate highly conformal dose distributions, but it is more sensitive to setup and range uncertainties than SSPT using single-field optimization (SFO). The authors compared the two optimization methods for the treatment of head and neck cancer with bilateral targets and determined the superior method on the basis of both the plan quality and the plan robustness in the face of setup and range uncertainties., Methods: Four patients with head and neck cancer with bilateral targets who received SSPT treatment in the authors' institution were studied. The patients had each been treated with a MFO plan using three fields. A three-field SFO plan (3F-SFO) and a two-field SFO plan (2F-SFO) with the use of a range shifter in the beam line were retrospectively generated for each patient. The authors compared the plan quality and robustness to uncertainties of the SFO plans with the MFO plans. Robustness analysis of each plan was performed to generate the two dose distributions consisting of the highest and the lowest possible doses (worst-case doses) from the spatial and range perturbations at every voxel. Dosimetric indices from the nominal and worst-case plans were compared., Results: The 3F-SFO plans generally yielded D95 and D5 values in the targets that were similar to those of the MFO plans. 3F-SFO resulted in a lower dose to the oral cavity than MFO in all four patients by an average of 9.9 Gy, but the dose to the two parotids was on average 6.7 Gy higher for 3F-SFO than for MFO. 3F-SFO plans reduced the variations of dosimetric indices under uncertainties in the targets by 22.8% compared to the MFO plans. Variations of dosimetric indices under uncertainties in the organs at risk (OARs) varied between organs and between patients, although they were on average 9.2% less for the 3F-SFO plans than for the MFO plans. Compared with the MFO plans, the 2F-SFO plans showed a reduced dose to the parotids for both the nominal dose and in the worst-case scenario, but the plan robustness in the target of the 2F-SFO plans was not notably greater than that of the MFO plans., Conclusions: Compared with MFO, 3F-SFO improves plan robustness in the targets but degrades dose sparing in the parotids in both the nominal and worst-case scenarios. Although 2F-SFO improves parotid sparing compared with MFO, it produces little improvement in plan robustness. Therefore, considering its tolerable target coverage and sparing of OARs in worst-case scenarios, the authors recommend MFO as the planning method for the treatment of head and neck cancer with bilateral targets.

Purpose: Intensity-modulated proton therapy (IMPT) is highly sensitive to uncertainties in beam range and patient setup. Conventionally, these uncertainties are dealt using geometrically expanded planning target volume (PTV). In this paper, the authors evaluated a robust optimization method that deals with the uncertainties directly during the spot weight optimization to ensure clinical target volume (CTV) coverage without using PTV. The authors compared the two methods for a population of head and neck (H&N) cancer patients., Methods: Two sets of IMPT plans were generated for 14 H&N cases, one being PTV-based conventionally optimized and the other CTV-based robustly optimized. For the PTV-based conventionally optimized plans, the uncertainties are accounted for by expanding CTV to PTV via margins and delivering the prescribed dose to PTV. For the CTV-based robustly optimized plans, spot weight optimization was guided to reduce the discrepancy in doses under extreme setup and range uncertainties directly, while delivering the prescribed dose to CTV rather than PTV. For each of these plans, the authors calculated dose distributions under various uncertainty settings. The root-mean-square dose (RMSD) for each voxel was computed and the area under the RMSD-volume histogram curves (AUC) was used to relatively compare plan robustness. Data derived from the dose volume histogram in the worst-case and nominal doses were used to evaluate the plan optimality. Then the plan evaluation metrics were averaged over the 14 cases and were compared with two-sided paired t tests., Results: CTV-based robust optimization led to more robust (i.e., smaller AUCs) plans for both targets and organs. Under the worst-case scenario and the nominal scenario, CTV-based robustly optimized plans showed better target coverage (i.e., greater D95%), improved dose homogeneity (i.e., smaller D5% - D95%), and lower or equivalent dose to organs at risk., Conclusions: CTV-based robust optimization provided significantly more robust dose distributions to targets and organs than PTV-based conventional optimization in H&N using IMPT. Eliminating the use of PTV and planning directly based on CTV provided better or equivalent normal tissue sparing.

Purpose: To present our method and experience in commissioning dose models in water for spot scanning proton therapy in a commercial treatment planning system (TPS)., Methods: The input data required by the TPS included in-air transverse profiles and integral depth doses (IDDs). All input data were obtained from Monte Carlo (MC) simulations that had been validated by measurements. MC-generated IDDs were converted to units of Gy mm(2)/MU using the measured IDDs at a depth of 2 cm employing the largest commercially available parallel-plate ionization chamber. The sensitive area of the chamber was insufficient to fully encompass the entire lateral dose deposited at depth by a pencil beam (spot). To correct for the detector size, correction factors as a function of proton energy were defined and determined using MC. The fluence of individual spots was initially modeled as a single Gaussian (SG) function and later as a double Gaussian (DG) function. The DG fluence model was introduced to account for the spot fluence due to contributions of large angle scattering from the devices within the scanning nozzle, especially from the spot profile monitor. To validate the DG fluence model, we compared calculations and measurements, including doses at the center of spread out Bragg peaks (SOBPs) as a function of nominal field size, range, and SOBP width, lateral dose profiles, and depth doses for different widths of SOBP. Dose models were validated extensively with patient treatment field-specific measurements., Results: We demonstrated that the DG fluence model is necessary for predicting the field size dependence of dose distributions. With this model, the calculated doses at the center of SOBPs as a function of nominal field size, range, and SOBP width, lateral dose profiles and depth doses for rectangular target volumes agreed well with respective measured values. With the DG fluence model for our scanning proton beam line, we successfully treated more than 500 patients from March 2010 through June 2012 with acceptable agreement between TPS calculated and measured dose distributions. However, the current dose model still has limitations in predicting field size dependence of doses at some intermediate depths of proton beams with high energies., Conclusions: We have commissioned a DG fluence model for clinical use. It is demonstrated that the DG fluence model is significantly more accurate than the SG fluence model. However, some deficiencies in modeling the low-dose envelope in the current dose algorithm still exist. Further improvements to the current dose algorithm are needed. The method presented here should be useful for commissioning pencil beam dose algorithms in new versions of TPS in the future.

Purpose: Robust optimization leads to intensity-modulated proton therapy (IMPT) plans that are less sensitive to uncertainties and superior in terms of organs-at-risk (OARs) sparing, target dose coverage, and homogeneity compared to planning target volume (PTV)-based optimized plans. Robust optimization incorporates setup and range uncertainties, which implicitly adds margins to both targets and OARs and is also able to compensate for perturbations in dose distributions within targets and OARs caused by uncertainties. In contrast, the traditional PTV-based optimization considers only setup uncertainties and adds a margin only to targets but no margins to the OARs. It also ignores range uncertainty. The purpose of this work is to determine if robustly optimized plans are superior to PTV-based plans simply because the latter do not assign margins to OARs during optimization., Methods: The authors retrospectively selected from their institutional database five patients with head and neck (H&N) cancer and one with prostate cancer for this analysis. Using their original images and prescriptions, the authors created new IMPT plans using three methods: PTV-based optimization, optimization based on the PTV and planning risk volumes (PRVs) (i.e., "PTV+PRV-based optimization"), and robust optimization using the "worst-case" dose distribution. The PRVs were generated by uniformly expanding OARs by 3 mm for the H&N cases and 5 mm for the prostate case. The dose-volume histograms (DVHs) from the worst-case dose distributions were used to assess and compare plan quality. Families of DVHs for each uncertainty for all structures of interest were plotted along with the nominal DVHs. The width of the "bands" of DVHs was used to quantify the plan sensitivity to uncertainty., Results: Compared with conventional PTV-based and PTV+PRV-based planning, robust optimization led to a smaller bandwidth for the targets in the face of uncertainties {clinical target volume [CTV] bandwidth: 0.59 [robust], 3.53 [PTV+PRV], and 3.53 [PTV] Gy (RBE)}. It also resulted in higher doses to 95% of the CTV {D(95%): 60.8 [robust] vs 59.3 [PTV+PRV] vs 59.6 [PTV] Gy (RBE)}, smaller D(5%) (doses to 5% of the CTV) minus D(95%) {D(5%) - D(95%): 13.2 [robust] vs 17.5 [PTV+PRV] vs 17.2 [PTV] Gy (RBE)}. At the same time, the robust optimization method irradiated OARs less {maximum dose to 1 cm(3) of the brainstem: 48.3 [robust] vs 48.8 [PTV+PRV] vs 51.2 [PTV] Gy (RBE); mean dose to the oral cavity: 22.3 [robust] vs 22.9 [PTV+PRV] vs 26.1 [PTV] Gy (RBE); maximum dose to 1% of the normal brain: 66.0 [robust] vs 68.0 [PTV+PRV] vs 69.3 [PTV] Gy (RBE)}., Conclusions: For H&N cases studied, OAR sparing in PTV+PRV-based optimization was inferior compared to robust optimization but was superior compared to PTV-based optimization; however, target dose robustness and homogeneity were comparable in the PTV+PRV-based and PTV-based optimizations. The same pattern held for the prostate case. The authors' data suggest that the superiority of robust optimization is not due simply to its inclusion of margins for OARs, but that this is due mainly to the ability of robust optimization to compensate for perturbations in dose distributions within target volumes and normal tissues caused by uncertainties.

Purpose: Former studies have shown that in homogeneities in the path of therapeutic proton beams can lead to a degradation of the distal edge of the Bragg peak. These studies mostly investigated bone-air interfaces. This study focuses on distal edge degradation caused by finely structured soft tissue - air interfaces, which can be found in lung tissue., Methods: A randomly filled voxelized lung-like phantom was designed and produced using rapid prototyping methods. The results of transmission measurements on this phantom were used to validate Monte Carlo (MC) calculations, which were then used as gold standard to calculate doses in several lung equivalent geometries (phantoms). The results were compared to the results of analytical dose calculation engines., Results: Transmission measurements showed that the distal falloff width (from 90 % of the peak dose to 10 %) in water increased from 3.32 mm by 117 % to 7.19 mm for an initial proton energy of 140 MeV, and from 5.95 mm to 9.03 mm (52 %) for 200 MeV. The peak dose in the degraded beam was only 70 % (for 140 MeV) and 84 % (for 200 MeV) of the value observed in non-degraded beams. These findings were in contrast to the results obtained with analytical dose computation engines, but are in agreement with MC calculations., Conclusions: If not predicted correctly, Distal Edge Degradation in lung cancer therapy can lead to severe under-dosage of the target region and unwanted dose in organs at risk distal to the Bragg peak. Therefore clinically used dose calculation algorithms have to be extended to take lateral in homogeneities into account., (© 2012 American Association of Physicists in Medicine.)

Purpose: Accurate dose predictions in proton beam therapy using magnetically scanned beams are highly dependent on the accurate modeling of the lateral dose profiles. This study was performed to provide proton phase spaces for Monte Carlo simulations, used to accurately simulate doses at distances up to 12 cm from the central axis of the beam., Methods: Measured lateral dose profiles at various depths in water were compared to Monte Carlo simulations of doses for 90 discreet initial proton energies. Phase spaces were produced using a one dimensional energy distribution, and a combination of several two dimensional spatial and directional distributions. Simulations were performed iteratively using variations in the initial phase space distributions to achieve acceptable agreement between measured and simulated lateral dose profiles, i.e. differences in FWHM < 0.5 mm and dose differences less that 0.1% at distances up to 12.5 cm., Results: 90 phase spaces of proton sources for different initial beam energies were created for use in Monte Carlo simulations of scanned proton beam therapy patient plans. At a depth of 2 cm in water, the simulated and measured FWHM of the lateral dose profiles differed in in-plane direction by an average of 0.05 mm, in cross-plane direction by 0.13 mm. All simulated profiles were within 0.1% of the measured doses at distances between 2cm and 12.5 cm from the central beam axis., Conclusions: A library of 90 phase space files has been created to accurately simulate magnetically scanned proton beams for IMPT, providing accurate dose distributions up to 12 cm distance from the central beam axis. This project is supported in part by P01CA021239 from the National Cancer Institute. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute or the National Institutes of Health., (© 2012 American Association of Physicists in Medicine.)

Purpose: The analytical algorithms which are used widely for proton treatment planning in the current clinical practice may have significant dosimetric uncertainties in highly heterogeneous regions. The aim of this study is the assessment of the potential clinical impact of these uncertainties., Methods: A cohort of 8 patients with local (in field) recurrences, originally treated for lung cancer at our institution, was selected for this study. CT scans and treatment plans were used to assemble the input files for the Monte Carlo (MC) code MCNPX. The total energy deposition inside the patient volume was computed with statistical uncertainty of less than 2% and converted to dose-in-water. The results were compared to the dose computed by the clinical treatment planning system (TPS). The area of the recurrence was contoured on the follow-up PET/CT study for each of the patients and registered to the planning CT., Results: While there is acceptable agreement between the TPS and the Monte Carlo dose in homogeneous regions, there are noticeable differences caused by heterogeneities. The regions of largest differences are the points around and beyond the distal edge and points around the lateral penumbra and in several patients the target has received lower then the prescribed dose. The area of the recurrence corelates well with the MC predicted underdosed area of the target., Conclusions: The uncertanties in analytical dose algorithms used in clinical TPSs may result in suboptimal target coverage increasing the possibility of tumor recurrence. Accurate Monte Carlo simulations can be used to predict and avoid the situations in which the analytical algorithms have high uncertanties providing for more robust treatment planning., (© 2012 American Association of Physicists in Medicine.)

Purpose: The effectiveness of IMPT may be significantly diminished by range and patient setup uncertainties. The purpose of this presentation is to evaluate the ability of robust optimization methods to desensitize H&N IMPT plans to uncertainties and their impact on plan optimality., Methods: We use a robust optimization method, in which the objective function value for a given iteration is computed using the 'worst case' dose distribution. The conventionally optimized PTV-based IMPT plans and robustly optimized plans were generated for 14 head and neck cancer cases. The dose standard deviation was calculated for every voxel and used to compute 'standard-deviation volume histograms' (SVHs). The area under SVH curves was used to quantify the plan robustness. In addition, D1cc doses for spinal cord and brainstem, mean doses Dmean for oral cavity and parotids, and D1% doses for other organs were used to assess plan optimality. D5% and D95% doses are used to assess target dose coverage and homogeneity. The plan optimality and robustness are then compared statistically by the pair t-tests using SPSS 19.0 software., Results: Compared with PTV-based optimization, robust optimization provides significantly more robust dose distribution for both targets and organs without sacrificing, and possibly even improving, the sparing of normal tissues. In addition, our robust optimization method also leads to more homogeneous dose distribution in targets with better prescription dose coverage. Improvements are statistically significant with p-value smaller than 0.05 for almost all end points compared., Conclusion: Robust optimization results in patient-specific, optimizer-determined, and effectively reduced margins compared to a predefined and fixed margin used in the PTV approach. The optimizer can find a desired beamlet weight solution from the degenerate solution space so that the dose distribution follows the changes in anatomical geometry and is minimally perturbed by uncertainties. Our results demonstrate the importance of robust optimization. This research is supported by National Cancer Institute (NCI) grant P01CA021239, the University Cancer Foundation via the Institutional Research Grant program at the University of Texas MD Anderson Cancer Center, and MD Anderson’s cancer center support grant CA0 16672., (© 2012 American Association of Physicists in Medicine.)

Purpose: The purpose was to investigate the interplay of residual motion in realistically delivered respiratory gated spot scanning proton beam by a synchrotron., Methods: A MatriXX 2D ion-chamber array detector was placed on a moving platform. The platform with the 2D ion-chamber array detector was moved based on sin4 motion with 3s and 5s cycle and 20 mm amplitude. Its motion was monitored by a laser displacement sensor (ZS-LDS2VT, omron, Japan). The respiration gate threshold level was set at 30% duty cycle and the residual motion within the gate window was approximately 6 mm. A 10×10 cm 2 uniform field was delivered by a matrix of 13×13 spots with ∼ 8 mm spot size (s) and 8 mm spot spacing. Measurements were done for the field delivered with a single painting and multiple re-painting, from 2 to 12 times, for both orthogonal and parallel scan directions. The same field was also measured without moving the detector, defined as the static reference dose. Dose homogeneity was compared between with gated and the static dose distributions., Results: The worst single painting result of the dose homogeneity ratio was 0.90 in 3s motion cycle and 0.93 in 5s motion cycle with the orthogonal scan pattern, and 0.97 in 3s and 0.98 in 5s motion with the parallel scan pattern, respectively . The homogeneity ratio improved to over 0.98 by 4∼6 times repainting in orthogonal and only 2 times re-painting with the parallel scan., Conclusions: The respiratory gated spot scanning proton beam delivery is sensitive to spot movement direction relative to the residual motion of the target. A proper selection of the number of repainting and the scan direction can improve beam delivery quality. The study offers a basic understanding when implementing respiratory gated spot scanning proton beam treatment., (© 2012 American Association of Physicists in Medicine.)

Purpose: Providing a user friendly automated Monte Carlo dose computation system for proton treatments using passively scattered and intensity modulated proton therapy plans, developed at the proton therapy facility of the M.D. Anderson Cancer Center., Methods: In house software was developed to automatically extract patient CT images, as well as the setup geometry and proton beam parameters from DICOM files, to create a Monte Carlo (MCNPX) model simulating the beam line arrangements of the various beams used in any given proton treatment plan. A graphical user interface provides an easy and intuitive workspace. A library of phase space files provides source proton beams with the desired modulation width and range in water. Energy deposition is scored in the voxelized CT volume, converted to dose and compared to results of analytical dose computations., Results: Monte Carlo models of patient specific beam line equipment, such as the brass collimator and the range compensator, as well as avoxelized model of the patient, are automatically created and implemented into the model of the simulated beam. Simulation of proton beams result in energy deposition distributions in a volume of interest defined by the user during program start., Conclusions: Current efforts focus on production ofthe phase space library and final debugging of the program flow. It is expected that a prototype version of the system will be functional in summer 2012., (© 2012 American Association of Physicists in Medicine.)

Purpose: Proton dose distributions, IMPT in particular, are highly sensitive to setup and range uncertainties. We report a novel method, based on per-voxel standard deviation (SD) of dose distributions, to evaluate the robustness of proton plans and to robustly optimize IMPT plans to render them less sensitive to uncertainties., Methods: For each optimization iteration, nine dose distributions are computed - the nominal one, and one each for ± setup uncertainties along x, y and z axes and for ± range uncertainty. SD of dose in each voxel is used to create SD-volume histogram (SVH) for each structure. SVH may be considered a quantitative representation of the robustness of the dose distribution. For optimization, the desired robustness may be specified in terms of an SD-volume (SV) constraint on the CTV and incorporated as a term in the objective function. Results of optimization with and without this constraint were compared in terms of plan optimality and robustness using the so called'worst case' dose distributions; which are obtained by assigning the lowest among the nine doses to each voxel in the clinical target volume (CTV) and the highest to normal tissue voxels outside the CTV. The SVH curve and the area under it for each structure were used as quantitative measures of robustness. Penalty parameter of SV constraint may be varied to control the tradeoff between robustness and plan optimality. We applied these methods to one case each of H&N and lung., Results: In both cases, we found that imposing SV constraint improved plan robustness but at the cost of normal tissue sparing., Conclusions: SVH-based optimization and evaluation is an effective tool for robustness evaluation and robust optimization of IMPT plans. Studies need to be conducted to test the methods for larger cohorts of patients and for other sites. This research is supported by National Cancer Institute (NCI) grant P01CA021239, the University Cancer Foundation via the Institutional Research Grant program at the University of Texas MD Anderson Cancer Center, and MD Anderson’s cancer center support grant CA016672., (© 2012 American Association of Physicists in Medicine.)

Purpose: Robust optimization leads to IMPT plans that are more robust than and superior in optimality compared to PTV-based optimized plans. Robust optimization incorporates setup and range uncertainties, which implicitly adds margins to targets and organs-at-risk (OARs); whereas PTV-based optimization only considers setup uncertainties and adds margins only to targets in practice. The purpose of this work is to determine if the superiority of robustly optimized plans is due to not assigning margins to OARs during PTV-based optimization., Methods: Plan robustness and optimality of the PTV plus Planning organs-at-Risk Volume (PRVs)-based plans and robustly optimized plans were compared for 5 head and neck cancer cases and one rhabdomyosarcoma case. The PRVs were generated by expansion from OARs by 3 mm. 9 different dose distributions were computed - one each for ± setup uncertainties along three spatial directions, for ± range uncertainty, and the nominal dose distribution. The worst-case dose distribution was obtained by assigning the lowest dose among the 9 doses to each voxel in the target and the highest dose to each voxel outside the target. The DVHs from the worst-case dose were used to assess the plan optimality and robustness. D1cc doses for spinal cord and brainstem, mean doses Dmean for oral cavity and parotids, and D1% doses for other organs were also used to assess plan optimality. D5% and D95% doses are used to assess target dose coverage and homogeneity., Results: For H&N cases, PTV+PRV-based optimization was inferior to robust optimization. However, PTV+PRV-based optimization yielded plans that spared OARs better than PTV-based optimization, although the target dose robustness and homogeneity were comparable to the PTV-based optimization. The same conclusions are also valid in the rhabdomyosarcoma case., Conclusions: We find that the PTV+PRV method can partly improve plan optimality, but it is still inferior to robust optimization method. This research is supported by National Cancer Institute (NCI) grant P01CA021239, the University Cancer Foundation via the Institutional Research Grant program at the University of Texas MD Anderson Cancer Center, and MD Anderson’s cancer center support grant CA016672., (© 2012 American Association of Physicists in Medicine.)

Purpose: While intensity-modulated proton therapy (IMPT) has great potential to deliver highly conformal tumoricidal dose to targets whilst minimizing dose to nearby organs-at-risk, IMPT optimization is very time consuming and memory extensive due to finer dose grids and a large number of energy layers used compared to intensity-modulated radiation therapy (IMRT). In this presentation, for the first time, a new approach is introduced to speed up the IMPT treatment planning through application of parallel computing with Graphic Processor Units (GPUs)., Methods: Parallel computation with GPUs, which are affordable and can be plugged in a workstation easily, is potentially a good way to improve the computation efficiency. In our approach, we used the standard quadratic objective function to optimize the intensity map of beamlets. The objective function and gradient equations, which are the most time consuming parts of the optimization, were calculated with GPUs. We compared the computation time of optimization done by an Intel ® Core™ i7 CPU and that by the same CPU accelerated by GPUs (TESLA C1060). The influence matrix was pre- calculated before optimization with an in-house proton pencil beam dose calculation engine. Two clinical cases were studied: one base-of-skull (BOS) case (clivus chordoma) and one prostate case (adenocarcinoma). The dose volume histogram (DVH) data for the tumor and critical organs were derived for comparison of optimization results generated by CPU and GPUs., Results: For the BOS case, application of GPUs for the optimization and overall gained 54 and 36.5 times speedup. For the prostate case, application of GPUs for the optimization and overall gained 69 and 28.5 times speedup., Conclusions: The application of GPUs for the parallel computing of IMPT treatment plan optimization can dramatically improve the computation efficiency. The optimization time can be reduced from typically half to one hour to only several minutes., (© 2012 American Association of Physicists in Medicine.)

Purpose: Intensity-modulated proton therapy (IMPT) using multi-field optimization (MFO) could generate highly conformal dose distributions but it is more sensitive to setup and proton range uncertainties than IMPT using single-field optimization (SFO). This work evaluates the effectiveness of SFO treatment plans with the use of energy absorbers (EAs) to improve the robustness and delivery efficiency of IMPT for head and neck cancers., Methods: IMPT treatment plans were generated using 2-field SFO with an EA in each field (EA-SFO) for four patients with head and neck cancers. We compared the plan quality, robustness, and delivery efficiency of the EA- SFO plan with a 3-field MFO plan that was used to treat the patient. Robustness analysis of each plan was performed to generate two dose distributions, consisting of the highest and the lowest possible doses from spatial and range perturbations at every voxel. Dosimetric indices and the numbers of energy layers required in the EA-SFO and MFO plans were compared., Results: All the nominal EA-SFO plans are clinically acceptable. They achieved similar levels of target coverage compared to the MFO plans; the differences in D95 of the GTV and CTVs between the two plans were within 3.5%. Although some of the OARs received higher dose in the EA- SFO plan, they were all within tolerance. The EA-SFO plans yielded an average of 38.5% reduction of plan sensitivity to uncertainties in the targets and 18.5% overall. The EA-SFO plans used an average of 79 (46%) fewer energy layers than the MFO plans, which corresponds to nearly 3 minutes shorter delivery time., Conclusions: The use of energy absorber greatly facilitated the design of clinically acceptable SFO treatment plans. Compared to MFO, EA-SFO not only improved the robustness to setup and range uncertainties, but also reduced the time required for delivery and patient QA., (© 2012 American Association of Physicists in Medicine.)

Purpose: To explore the potential of beam angle optimization (BAO) for IMPT and compare fixed beamlines with gantries., Methods: For three patients with challenging intracranial lesions, we generate reference IMPT treatment plans applying three manually selected beam orientations and treatment plans applying three optimized beam orientations considering five scenarios: (1) patients are in supine position and the treatment room features (1.a) a horizontal beamline, (1.b) a horizontal, 45°, and vertical beamline, (1.c) a gantry, (2) patients are in supine or seated position and the treatment room features (2.a) a horizontal beamline, or (2.b) a horizontal, 45°, and vertical beamline. We use a genetic algorithm that considers up to 1,400 non-coplanar candidate beams and evaluates 10,000 beam ensembles for one BAO. Beam orientations that may compromise the robustness of treatment plans are excluded before the optimization based on an objective measure of existing tissue heterogeneities., Results: The optimized beam ensembles exhibit certain similarities even though the sets of candidate beams differ significantly for the five scenarios. Compared to manually selected beam orientations, they provide improved OAR sparing and equivalent target coverage. Compared to one another, they yield comparable target conformity (deviations of the conformity number <1%), target homogeneity (standard deviations of the target dose <0.8 Gy), and sparing of OARs (deviations of average mean and maximum doses in OARs +/- 1 Gy). Using a gantry, however, the integral dose can be reduced by 5-15% compared to a horizontal beamline with patients in supine position. For the investigated cases comparable reductions can be achieved by also irradiating in seated position with a horizontal, 45°, and vertical beamline., Conclusions: BAO has the potential to provide beneficial IMPT treatment plans. Compared to fixed beamlines, gantries yield only modest effects regarding OAR sparing but may enable a significant reduction of integral dose for individual patients., (© 2012 American Association of Physicists in Medicine.)

Purpose: To evaluate treatment deviations and the impact of treatment modality in the presence of breathing motion and anatomical changes during the course of lung cancer radiotherapy., Methods: Two non-small cell lung cancer patients were enrolled in a randomized clinical trial to compare IMRT and proton therapy. To rigorously evaluate the impact of motion and anatomical changes, we used a '5D' dose accumulation approach to sum dose distributions from phase-to-phase and week-to-week to the reference (end-expiration) phase of the original planning 4DCT data set. Six to eight weekly 4DCT data sets that consisted of 10 breathing phases were acquired during the treatment course. The original plan was re-calculated for each phase and deformably mapped to the reference phase to compare the 'delivered' dose distribution with the planned dose distribution of both the IMRT plan and the proton plan for each patient. DVHs derived from delivered dose distribution were compared to that from the planned dose distribution., Results: The delivered dose showed 3% and 2% increase in the dose to the CTV for IMRT and proton plan respectively. Target coverage remained acceptable despite tumor shrinkage from 29% to 49%. The doses to normal structures, such as lung and heart, increased more in the proton plan than in the IMRT plan. The V20 of the total lung volume increased by 4% and 6% from the delivered dose compared to the planned dose for IMRT and proton plan, respectively., Conclusions: The results showed sufficient target coverage was maintained for both modalities. Increases in lung dose were observed in both modalities, but more in the proton arm, perhaps due to weight loss and tumor shrinkage. Adaptive proton therapy strategy is recommended to minimize normal tissue doses. Supported in part by NCI P01 CA021239-29A1., (© 2012 American Association of Physicists in Medicine.)

Purpose: Intensity-modulated proton therapy (IMPT) using spot scanned proton beams relies on the delivery of a large number of beamlets to shape the dose distribution in a highly conformal manner. The authors have developed a 3D system based on liquid scintillator to measure the spatial location, intensity, and depth of penetration (energy) of the proton beamlets in near real-time., Methods: The detector system consists of a 20 × 20 × 20 cc liquid scintillator (LS) material in a light tight enclosure connected to a CCD camera. This camera has a field of view of 25.7 by 19.3 cm and a pixel size of 0.4 mm. While the LS is irradiated, the camera continuously acquires images of the light distribution produced inside the LS. Irradiations were made with proton pencil beams produced with a spot-scanning nozzle. Pencil beams with nominal ranges in water between 9.5 and 17.6 cm were scanned to irradiate an area of 10 × 10 cm square on the surface of the LS phantom. Image frames were acquired at 50 ms per frame., Results: The signal to noise ratio of a typical Bragg peak was about 170. Proton range measured from the light distribution produced in the LS was accurate to within 0.3 mm on average. The largest deviation seen between the nominal and measured range was 0.6 mm. Lateral position of the measured pencil beam was accurate to within 0.4 mm on average. The largest deviation seen between the nominal and measured lateral position was 0.8 mm; however, the accuracy of this measurement could be improved by correcting light scattering artifacts. Intensity of single proton spots were measured with precision ranging from 3 % for the smallest spot intensity (0.005 MU) to 0.5 % for the largest spot (0.04 MU)., Conclusions: Our LS detector system has been shown to be capable of fast, submillimeter spatial localization of proton spots delivered in a 3D volume. This system could be used for beam range, intensity and position verification in IMPT.

Purpose: Planar integral spot dose (PISD) of proton pencil beam spots (PPBSs) is a required input parameter for beam modeling in some treatment planning systems used in proton therapy clinics. The measurement of PISD by using commercially available large area ionization chambers, like the PTW Bragg peak chamber (BPC), can have large uncertainties due to the size limitation of these chambers. This paper reports the results of our study of a novel method to determine PISD values from the measured lateral dose profiles and peak dose of the PPBS., Methods: The PISDs of 72.5, 89.6, 146.9, 181.1, and 221.8 MeV energy PPBSs were determined by area integration of their planar dose distributions at different depths in water. The lateral relative dose profiles of the PPBSs at selected depths were measured by using small volume ion chambers and were investigated for their angular anisotropies using Kodak XV films. The peak spot dose along the beam's central axis (D(0)) was determined by placing a small volume ion chamber at the center of a broad field created by the superposition of spots at different locations. This method allows eliminating positioning uncertainties and the detector size effect that could occur when measuring it in single PPBS. The PISD was then calculated by integrating the measured lateral relative dose profiles for two different upper limits of integration and then multiplying it with corresponding D(0). The first limit of integration was set to radius of the BPC, namely 4.08 cm, giving PISD(RBPC). The second limit was set to a value of the radial distance where the profile dose falls below 0.1% of the peak giving the PISD(full). The calculated values of PISD(RBPC) obtained from area integration method were compared with the BPC measured values. Long tail dose correction factors (LTDCFs) were determined from the ratio of PISD(full)∕PISD(RBPC) at different depths for PPBSs of different energies., Results: The spot profiles were found to have angular anisotropy. This anisotropy in PPBS dose distribution could be accounted in a reasonable approximate manner by taking the average of PISD values obtained using the in-line and cross-line profiles. The PISD(RBPC) values fall within 3.5% of those measured by BPC. Due to inherent dosimetry challenges associated with PPBS dosimetry, which can lead to large experimental uncertainties, such an agreement is considered to be satisfactory for validation purposes. The PISD(full) values show differences ranging from 1 to 11% from BPC measured values, which are mainly due to the size limitation of the BPC to account for the dose in the long tail regions of the spots extending beyond its 4.08 cm radius. The dose in long tail regions occur both for high energy beams such as 221.8 MeV PPBS due to the contributions of nuclear interactions products in the medium, and for low energy PPBS because of their larger spot sizes. The calculated LTDCF values agree within 1% with those determined by the Monte Carlo (MC) simulations., Conclusions: The area integration method to compute the PISD from PPBS lateral dose profiles is found to be useful both to determine the correction factors for the values measured by the BPC and to validate the results from MC simulations.

Purpose: Intensity modulated proton therapy (IMPT) is highly sensitive to range uncertainties and uncertainties caused by setup variation. The conventional inverse treatment planning of IMPT optimized based on the planning target volume (PTV) is not often sufficient to ensure robustness of treatment plans. In this paper, a method that takes the uncertainties into account during plan optimization is used to mitigate the influence of uncertainties in IMPT., Methods: The authors use the so-called "worst-case robust optimization" to render IMPT plans robust in the face of uncertainties. For each iteration, nine different dose distributions are computed-one each for ± setup uncertainties along anteroposterior (A-P), lateral (R-L) and superior-inferior (S-I) directions, for ± range uncertainty, and the nominal dose distribution. The worst-case dose distribution is obtained by assigning the lowest dose among the nine doses to each voxel in the clinical target volume (CTV) and the highest dose to each voxel outside the CTV. Conceptually, the use of worst-case dose distribution is similar to the dose distribution achieved based on the use of PTV in traditional planning. The objective function value for a given iteration is computed using this worst-case dose distribution. The objective function used has been extended to further constrain the target dose inhomogeneity., Results: The worst-case robust optimization method is applied to a lung case, a skull base case, and a prostate case. Compared with IMPT plans optimized using conventional methods based on the PTV, our method yields plans that are considerably less sensitive to range and setup uncertainties. An interesting finding of the work presented here is that, in addition to reducing sensitivity to uncertainties, robust optimization also leads to improved optimality of treatment plans compared to the PTV-based optimization. This is reflected in reduction in plan scores and in the lower normal tissue doses for the same coverage of the target volume when subjected to uncertainties., Conclusions: The authors find that the worst-case robust optimization provides robust target coverage without sacrificing, and possibly even improving, the sparing of normal tissues. Our results demonstrate the importance of robust optimization. The authors assert that all IMPT plans should be robustly optimized.

Purpose: The purposes of this study were to validate a discrete spot scanning proton beam nozzle using the Monte Carlo (MC) code MCNPX and use the MC validated model to investigate the effects of a low-dose envelope, which surrounds the beam's central axis, on measurements of integral depth dose (IDD) profiles., Methods: An accurate model of the discrete spot scanning beam nozzle from The University of Texas M. D. Anderson Cancer Center (Houston, Texas) was developed on the basis of blueprints provided by the manufacturer of the nozzle. The authors performed simulations of single proton pencil beams of various energies using the standard multiple Coulomb scattering (MCS) algorithm within the MCNPX source code and a new MCS algorithm, which was implemented in the MCNPX source code. The MC models were validated by comparing calculated in-air and in-water lateral profiles and percentage depth dose profiles for single pencil beams with their corresponding measured values. The models were then further tested by comparing the calculated and measured three-dimensional (3-D) dose distributions. Finally, an IDD profile was calculated with different scoring radii to determine the limitations on the use of commercially available plane-parallel ionization chambers to measure IDD., Results: The distance to agreement, defined as the distance between the nearest positions of two equivalent distributions with the same value of dose, between measured and simulated ranges was within 0.13 cm for both MCS algorithms. For low and intermediate pencil beam energies, the MC simulations using the standard MCS algorithm were in better agreement with measurements. Conversely, the new MCS algorithm produced better results for high-energy single pencil beams. The IDD profile calculated with cylindrical tallies with an area equivalent to the area of the largest commercially available ionization chamber showed up to 7.8% underestimation of the integral dose in certain depths of the IDD profile., Conclusions: The authors conclude that a combination of MCS algorithms is required to accurately reproduce experimental data of single pencil beams and 3-D dose distributions for the scanning beam nozzle. In addition, the MC simulations showed that because of the low-dose envelope, ionization chambers with radii as large as 4.08 cm are insufficient to accurately measure IDD profiles for a 221.8 MeV pencil beam in the scanning beam nozzle.

Purpose: The purpose of this study is to describe the University of Texas M. D. Anderson proton therapy system (PTC-H) including the accelerator, beam transport, and treatment delivery systems, the functionality and clinical parameters for passive scattering and pencil beam scanning treatment modes, and the results of acceptance tests., Methods: The PTC-H has a synchrotron (70-250 MeV) and four treatment rooms. An overall control system manages the treatment, physics, and service modes of operation. An independent safety system ensures the safety of patients, staff, and equipment. Three treatment rooms have isocentric gantries and one room has two fixed horizontal beamlines, which include a large-field treatment nozzle, used primarily for prostate treatments, and a small-field treatment nozzle for ocular treatments. Two gantry treatment rooms and the fixed-beam treatment room have passive scattering nozzles. The third gantry has a pencil beam scanning nozzle for the delivery of intensity modulated proton treatments (IMPT) and single field uniform dose (SFUD) treatments. The PTC-H also has an experimental room with a fixed horizontal beamline and a passive scattering nozzle. The equipment described above was provided by Hitachi, Ltd. Treatment planning is performed using the Eclipse system from Varian Medical Systems and data management is handled by the MOSAIQ system from IMPAC Medical Systems, Inc. The large-field passive scattering nozzles use double scattering systems in which the first scatterers are physically integrated with the range modulation wheels. The proton beam is gated on the rotating range modulation wheels at gating angles designed to produce spread-out-Bragg peaks ranging in size from 2 to 16 g/cm2. Field sizes of up to 25 x 25 cm2 can be achieved with the double scattering system. The IMPT delivery technique is discrete spot scanning, which has a maximum field size of 30 x 30 cm2. Depth scanning is achieved by changing the energy extracted from the synchrotron (energy can be changed pulse to pulse). The PTC-H is fully integrated with DICOM-RT ION interfaces for imaging, treatment planning, data management, and treatment control functions., Results: The proton therapy system passed all acceptance tests for both passive scattering and pencil beam scanning. Treatments with passive scattering began in May 2006 and treatments with the scanning system began in May 2008. The PTC-H was the first commercial system to demonstrate capabilities for IMPT treatments and the first in the United States to treat using SFUD techniques. The facility has been in clinical operation since May 2006 with up-time of approximately 98%., Conclusions: As with most projects for which a considerable amount of new technology is developed and which have duration spanning several years, at project completion it was determined that several upgrades would improve the overall system performance. Some possible upgrades are discussed. Overall, the system has been very robust, accurate, reproducible, and reliable. The authors found the pencil beam scanning system to be particularly satisfactory; prostate treatments can be delivered on the scanning nozzle in less time than is required on the passive scattering nozzle.

In this study, the authors investigated the feasibility of using a 3D liquid scintillator (LS) detector system for the verification and characterization of proton beams in real time for intensity and energy-modulated proton therapy. A plastic tank filled with liquid scintillator was irradiated with pristine proton Bragg peaks. Scintillation light produced during the irradiation was measured with a CCD camera. Acquisition rates of 20 and 10 frames per second (fps) were used to image consecutive frame sequences. These measurements were then compared to ion chamber measurements and Monte Carlo simulations. The light distribution measured from the images acquired at rates of 20 and 10 fps have standard deviations of 1.1% and 0.7%, respectively, in the plateau region of the Bragg curve. Differences were seen between the raw LS signal and the ion chamber due to the quenching effects of the LS and due to the optical properties of the imaging system. The authors showed that this effect can be accounted for and corrected by Monte Carlo simulations. The liquid scintillator detector system has a good potential for performing fast proton beam verification and characterization.

Complex radiation therapy techniques require dosimetric verification of treatment planning and delivery. The authors investigated a liquid scintillator (LS) system for application for real-time high-energy photon beam dosimetry. The system was comprised of a transparent acrylic tank filled with liquid scintillating material, an opaque outer tank, and a CCD camera. A series of images was acquired when the tank with liquid scintillator was irradiated with a 6 MV photon beam, and the light data measured with the CCD camera were filtered to correct for scattering of the optical light inside the liquid scintillator. Depth-dose and lateral profiles as well as two-dimensional (2D) dose distributions were found to agree with results from the treatment planning system. Further, the corrected light output was found to be linear with dose, dose rate independent, and is robust for single or multiple acquisitions. The short time needed for image acquisition and processing could make this system ideal for fast verification of the beam characteristics of the treatment machine. This new detector system shows a potential usefulness of the LS for 2D QA.

The purpose of this work was to determine the feasibility of producing a spread out Bragg peak (SOBP) without a range modulation wheel (RMW) using the passive scattering beam delivery technique. For this study, a comprehensive Monte Carlo model of a passive scattering treatment nozzle was used. The RMW was removed from the model leaving only the initial fixed scatterer (RMW-free configuration). Range modulation was achieved by directly changing the energy of the proton beam entering the nozzle. To produce a uniform SOBP, the number of protons injected into the nozzle at each beam energy was "dose weighted." To do so, the effective number of protons was calculated for the individual initial energies using an analytical dose-weighting function, and the resulting weighted Bragg curves were summed together to produce an SOBP of the desired width. We found that SOBPs calculated using the RMW-free nozzle configuration were in very good agreement to those calculated with the standard nozzle configuration containing the RMW for the 250, 180, and 100 MeV maximum beam energies. The depth of the distal 90% dose and the 80%-20% distal dose falloff of SOBPs calculated with the two different nozzle configurations agreed to within a millimeter for the three beam energy options considered in this study. In addition, the 80%-20% lateral penumbra for the cross-field dose profiles calculated with the RMW-free delivery method agreed with results calculated using the standard RMW technique to less than one millimeter. For an equal number of protons injected into the nozzle, an increase of up to 10% in the delivered dose and a significant reduction in both the in-air secondary neutron fluence and dose equivalent (H/D) were observed at the isocenter by removing the RMW from the treatment nozzle and modulating the initial proton beam energy. However, increases in delivery time of up to 70% were also estimated with this method. Our results suggest that it is feasible to deliver a passively scattered dose distribution with an RMW-free nozzle configuration with clinical characteristics comparable to those using standard methods.

Neutron production is an unwanted result of high-energy radiation therapy and results in secondary exposure of patients and radiation therapists to radiation. Recent studies have shown that delivering therapy using a standard medical accelerator with the flattening filter removed may reduce neutron fluence by nearly 70% over the course of prostate intensity-modulated radiation therapy (IMRT). In the current study, the 197Au Bonner sphere technique was used to compare the neutron spectrum produced when the filter is present and when it is absent. In addition, the following was calculated: (1) the neutron-shielding parameters of source strength and ambient dose equivalent (H0) and (2) using the Monte Carlo technique, the sources of neutron production in the accelerator head. It was found that the neutron spectrum was nearly constant, regardless of the presence of the flattening filter; however, the total fluence and ambient dose equivalent over the course of prostate IMRT were more than 70% lower when the filter was removed. Similarly, shielding parameters were lower when the filter was removed. Finally, the primary collimator and jaws accounted for the majority of neutron production, both with and without the flattening filter; however, with the flattening filter removed, the upper jaw accounted for much more neutron production relative to when the filter was present. Ultimately, removal of the flattening filter may offer several clinical advantages, including a reduction in the dose from neutrons to the patient and to radiation personnel.

The goal of this study was to evaluate the improvement in electron density measurement and metal artifact reduction using orthovoltage computed tomography (OVCT) imaging compared with conventional kilovoltage CT (KVCT). For this study, a bench-top system was constructed with adjustable x-ray tube voltage up to 320 kVp. A commercial tissue-characterization phantom loaded with inserts of various human tissue substitutes was imaged using 125 kVp (KVCT) and 320 kVp (OVCT) x rays. Stoichiometric calibration was performed for both KVCT and OVCT imaging using the Schneider method. The metal inserts-titanium rods and aluminum rods-were used to study the impact of metal artifacts on the electron-density measurements both inside and outside the metal inserts. It was found that the relationships between Hounsfield units and relative electron densities (to water) were more predictable for OVCT than KVCT. Unlike KVCT, the stoichiometric calibration for OVCT was insensitive to the use of tissue substitutes for direct electron density calibration. OVCT was found to significantly reduce metal streak artifacts. Errors in electron-density measurements within uniform tissue substitutes were reduced from 42% (maximum) and 18% (root-mean-square) in KVCT to 12% and 2% in OVCT, respectively. Improvements were also observed inside the metal implants. For the detectors optimized for KVCT, the imaging dose is almost doubled for OVCT for the image quality comparable to KVCT. OVCT may be a good option for high-precision radiotherapy treatment planning, especially for patients with metal implants and especially for charged particle therapy, such as proton therapy.

Four-dimensional (4D) radiotherapy is the explicit inclusion of the temporal changes in anatomy during the imaging, planning, and delivery of radiotherapy. One key component of 4D radiotherapy planning is the ability to automatically ("auto") create contours on all of the respiratory phase computed tomography (CT) datasets comprising a 4D CT scan, based on contours manually drawn on one CT image set from one phase. A tool that can be used to automatically propagate manually drawn contours to CT scans of other respiratory phases is deformable image registration. The purpose of the current study was to geometrically quantify the difference between automatically generated contours with manually drawn contours. Four-DCT data sets of 13 patients consisting of ten three-dimensional CT image sets acquired at different respiratory phases were used for this study. Tumor and normal tissue structures [gross tumor volume (GTV), esophagus, right lung, left lung, heart and cord] were manually drawn on each respiratory phase of each patient. Large deformable diffeomorphic image registration was performed to map each CT set from the peak-inhale respiration phase to the CT image sets corresponding with subsequent respiration phases. The calculated displacement vector fields were used to deform contours automatically drawn on the inhale phase to the other respiratory phase CT image sets. The code was interfaced to a treatment planning system to view the resulting images and to obtain the volumetric, displacement, and surface congruence information; 692 automatically generated structures were compared with 692 manually drawn structures. The auto- and manual methods showed similar trends, with a smaller difference observed between the GTVs than other structures. The auto-contoured structures agree with the manually drawn structures, especially in the case of the GTV, to within published interobserver variations. For the GTV, fractional volumes agree to within 0.2+/-0.1, center of mass displacements agree to within 0.5+/-1.5 mm, and agreement of surface congruence is 0.0+/-1.1 mm. The surface congruence between automatic and manual contours for the GTV, heart, left lung, right lung and esophagus was less than 5 mm in 99%, 94%, 94%, 91% and 89%, respectively. Careful assessment of the performance of automatic algorithms is needed in the presence of 4D CT artifacts.

The feasibility and accuracy of using a mock treatment to screen suitable patients for respiratory-gated image-guided radiotherapy was investigated. Radio-opaque fiducials implanted adjacent to the liver tumor were used for online positioning to minimize the systematic error in patient positioning. The consistency in the degree of correlation between the external and internal fiducials was analyzed during a mock treatment. This technique could screen patients for gated therapy, reduce setup inaccuracy, and possibly individualize treatment margins.

Four-dimensional (4D) computed tomography (CT) imaging has found increasing importance in the localization of tumor and surrounding normal structures throughout the respiratory cycle. Based on such tumor motion information, it is possible to identify the appropriate phase interval for respiratory gated treatment planning and delivery. Such a gating phase interval is determined retrospectively based on tumor motion from internal tumor displacement. However, respiratory-gated treatment is delivered prospectively based on motion determined predominantly from an external monitor. Therefore, the simulation gate threshold determined from the retrospective phase interval selected for gating at 4D CT simulation may not correspond to the delivery gate threshold that is determined from the prospective external monitor displacement at treatment delivery. The purpose of the present work is to establish a relationship between the thresholds for respiratory gating determined at CT simulation and treatment delivery, respectively. One hundred fifty external respiratory motion traces, from 90 patients, with and without audio-visual biofeedback, are analyzed. Two respiratory phase intervals, 40%-60% and 30%-70%, are chosen for respiratory gating from the 4D CT-derived tumor motion trajectory. From residual tumor displacements within each such gating phase interval, a simulation gate threshold is defined based on (a) the average and (b) the maximum respiratory displacement within the phase interval. The duty cycle for prospective gated delivery is estimated from the proportion of external monitor displacement data points within both the selected phase interval and the simulation gate threshold. The delivery gate threshold is then determined iteratively to match the above determined duty cycle. The magnitude of the difference between such gate thresholds determined at simulation and treatment delivery is quantified in each case. Phantom motion tests yielded coincidence of simulation and delivery gate thresholds to within 0.3%. For patient data analysis, differences between simulation and delivery gate thresholds are reported as a fraction of the total respiratory motion range. For the smaller phase interval, the differences between simulation and delivery gate thresholds are 8 +/- 11% and 14 +/- 21% with and without audio-visual biofeedback, respectively, when the simulation gate threshold is determined based on the mean respiratory displacement within the 40%-60% gating phase interval. For the longer phase interval, corresponding differences are 4 +/- 7% and 8 +/- 15% with and without audiovisual biofeedback, respectively. Alternatively, when the simulation gate threshold is determined based on the maximum average respiratory displacement within the gating phase interval, greater differences between simulation and delivery gate thresholds are observed. A relationship between retrospective simulation gate threshold and prospective delivery gate threshold for respiratory gating is established and validated for regular and nonregular respiratory motion. Using this relationship, the delivery gate threshold can be reliably estimated at the time of 4D CT simulation, thereby improving the accuracy and efficiency of respiratory-gated radiation delivery.