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In proton-based radiotherapy, proton radiography could allow for direct measurement of the water-equivalent path length (WEPL) in tissue, which can then be used to determine relative stopping power (RSP). Additionally, proton radiographs allow for imaging in the beam's-eye-view. In this work, a proton radiography technique using a flat-panel imager and a pencil-beam scanning (PBS) system is demonstrated in phantom. Proton PBS plans were delivered on a Varian ProBeam system to a flat-panel imager. Each proton plan consisted of energy layers separated by 4.8 MeV, and a field size of 25 cm × 25 cm. All measured data is binned into a layer-by-layer delivery in post processing. To build a calibration curve correlating detector response to WEPL, the plans were delivered to slabs of solid water of increasing thickness. Pixel-by-pixel detector response in the time/energy domain is then fit as a function of WEPL. Tissue equivalent phantoms are imaged for evaluation of WEPL accuracy. A spatial resolution phantom and a head phantom are also imaged. For all experiments, the detector was run with an effective pixel size of 0.4 mm × 0.4 mm. The proposed method reconstructed RSP with mean errors of 2.65%, -0.14%, and 0.61% for lung, soft tissue, and bone, respectively. In a 40 mm thick spatial resolution phantom, a 2 mm deep pinhole with 1 mm diameter can be seen. The accuracy and spatial resolution of the method show that it could be implemented for patient position verification. Further development could lead to patient-specific verification of RSP to be used for treatment guidance.

Background: Proton therapy is preferred for its dose conformality to spare normal tissues and organs‐at‐risk (OAR) via Bragg peaks with negligible exit dose. However, proton dose conformality can be further optimized: (1) the spot placement is based on the structured (e.g., Cartesian) grid, which may not offer conformal shaping to complex tumor targets; (2) the spot sampling pattern is uniform, which may be insufficient at the tumor boundary to provide the sharp dose falloff, and at the same time may be redundant at the tumor interior to provide the uniform dose coverage, for example, due to multiple Coulomb scattering (MCS); and (3) the lateral spot penumbra increases with respect to the depth due to MCS, which blurs the lateral dose falloff. On the other hand, while (1) the deliverable spots are subject to the minimum‐monitor‐unit (MMU) constraint, and (2) the dose rate is proportional to the MMU threshold, the current spot sampling method is sensitive to the MMU threshold and can fail to provide satisfactory plan quality for a large MMU threshold (i.e., high‐dose‐rate delivery). Purpose: This work will develop a novel Triangular‐mEsh‐based Adaptive and Multiscale (TEAM) proton spot generation method to address these issues for optimizing proton dose conformality and plan delivery efficiency. Methods: Compared to the standard clinically‐used spot placement method, three key elements of TEAM are as follows: (1) a triangular mesh instead of a structured grid: the triangular mesh is geometrically more conformal to complex target shapes and therefore more efficient and accurate for dose shaping inside and around the target; (2) adaptive sampling instead of uniform sampling: the adaptive sampling consists of relatively dense sampling at the tumor boundary to create the sharp dose falloff, which is more accurate, and coarse sampling at the tumor interior to uniformly cover the target, which is more efficient; and (3) depth‐dependent sampling instead of depth‐independent sampling: the depth‐dependent sampling is used to compensate for MCS, that is, with increasingly dense sampling at the tumor boundary to improve dose shaping accuracy, and increasingly coarse sampling at the tumor interior to improve dose shaping efficiency, as the depth increases. In the TEAM method the spot locations are generated for each energy layer and layer‐by‐layer in the multiscale fashion; and then the spot weights are derived by solving the IMPT problem of dose‐volume planning objectives, MMU constraints, and robustness optimization with respect to range and setup uncertainties. Results: Compared to the standard clinically‐used spot placement method UNIFORM, TEAM achieved (1) better plan quality using <60% number of spots of UNIFORM; (2) better robustness to the number of spots; (3) better robustness to a large MMU threshold. Furthermore, TEAM provided better plan quality with fewer spots than other adaptive methods (Cartesian‐grid or triangular‐mesh). Conclusions: A novel triangular‐mesh‐based proton spot placement method called TEAM is proposed, and it is demonstrated to improve plan quality, robustness to the number of spots, and robustness to the MMU threshold, compared to the clinically‐used spot placement method and other adaptive methods. [ABSTRACT FROM AUTHOR]

Background: Proton spatially fractionated RT (SFRT) can potentially synergize the unique advantages of using proton Bragg peak and SFRT peak‐valley dose ratio (PVDR) to reduce the radiation‐induced damage for normal tissues. Uniform‐target‐dose (UTD) proton GRID is a proton SFRT modality that can be clinically desirable and conveniently adopted since its UTD resembles target dose distribution in conventional proton RT (CONV). However, UTD proton GRID is not used clinically, which is likely due to the lack of an effective treatment planning method. Purpose: This work will develop a novel treatment planning method using scissor beams (SB) for UTD proton GRID, with the joint optimization of PVDR and dose objectives. Methods: The SB method for spatial dose modulation in normal tissues with UTD has two steps: (1) a primary beam (PB) is halved with interleaved beamlets, to generate spatial dose modulation in normal tissues; (2) a complementary beam (CB) is added to fill in previously valley‐dose positions in the target to generate UTD, while the CB is angled slightly from the PB, to maintain spatial dose modulation in normal tissues. A treatment planning method with PVDR optimization via the joint total variation and L1 (TVL1) regularization is developed to jointly optimize PVDR and dose objectives. The plan optimization solution is obtained using an iterative convex relaxation algorithm. Results: The new methods SB and SB‐TVL1 were validated in comparison with CONV. Compared to CONV of relatively homogeneous dose distribution, SB had modulated spatial dose pattern in normal tissues with UTD and comparable plan quality. Compared to SB, SB‐TVL1 further maximized PVDR, with comparable dose‐volume parameters. Conclusions: A novel SB method is proposed that can generate modulated spatial dose pattern in normal tissues to achieve UTD proton GRID. A treatment planning method with PVDR optimization capability via TVL1 regularization is developed that can jointly optimize PVDR and dose objectives for proton GRID. [ABSTRACT FROM AUTHOR]

Background: Although the FLASH radiotherapy (FLASH) can improve the sparing of organs‐at‐risk (OAR) via the FLASH effect, it is generally a tradeoff between the physical dose coverage and the biological FLASH coverage, for which the concept of FLASH effective dose (FED) is needed to quantify the net improvement of FLASH, compared to the conventional radiotherapy (CONV). Purpose: This work will develop the first‐of‐its‐kind treatment planning method called simultaneous dose and dose rate optimization via dose modifying factor modeling (SDDRO‐DMF) for proton FLASH that directly optimizes FED. Methods: SDDRO‐DMF models and optimizes FED using FLASH dose modifying factor (DMF) models, which can be classified into two categories: (1) the phenomenological model of the FLASH effect, such as the FLASH effectiveness model (FEM); (2) the mechanistic model of the FLASH radiobiology, such as the radiolytic oxygen depletion (ROD) model. The general framework of SDDRO‐DMF will be developed, with specific DMF models using FEM and ROD, as a demonstration of general applicability of SDDRO‐DMF for proton FLASH via transmission beams (TB) or Bragg peaks (BP) with single‐field or multi‐field irradiation. The FLASH dose rate is modeled as pencil beam scanning dose rate. The solution algorithm for solving the inverse optimization problem of SDDRO‐DMF is based on iterative convex relaxation method. Results: SDDRO‐DMF is validated in comparison with IMPT and a state‐of‐the‐art method called SDDRO, with demonstrated efficacy and improvement for reducing the high dose and the high‐dose volume for OAR in terms of FED. For example, in a SBRT lung case of the dose‐limiting factor that the max dose of brachial plexus should be no more than 26 Gy, only SDDRO‐DMF met this max dose constraint; moreover, SDDRO‐DMF completely eliminated the high‐dose (V70%) volume to zero for CTV10mm (a high‐dose region as a 10 mm ring expansion of CTV). Conclusion: We have proposed a new proton FLASH optimization method called SDDRO‐DMF that directly optimizes FED using phenomenological or mechanistic models of DMF, and have demonstrated the efficacy of SDDO‐DMF in reducing the high‐dose volume or/and the high‐dose value for OAR, compared to IMPT and a state‐of‐the‐art method SDDRO. [ABSTRACT FROM AUTHOR]

Background: Minibeam represents a preclinical spatially fractionated radiotherapy modality with great translational potential. The advantage lies in its high therapeutic index (compared to GRID and LATTICE) and ability to treat at greater depth (compared to microbeam). Proton minibeam radiotherapy (pMBRT) is a synergy of proton and minibeam. While the single‐gantry proton facility has gained popularity due to its affordability and compact design, it often has limited beam time available for research purposes. Conversely, given the current requirement of pMBRT on specific minibeam hardware collimators, necessitates a reproducible and fast setup to minimize pMBRT treatment time and streamline the switching time between pMBRT and conventional treatment for clinically translation. Purpose: The contribution of this work is the development and characterization of the first pMBRT system tailored for single‐gantry proton facility. The system allows for efficient and reproducible plug‐and‐play setup, achievable within minutes. Methods: The single room pMBRT system is constructed based on IBA ProteusONE proton machine. The end of nozzle is attached with beam modifying accessories though an accessory drawer. A small snout is attached to the accessory drawer and used to hold apertures and range shifters. The minibeam aperture consists of two components: a fitting ring and an aperture body. Three minibeam apertures were manufactured. The first‐generation apertures underwent qualitatively analysis with film, and the second generation aperture underwent more comprehensive quantitative measurement. The reproducibility of the setup is accessed, and the film measurements are performed to characterize the pMBRT system in cross validation with Monte Carlo (MC) simulations. Results: We presented initial results of large field pMBRT aperture and the film measurements indicates the effect of source‐to‐isocenter distance = 930 cm in Y proton scanning direction. Consistent with TOPAS MC simulation, the dose uniformity of pMBRT field <2 cm is demonstrated to be better than 2%, rendering its suitability for pre‐clinical studies. Subsequently, we developed the second generation of aperture with five slits and characterized the aperture with film dosimetry studies and compared the results to the benchmark MC. Comprehensive film measurements were also performed to evaluate the effect of divergence, air gap and gantry‐angle dependency and repeatability and revealing a consistent performance within 5%. Furthermore, the 2D gamma analysis indicated a passing rate exceeding 99% using 3% dose difference and 0.2 mm distance agreement criteria. We also establish the peak valley dose ratio and the depth dose profile measurements, and the results are within 10% from MC simulation. Conclusions: We have developed the first pMBRT system tailored for a single‐gantry proton facility, which has demonstrated accuracy in benchmark with MC simulations, and allows for efficient plug‐and‐play setup, emphasizing efficiency. [ABSTRACT FROM AUTHOR]

Background: LATTICE radiation therapy delivers 3D heterogenous dose of high peak‐to‐valley dose ratio (PVDR) to the tumor target, with peak dose at lattice vertices inside the target and valley dose for the rest of the target. Although the lattice vertex positions can impact PVDR inside the target and sparing of organs‐at‐risk (OAR), they are fixed as constants and not optimized during treatment planning in current clinical practice. Purpose: This work proposes a new LATTICE plan optimization method that can optimize lattice vertex positions during LATTICE treatment planning, which is the first lattice position optimization study to the best of our knowledge. Methods: The new LATTICE treatment planning method optimizes lattice vertex positions as well as other plan variables (e.g., photon fluences or proton spot weights), with optimization objectives for target PVDR and OAR sparing. To satisfy mathematical differentiability, the lattice vertices are approximated in sigmoid functions. For geometric feasibility, proper geometry constraints are enforced onto lattice vertex positions. The lattice position optimization problem is solved by iterative convex relaxation (ICR) method and alternating direction method of multipliers (ADMM), and lattice vertex positions and photon/proton plan variables are jointly updated via the Quasi‐Newton method. Results: Both photon and proton LATTICE RT were considered, and the optimal lattice vertex positions in terms of plan objectives were found by solving all possible combinations on given discrete positions via exhaustive searching based on standard IMRT/IMPT, which served as the ground truth for validating the new LATTICE method. The results show that the new method indeed provided the optimal lattice vertex positions with the smallest optimization objective, the largest target PVDR, and the best OAR sparing. Conclusions: A new LATTICE treatment planning method is proposed and validated that can optimize lattice vertex positions as well as other photon or proton plan variables for improving target PVDR and OAR sparing. [ABSTRACT FROM AUTHOR]

Background: The intensities (i.e., number of protons in monitor unit [MU]) of deliverable proton spots need to be either zero or meet a minimum‐MU (MMU) threshold, which is a nonconvex problem. Since the dose rate is proportionally associated with the MMU threshold, higher‐dose‐rate proton radiation therapy (RT) (e.g., efficient intensity modulated proton therapy (IMPT) and ARC proton therapy, and high‐dose‐rate‐induced FLASH effect needs to solve the MMU problem with larger MMU threshold, which however makes the nonconvex problem more difficult to solve. Purpose: This work will develop a more effective optimization method based on orthogonal matching pursuit (OMP) for solving the MMU problem with large MMU thresholds, compared to state‐of‐the‐art methods, such as alternating direction method of multipliers (ADMM), proximal gradient descent method (PGD), or stochastic coordinate descent method (SCD). Methods: The new method consists of two essential components. First, the iterative convex relaxation (ICR) method is used to determine the active sets for dose‐volume planning constraints and decouple the MMU constraint from the rest. Second, a modified OMP optimization algorithm is used to handle the MMU constraint: the non‐zero spots are greedily selected via OMP to form the solution set to be optimized, and then a convex constrained subproblem is formed and can be conveniently solved to optimize the spot weights restricted to this solution set via OMP. During this iterative process, the new non‐zero spots localized via OMP will be adaptively added to or removed from the optimization objective. Results: The new method via OMP is validated in comparison with ADMM, PGD and SCD for high‐dose‐rate IMPT, ARC, and FLASH problems of large MMU thresholds, and the results suggest that OMP substantially improved the plan quality from PGD, ADMM and SCD in terms of both target dose conformality (e.g., quantified by max target dose and conformity index) and normal tissue sparing (e.g., mean and max dose). For example, in the brain case, the max target dose for IMPT/ARC/FLASH was 368.0%/358.3%/283.4% respectively for PGD, 154.4%/179.8%/150.0% for ADMM, 134.5%/130.4%/123.0% for SCD, while it was <120% in all scenarios for OMP; compared to PGD/ADMM/SCD, OMP improved the conformity index from 0.42/0.52/0.33 to 0.65 for IMPT and 0.46/0.60/0.61 to 0.83 for ARC. Conclusions: A new OMP‐based optimization algorithm is developed to solve the MMU problems with large MMU thresholds, and validated using examples of IMPT, ARC, and FLASH with substantially improved plan quality from ADMM, PGD, and SCD. [ABSTRACT FROM AUTHOR]

Objective. The optimization of energy layer distributions is crucial to proton arc therapy: on one hand, a sufficient number of energy layers is needed to ensure the plan quality; on the other hand, an excess number of energy jumps (NEJ) can substantially slow down the treatment delivery. This work will develop a new treatment plan optimization method with direct minimization of (NEJ), which will be shown to outperform state-of-the-art methods in both plan quality and delivery efficiency. Approach. The proposed method jointly optimizes the plan quality and minimizes the NEJ. To minimize NEJ, (1) the proton spots x is summed per energy layer to form the energy vector y ; (2) y is binarized via sigmoid transform into y 1 ; (3) y 1 is multiplied with a predefined energy order vector via dot product into y 2; (4) y 2 is filtered through the finite-differencing kernel into y 3 in order to identify NEJ; (5) only the NEJ of y 3 is penalized, while x is optimized for plan quality. The solution algorithm to this new method is based on iterative convex relaxation. Main results. The new method is validated in comparison with state-of-the-art methods called energy sequencing (ES) method and energy matrix (EM) method. In terms of delivery efficiency, the new method had fewer NEJ, less energy switching time, and generally less total delivery time. In terms of plan quality, the new method had smaller optimization objective values, lower normal tissue dose, and generally better target coverage. Significance. We have developed a new treatment plan optimization method with direct minimization of NEJ, and demonstrated that this new method outperformed state-of-the-art methods (ES and EM) in both plan quality and delivery efficiency. [ABSTRACT FROM AUTHOR]

Objective: A constant relative biological effectiveness of 1.1 in current clinical practice of proton radiotherapy (RT) is a crude approximation and may severely underestimate the biological dose from proton RT to normal tissues, especially near the treatment target at the end of Bragg peaks that exhibits high linear energy transfer (LET). LET optimization can account for biological effectiveness of protons during treatment planning, for minimizing biological proton dose and hot spots to normal tissues. However, the LET optimization is usually nonlinear and nonconvex to solve, for which this work will develop an effective optimization method based on iterative convex relaxation (ICR). Approach : In contrast to the generic nonlinear optimization method, such as Quasi-Newton (QN) method, that does not account for specific characteristics of LET optimization, ICR is tailored to LET modeling and optimization in order to effectively and efficiently solve the LET problem. Specifically, nonlinear dose-averaged LET term is iteratively linearized and becomes convex during ICR, while nonconvex dose-volume constraint and minimum-monitor-unit constraint are also handled by ICR, so that the solution for LET optimization is obtained by solving a sequence of convex and linearized convex subproblems. Since the high LET mostly occurs near the target, a 1 cm normal-tissue expansion of clinical target volume (CTV) (excluding CTV), i.e. CTV1cm, is defined to as an auxiliary structure during treatment planning, where LET is minimized. Main results : ICR was validated in comparison with QN for abdomen, lung, and head-and-neck cases. ICR was effective for LET optimization, as ICR substantially reduced the LET and biological dose in CTV1cm the ring, with preserved dose conformality to CTV. Compared to QN, ICR had smaller LET, physical and biological dose in CTV1cm, and higher conformity index values; ICR was also computationally more efficient, which was about 3 times faster than QN. Significance : A LET-specific optimization method based on ICR has been developed for solving proton LET optimization, which has been shown to be more computationally efficient than generic nonlinear optimizer via QN, with better plan quality in terms of LET, biological and physical dose conformality. [ABSTRACT FROM AUTHOR]

Purpose: Spot‐scanning arc therapy (SPArc) is an emerging proton modality that can potentially offer a combination of advantages in plan quality and delivery efficiency, compared with traditional IMPT of a few beam angles. Unlike IMPT, frequent low‐to‐high energy layer switching (so called switch‐up (SU)) can degrade delivery efficiency for SPArc. However, it is a tradeoff between the minimization of SU times and the optimization of plan quality. This work will consider the energy layer optimization (ELO) problem for SPArc and develop a new ELO method via energy matrix (EM) regularization to improve plan quality and delivery efficiency. Methods: The major innovation of EM method for ELO is to design an EM that encourages desirable energy‐layer map with minimal SU during SPArc, and then incorporate this EM into the SPArc treatment planning to simultaneously minimize the number of SU and optimize plan quality. The EM method is solved by the fast iterative shrinkage‐thresholding algorithm and validated in comparison with a state‐of‐the‐art method, so‐called energy sequencing (ES). Results: EM is validated and compared with ES using representative clinical cases. In terms of delivery efficiency, EM had fewer SU than ES with an average of 35% reduction of SU. In terms of plan quality, compared with ES, EM had smaller optimization objective values and better target dose conformality, and generally lower dose to organs‐at‐risk and lower integral dose to body. In terms of computational efficiency, EM was substantially more efficient than ES by at least 10‐fold. Conclusion: We have developed a new ELO method for SPArc using EM regularization and shown that this new method EM can improve both delivery efficiency and plan quality, with substantially reduced computational time, compared with ES. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this work is to investigate the radiosensitizing effect of gold nanoparticle (GNP) induced vasculature damage for proton, megavoltage (MV) photon, and kilovoltage (kV) photon irradiation. Methods: Monte Carlo simulations were carried out using tool for particle simulation (TOPAS) to obtain the spatial dose distribution in close proximity up to 20 µm from the GNPs. The spatial dose distribution from GNPs was used as an input to calculate the dose deposited to the blood vessels. GNP induced vasculature damage was evaluated for three particle sources (a clinical spread out Bragg peak proton beam, a 6 MV photon beam, and two kV photon beams). For each particle source, various depths in tissue, GNP sizes (2, 10, and 20 nm diameter), and vessel diameters (8, 14, and 20 µm) were investigated. Two GNP distributions in lumen were considered, either homogeneously distributed in the vessel or attached to the inner wall of the vessel. Doses of 30 Gy and 2 Gy were considered, representing typical in vivo enhancement studies and conventional clinical fractionation, respectively. Results: These simulations showed that for 20 Au-mg/g GNP blood concentration homogeneously distributed in the vessel, the additional dose at the inner vascular wall encircling the lumen was 43% of the prescribed dose at the depth of treatment for the 250 kVp photon source, 1% for the 6 MV photon source, and 0.1% for the proton beam. For kV photons, GNPs caused 15% more dose in the vascular wall for 150 kVp source than for 250 kVp. For 6 MV photons, GNPs caused 0.2% more dose in the vascular wall at 20 cm depth in water as compared to at depth of maximum dose (Dmax). For proton therapy, GNPs caused the same dose in the vascular wall for all depths across the spread out Bragg peak with 12.7 cm range and 7 cm modulation. For the same weight of GNPs in the vessel, 2 nm diameter GNPs caused three times more damage to the vessel than 20 nm diameter GNPs. When the GNPs were attached to the inner vascular wall, the damage to the inner vascular wall can be up to 207% of the prescribed dose for the 250 kVp photon source, 4% for the 6 MV photon source, and 2% for the proton beam. Even though the average dose increase from the proton beam and MV photon beam was not large, there were high dose spikes that elevate the local dose of the parts of the blood vessel to be higher than 15 Gy even for 2 Gy prescribed dose, especially when the GNPs can be actively targeted to the endothelial cells. Conclusions: GNPs can potentially be used to enhance radiation therapy by causing vasculature damage through high dose spikes caused by the addition of GNPs especially for hypofractionated treatment. If GNPs are designed to actively accumulate at the tumor vasculature walls, vasculature damage can be increased significantly. The largest enhancement is seen using kilovoltage photons due to the photoelectric effect. Although no significant average dose enhancement was observed for the whole vasculature structure for both MV photons and protons, they can cause high local dose escalation (>15 Gy) to areas of the blood vessel that can potentially contribute to the disruption of the functionality of the blood vessels in the tumor. [ABSTRACT FROM AUTHOR]