We summarize recent results and ongoing activities in mathematical algorithms and computer science methods related to proton computed tomography (pCT) and intensity-modulated particle therapy (IMPT) treatment planning. Proton therapy necessitates a high level of delivery accuracy to exploit the selective targeting imparted by the Bragg peak. For this purpose, pCT utilizes the proton beam itself to create images. The technique works by sending a low-intensity beam of protons through the patient and measuring the position, direction, and energy loss of each exiting proton. The pCT technique allows reconstruction of the volumetric distribution of the relative stopping power (RSP) of the patient tissues for use in treatment planning and pre-treatment range verification. We have investigated new ways to make the reconstruction both efficient and accurate. Better accuracy of RSP also enables more robust inverse approaches to IMPT. For IMPT, we developed a framework for performing intensity-modulation of the proton pencil beams. We expect that these developments will lead to additional project work in the years to come, which requires a regular exchange between experts in the fields of mathematics, computer science, and medical physics. We have initiated such an exchange by organizing annual workshops on pCT and IMPT algorithm and technology developments. This report is, admittedly, tilted toward our interdisciplinary work and methods. We offer a comprehensive overview of results, problems, and challenges in pCT and IMPT with the aim of making other scientists wanting to tackle such issues and to strengthen their interdisciplinary collaboration by bringing together cutting-edge know-how from medicine, computer science, physics, and mathematics to bear on medical physics problems at hand.
This contribution describes general concepts for control and safety systems in proton therapy. These concepts are illustrated by concrete examples implemented in the Proscan facility at PSI.
We apply the recently proposed superiorization methodology (SM) to the inverse planning problem in radiation therapy. The inverse planning problem is represented here as a constrained minimization problem of the total variation (TV) of the intensity vector over a large system of linear two-sided inequalities. The SM can be viewed conceptually as lying between feasibility-seeking for the constraints and full-fledged constrained minimization of the objective function subject to these constraints. It is based on the discovery that many feasibility-seeking algorithms (of the projection methods var…
We review the field of multi-criteria optimization for radiation therapy treatment planning. Special attention is given to the technique known as Pareto surface navigation, which allows physicians and treatment planners to interactively navigate through treatment planning options to get an understanding of the tradeoffs (dose to the target versus over-dosing of important nearby organs) involved in each patient's plan. We also describe goal programming and prioritized optimization, two other methods designed to handle multiple conflicting objectives. Issues related to nonconvexities, both in te…
In proton therapy both the energy, which determines the range, and the distal slope, which reflects the rate at which the protons decelerate, are of import if we are to ensure accurate dose deposition and maximum tissue sparing. This publication describes a Geant4 model and presents a two-dimensional polynomial relationship between energy, the energy spread and the distal slope for beams with Gaussian energy spectra for proton therapy. This simple polynomial relationship will be useful for non-invasive or minimally invasive near real-time monitoring of the energy and energy spread of a proton …
Therapeutic protons acting on O18-substituted thymidine increase cytotoxicity in radio-resistant human cancer cells. We consider here the physics behind the irradiation during proton beam therapy and diagnosis using O18-enriched thymine in DNA, with attention to the effect of the presence of thymine-18 on cancer cell death.
In this paper we study a feasibility-seeking problem with percentage violation constraints. These are additional constraints, that are appended to an existing family of constraints, which single out certain subsets of the existing constraints and declare that up to a specified fraction of the number of constraints in each subset is allowed to be violated by up to a specified percentage of the existing bounds. Our motivation to investigate problems with percentage violation constraints comes from the field of radiation therapy treatment planning wherein the fully-discretized inverse planning pr…
We present calculations and simulations on the role of the p+$^{11}$B$\to$3$α$ reaction in proton therapy. This reaction has been recently suggested to be responsible for a decrease in the survival probability of tumor cells, when they are irradiated with low-energy protons. However, at the concentration levels typical of the proposed boron carrier (sodium borocaptate, Na$_{2}$B$_{12}$H$_{11}$SH, in short BSH), i.e. less than 100 ppm, both calculations and Monte Carlo simulations suggest that the dose related to this reaction is orders of magnitude lower than the dose delivered by the primary …
A split feasibility formulation for the inverse problem of intensity-modulated radiation therapy (IMRT) treatment planning with dose-volume constraints (DVCs) included in the planning algorithm is presented. It involves a new type of sparsity constraint that enables the inclusion of a percentage-violation constraint in the model problem and its handling by continuous (as opposed to integer) methods. We propose an iterative algorithmic framework for solving such a problem by applying the feasibility-seeking CQ-algorithm of Byrne combined with the automatic relaxation method (ARM) that uses cycl…
Background and Objective: Recent experimental studies using ultra-high dose rate radiation therapy (FLASH-RT) have shown improved normal tissue sparing and comparable tumor control compared to conventional dose rate RT. Pencil beam scanning (PBS) proton therapy with superior dosimetry characteristics has begun to draw attention to the delivery of conformal FLASH-RT for preclinical studies. This review aims to provide recent updates on the development of PBS FLASH-RT. Methods: The information summarized in this review article is based on search results in databases such as PubMed and search eng…
Secondary radiation in a radiation therapy environment is considered a cause for post-treatment side effects including secondary carcinogenesis. In a proton-therapy setup, neutrons deliver a considerable extra dose to the patient. Various measurements and calculations of neutron dose suggest a wide range of values for this quantity. This paper provides a comparison between the previously published values and analyzes the Monte Carlo calculated neutron dose from the present work using the neutron cross-section data. The purpose is to provide a range for the convergence of several neutron-absorb…
Uncertainties in the proton range in tissue during proton therapy limit the precision in treatment delivery. These uncertainties result in expanded treatment margins, thereby increasing radiation dose to healthy tissue. Real-time range verification techniques aim to reduce these uncertainties in order to take full advantage of the finite range of the primary protons. In this paper, we propose a novel concept for real-time range verification based on detection of secondary neutrons produced in nuclear interactions during proton therapy. The proposed detector concept is simple; consisting of a h…
The advanced imaging and delivery techniques in proton therapy allow conformal high-dose irradiation of the target volume with high accuracy using pencil beam scanning or beam shaping apertures. These irradiation methods increasingly include small radiation fields with large dose gradients, which require detector systems with high spatial resolution for quality assurance. In addition the measurement of all success parameters for daily quality assurance with only one proton field and one simple detector system would save a lot of time in clinical usage. Based on their good spatial resolution an…
Previous measurements have shown large cross sections for the 11B(p,$α$)8Be reaction and K-shell ionization of boron from H+ ions. Past publications have shown that this reaction will likely increase the efficacy of proton therapy. This study investigates the size of boron particles for optimum treatment enhancement in proton therapy. Simulations of protons passing through varying sized boron particles were developed to compare energy outputs for alpha particles and low energy electrons. The results for the boron particle radius that produced the largest radiation output are presented in graph…
Noncoplanar radiation therapy treatment planning has the potential to improve dosimetric quality as compared to traditional coplanar techniques. Likewise, automated treatment planning algorithms can reduce a planner's active treatment planning time and remove inter-planner variability. To address the limitations of traditional treatment planning, we have been developing a suite of algorithms called station parameter optimized radiation therapy (SPORT). Within the SPORT suite of algorithms, we propose a method called NC-POPS to produce noncoplanar (NC) plans using the fully automated Pareto Opt…
Proton Pencil-Beam Scanning Stereotactic Body Radiation Therapy and Hypofractionated Radiation Therapy for Thoracic Malignancies: Patterns of Practice Survey and Recommendations for Future Development from NRG Oncology and PTCOG
University of Toronto（多伦多大学）；Princess Margaret Cancer Centre（玛格丽特公主癌症中心）；York University（约克大学）
Knowledge-based planning (KBP) is an automated approach to radiation therapy treatment planning that involves predicting desirable treatment plans before they are then corrected to deliverable ones. We propose a generative adversarial network (GAN) approach for predicting desirable 3D dose distributions that eschews the previous paradigms of site-specific feature engineering and predicting low-dimensional representations of the plan. Experiments on a dataset of oropharyngeal cancer patients show that our approach significantly outperforms previous methods on several clinical satisfaction crite…
We present an optimization-based approach to radiation treatment planning over time. Our approach formulates treatment planning as an optimal control problem with nonlinear patient health dynamics derived from the standard linear-quadratic cell survival model. As the formulation is nonconvex, we propose a method for obtaining an approximate solution by solving a sequence of convex optimization problems. This method is fast, efficient, and robust to model error, adapting readily to changes in the patient's health between treatment sessions. Moreover, we show that it can be combined with the ope…
The proton boron fusion reaction, 11B(p, 3α), is investigated using MCNP6 to assess the viability for potential use in radiation therapy. The 11B(p, 3α) is theoretically desirable because it could combine the localized dose delivery protons exhibit (Bragg peak) with the creation of three high LET α particles that locally deposit energy in tumor regions. Simple simulations of a proton pencil beam incident upon a water phantom and a water phantom with an axial region also containing boron were modeled using MCNP6 in order to determine the extent of the impact boron had upon the calculated energy…
PET imaging is a non-invasive technique for particle range verification in proton therapy. It is based on measuring the beta+ annihilations caused by nuclear interactions of the protons in the patient. In this work we present measurements for proton range verification in phantoms, performed at the CNAO particle therapy treatment center in Pavia, Italy, with our 10 x 10 cm^2 planar PET prototype DoPET. PMMA phantoms were irradiated with mono-energetic proton beams and clinical treatment plans, and PET data were acquired during and shortly after proton irradiation. We created 1-D profiles of the…
Cao et al (2018) published an article on inverse planning based on dose-averaged linear energy transfer (LET). Their claim that the problem can be cast as a linear optimization model relies on an incorrect application of the Charnes-Cooper transformation. In this comment we show that their linear model is simlar to one where dose-averaged LET is multiplied with dose, explaining why their model was nonetheless able to improve the LET distribution.
Physical and biological range uncertainties limit the clinical potential of Proton Beam Therapy (PBT). In this proceedings, we report on two research projects, which we are conducting in parallel and which both tackle the problem of range uncertainties. One aims at developing software tools and the other at developing detector instrumentation. Regarding the first, we report on our development and pre-clinical application of a GPU-accelerated Monte Carlo (MC) simulation toolkit Fred. Concerning the letter, we report on our investigations of plastic scintillator based PET detectors for particle …
To expedite the commissioning process of the proton therapy system at Samsung Medical Center (SMC), we have developed a Monte Carlo simulation model of the proton therapy nozzles using TOPAS. At SMC proton therapy center, we have two gantry rooms with different types of nozzles; a multi-purpose nozzle and a dedicated scanning nozzle. Each nozzle has been modeled in detail following the geometry information provided by the manufacturer, Sumitomo Heavy Industries, Ltd. For this purpose, novel features of TOPAS, such as the time feature or the ridge filter class, have been used. And the appropria…
Radiotherapy is one of the main methods in the successful treatment of cancer. The tumor is irradiated with photons or charged particles (e.g. protons), and in the case of massive charged particles, the treatment results in less unnecessary dose outside the tumor and therefore less side effects for the patient and a faster recovery. However, the dose planning of hadron therapy is calculated from photon CT measurements, which results in large uncertainties in the planning and therefore in a necessary enlargement of the treatment area. This uncertainty can be reduced by performing the CT scan us…
Objective: Radiation therapy treatment planning is a time-consuming process involving iterative adjustments of hyperparameters. To automate the treatment planning process, we propose a meta-optimization framework, called MetaPlanner (MP). Methods: Our MP algorithm automates planning by performing optimization of treatment planning hyperparameters. The algorithm uses a derivative-free method (i.e. parallel Nelder-Mead simplex search) to search for weight configurations that minimize a meta-scoring function. Meta-scoring is performed by constructing a tier list of the relevant considerations (e.…
Background: A relative biological effectiveness (RBE) of 1.1 is used for proton therapy though clinical evidence of varying RBE was raised. Clinical studies on RBE variability have been conducted for decades for carbon radiation, which could advance the understanding of the clinical proton RBE given an ion-independent RBE model. In this work, such a model, linear and simple, using the beam quantity Q = Z^2/E (Z = ion charge, E = kinetic energy per nucleon) was tested and compared to the commonly used, proton-specific and linear energy transfer (LET) based Wedenberg RBE model. Material and meth…
Radiation therapy treatment planning can be viewed as an iterative hyperparameter tuning process to balance conflicting clinical goals. In this work, we investigated the performance of modern Bayesian Optimization (BO) methods on automated treatment planning problems in high-dimensional settings. 20 locally advanced rectal cancer patients treated with intensity-modulated radiation therapy (IMRT) were retrospectively selected as test cases. We implemented an automated treatment planning framework that adjusts dose objectives and weights simultaneously, and tested the performance of two BO metho…
For the in vivo range verification in proton therapy, it has been tried to measure the spatial distribution of the prompt gammas generated by the proton-induced interactions with the close relationship with the proton dose distribution. However, the high energy of the prompt gammas and background gammas are still problematic in measuring the distribution. In this study, we suggested a new method determining the in vivo range by utilizing the time structure of the prompt gammas formed with the rotation of a range modulation wheel (RMW) in the passive scattering proton therapy. To validate the M…
The radiotherapy of malignant diseases has reached much progress during the past decade. Thus, intensity modulated radiation therapy (IMRT) and VMAT (Rapidarc) now belong to the standard modalities of tumor treatment with high energy radiation in clinical practice. In recent time, the particle therapy (protons and partially with heavy carbon ions) has reached an important completion of these modalities with regard to some suitable applications. In spite of this enrichment essential features need further research activities and publications in this field: Nuclear reactions and the role of the r…
We propose a novel optimization model for volumetric modulated arc therapy (VMAT) planning that directly optimizes deliverable leaf trajectories in the treatment plan optimization problem, and eliminates the need for a separate arc-sequencing step. In this model, a 360-degree arc is divided into a given number of arc segments in which the leaves move unidirectionally. This facilitates an algorithm that determines the optimal piecewise linear leaf trajectories for each arc segment, which are deliverable in a given treatment time. Multi-leaf collimator (MLC) constraints, including maximum leaf s…
The performance of the energy degrader in terms of beam properties directly impacts the design and cost of cyclotron-based proton therapy centers. The aim of this study is to evaluate the performances of different existing and novel degrader materials. The quantitative estimate is based on detailed GEANT4 simulations that analyze the beam-matter interaction and provide a determination of the beam emittance increase and transmission. Comparisons between existing (aluminum, graphite, beryllium) and novel (boron carbide and diamond) degrader materials are provided and evaluated against semi-analy…
The total nuclear cross-section Qtot(E) resulting from the interaction of protons with nuclei is decomposed in 3 different contributions: 1. elastic scatter at the complete nucleus, which adopts a part of the proton kinetic energy; 2. inelastic scatter at a nucleus, which changes its quantum numbers by vibrations, rotations, transition to highly excited states; 3. proper nuclear reactions with change of the mass and/or charge number. Then different particles leave the hit nucleus (neutrons, protons, etc.), which is now referred to as 'heavy recoil' nucleus. The scatter parts of Qtot(E) accordi…
Objective: We propose a semiautomatic pipeline for radiation therapy treatment planning, combining ideas from machine learning-automated planning and multicriteria optimization (MCO). Approach: Using knowledge extracted from historically delivered plans, prediction models for spatial dose and dose statistics are trained and furthermore systematically modified to simulate changes in tradeoff priorities, creating a set of differently biased predictions. Based on the predictions, an MCO problem is subsequently constructed using previously developed dose mimicking functions, designed in such a way…
Depth distributions of positron-emitting nuclei in PMMA phantoms are calculated within a Monte Carlo model for Heavy-Ion Therapy (MCHIT) based on the GEANT4 toolkit (version 8.0). The calculated total production rates of $^{11}$C, $^{10}$C and $^{15}$O nuclei are compared with experimental data and with corresponding results of the FLUKA and POSGEN codes. The distributions of e$^+$ annihilation points are obtained by simulating radioactive decay of unstable nuclei and transporting positrons in surrounding medium. A finite spatial resolution of the Positron Emission Tomography (PET) is taken in…
We present a method of directly optimizing on deviations in clinical goal values in radiation therapy treatment planning. Using a new mathematical framework in which metrics derived from the dose-volume histogram are regarded as functionals of an auxiliary random variable, we are able to obtain volume-at-dose and dose-at-volume as infinitely differentiable functions of the dose distribution with easily evaluable function values and gradients. Motivated by the connection to risk measures in finance, which is formalized in this framework, we also derive closed-form formulas for mean-tail-dose an…
We demonstrate the application of mixture density networks (MDNs) in the context of automated radiation therapy treatment planning. It is shown that an MDN can produce good predictions of dose distributions as well as reflect uncertain decision making associated with inherently conflicting clinical tradeoffs, in contrast to deterministic methods previously investigated in literature. A two-component Gaussian MDN is trained on a set of treatment plans for postoperative prostate patients with varying extents to which rectum dose sparing was prioritized over target coverage. Examination on a test…
The determination of relative stopping power (RSP) via proton computed tomography (pCT) of a patient is dependent in part on the knowledge of the incoming proton kinetic energies; the uncertainty in these energies is in turn determined by the proton source -- typically a cyclotron. Here we show that reducing the incident proton beam energy spread may significantly improve RSP determination in pCT. We demonstrate that the reduction of beam energy spread from the typical 1.0% (at 70MeV) down to 0.2%, can be achieved at the proton currents needed for imaging at the Paul Scherrer Institut 230MeV c…
Introduction. Treatment planning systems (TPS) are an essential component for simulating and optimizing a radiation therapy treatment before administering it to the patient. It ensures that the tumor is well covered and the dose to the healthy tissues is minimized. However, the TPS provided by commercial companies often come with a large panel of tools, each implemented in the form of a black-box making it difficult for researchers to use them for implementing and testing new ideas. To address this issue, we have developed an open-source TPS. Approach. We have developed an open-source software…
Radiotherapy treatment planning currently requires many trail-and-error iterations between the planner and treatment planning system, as well as between the planner and physician for discussion/consultation. The physician's preferences for a particular patient cannot be easily quantified and precisely conveyed to the planner. In this study we present a real-time volumetric Pareto surface dose generation deep learning neural network that can be used after segmentation by the physician, adding a tangible and quantifiable end-point to portray to the planner. From 70 prostate patients, we first ge…
Purpose: We present a framework for robust automated treatment planning using machine learning, comprising scenario-specific dose prediction and robust dose mimicking. Methods: The scenario dose prediction pipeline is divided into the prediction of nominal dose from input image and the prediction of scenario dose from nominal dose, each using a deep learning model with U-net architecture. By using a specially developed dose-volume histogram-based loss function, the predicted scenario doses are ensured sufficient target coverage despite the possibility of the training data being non-robust. Del…
Charged particle therapy (CPT) is an advanced modality of radiation therapy which has grown rapidly worldwide, driven by recent developments in technology and methods of delivery. To ensure safe and high quality treatments, various instruments are used for a range of different measurements such as for quality assurance, monitoring and dosimetry purposes. With the emergence of new and enhanced delivery techniques, systems with improved capabilities are needed to exceed existing performance limitations of conventional tools. The Medipix3 is a hybrid pixel detector able to count individual proton…
This manuscript provides a response to a recent report by Mazzone et al. available online on arXiv that, in turn, tentatively aims at demonstrating the inefficacy of proton boron capture in hadrotherapy. We clarify that Mazzone et al. do not add any scientific or technical insights to the points extensively discussed in the original manuscript by Cirrone et al., and/or in the series of iterations had with the Referee, which ultimately lead to the publication of our original and pioneering experimental work. Here we summarize some of the key points of the long scientific debate we had during th…
