Purpose: To develop a novel aperture-based algorithm for volumetric modulated arc therapy (VMAT) treatment plan optimization with high quality and high efficiency. Methods: The VMAT optimization problem is formulated as a large-scale convex programming problem solved by a column generation approach. We consider a cost function consisting two terms, the first which enforces a desired dose distribution while the second guarantees a smooth dose rate variation between successive gantry angles. At each iteration of the column generation method, a subproblem is first solved to generate one more deliverable MLC aperture which potentially decreases the cost function most effectively. A subsequent master problem is then solved to determine the dose rate at all currently generated apertures by minimizing the cost function. The iteration of such an algorithm yields a set of deliverable apertures, as well as dose rates, at all gantry angles. Results: The algorithm was preliminarily tested on five prostate and five head-and-neck clinical cases, each with one full gantry rotation and without any couch/collimator rotations. Compared to corresponding co-planar IMRT treatment plans (9 fields for prostate cases and 5 fields for head-and-neck cases), the VMAT plans delivered much lower doses to critical structures and more conformal doses to targets. Moreover, extremely high efficiency has been achieved in our algorithm. It takes only 5~8 minutes on CPU (MATLAB code on an Intel Xeon 2.27 GHz CPU) and 18~31 seconds on GPU (CUDA code on an NVIDIA Tesla C1060 GPU card) to generate such a plan. Conclusions: We have developed an aperture-based VMAT optimization algorithm which can generate clinically deliverable and high quality treatment plans at very high efficiency.
This study evaluates dynamic conformal arc (DCA) therapy as an alternative to volumetric modulated arc therapy (VMAT) for stereotactic body radiation therapy (SBRT) of lung cancer. The rationale for DCA is lower geometric complexity and hence reduced risk for interplay errors induced by respiratory motion. Forward planned DCA and inverse planned DCA based on segment-weight optimization were compared to VMAT for single arc treatments of three lung patients. Analysis of dose-volume histograms and clinical goal fulfillment revealed that DCA can generate satisfactory and near equivalent dosimetric…
Background: The deep inspiration breath hold technique (DIBH) is widely used for left-sided breast radiotherapy (RT), in order to reduce the dose to the heart and the risk of cardiotoxicity. The volumetric arc therapy (VMAT) technique increases the dose conformity to the planning target volume (PTV). We hereby describe the procedure of combining VMAT and DIBH without a dedicated equipment, and report a dosimetric study related on our implemented technique. Methods: The DIBH technique is based on voluntary breath hold of the patient which is controlled by a laser on tattoo marks. Patients were …
The main approach to smooth Pareto surface navigation for radiation therapy multi-criteria treatment planning involves taking real-time averages of pre-computed treatment plans. In fluence-based treatment planning, fluence maps themselves can be averaged, which leads to the dose distributions being averaged due to the linear relationship between fluence and dose. This works for fluence-based photon plans and proton spot scanning plans. In this technical note, we show that two or more sliding window volumetric modulated arc therapy (VMAT) plans can be combined by averaging leaf positions in a c…
The aim of this study is to set up statistical quality control for monitoring of volumetric modulated arc therapy (VMAT) delivery error using machine log data. Eclipse and Clinac iX linac with the RapidArc system (Varian Medical Systems, Palo Alto, USA) is used for delivery of the VMAT plan. During the delivery of the RapidArc fields, the machine determines the delivered motor units (MUs) and gantry angle position accuracy and the standard deviations of MU (sigma_MU; dosimetric error) and gantry angle (sigma_GA; geometric error) are displayed on the console monitor after completion of the Rapi…
Collimator angle is usually rotated when planning volumetric modulated arc therapy (VMAT) due to the leakage of radiation between multi-leaf collimator (MLC) leaves. We studied the effect of the collimator angles on the results of dosimetric verification of the VMAT plans for head and neck patients. We studied VMAT plans for 10 head and neck patients. We made 2 sets of VMAT plans for each patient. Each set was composed of 10 plans with collimator angles of 0, 5, 10, 15, 20, 25, 30, 35, 40, 45 degrees. Plans in the first set were optimized individually and plans in the second set shared the 30 …
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.…
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…
Purpose: To make the planning of volumetric modulated arc therapy (VMAT) faster and to explore the tradeoffs between planning objectives and delivery efficiency. Methods: A convex multicriteria dose optimization problem is solved for an angular grid of 180 equi-spaced beams. This allows the planner to navigate the ideal dose distribution Pareto surface and select a plan of desired target coverage versus organ at risk sparing. The selected plan is then made VMAT deliverable by a fluence map merging and sequencing algorithm, which combines neighboring fluence maps based on a similarity score and…
Purpose: To verify dose delivery and quality assurance of volumetric modulated arc therapy (VMAT) for head and neck cancer. Method: The Imaging and Radiation Oncology Core Houston (IROC-H) head and neck phantom with thermo- luminescent dosimeters (TLDs) and films, were imaged with computed tomography scan and the reconstructed image was transferred to pinnacle treatment planning system (TPS). On TPS the planning target volume (PTV), secondary target volume (STV) and organ at risk (OAR) were delineated manually and a treatment plan was made. The dose constraints were determined for the concerne…
In recent years, volumetric modulated arc therapy (VMAT) has been becoming a more and more important radiation technique widely used in clinical application for cancer treatment. One of the key problems in VMAT is treatment plan optimization, which is complicated due to the constraints imposed by the involved equipments. In this paper, we consider a model with four major constraints: the bound on the beam intensity, an upper bound on the rate of the change of the beam intensity, the moving speed of leaves of the multi-leaf collimator (MLC) and its directional-convexity. We solve the model by a…
The purpose of this study is to give an exact formulation of optimization of volumetric-modulated arc therapy (VMAT) with sliding-window delivery, and to investigate the plan quality effects of decreasing the number of sliding-window sweeps made on the 360-degree arc for a faster VMAT treatment. In light of the exact formulation, we interpret an algorithm previously suggested in the literature as a heuristic method for solving this optimization problem. By first making a generalization, we suggest a modification of this algorithm for better handling of plans with fewer sweeps. In a numerical s…
Aim: To improve treatment plan robustness with respect to small shifts in patient position during the VMAT treatment by ensuring a linear ramp-like dose profile in treatment field overlap regions. Background: Craniospinal irradiation (CSI) is considered technically challenging because the target size exceeds the maximal field size, which necessitates using abutted or overlapping treatment fields. Volumetric modulated arc therapy (VMAT) is increasingly being examined for CSI, as it offers both better dose homogeneity and better dose conformance while also offering a possibility to create field …
In this article we provide a method to generate the trade-off between delivery time and fluence map matching quality for volumetric modulated arc therapy (VMAT). At the heart of our method lies a mathematical programming model that, for a given duration of delivery, optimizes leaf trajectories and dose rates such that the desired fluence map is reproduced as well as possible. This model was presented for the single map case in a companion paper (Fast approximate delivery of fluence maps: the single map case). The resulting large-scale, non-convex optimization problem was solved using a heurist…
The first purpose of this paper is to shed some new light on the old question of selecting the number of beams in intensity-modulated radiation therapy (IMRT). The second purpose is to illuminate the related issue of discrete static beam angles vs. rotational techniques, which has recently re-surfaced due to the advancement of volumetric arc therapy (VMAT). A specific objective is to find analytical expressions that allow one to address the points raised above. To make the problem mathematically tractable, it is assumed that the depth dose is flat and that the lateral dose profile can be appro…
In the past decades mathematical optimization has found its way into radiation therapy and has made profound practice changing impact. Today, virtually all advanced treatment delivery methods, such as IMRT, VMAT, tomotherapy, LDR/HDR brachytherapy, proton therapy, are based on some form of optimization approach that changes the treatment variables (beam intensities, multileaf collimator shapes, beam angles, dwell times and seed or source positions) in the planning computer using an optimization algorithm, until the best value of the treatment (planning) objective has been found. It is fair to …
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…
We present a technique for continuous generation of volumetric images during SBRT using periodic kV imaging and an external respiratory surrogate signal to drive a patient-specific PCA motion model. Using the on-board imager, kV radiographs are acquired every 3 seconds and used to fit the parameters of a motion model so that it matches observed changes in internal patient anatomy. A multi-dimensional correlation model is established between the motion model parameters and the external surrogate position and velocity, enabling volumetric image reconstruction between kV imaging time points. Perf…
Within the setting of intensity modulated radiation therapy (IMRT) and the fully continuous version of IMRT called volumetric modulated radiation therapy (VMAT), we consider the problem of matching a given fluence map as well as possible in limited time by the use of a linear accelerator (linac) with a multi-leaf collimator (MLC). We introduce two modeling strategies to manage the nonconvexity and the associated local minima of this problem. The first is the use of linear splines to model the MLC leaf positions as functions of time. The second is a progressively controllable smooth model (inst…
In this first paper of a two-paper series, we present a method for optimizing the dynamic delivery of fluence maps in radiation therapy. For a given fluence map and a given delivery time, the optimization of the leaf trajectories of a multi-leaf collimator to approximately form the given fluence map is a non-convex optimization problem. Its general solution has not been addressed in the literature, despite the fact that dynamic delivery of fluence maps has long been a common approach to intensity modulated radiation therapy. We model the leaf trajectory and dose rate optimization as a non-conv…
Patient-specific immobilisation for radiotherapy treatment of extensive lower-limb carcinoma
Royal Brisbane and Women's Hospital（皇家布里斯班和女子医院）；University of Queensland（昆士兰大学）；Queensland University of Technology（昆士兰科技大学）；Herston Biofabrication Institute, Metro North Hospital and Health Service（赫斯顿生物制造研究所，北岸大都会医院与健康服务）
Purpose: To develop a model to generate volumetric dose distribution from two isodose surfaces (iso-surfaces), and to interactively tune dose distribution by iso-surface dragging. Methods: We model volumetric dose distribution as analytical extension of two iso-surfaces with the extension variables as distances to iso-surfaces. We built a 3D lookup table (LUT) which are generated based on clinical dose distributions. Two LUT tables store the mean and standard deviation of voxel dose values of clinical doses and binned as distance to 100% iso-surface, reference iso-surface and reference dose le…
Due to the inter- and intra- variation of respiratory motion, it is highly desired to provide real-time volumetric images during the treatment delivery of lung stereotactic body radiation therapy (SBRT) for accurate and active motion management. In this proof-of-concept study, we propose a novel generative adversarial network integrated with perceptual supervision to derive instantaneous volumetric images from a single 2D projection. Our proposed network, named TransNet, consists of three modules, i.e., encoding, transformation and decoding modules. Rather than only using image distance loss b…
UT Southwestern Medical Center（德克萨斯大学西南医学中心）；University of North Texas（北德克萨斯大学）；UCLouvain（鲁汶大学）；Erasmus University Medical Center（伊拉斯姆斯大学医学中心）
This work aims to study the generalizability of a pre-developed deep learning (DL) dose prediction model for volumetric modulated arc therapy (VMAT) for prostate cancer and to adapt the model to three different internal treatment planning styles and one external institution planning style. We built the source model with planning data from 108 patients previously treated with VMAT for prostate cancer. For the transfer learning, we selected patient cases planned with three different styles from the same institution and one style from a different institution to adapt the source model to four targ…
We compared the treatment planning performance of RapidArc (RA) vs. CyberKnife (CK) for spinal stereotactic body radiation therapy (SBRT). Ten patients with spinal lesions who had been treated with CK were re-planned with RA, which consisted of two complete arcs. Computed tomography (CT) and volumetric dose data of CK, generated using the Multiplan (Accuray) treatment planning system (TPS) and the Ray-Trace algorithm, were imported to Varian Eclipse TPS in Dicom format, and the data were compared with the RA plan using analytical anisotropic algorithm (AAA) dose calculation. The optimized dose…
The physical and clinical benefits of charged particle therapy (CPT) are well recognised and recent developments have led to the rapid emergence of facilities, resulting in wider adoption worldwide. Nonetheless, the availability of CPT and complete exploitation of dosimetric advantages are still limited by high facility costs and technological challenges. There are extensive ongoing efforts to improve upon these, which will lead to greater accessibility, superior delivery, and therefore better treatment outcomes. Several of these aspects can be addressed by developments to the beam delivery sy…
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…
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 allo…
Purpose: To quantitatively compare the dosimetric and biologic differences in treatment plans from flattened and flattening-filter-free (FFF) beam for three anatomic cancer sites. Methods and Materials: Treatment plans with static intensity-modulated radiotherapy beams and volumetric modulated arc therapy beams were generated for 13 patients for both the flattened beam and the FFF beam of the TrueBeam system. Beam energies of 6 MV and 10 MV were chosen for planning. A total of 104 treatment plans were generated in 13 patients. In order to analyze the biological effectiveness of treatment plans…
Toward Ultra-fast Treatments: Large Energy Acceptance Beam Delivery Systems and Opportunities for Proton Beam Therapy
Peter MacCallum Cancer Centre（彼得·麦卡勒姆癌症中心）；University of Melbourne（墨尔本大学）；Cockcroft Institute（科克克罗夫特研究所）；University of Manchester（曼彻斯特大学）；Massachusetts General Hospital（麻省总医院）；Harvard Medical School（哈佛医学院）；Australian Nuclear Science and Technology Organisation (ANSTO)（澳大利亚核科学和技术组织）
The widespread adoption of on-board volumetric imaging in cancer radiotherapy has stimulated research efforts to develop online adaptive radiotherapy techniques to handle the inter-fraction variation of the patient's geometry. Such efforts face major technical challenges to perform treatment planning in real-time. To overcome this challenge, we are developing a supercomputing online re-planning environment (SCORE) at the University of California San Diego (UCSD). As part of the SCORE project, this paper presents our work on the implementation of an intensity modulated radiation therapy (IMRT) …
Cone-beam CT (CBCT) has been widely used in image guided radiation therapy (IGRT) to acquire updated volumetric anatomical information before treatment fractions for accurate patient alignment purpose. However, the excessive x-ray imaging dose from serial CBCT scans raises a clinical concern in most IGRT procedures. The excessive imaging dose can be effectively reduced by reducing the number of x-ray projections and/or lowering mAs levels in a CBCT scan. The goal of this work is to develop a fast GPU-based algorithm to reconstruct high quality CBCT images from undersampled and noisy projection…
Focal-point scanning for dose delivery and optimization with focused laser-accelerated very-high-energy electron beams
Zhengzhou University（郑州大学）；Tsinghua University（清华大学）；Microsoft Research, AI for Science（微软研究院 AI for 科学）；The First Affiliated Hospital of Zhengzhou University（郑州大学第一附属医院）；University of Michigan, Ann Arbor（密歇根大学安娜堡分校）；National Institute of Metrology（中国计量科学研究院）
