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.

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.

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.

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.