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Monte Carlo techniques in medical radiation physics

The results obtained in the heterogeneous cases are shown on Figures 2 thru 5. The curves show the percentage of absorbed dose as a function of depth in centimeters. This difference is observed because the simulation was made with a monoenergetic source of 6 MV, and not with the spectrum of a clinical accelerator.

Figure 2 shows the behavior of the beam when the heterogeneity of aluminum is introduced. For a depth of 24 cm, the absorbed dose in aluminum is In the case of bone heterogeneity Figure 3 , the absorbed dose is Figure 4 shows the silver heterogeneity, a material with high electronic density, in which the absorbed dose at the 24 cm depth is The case of the lung Figure 6 presents a different behavior from all the others, as the electronic density of this material is lower than that of water. Thus, in this case the absorbed dose at the 24 cm depth is On Figures 2 thru 5 , a transition region can be observed, where the scattering contributes for a peak in the region between The peak occurs when the beam passes from a lower density medium to a higher density medium, and the buildup loss region occurs in the reverse sense, from higher to lower density.

In denser materials, such as titanium and silver, these regions become more evident than in less dense materials, such as bone and aluminum. Figure 6 , related lung heterogeneity, shows opposite behavior in the scattering region, that is, the build-up loss region is between These scattering regions may contribute for an unnecessary dose increase in organs adjacent to heterogeneities.

In the present study the absorbed dose was evaluated in the interior and in the proximity of certain materials containing heterogeneities with different densities by means of Monte Carlos simulations. There is a consensus amongst practitioners that an overdose may increase the risk for necrosis, and an underdose may impair the destruction of the tumor, and should also be evaluated The main objective of the simulation was to study the behavior of the photon beam as it passes through interfaces and media not equivalent to water.

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In order to evaluate the behavior of the beam, curves of absorbed dose percentages as a function of depth in the phantoms, were obtained. This difference is observed because the simulation was performed considering a monoenergetic source of 6 MV, and not the actual spectrum of an accelerator. Studies developed by Allal et al. Studies developed by Carolan et al. In this study, prostheses cast with Co-Cr-Mo alloys were analyzed due to their high electronic density, presenting greater impact on the irradiated dose distribution.

The results have demonstrated that an increase in dose can be observed in the tissue above the prosthesis, at 5 mm, and a decrease in absorbed dose in the tissue immediately below the prosthesis, when it is present. Silver, amongst the materials analyzed in the present study, is the one with the highest electronic density, For the depth of 24 cm, for example, the absorbed dose by silver was In the PDD curves, one can also observe that the scattering in the beginning and at the end of heterogeneities corresponds, respectively, to a peak region and a region of build-up loss.

These regions are more evident in denser materials such as silver. Gez et al. Validation and verification of absorbed dose calculations in radionuclide therapy. Monte Carlo methods and mathematical models for the dosimetry of skeleton and bone marrow. Monte Carlo modeling of dose distributions in intravascular radiation therapy. Hur blir jag sjukhusfysiker? Webbkarta Om kakor. International website. Lyssna med talande webb. Aktivera Talande Webb. Order here Monte Carlo Techniques in Radiation Therapy Eds: Joao Seco, Frank Verhaegen Modern cancer treatment relies on Monte Carlo simulations to help radiotherapists and clinical physicists better understand and compute radiation dose from imaging devices as well as exploit four-dimensional imaging data.

Monte Carlo Techniques in Radiation Therapy. Persson, Professor emeritus Fysik i Lund. Phys Med Biol. Bielajew A. Monte Carlo Techniques in Radiation Therapy. Fundamentals of Ionizing Radiation Dosimetry.

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Weinheim: Wiley-VCH; Consistency in reference radiotherapy dosimetry: resolution of an apparent conundrum when 60 Co is the reference quality for charged-particle and photon beams. Andreo P, Benmakhlouf H. Role of the density, density effect and mean excitation energy in solid-state detectors for small photon fields. Vienna: International Atomic Energy Agency; Berger MJ. Methods in Computational Physics. New York: Academic Press: Salvat F. Ottawa: National Research Council Canada; Calculation of energy and charge deposition and of the electron flux in a water medium bombarded with 20 MeV electrons.

Ann N Y Acad Sci. Stopping-power ratios for electron dosimetry with ionization chambers. Vienna: International Atomic Energy Agency: Nahum AE. Andreo P, Brahme A. Stopping power data for high-energy photon beams. Med Phys. Beam quality specification for photon beam dosimetry. Improved calculations of stopping-power ratios and their correlation with the quality of therapeutic photon beams. In: Measurement Assurance in Dosimetry. R 50 as a beam quality specifier for selecting stopping-power ratios and reference depths for electron dosimetry.

Nath R, Schulz RJ. Calculated response and wall correction factors for ionization chambers exposed to 60 Co gamma-rays. Christchurch: National Radiation Laboratory; Nucl Instr Meth B. Smyth VG. Interface effects in the Monte Carlo simulation of electron tracks.

RMP Rounds - An Eclectic Showcase of Monte Carlo Applications in Radiotherapy

Calculated and measured air-kerma response of ionization chambers in low and medium energy photon beams In: Seuntjens J, Mobit PN, editors. Madison: Medical Physics Publishing: Sempau J, Andreo P. Monte Carlo-based perturbation and beam quality correction factors for thimble ionization chambers in high-energy photon beams. Benmakhlouf H, Andreo P. Spectral distribution of particle fluence in small field detectors and its implication on small field dosimetry. Investigation of buildup dose from electron contamination of clinical photon beams. Energy and angular distributions of photons from medical linear accelerators.

Udale M. A Monte Carlo investigation of surface doses for broad electron beams.


Standford: Stanford Linear Accelerator Center; Mackie TR. New developments in radiotherapy dose planning.

In: 17th Int. Paris: Hughes G. Progr Nucl Sci Tech. GEANT4 - a simulation toolkit. Nucl Instr Meth A. Strahlenther Onkol. Neuenschwander H, Ernst JB.

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A Macro Monte Carlo method for electron beam dose calculations. Fippel M. DPM, a fast, accurate Monte Carlo code optimized for photon and electron radiotherapy treatment planning dose calculations. Seco J, Verhaegen F. Converting absorbed dose to medium to absorbed dose to water for Monte Carlo based photon beam dose calculations. Collision-kerma conversion between dose-to-tissue and dose-to-water by photon energy-fluence corrections in low-energy brachytherapy. Intermediate dosimetric quantities. Radiat Res.

Monte Carlo techniques in radiation therapy Joao Seco

Download references. Data sharing not applicable to this article as no datasets were generated during the current study. Correspondence to Pedro Andreo.

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By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate. Please note that comments may be removed without notice if they are flagged by another user or do not comply with our community guidelines. Search all BMC articles Search. Abstract Background The use of the Monte Carlo MC method in radiotherapy dosimetry has increased almost exponentially in the last decades.