974 resultados para analogy calculation


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The electron Monte Carlo (eMC) dose calculation algorithm available in the Eclipse treatment planning system (Varian Medical Systems) is based on the macro MC method and uses a beam model applicable to Varian linear accelerators. This leads to limitations in accuracy if eMC is applied to non-Varian machines. In this work eMC is generalized to also allow accurate dose calculations for electron beams from Elekta and Siemens accelerators. First, changes made in the previous study to use eMC for low electron beam energies of Varian accelerators are applied. Then, a generalized beam model is developed using a main electron source and a main photon source representing electrons and photons from the scattering foil, respectively, an edge source of electrons, a transmission source of photons and a line source of electrons and photons representing the particles from the scrapers or inserts and head scatter radiation. Regarding the macro MC dose calculation algorithm, the transport code of the secondary particles is improved. The macro MC dose calculations are validated with corresponding dose calculations using EGSnrc in homogeneous and inhomogeneous phantoms. The validation of the generalized eMC is carried out by comparing calculated and measured dose distributions in water for Varian, Elekta and Siemens machines for a variety of beam energies, applicator sizes and SSDs. The comparisons are performed in units of cGy per MU. Overall, a general agreement between calculated and measured dose distributions for all machine types and all combinations of parameters investigated is found to be within 2% or 2 mm. The results of the dose comparisons suggest that the generalized eMC is now suitable to calculate dose distributions for Varian, Elekta and Siemens linear accelerators with sufficient accuracy in the range of the investigated combinations of beam energies, applicator sizes and SSDs.

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Although the Monte Carlo (MC) method allows accurate dose calculation for proton radiotherapy, its usage is limited due to long computing time. In order to gain efficiency, a new macro MC (MMC) technique for proton dose calculations has been developed. The basic principle of the MMC transport is a local to global MC approach. The local simulations using GEANT4 consist of mono-energetic proton pencil beams impinging perpendicularly on slabs of different thicknesses and different materials (water, air, lung, adipose, muscle, spongiosa, cortical bone). During the local simulation multiple scattering, ionization as well as elastic and inelastic interactions have been taken into account and the physical characteristics such as lateral displacement, direction distributions and energy loss have been scored for primary and secondary particles. The scored data from appropriate slabs is then used for the stepwise transport of the protons in the MMC simulation while calculating the energy loss along the path between entrance and exit position. Additionally, based on local simulations the radiation transport of neutrons and the generated ions are included into the MMC simulations for the dose calculations. In order to validate the MMC transport, calculated dose distributions using the MMC transport and GEANT4 have been compared for different mono-energetic proton pencil beams impinging on different phantoms including homogeneous and inhomogeneous situations as well as on a patient CT scan. The agreement of calculated integral depth dose curves is better than 1% or 1 mm for all pencil beams and phantoms considered. For the dose profiles the agreement is within 1% or 1 mm in all phantoms for all energies and depths. The comparison of the dose distribution calculated using either GEANT4 or MMC in the patient also shows an agreement of within 1% or 1 mm. The efficiency of MMC is up to 200 times higher than for GEANT4. The very good level of agreement in the dose comparisons demonstrate that the newly developed MMC transport results in very accurate and efficient dose calculations for proton beams.

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BACKGROUND: Ankle-brachial pressure index (ABI) is a simple, inexpensive, and useful tool in the detection of peripheral arterial occlusive disease (PAD). The current guidelines published by the American Heart Association define ABI as the quotient of the higher of the systolic blood pressures (SBPs) of the two ankle arteries of that limb (either the anterior tibial artery or the posterior tibial artery) and the higher of the two brachial SBPs of the upper limbs. We hypothesized that considering the lower of the two ankle arterial SBPs of a side as the numerator and the higher of the brachial SBPs as the denominator would increase its diagnostic yield. METHODS: The former method of eliciting ABI was termed as high ankle pressure (HAP) and the latter low ankle pressure (LAP). ABI was assessed in 216 subjects and calculated according to the HAP and the LAP method. ABI findings were confirmed by arterial duplex ultrasonography. A significant arterial stenosis was assumed if ABI was <0.9. RESULTS: LAP had a sensitivity of 0.89 and a specificity of 0.93. The HAP method had a sensitivity of 0.68 and a specificity of 0.99. McNemar's test to compare the results of both methods demonstrated a two-tailed P < .0001, indicating a highly significant difference between both measurement methods. CONCLUSIONS: LAP is the superior method of calculating ABI to identify PAD. This result is of great interest for epidemiologic studies applying ABI measurements to detect PAD and assessing patients' cardiovascular risk.

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Different codes are used for Monte Carlo (MC) calculations in radiation therapy. In this research, MCNP4C and GEANT3 codes have been compared in calculations of dosimetric characteristics of Varian Clinac 2300C/D. The parameters of influence in the differences seen in dosimetric features were discussed. This study emphasizes that both MCNP4C and GEANT3 MC can be used in radiation therapy computations and their differences in photon spectra calculations have a negligible effect on percentage depth dose computations in radiation therapy.

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The article describes the results of fatigue tests with sideflexing polymer chains conducted on a dynamic testing machine and in testing conveyors. A new approach is suggested, that allows a calculatory estimation of the fatigue life of these chains. Finally, a calculation-software is presented, that has been developed based on the test results and the new equations.

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In this paper a superelement formulation for geometric nonlinear finite element analysis is proposed. The element formulation is based on matrices generated by the static condensation algorithm. After defining the element characteristics, a method for the calculation of the element forces in a large displacement and rotation analysis is developed. In order to use the element in the solution of stability problems, the formulation of the geometric stiffness matrix is derived. An example shows the benefits of the element for the calculation of lattice-boom cranes.

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The estimation of the average travel distance in a low-level picker-to-part order picking system can be done by analytical methods in most cases. Often a uniform distribution of the access frequency over all bin locations is assumed in the storage system. This only applies if the bin location assignment is done randomly. If the access frequency of the articles is considered in the bin location assignment to reduce the average total travel distance of the picker, the access frequency over the bin locations of one aisle can be approximated by an exponential density function or any similar density function. All known calculation methods assume that the average number of orderlines per order is greater than the number of aisles of the storage system. In case of small orders this assumption is often invalid. This paper shows a new approach for calculating the average total travel distance taking into account that the average number of orderlines per order is lower than the total number of aisles in the storage system and the access frequency over the bin locations of an aisle can be approximated by any density function.