Monte Carlo treatment planning for stereotactic radiosurgery

A position-dependent pattern of epidermal cell types is produced during root development in Arabidopsis thaliana. This pattern is reflected in the expression pattern of GLABRA2 (GL2), a homeobox gene that regulates cell differentiation in the root epidermis. GL2 promoter::GUS fusions were used to show that the TTG gene, a regulator of root epidermis development, is necessary for maximal GL2 activity but is not required for the pattern of GL2 expression. Furthermore, GL2-promoter activity is influenced by expression of the myc-like maize R gene (35S::R) in Arabidopsis but is not affected by gl2 mutations. A position-dependent pattern of cell differentiation and GL2-promoter activity was also discovered in the hypocotyl epidermis that was analogous to the pattern in the root. Non-GL2-expressing cell files in the hypocotyl epidermis located outside anticlinal cortical cell walls exhibit reduced cell length and form stomata. Like the root, the hypocotyl GL2 activity was shown to be influenced by ttg and 35S::R but not by gl2. The parallel pattern of cell differentiation in the root and hypocotyl indicates that TTG and GL2 participate in a common position-dependent mechanism to control cell-type patterning throughout the apical-basal axis of the Arabidopsis seedling.     

The regional Monte Carlo method: a dose calculation method based on accuracy requirement

In this work we propose the regional Monte Carlo (RMC) method of dose calculation. This method combines the Monte Carlo (MC) algorithm and a non-MC algorithm (such as the convolution method) for optimal speed and accuracy in dose calculation for both photon and electron beams and for various irradiation and patient geometries. For specific regions in the geometry where high accuracy is required but difficult to obtain with analytical or empirical calculations, such as critical organs surrounded by complicated inhomogeneities, the MC algorithm is used. For regions with simple geometries, or where a high degree of dose accuracy is not critical, the non-MC algorithm is used to increase speed. There are two aspects of the RMC method. The first one involves determining critical regions and boundaries, and the other involves the actual implementation and mixing of the two computational algorithms. Two examples of different geometries are used to illustrate the different ways to apply the RMC method. The possibility to extend the method to more complicated geometries and inhomogeneities, as well as the ability of the method to incorporate different calculation algorithms, are also discussed.     

Monte Carlo calculation of dose enhancement by neutron capture of 10B in fast neutron therapy

Since 1978 the Essen Medical Cyclotron Facility has been used for fast neutron therapy. The treatment of deep-seated tumours by d(14) + Be neutron beam therapy (mean energy = 5.8 MeV) is still limited because of the steep decrease in depth-dose distribution. The interactions of fast neutrons in tissue leads to a thermal neutron distribution. These partially thermalized neutrons can be used to produce neutron capture reactions with 10B. Thus incorporation of 10B in tumours treated with fast neutrons will increase the relative local tumour dose due to the reaction 10B (n, alpha) 7Li. The magnitude of dose enhancement by 10B depends on the distribution of the thermal neutron fluence, 10B concentration, field size of the neutron beam, beam energy and the specific phantom geometry. The slowing down of the fast neutrons, resulting in a thermal neutron distribution in a phantom, has been computed using a Monte Carlo model. This model, which includes a deep-seated tumour, was experimentally verified by measurements of the thermal neutron fluence rate in a phantom using neutron activation of gold foil. When non-boronated water phantoms were irradiated with a total dose of 1 Gy at a depth of 6 cm, the thermal fluencies at this depth were found to be 2 x 10(10) cm-2. The absorbed dose in a tumour with 100 ppm 10B, at the same depth, was enhanced by 15%.     

Monte Carlo method to study the proton fluence for treatment planning

The proton beam at the Hahn Meitner Institute (HMI) in Berlin will be used for proton therapy of eye melanoma in the near future. As part of the pre-therapeutic studies, Monte Carlo calculations have been performed to investigate the primary fluence distribution of the proton beam including the influence of scattering foils, range shifters, modulator wheels, and collimators. Any material in the beam path will modify the therapeutic beam because of energy loss, multiple scattering, range straggling, and nuclear reactions. The primary fluence information is a pre-requisite for most pencil-beam treatment planning algorithms. The measured beam penumbra has been used as one of the parameters to characterize a proton beam for further calculations in a treatment planning algorithm. However, this phenomenological quantity represents only indirect information about the properties of the proton beam. In this work, an alternative parameterization of the beam exiting the vacuum window of the accelerator, as well as the beam right in front of the patient collimator, is introduced. A beam is fully characterized if one knows (for instance from Monte Carlo simulations) the particle distribution in energy, position, and angle, i.e., the phase space distribution. Therefore, parameters derived from this distribution can provide an alternative input in treatment planning algorithms. In addition, the method of calculation is introduced as a tool to investigate the influence of modifications in the beam delivery system on the behavior of the therapeutic proton beam.     

Three-dimensional optimization of treatment planning for gamma unit treatment system

During a treatment using the Leksell gamma unit, the physician and physicist need to determine a treatment plan by changing the parameters such as collimator sizes, the position of isocenters and isocenters' weights. This is a complex problem because the set of parameters is large, especially when targets are geometrically close to a critical structure. For this reason, we present here an optimization algorithm, namely the multiplier penalty method, to mathematically determine those parameters. Two cases are presented in this article: the first one is really planned by a physicist in a clinical treatment, and is redone in our optimization algorithm to show the effectiveness of this method; the second one is theoretical where a critical structure is placed close to the target volume. The results show that this method achieves an excellent conformation to the specified isodose curve with the contour of the target volume, allowing minimal damage to surrounding healthy tissue.     

Monte Carlo and analytical calculation of proton pencil beams for computerized treatment plan optimization

Proton pencil beams in water, in a format suitable for treatment planning algorithms and covering the radiotherapy energy range (50-250 MeV), have been calculated using a modified version of the Monte Carlo code PTRAN. A simple analytical model has also been developed for calculating proton broad-beam dose distributions which is in excellent agreement with the Monte Carlo calculations. Radial dose distributions are also calculated analytically and narrow proton pencil-beam dose distributions derived. The physical approximations in the Monte Carlo code and in the analytical model together with their limitations are discussed. Examples showing the use of the calculated set of proton pencil beams as input to an existing photon treatment planning algorithm based on biological optimization are given for fully 3D scanned proton pencil beams; these include intensity modulated beams with range shift and scanning in the transversal plane.