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The source-axis distance (SAD) is a treatment machine design parameter that affects integral dose, dose rate and patient clearance. The aim of this work was to investigate the effect of source-axis distance on integral dose for conformal arc therapy. This work is part of a larger project to determine the ideal characteristics of a dedicated IMRT machine. The sensitivity of SAD to beam energy, PTV size, body size and PTV position were determined for conformal arc therapy. For the calculations performed here it was assumed that dose equals terma. The integral dose ratio (IDR) was used to quantify the calculation results. It was found that the IDR increases as both SAD and photon energy increase, though the dependence of IDR on SAD decreases as energy increases. The PTV size was found to have a negligible effect on the relationship between the SAD and IDR, however the body size does affect the relationship between the SAD and IDR. The position of the PTV within the body also affects the IDR. From dosimetric considerations alone, the larger the SAD, the better the possible dose distribution. The IDR for a very large SAD is increased by approximately 5% when compared with the IDR for 100 cm SAD. Similarly, the IDR for 100 cm SAD is approximately 5% higher than the IDR at 50 cm SAD.

Dose calculations for intensity modulated radiation therapy (IMRT) face new challenges due to the complex leaf geometry and time dependent nature of the delivery. A fast method of particle transport through a dynamic multileaf collimator (MLC) geometry that accounts for photon attenuation and first-scattered Compton photon production has been incorporated into an existing Monte Carlo code used for patient dose calculations. Dosimetric agreement between calculation and measurement for two photon energies and MLC types is within experimental error for the sliding window tests. For a patient IMRT field, the Monte Carlo calculations are closer to measured dose than similar superposition or pencil beam calculations.

Intrafraction motion caused by breathing requires increased treatment margins for chest and abdominal radiotherapy and may lead to 'motion artefacts' in dose distributions during intensity modulated radiotherapy (IMRT). Technologies such as gated radiotherapy may significantly increase the treatment time, while breath-hold techniques may be poorly tolerated by pulmonarily compromised patients. A solution that allows reduced margins and dose distribution artefacts, without compromising delivery time, is to synchronously follow the target motion by adapting the x-ray beam using a dynamic multileaf collimator (MLC), i.e. motion adaptive x-ray therapy, or MAX-T for short. Though the target is moving with time, in the MAX-T beam view the target is static. The MAX-T method superimposes the target motion due to respiration onto the beam originally planned for delivery. Thus during beam delivery the beam is dynamically changing position with respect to the isocentre using a dynamic MLC, the leaf positions of which are dependent upon the target position. Synchronization of the MLC motion and target motion occurs using respiration gated radiotherapy equipment. The concept and feasibility of MAX-T and the capability of the treatment machine to deliver such a treatment were investigated by performing measurements for uniform and IMRT fields using a mechanical sinusoidal oscillator to simulate target motion. Target dose measurements obtained using MAX-T for a moving target were found to be equivalent to those delivered to a static target by a static beam.

The effect of the statistical uncertainty, or noise, in inverse treatment planning for intensity modulated radiotherapy (IMRT) based on Monte Carlo dose calculation was studied. Sets of Monte Carlo beamlets were calculated to give uncertainties at Dmax ranging from 0.2% to 4% for a lung tumour plan. The weights of these beamlets were optimized using a previously described procedure based on a simulated annealing optimization algorithm. Several different objective functions were used. It was determined that the use of Monte Carlo dose calculation in inverse treatment planning introduces two errors in the calculated plan. In addition to the statistical error due to the statistical uncertainty of the Monte Carlo calculation, a noise convergence error also appears. For the statistical error it was determined that apparently successfully optimized plans with a noisy dose calculation (3% 1sigma at Dmax), which satisfied the required uniformity of the dose within the tumour, showed as much as 7% underdose when recalculated with a noise-free dose calculation. The statistical error is larger towards the tumour and is only weakly dependent on the choice of objective function. The noise convergence error appears because the optimum weights are determined using a noisy calculation, which is different from the optimum weights determined for a noise-free calculation. Unlike the statistical error, the noise convergence error is generally larger outside the tumour, is case dependent and strongly depends on the required objectives.

The main purpose of this work is to demonstrate a practical means of determining the leaf transmission and scatter characteristics of a multileaf collimator (MLC) pertinent to the commissioning of dynamic intensity modulated radiotherapy, especially for the sweeping window technique. The data are necessary for the conversion of intensity distributions produced by intensity-modulated radiotherapy optimization systems into trajectories of MLC leaves for dynamic delivery. Measurements are described for two, tungsten alloy MLCs: a Mark II 80-leaf MLC on a Varian 2100C accelerator and a Millenium 120-leaf MLC on a Varian 2100EX accelerator. MLC leakage was measured by film for a series of field sizes. Measured MLC leakage was 1.68% for a 10 x 10 cm2 field for both 6 and 18 MV for the 80-leaf MLC. For the 6 MV field, the 1.68% leakage consisted of 1.48% direct transmission and 0.20% leaf scatter. Direct transmission through the 80-leaf MLC, including the rounded leaf tip, was calculated analytically taking into account the detailed leaf geometry and a Monte Carlo-generated energy spectrum of the accelerator. The integrated fluence under the leaf tip was equivalent to an inward shift of 0.06 cm of a hypothetical leaf with a flat, focused tip. Monte Carlo calculations of the dose to phantom beyond a closed 80-leaf MLC showed excellent agreement with the analytic results. The transmission depends on the density of the MLC alloy, which may differ among individual MLCs. Thus, it is important to measure the transmission of any particular MLC. Calculated doses for a series of uniform fields produced by dynamic sweeping windows of various widths agree with measurements within 2%.

Current clinical experience in radiation therapy is based upon dose computations that report the absorbed dose to water, even though the patient is not made of water but of many different types of tissue. While Monte Carlo dose calculation algorithms have the potential for higher dose accuracy, they usually transport particles in and compute the absorbed dose to the patient media such as soft tissue, lung or bone. Therefore, for dose calculation algorithm comparisons, or to report dose to water or tissue contained within a bone matrix for example, a method to convert dose to the medium to dose to water is required. This conversion has been developed here by applying Bragg-Gray cavity theory. The dose ratio for 6 and 18 MV photon beams was determined by computing the average stopping power ratio for the primary electron spectrum in the transport media. For soft tissue, the difference between dose to medium and dose to water is approximately 1.0%, while for cortical bone the dose difference exceeds 10%. The variation in the dose ratio as a function of depth and position in the field indicates that for photon beams a single correction factor can be used for each particular material throughout the field for a given photon beam energy. The only exception to this would be for the clinically non-relevant dose to air. Pre-computed energy spectra for 60Co to 24 MV are used to compute the dose ratios for these photon beams and to determine an effective energy for evaluation of the dose ratio.

Monte Carlo dose calculations will potentially reduce systematic errors that may be present in currently used dose calculation algorithms. However, Monte Carlo calculations inherently contain random errors, or statistical uncertainty, the level of which decreases inversely with the square root of computation time. Our purpose in this study was to determine the level of uncertainty at which a lung treatment plan is clinically acceptable. The evaluation methods to decide acceptability were visual examination of both isodose lines on CT scans and dose volume histograms (DVHs), and reviewing calculated biological indices. To study the effect of systematic and/or random errors on treatment plan evaluation, a simulated "error-free" reference plan was used as a benchmark. The relationship between Monte Carlo statistical uncertainty and dose was found to be approximately proportional to the square root of the dose. Random and systematic errors were applied to a calculated lung plan, creating dose distributions with statistical uncertainties of between 0% and 16% (1 s.d.) at the maximum dose point and also distributions with systematic errors of -16% to 16% at the maximum dose point. Critical structure DVHs and biological indices are less sensitive to calculation uncertainty than those of the target. Systematic errors affect plan evaluation accuracy significantly more than random errors, suggesting that Monte Carlo dose calculation will improve outcomes in radiotherapy. A statistical uncertainty of 2% or less does not significantly affect isodose lines, DVHs, or biological indices.

Monte Carlo based dose calculation algorithms require input data or distributions describing the phase space of the photons and secondary electrons prior to the patient-dependent part of the beam-line geometry. The accuracy of the treatment plan itself is dependent upon the accuracy of this distribution. The purpose of this work is to compare phase space distributions (PSDs) generated with the MCNP4b and EGS4 Monte Carlo codes for the 6 and 18 MV photon modes of the Varian 2100C and determine if differences relevant to Monte Carlo based patient dose calculations exist. Calculations are performed with the same energy transport cut-off values. At 6 MV, target bremsstrahlung production for MCNP4b is approximately 10% less than for EGS4, while at 18 MV the difference is about 5%. These differences are due to the different bremsstrahlung cross sections used in the codes. Although the absolute bremsstrahlung production differs between MCNP4b and EGS4, normalized PSDs agree at the end of the patient-independent geometry (prior to the jaws), resulting in similar dose distributions in a homogeneous phantom. EGS4 and MCNP4b are equally suitable for the generation of PSDs for Monte Carlo based dose computations.

A method is described which determines the radiological equivalence of different materials by comparing their macroscopic photon and electron interaction parameters over the energy range of interest. This method has been applied to Fricke and polymer gels used for radiation dosimetry. Photon and electron dose distributions were calculated using a Monte Carlo technique. 6 MV photon gel depth dose curves were all within 1% of those in water over the depth range studied. 6 MeV electron beam depth dose curves were all within 1 mm of those in water. The results show that for the gels investigated, at megavoltage energies the dominant property determining water equivalence is the electron density of the gel, and therefore future research into gel manufacture for external beam radiotherapy should aim to have the electron density (electrons per unit volume) as close as possible to water. However, care needs to be taken when using gels for dosimetry of photons with incident energy < 100 keV.

Our aim in this project was to quantify a kilovoltage beam phase space for use in dose calculations. The phase space was modeled by incorporating the following analytically derived x-ray beam production properties: the intensity variation due to the heel effect, the energy variation due to the differing amount of target material traversed by the photons, and the finite source size. The initial energy spectrum used was generated using a computer program. A Monte Carlo code was adapted in order to examine the validity of the calculated phase space. Dose distributions calculated using the modeled phase space for 10x10 and 20x20 cm2 fields show agreement with experimental values to within 2% and 4%, respectively, for the central 80% of the field size. Within the field but outside this range a maximum of 6% difference (for the 20x20 cm2 field) was observed, however, these values were in a region of sharp gradient and hence small geometric shift. The "tails" of the profiles were underpredicted by up to 6%. Due to uncertainties in experiment (3%) and Monte Carlo (1.5%), the modeled phase space is deemed acceptable for phantom and in-vivo dosimetric calculations within the field boundaries.

A Monte Carlo based inverse treatment planning system (MCI) has been developed which combines arguably the most accurate dose calculation method (Monte Carlo particle transport) with a 'guaranteed' optimization method (simulated annealing). A distribution of photons is specified in the tumour volume; they are transported using an adjoint calculation method to outside the patient surface to build up an intensity distribution. This intensity distribution is used as the initial input into an optimization algorithm. The dose distribution from each beam element from a number of fields is pre-calculated using Monte Carlo transport. Simulated annealing optimization is then used to find the weighting of each beam element, to yield the optimal dose distribution for the given criteria and constraints. MCI plans have been generated in various theoretical phantoms and patient geometries. These plans show conformation of the dose to the target volume and avoidance of critical structures. To verify the code, an experiment was performed on an anthropomorphic phantom.

The dose distributions for a patient with cancer involving the sternum were calculated for both a kilovoltage x-ray beam and a megavoltage electron beam. The minimum target dose and dose uniformity over the target volume were significantly better using electrons (90%-101%) than kilovoltage x-rays (68%-119%). The calculated lung dose and integral patient dose were also less for electrons than kilovoltage x-rays. For treating cancers of the sternum with radical intent, megavoltage electrons are recommended as the treatment mode of choice rather than kilovoltage x-rays.

Dose distributions calculated by commercial treatment planning systems do not allow incorporation of the effects of patient position variation or organ motion throughout the course of radiation therapy treatment. We have established a convolution-based method, which enables us to display dose distributions using a commercial treatment planning system that can take into account target movement. An example of the method applied to a prostate treatment plan is presented. For the method to be of clinical use it requires assessment of the parameters leading to target movement in a scientific manner in the same treatment department that it is to be used. It is not sufficient to rely on published data especially that relating to set-up accuracy as this has been shown to vary widely from centre to centre. We believe that with appropriate movement data, a convolution-based approach can lead to more optimal radiation margins around clinical target volumes (CTV). Optimal margins will help prevent geometric misses as well as ensure that the amount of critical late reacting normal tissues surrounding the CTV irradiated is minimised. Optimal margins cannot be guaranteed with the more conventionally used "rule of thumb" techniques for placing a planning target volume around the CTV.

Understanding the limitations of Monte Carlo codes is essential in order to avoid systematic errors in simulations, and to suggest further improvement of the codes. MCNP and EGS4, Monte Carlo codes commonly used in medical physics, were compared and evaluated against electron depth dose data and experimental backscatter results obtained using clinical radiotherapy beams. Different physical models and algorithms used in the codes give significantly different depth dose curves and electron backscattering factors. The default version of MCNP calculates electron depth dose curves which are too penetrating. The MCNP results agree better with experiment if the ITS-style energy-indexing algorithm is used. EGS4 underpredicts electron backscattering for high-Z materials. The results slightly improve if optimal PRESTA-I parameters are used. MCNP simulates backscattering well even for high-Z materials. To conclude the comparison, a timing study was performed. EGS4 is generally faster than MCNP and use of a large number of scoring voxels dramatically slows down the MCNP calculation. However, use of a large number of geometry voxels in MCNP only slightly affects the speed of the calculation.

A method to increase the photon fluence of the linac is to apply a magnetic field to the bremsstrahlung producing electrons in the target. This field changes the electron paths, and therefore the photon trajectories. In this research Monte Carlo techniques are used to model the effect of three separate magnetic field configurations applied to a tungsten target, on the forward projection of bremsstrahlung created from incident 6 MeV electrons. A radial fluence spectrum is produced for each magnetic field. The maximum increase in fluence is shown to be around 10% for a physically possible field. We conclude that the cost of constructing and installing such magnets (currently) outweighs the small increase in fluence yield.

The aim of this work was to compare dose calculation algorithm results at orthovoltage energies for a phantom composed of a bone slab in water. The calculation methods investigated were: no correction, ETAR, Batho, convolution/superposition and Monte Carlo. All algorithms calculated depth dose curves in a water phantom within 4% of experiment. However in the bone phantom, differences of over 40% between the No Correction/ETAR/Batho/Convolution and Monte Carlo results in the 1 cm thick bone slab were observed. These differences are predominantly because the algorithms do not account for the differing atomic number of the bone compared to water. The increased dose to bone and the tissue adjacent to the bone interface should be considered when treating with orthovoltage photons.

A Siemens Mevatron KV2 accelerator installed at the Royal Adelaide Hospital employs cylindrical solid-walled electron cones for some electron collimation. The cones being used at present result in treatment fields that do not always conform with the International Electrotechnical Commission (IEC) Standards (particularly at high energies). The aim of this project was to simulate the existing cones using Monte Carlo methods in order to evaluate potential cone modifications required to overcome the field irregularities. Simulations were performed using the EGS4 (Electron Gamma Shower version 4, distribution II) Monte Carlo code installed on a DEC Alpha workstation at the University of South Australia. To rigorously simulate the existing electron cones it was necessary to also simulate various components within the treatment head of the linear accelerator. Results of simulations for existing cones were found to be consistent with experimental data. (obtained from Royal Adelaide Hospital beam quality assurance measurements). Two proposed changes to the cones were then simulated and the effects of these alterations were assessed. This study has shown how treatment head simulation techniques can be used to assess the changes in dose distribution that result from alterations to the treatment head and accessories. Within practical engineering constraints modifications to an existing electron collimation system were proposed and theoretically evaluated.

Orthovoltage x-ray beams exhibit the characteristic of depth dose buildup which is not well described in the literature. The principal reason for this phenomenon is the increase in dose deposited due to electrons set in motion by secondary (Compton) scattered photons within the phantom, as depth is increased until longitudinal equilibrium is reached. This happens within a few millimetres of the surface and has been demonstrated both experimentally and by Monte Carlo methods. The Monte Carlo technique also enabled description of a second order primary dose buildup effect (due to longitudinal electronic disequilibrium) that would be impossible to detect with conventional detectors due to the short range of the electrons. The magnitude of buildup was observed to alter with various combinations of beam parameters. Variations will also occur with detectors used to measure buildup. It is recommended that radiation oncology departments assess this effect in the context of their clinical data in current use to ensure that there are not doses higher than prescribed being applied a few millimetres below the skin surface, especially if data was collected with a thin windowed, parallel plate ionisation chamber and/or that coarse steps for depth dose data collection were used along the beam central axis.

Dose profiles produced by wedge filters in the non-wedged direction can exhibit a 7% or greater dose reduction at the outer ends of the field compared with open field profiles. However, many planning systems use open field profiles to model wedged dose distributions. In the present work, wedges have been modified to reproduce open field profile shapes. This modification involved removing varying thicknesses of the wedge using a simple milling machine. The wedge thickness was calculated using the assumption that dose is proportional to primary collision kerma. The discrepancies in dose between wedged field and open field profile shapes of up to 7% were reduced to less than 3% with the modifications, even for varying depths and off-axis distances. The necessary measurements are simple to perform, and hence this technique could be applied to improve wedged field dose distributions in other radiotherapy departments.

An electron beam dose calculation algorithm has been developed which is based on a superposition of pregenerated Monte Carlo electron track kernels. Electrons are transported through media of varying density and atomic number using electron tracks produced in water. The perturbation of the electron fluence due to each material encountered by the electrons is explicitly accounted for by considering the effect of (i) varying stopping power, (ii) scattering power, and (iii) radiation yield. For each step of every electron track, these parameters affect the step length, the step direction, and for energy deposited in that step respectively. Dose distributions in both homogeneous water and nonwaterlike phantoms, and heterogeneous phantoms show consistent agreement with "standard" Monte Carlo results. For the same statistical uncertainty in broad beam geometries, this new calculation method uses a factor of 9 less computation time than a full Monte Carlo simulation.

Radiotherapy dose calculation algorithms currently under development (and some in use) require knowledge of the characteristics of particles in linear accelerator-generated radiation beams. A range of techniques have been developed which allow determination of those characteristics requiring minimal interaction with the physical beam. Such techniques may be analytical in nature, making use of analytical transport results and cross sections, or they may be numerical, employing the increasing utility of Monte Carlo techniques. These techniques provide us with an extensive description of clinical beams and the ability to refine beam production and collimation systems. This review details several published analytical and numerical approaches to megavoltage photon and electron beam modelling, the characteristics that they provide, and their relative accuracy and utility.

The advantage of accurate dose calculation in radiotherapy is the availability of better quality information with which to prescribe treatments, and also increased confidence when optimisation procedures are applied in the planning process. Due to the continual increase in computation speed through improvements in technology, a number of advanced electron beam dose calculation algorithms have recently been developed which incorporate physically rigorous modelling of the scattering and interaction processes involved in electron transport. These algorithms are significantly more accurate than those employed by commercially available radiotherapy planning systems. The advantages and disadvantages of the 3D Pencil beam method, the Pencil Beam Redefinition Method, the Multi-ray model, theoretical perturbative methods, the Phase Space Evolution model, Monte Carlo techniques, the Superposition/Convolution method, the Macro-Monte Carlo algorithm, the Super-Monte Carlo method and the Voxel-based Monte Carlo method are discussed in this review.

Knowledge of the angular distribution of an electron beam at the applicator face is a necessary parameter in defining a beam when the Hogstrom pencil beam method of dose calculation is used. The angular spread can be found experimentally using penumbra widths measured at various distances from the applicator face. Using knowledge of the geometry and composition of the scattering foils of the linear accelerator, the angular standard deviation was calculated theoretically using Fermi-Eyges theory. The obtained angular spread values agree with experimentally derived values to within experimental error for electron energies from 6 to 21 MeV. The Fermi-Eyges calculation is fast, and can be used as a quick check to validate experimental angular spread values.

The superposition/convolution method and the transport of pregenerated Monte Carlo electron track data have been combined into the Super-Monte Carlo (SMC) method, an accurate 3-D x-ray dose calculation algorithm. The primary dose (dose due to electrons ejected by primary photons) is calculated by transporting pregenerated (in water) Monte Carlo electron tracks from each primary photon interaction site, weighted by the terma for that site. The length of each electron step is scaled by the inverse of the density of the medium at the beginning of the step. Because the density scaling of the electron tracks is performed for each individual transport step, the limitations of the macroscopic scaling of kernels (in the superposition algorithm) are overcome. This time-consuming step-by-step transport is only performed for the primary dose calculation, where current superposition methods are most lacking. The scattered dose (dose due to electrons set in motion by scattered photons) is calculated by superposition. In both a water-lung-water phantom and a two lung-block phantom, SMC dose distributions are more consistent with Monte Carlo generated dose distributions than are superposition dose distributions, especially for small fields and high energies-for an 18-MV, 5 X 5-cm(2) beam, the central axis dose discrepancy from Monte Carlo is reduced from 4.5% using superposition to 1.5% using SMC. The computation time for this technique is approximately 2 h (depending on the simulation history), 20 times slower than superposition, but 15 times faster than a full Monte Carlo simulation (on our platform).

Fermi-Eyges electron-scattering theory has been incorporated into the primary dose calculation for external x-ray beam radiotherapy using the convolution method. Incorporating scattering theory into the convolution technique accounts for the density distribution between the interaction and deposition sites, whereas conventional convolution methods only consider the average density between these two points. As the lateral spread of electrons ejected from an interaction site depends on the density distribution, the energy deposition (and hence dose distribution) is predicted more accurately if scattering is accounted for. This new method gives depth dose curves which show better agreement with Monte Carlo calculations in a (slab inhomogeneity) lung phantom than a conventional convolution method, especially at high energies and small field sizes where lateral electronic disequilibrium exists at the central axis. For a 5 x 5-cm2 18-MV beam incident on the lung phantom, a reduction in the maximum error between the convolution and Monte Carlo depth dose curves from 5% to 2.5% is obtained when scattering theory is used in the primary dose calculation. Incorporating scattering theory into the convolution calculation increases the computation time of the primary dose by a factor of 3.

The angular distribution for electron beams produced by the Siemens KD-2 linear accelerator has been found by simulating electron transport through the scattering foils and air using two methods: Fermi-Eyges multiple Coulomb scattering calculations, and EGS4 Monte Carlo simulations. Fermi-Eyges theory gives solutions where both the angular and spatial fluence distributions are Gaussian, with the angular standard deviation being invariant with off-axis distance. The EGS4 results show slightly non-Gaussian angular and lateral distributions as a result of the use of Moliére theory rather than Fermi-Eyges multiple scattering theory, as well as the simulation of discrete bremsstrahlung and Møller interactions. However, the results from both methods are very similar. The angular standard deviations obtained by these methods agree very closely with those found experimentally. The similar shape of the Monte Carlo and Fermi-Eyges results indicate that a Gaussian approximation to the incident angular distribution will be adequate for use in treatment planning algorithms. Furthermore, the angular standard deviation may be determined using Fermi-Eyges theory as an alternative to experimental methods. Both Monte Carlo simulations, and Fermi-Eyges theory predict that the mean electron angle is proportional to off axis distance for all useful field sizes. For a 15 MeV electron beam, an effective source position of 99 cm and 98 cm from the nominal 100 SSD plane was obtained from Fermi-Eyges and Monte Carlo results respectively for a 15 MeV beam. The effective source position found experimentally for this energy was 98 cm.(ABSTRACT TRUNCATED AT 250 WORDS)

The quality of phantom materials is crucial for accurate dosimetry in radiotherapy. A wide range of factors such as density, electron density and elemental composition can influence the radiation properties, and hence the absorbed dose, of materials. New materials can be tested by direct measurements which requires considerable time and the availability of relatively large amounts of the material. Alternatively, the dosimetric properties of a proposed phantom material can be compared to those of water or tissue using Monte Carlo calculations. The aim of this study was to evaluate the use of a Monte Carlo technique for the investigation of the water/tissue equivalence of phantom materials. The material used for this investigation was Standard Dosimetry Agarose (SDA) gel, which is useful in MRI dosimetry. Depth doses in gel and water were calculated for mono-energetic electron beams of 6, 12 and 20 MeV, and photon beams of 60 keV and 6 MV. For each radiation quality the depth dose distributions are in close agreement.