A compact linac for intensity modulated proton therapy based on a dielectric wall accelerator.

A novel compact CT-guided intensity modulated proton radiotherapy (IMPT) system is described. The system is being designed to deliver fast IMPT so that larger target volumes and motion management can be accomplished. The system will be ideal for large and complex target volumes in young patients. The basis of the design is the dielectric wall accelerator (DWA) system being developed at the Lawrence Livermore National Laboratory (LLNL). The DWA uses fast switched high voltage transmission lines to generate pulsed electric fields on the inside of a high gradient insulating (HGI) acceleration tube. High electric field gradients are achieved by the use of alternating insulators and conductors and short pulse times. The system will produce individual pulses that can be varied in intensity, energy and spot width. The IMPT planning system will optimize delivery characteristics. The system will be capable of being sited in a conventional linac vault and provide intensity modulated rotational therapy. Feasibility tests of an optimization system for selecting the position, energy, intensity and spot size for a collection of spots comprising the treatment are underway. A prototype is being designed and concept designs of the envelope and environmental needs of the unit are beginning. The status of the developmental new technologies that make the compact system possible will be reviewed. These include, high gradient vacuum insulators, solid dielectric materials, SiC photoconductive switches and compact proton sources.

Measurements of the electron dose distribution near inhomogeneities using a plastic scintillation detector.

PURPOSE: Accurate measurement of the electron dose distribution near an inhomogeneity is difficult with traditional dosimeters which themselves perturb the electron field. We tested the performance of a new high resolution, water-equivalent plastic scintillation detector which has ideal properties for this application. METHODS AND MATERIALS: A plastic scintillation detector with a 1 mm diameter, 3 mm long cylindrical sensitive volume was used to measure the dose distributions behind standard benchmark inhomogeneities in water phantoms. The plastic scintillator material is more water equivalent than polystyrene in terms of its mass collision stopping power and mass scattering power. Measurements were performed for beams of electrons having initial energies of 6 and 18 MeV at depths from 0.2-4.2 cm behind the inhomogeneities. RESULTS: The detector reveals hot and cold spots behind heterogeneities at resolutions equivalent to typical film digitizer spot sizes. Plots of the dose distributions behind air, aluminum, lead, and formulations for cortical and inner bone-equivalent materials are presented. CONCLUSION: The plastic scintillation detector is suited for measuring the electron dose distribution near an inhomogeneity.

A proposal for a standard electronic anthropomorphic phantom for radiotherapy.

To create a database of human male and female computed tomography (CT) slices, the National Library of Medicine organized the "Visible Human Project." Since the male and female data sets provided are approximately 269 MB and 915 MB, respectively, both the size and complexity have been reduced. While making the slices accessible to those with limited computing resources, the production of these reduced data sets also presents a unique opportunity to establish a standard human CT slice library for research in radiation therapy. A brief history of the original data sets is included, as well as details of the reduction process, applications to radiotherapy, and information on accessing these reduced image files.

A feasible method for clinical delivery verification and dose reconstruction in tomotherapy.

Delivery verification is the process in which the energy fluence delivered during a treatment is verified. This verified energy fluence can be used in conjunction with an image in the treatment position to reconstruct the full three-dimensional dose deposited. A method for delivery verification that utilizes a measured database of detector signal is described in this work. This database is a function of two parameters, radiological path-length and detector-to-phantom distance, both of which are computed from a CT image taken at the time of delivery. Such a database was generated and used to perform delivery verification and dose reconstruction. Two experiments were conducted: a simulated prostate delivery on an inhomogeneous abdominal phantom, and a nasopharyngeal delivery on a dog cadaver. For both cases, it was found that the verified fluence and dose results using the database approach agreed very well with those using previously developed and proven techniques. Delivery verification with a measured database and CT image at the time of treatment is an accurate procedure for tomotherapy. The database eliminates the need for any patient-specific, pre- or post-treatment measurements. Moreover, such an approach creates an opportunity for accurate, real-time delivery verification and dose reconstruction given fast image reconstruction and dose computation tools.

MMC--a high-performance Monte Carlo code for electron beam treatment planning.

The macro Monte Carlo (MMC) method has been developed to improve the speed of traditional Monte Carlo (MC) high-energy electron transport calculations without loss in accuracy. The MMC algorithm uses results derived from conventional MC simulations of electron transport through macroscopic spheres of various radii and consisting of a variety of media. Based on these results, electrons are transported in macroscopic steps through the absorber. The absorber geometry is represented by a three-dimensional (3D) density matrix, typically derived from computer tomographic (CT) data. Energy lost by the electrons along their paths through the absorber is scored in a 3D dose matrix. Transport of secondary electrons and bremsstrahlung photons is taken into account. Major modifications of the original implementation of the MMC algorithm have resulted in an improved version of the code, resolving earlier problems with electron transport across interfaces of different materials, and running at a substantially higher speed. Furthermore, the code has been integrated into a clinical 3D treatment planning system. MMC results are in good agreement with results from conventional MC codes and are obtained with a speed gain of about one order of magnitude for clinically relevant irradiation situations. Calculation times to obtain a relative statistical accuracy of 2% per dose grid voxel for small electron field sizes are short enough to be routinely useful in radiotherapy clinics on present day affordable workstation computers. Considering speed, accuracy and memory requirements, MMC is a promising alternative to currently available electron dose planning algorithms.

Iterative approaches to dose optimization in tomotherapy.

This paper will present the results of an investigation into three iterative approaches to inverse treatment planning. These techniques have been examined in the hope of developing an optimization algorithm suitable for the large-scale problems that are encountered in tomotherapy. The three iterative techniques are referred to as the ratio method, iterative least-squares minimization and the maximum-likelihood estimator. Our results indicate that each of these techniques can serve as a useful tool in tomotherapy optimization. As compared with other mathematical programming techniques, the iterative approaches can reduce both memory demands and time requirements. In this paper, the results from small- and large-scale optimizations will be analysed. It will also be demonstrated that the flexibility of the iterative techniques can be greatly enhanced through the use of dose-volume histogram based penalty functions and/or through the use of weighting factors assigned to each region of the patient. Finally, results will be presented from an investigation into the stability of the iterative techniques.

Registration of synthetic tomographic projection data sets using cross-correlation.

Tomographic registration, a method that makes possible accurate patient registration directly from projection data, consists of three processing steps: (i) manual coarse positioning, (ii) tomographic projection set acquisition, and (iii) computer mediated refined positioning. In the coarse positioning stage, the degree of patient alignment is comparable with that achieved with the standard radiotherapy set-up. However, the accuracy requirements are somewhat more relaxed in that meticulous alignment of the patient using external laser indicators is not necessary. Instead, tomographic projection sets are compared with planning CTs in order to achieve improved patient set-up. The projection sets are cross-correlated to obtain the best-fit translation and rotation offsets. The algorithm has been tested on synthetic data with the incorporation of varying amounts of Gaussian pseudo-random noise. These tests demonstrate the algorithm's stability and also confirm that alignment can be achieved with an accuracy of less than one projection pixel.

Megavoltage CT imaging as a by-product of multileaf collimator leakage.

In addition to their potential for the delivery of highly conformal radiation therapy treatments, tomotherapeutic treatments also feature increased potential for verification. For example, megavoltage CT allows one to use the megavoltage linac to generate tomographic images of the patient in the treatment position. This is typically done before or after radiation therapy treatments. However, it is also possible to collect MVCT images entirely during the treatment itself. This process utilizes the leakage radiation through the closed leaves of the Nomos MIMiC MLC, along with slight inefficiencies in treatment delivery, to generate MVCT images during treatment that require neither additional time nor dose. The image quality is limited, yet sufficient to see a patient's external boundary, density differences over 8% for 25.0 mm objects and resolutions of 3.0 mm for high-contrast objects. Such images can potentially be viewed during treatment, used to flag additional CT immediately after the treatment and provide a representation of the patient's exact position during treatment for use with dose reconstruction.

Megavoltage CT image reconstruction during tomotherapy treatments.

An integrated tomotherapy system allows for improved radiotherapy verification by enabling the collection of megavoltage computed tomography (MVCT) images before or after treatment delivery. In this investigation, the possibility of collecting MV tomographic data and reconstructing images during a tomotherapy treatment is examined. By overcoming difficulties with the normalization of modulated treatment data and with the incompleteness of treatment data, it is possible to use data collected during tomotherapeutic treatments for MVCT reconstruction. The benefits of these techniques include potential increases in patient throughput, reductions in imaging dose, visualization of the patient in the treatment position and improvements in image contrast.

The application of correlated sampling to the computation of electron beam dose distributions in heterogeneous phantoms using the Monte Carlo method.

Although the Monte Carlo method is capable of computing the dose distribution in heterogeneous phantoms directly, there are some advantages to computing a heterogeneity correction factor. If this approach is adopted there are savings in time using correlated sampling. This technique forces histories to have the same energy, position, direction and random number seed as incident on both the heterogeneous and homogeneous water phantom. This ensures that a history that has, by chance, travelled through only water in the heterogeneous phantom will have the same path as it would have through the homogeneous phantom, resulting in a reduced variance when a ratio of heterogeneous dose to homogeneous dose is formed. Metrics to describe the distributions of uncertainty, efficiency, and degree of correlation are defined. EGS4 Monte Carlo calculation of the dose distribution from a 20 MeV electron beam on water phantoms containing aluminum or air slab heterogeneities illustrate that this technique is the most efficient when the heterogeneity is deep within the phantom, but that improved efficiency can be realized even when the heterogeneity is at or near the surface. This is because some correlation between the two histories is retained despite passage through the heterogeneity.

Delivery verification in sequential and helical tomotherapy.

Conformal and conformal avoidance radiation therapy are new therapeutic techniques that are generally characterized by high dose gradients. The success of this kind of treatment relies on quality assurance procedures in order to verify the delivery of the treatment. A delivery verification technique should consider quality assurance procedures for patient positioning and radiation delivery verification. A methodology for radiation delivery verification was developed and tested with our tomotherapy workbench. The procedure was investigated for two cases. The first treatment using a torus-shaped target was optimized for 72 beam directions and sequentially delivered as a single slice to a 33 cm diameter cylinder of homogeneous solid water. For the second treatment, a random pattern of energy fluence was helically delivered for two slices to a 9.0 cm diameter phantom containing inhomogeneities. The presented process provides the energy fluence (or a related quantity) delivered through the multileaf collimator (MLC) using the signal measured at the exit detector during the treatment delivery. As this information is created for every pulse of the accelerator, the energy fluence and state for each MLC leaf were verified on a pulse-by-pulse basis. The pulse-by-pulse results were averaged to obtain projection-by-projection information to allow for a comparison with the planned delivery. The errors between the planned and delivered energy fluences were concentrated between +/-2.0%, with none beyond +/-3.5%. In addition to accurately achieving radiation delivery verification, the process is fast, which could translate to radiation delivery verification in real time. This technique can also be extended to reconstruct the dose actually deposited in the patient or phantom (dose reconstruction).

Maximum likelihood as a common computational framework in tomotherapy.

Tomotherapy is a dose delivery technique using helical or axial intensity modulated beams. One of the strengths of the tomotherapy concept is that it can incorporate a number of processes into a single piece of equipment. These processes include treatment optimization planning, dose reconstruction and kilovoltage/megavoltage image reconstruction. A common computational technique that could be used for all of these processes would be very appealing. The maximum likelihood estimator, originally developed for emission tomography, can serve as a useful tool in imaging and radiotherapy. We believe that this approach can play an important role in the processes of optimization planning, dose reconstruction and kilovoltage and/or megavoltage image reconstruction. These processes involve computations that require comparable physical methods. They are also based on equivalent assumptions, and they have similar mathematical solutions. As a result, the maximum likelihood approach is able to provide a common framework for all three of these computational problems. We will demonstrate how maximum likelihood methods can be applied to optimization planning, dose reconstruction and megavoltage image reconstruction in tomotherapy. Results for planning optimization, dose reconstruction and megavoltage image reconstruction will be presented. Strengths and weaknesses of the methodology are analysed. Future directions for this work are also suggested.

On the accuracy and effectiveness of dose reconstruction for tomotherapy.

Dose reconstruction is a process that re-creates the treatment-time dose deposited in a patient provided there is knowledge of the delivered energy fluence and the patient's anatomy at the time of treatment. A method for reconstructing dose is presented. The process starts with delivery verification, in which the incident energy fluence from a treatment is computed using the exit detector signal and a transfer matrix to convert the detector signal to energy fluence. With the verified energy fluence and a CT image of the patient in the treatment position, the treatment-time dose distribution is computed using any model-based algorithm such as convolution/superposition or Monte Carlo. The accuracy of dose reconstruction and the ability of the process to reveal delivery errors are presented. Regarding accuracy, a reconstructed dose distribution was compared with a measured film distribution for a simulated breast treatment carried out on a thorax phantom. It was found that the reconstructed dose distribution agreed well with the dose distribution measured using film: the majority of the voxels were within the low and high dose-gradient tolerances of 3% and 3 mm respectively. Concerning delivery errors, it was found that errors associated with the accelerator, the multileaf collimator and patient positioning might be detected in the verified energy fluence and are readily apparent in the reconstructed dose. For the cases in which errors appear in the reconstructed dose, the possibility for adaptive radiotherapy is discussed.

Registration using tomographic projection files.

An algorithm has been developed and experimentally verified for tomographic registration--a patient positioning method using internal anatomy and standard external fiducial marks. This algorithm improves patient set-up and verification to an accuracy sufficient for tomotherapy. By implementation of this technique, the time-consuming reconstruction process is avoided. Instead, offsets in the x, y and z directions are determined directly from sinogram data by an algorithm that utilizes cross-correlations and Fourier transforms. To verify the efficiency and stability of the algorithm, data were collected on the University of Wisconsin's dedicated tomotherapy research workbench. The experiment indicates offset statistical errors of less than +/-0.8 mm for offsets up to 30 mm. With standard clinical techniques, initial patient offsets are expected to be less than 5 mm, so the 30 mm limitation is of no consequence. The angular resolution for the direction of patient translation is within the +/-2 degrees needed for tomotherapy.