Use of single scatter electron monte carlo transport for...

Data processing: structural design – modeling – simulation – and em – Modeling by mathematical expression

Reexamination Certificate

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C703S005000, C703S012000

Reexamination Certificate

active

06285969

ABSTRACT:

BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates to radiation therapy, and more specifically it relates to a method for modeling the precise microscopic interactions of electrons with matter to enhance physical understanding of radiation sciences.
2. Description of Related Art
Currently in the United States, radiation therapy is used to treat about 60% of all cancer patients. Since radiation therapy targets specific areas of the body, improvement in radiation treatment techniques has the potential to reduce both mortality and morbidity in a large number of patients.
The radiation source may be in the form of external beams of ionizing particles or radioactive sources internal to the patient. External beams are usually produced by machines acting as particle accelerators. The beam delivery system consists of the radiation source, which is mounted on a gantry which can rotate about a 360° arc around the patient. Each beam is shaped by a rotatable collimator. The patient lies on a rotatable table. The gantry and table both rotate about a single isocenter.
External beam radiation therapy is performed with several types of ionizing radiation. Approximately 80% of patients are treated with photons, ranging in maximum energy from 250 keV to 25 MeV. The balance are treated primarily with electrons with energies from 4 to 25 MeV. In addition, there are several fast neutron and proton therapy facilities which have treated thousands of patients worldwide. Fast neutron therapy is performed with neutron energies up to 70 MeV, while proton therapy is performed with proton energies ranging from about 50 to 250 MeV. Boron neutron capture therapy is conducted with thermal and epithermal neutron sources. Most internal radioactive sources irradiate the patient with photons, although some sources emit low energy electrons.
The effects of ionizing radiation on the body are quantified as radiation dose. Absorbed radiation dose is defined as the ratio of energy deposited to unit mass of tissue. Because tumors and sensitive structures are often located in close proximity, accuracy in the calculation of dose distributions is critically important. The goal of radiation therapy is to deliver a lethal dose to the tumor while maintaining an acceptable dose level in surrounding sensitive structures. This goal is achieved by computer-aided planning of the radiation treatments to be delivered. The treatment planning process consists of characterizing the individual patient's anatomy (most often, this is done using a computed tomography (CT) scan), determining the shape, intensity, and positioning of radiation sources (the subject of the present invention), and calculating the distribution of absorbed radiation dose in the patient. Most current methods used to calculate dose in the body are based on dose measurements made in a water box. Heterogeneities such as bone and airways are treated in an approximate way or ignored altogether. Next to direct measurements, Monte Carlo transport is the most accurate method of determining dose distributions in heterogeneous media. In a Monte Carlo transport method, a computer is used to simulate the passage of particles through an object of interest.
The CREEP single scatter electron Monte Carlo code, the subject of this invention, is designed to be the first phase in a two-part approach to a advanced electron transport package for PEREGRINE. PEREGRINE is an all-particle, first-principles 3D Monte Carlo dose calculation system designed to serve as a dose calculation engine for clinical radiation therapy treatment planning (RTP) systems. By taking advantage of recent advances in low-cost computer commodity hardware, modem symmetric multiprocessor architectures and state-of-the-art Monte Carlo transport algorithms, PEREGRINE performs high-resolution, high accuracy, Monte Carlo RTP calculations in times that are reasonable for clinical use. Because of its speed and simple interface with conventional treatment planning systems, PEREGRINE brings Monte Carlo radiation transport calculations to the clinical RTP desktop environment. PEREGRINE is designed to calculate dose distributions for photon, electron, fast neutron and proton therapy.
The PEREGRINE Monte Carlo dose calculation process depends on four key elements: complete material composition description of the patient as a transport mesh, accurate characterization of the radiation source , first-principles particle transport algorithms (the subject of the present invention), and reliable, self-consistent particle-interaction databases (also an element of the present invention). PEREGRINE uses these elements to provide efficient, accurate Monte Carlo transport calculation for radiation therapy planning.
The patient transport mesh is a Cartesian map of material composition and density determined from the patient's CT scan. Each CT scan pixel is used to identify the atomic composition and density of a corresponding transport mesh voxel. Atomic composition is determined from CT threshold values set by the user or by default values based on user-specified CT numbers for air and water. The user also assigns materials and densities to the interior of contoured structures. If the user specifies a structure as the outer contour of the patient, PEREGRINE constructs a transport mesh that is limited to the maximum extent of that structure, and sets all voxels outside that structure to be air. This provides a simple method of subtracting the CT table from the calculation. The default resolution of the transport mesh is 1×1×3 mm, for small-volume areas such as the head and neck, or 2×2×10 mm, for large-volume treatment sites such as the chest and pelvis. The resolution can also be reduced from the CT scan resolution. For reduced-resolution voxels, material composition and density are determined as the average of all CT pixels that fall within the transport mesh voxel.
The PEREGRINE source model, designed to provide a compact, accurate representation of the radiation source, divides the beam-delivery system into two parts: an accelerator-specific upper portion and a treatment-specific lower part. The accelerator-specific upper portion, consisting of the electron target, flattening filter, primary collimator and monitor chamber is precharacterized based on the machine vendor's model-specific information. These precharacterized sources are derived from Monte Carlo simulations from off-line Monte Carlo simulations using BEAM and MCNP4A, as described in copending U.S. Pat. No. 5,870,697, which is fully incorporated herein by reference. Particle histories from off-line simulations are cast into multidimensional probability distributions, which are sampled during the PEREGRINE calculation. The photon beam is divided into three subsources: primary, scattered, and contaminant. Separating the source into subsources facilitates investigation of the contributions of each individual component. To ensure site-specific model accuracy, the installation procedures will consist of a limited number of beam description parameter adjustments, based on simple beam characterization measurements. The lower portion of the radiation source consists of treatment-specific beam modifiers such as collimators, apertures, blocks, and wedges. This portion is modeled explicitly during each PEREGRINE calculation. Particles are transported through this portion of the source using a pared-down transport scheme. Photons intersecting the collimator jaws are absorbed. Photons intersecting the block or wedge are tracked through the material using the same physical database and methods described below for patient transport. However, all electrons set in motion by photon interactions in the block or wedge are immediately absorbed.
Using the Monte Carlo transport method, PEREGRINE tracks all photons, electrons, positrons and their daughter products through the transport mesh until they reach a specified minimum tracking energy or leave the patient transport mesh. Developing good statistics requires trackin

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