Biomedical subjects

S Zavgorodni

Publications and source records attributed to S Zavgorodni.

6 recordsLinked to original sources

PubMed2006

Coordinate transformations for BEAM/EGSnrc Monte Carlo dose calculations of non-coplanar fields received from a DICOM-compliant treatment planning system.

The Monte Carlo (MC) method provides the most accurate to-date dose calculations in heterogeneous media and complex geometries, and this spawns increasing interest in incorporating MC calculations in the treatment planning quality assurance process. This process involves MC dose calculations for the treatment plans produced clinically. Commonly used in radiotherapy, MC codes are BEAMnrc and DOSXYZnrc, which transport particles in a coordinate system (c.s.) that has been established historically and does not correspond to the c.s. of treatment planning systems (TPSs). Relative rotations of these c.s. are not straightforward, especially for non-coplanar treatments. Transformation equations are therefore required to re-calculate a treatment plan using BEAM/DOSXYZnrc codes. This paper presents such transformations for beam angles defined in a DICOM-compliant treatment planning coordinate system. Verification of the derived transformations with two three-field plans simulated on a phantom using TPS as well as MC codes has been performed demonstrating exact geometrical agreement of the MC treatment fields' placement.

Biophysical Phenomena↗

PubMed2005

EUD-based radiotherapy treatment plan evaluation: incorporating physical and Monte Carlo statistical dose uncertainties.

The purpose of this work is to quantify the impact of dose uncertainty on radiobiologically based treatment plan evaluation. Dose uncertainties are divided into two categories: physical and statistical. Physical dose uncertainty is associated with the systematic and/or random errors incurred during treatment planning and/or delivery. The dose uncertainty associated with Monte Carlo calculated dose distributions is deemed statistical and noted as artificial with respect to the actual delivered dose. We will refer to all dose uncertainties that arise from either calculation or delivery as stochastic. Both physical and statistical dose uncertainties are considered at the intra- and inter-voxel levels. To account for voxel dose uncertainty, we calculate the mean survival fraction (SF) for the random dose deposition. Mathematically, the expression for the mean survival fraction is identical to that used by Niemierko (1997 Med. Phys. 24 103-10) in defining equivalent uniform dose (EUD). To distinguish between spatial and probabilistic dose variations, we define equivalent stochastic dose (ESD) as a voxel dose that gives the mean expected survival fraction for the randomly deposited dose. For a probability density function f(D), that represents the probabilistic voxel dose, SF(ESD) can be calculated by convolving SF(D) with f(D). In the case where the probability density function follows a Gaussian distribution, an analytic expression is derived for SF(ESD). The derived expression is verified using the Monte Carlo method and ESD values calculated with varied radiosensitivities for cases of 60 and 70 Gy at 2 Gy per fraction. The analytic expression is also extended to account for a multi-voxel dose distribution that incorporates a spatial dose heterogeneity. The results show that survival fraction increases with an increased dose uncertainty. This reduction depends on radiobiological parameters attributed to tissue and tumour. For tissue, ESD drops to 55% of the mean physical dose when the dose has a 10% intra- and inter-voxel dose uncertainty and inhomogeneity.

Body Burden↗

PubMed2005

Implementation of random set-up errors in Monte Carlo calculated dynamic IMRT treatment plans.

The fluence-convolution method for incorporating random set-up errors (RSE) into the Monte Carlo treatment planning dose calculations was previously proposed by Beckham et al, and it was validated for open field radiotherapy treatments. This study confirms the applicability of the fluence-convolution method for dynamic intensity modulated radiotherapy (IMRT) dose calculations and evaluates the impact of set-up uncertainties on a clinical IMRT dose distribution. BEAMnrc and DOSXYZnrc codes were used for Monte Carlo calculations. A sliding window IMRT delivery was simulated using a dynamic multi-leaf collimator (DMLC) transport model developed by Keall et al. The dose distributions were benchmarked for dynamic IMRT fields using extended dose range (EDR) film, accumulating the dose from 16 subsequent fractions shifted randomly. Agreement of calculated and measured relative dose values was well within statistical uncertainty. A clinical seven field sliding window IMRT head and neck treatment was then simulated and the effects of random set-up errors (standard deviation of 2 mm) were evaluated. The dose-volume histograms calculated in the PTV with and without corrections for RSE showed only small differences indicating a reduction of the volume of high dose region due to set-up errors. As well, it showed that adequate coverage of the PTV was maintained when RSE was incorporated. Slice-by-slice comparison of the dose distributions revealed differences of up to 5.6%. The incorporation of set-up errors altered the position of the hot spot in the plan. This work demonstrated validity of implementation of the fluence-convolution method to dynamic IMRT Monte Carlo dose calculations. It also showed that accounting for the set-up errors could be essential for correct identification of the value and position of the hot spot.

Algorithms↗

PubMed2004

The impact of inter-fraction dose variations on biological equivalent dose (BED): the concept of equivalent constant dose.

Inter-fraction dose fluctuations, which appear as a result of setup errors, organ motion and treatment machine output variations, may influence the radiobiological effect of the treatment even when the total delivered physical dose remains constant. The effect of these inter-fraction dose fluctuations on the biological effective dose (BED) has been investigated. Analytical expressions for the BED accounting for the dose fluctuations have been derived. The concept of biological effective constant dose (BECD) has been introduced. The equivalent constant dose (ECD), representing the constant physical dose that provides the same cell survival fraction as the fluctuating dose, has also been introduced. The dose fluctuations with Gaussian as well as exponential probability density functions were investigated. The values of BECD and ECD calculated analytically were compared with those derived from Monte Carlo modelling. The agreement between Monte Carlo modelled and analytical values was excellent (within 1%) for a range of dose standard deviations (0-100% of the dose) and the number of fractions (2 to 37) used in the comparison. The ECDs have also been calculated for conventional radiotherapy fields. The analytical expression for the BECD shows that BECD increases linearly with the variance of the dose. The effect is relatively small, and in the flat regions of the field it results in less than 1% increase of ECD. In the penumbra region of the 6 MV single radiotherapy beam the ECD exceeded the physical dose by up to 35%, when the standard deviation of combined patient setup/organ motion uncertainty was 5 mm. Equivalently, the ECD field was approximately 2 mm wider than the physical dose field. The difference between ECD and the physical dose is greater for normal tissues than for tumours.

Algorithms↗

PubMed2002

Growth of a virtual tumour using probabilistic methods of cell generation.

A study into treatment enhancement in combined chemo-radiotherapy for unresectable head and neck cancer has initiated the development of a computer model of tumour growth. The model is based on biological parameters, and characterises tumour growth prior to chemo-radiotherapy. Tumour growth starting from a single stem cell is modelled using the Monte Carlo method. The type of the cell function, their relative proportions on mitosis, their proliferative capacity, the duration of the four phases of the cell cycle, the mean cell cycle time, and the cell loss due to natural causes are the main parameters of the basic model. A Gaussian distribution function operates in establishing the cell cycle time, with a mean value of 33 hours, while the cell type is sampled from a uniform distribution. With the established model, the sensitivity of the developed tumour's cell population to the stem, proliferative and nonproliferative ratio at mitosis was assessed. The present model accurately reflects the exponential distribution of cells along the cell cycle (70% cells in GI phase, 15% in S, 10% in G2, 5% in M) of a developed tumour as described in the literature. The proportion of stem, finitely proliferating and resting cells during tumour growth is maintained within their biological limits (2% stem, 13% finitely proliferating, 85% nonproliferating cells). The ratio (R = 3) between the time necessary to develop a clinically detectable tumour (10(9) cells) and the further time to grow to its lethal size (10(12) cells) is in accordance with the biological data when tumour volume is compared for the two periods (30 doublings and 10 doublings respectively). In conclusion, computer simulation can illustrate the biological growth of a tumour and the cell distribution along the cell cycle. These distributions may then be used in the assessment of tumour response to radiotherapy and to specific chemotherapeutic agents.

Cell Count↗

PubMed1997

Improving wedged field dose distributions.

Dose profiles produced by wedge filters in the non-wedged direction can exhibit a 7% or greater dose reduction at the outer ends of the field compared with open field profiles. However, many planning systems use open field profiles to model wedged dose distributions. In the present work, wedges have been modified to reproduce open field profile shapes. This modification involved removing varying thicknesses of the wedge using a simple milling machine. The wedge thickness was calculated using the assumption that dose is proportional to primary collision kerma. The discrepancies in dose between wedged field and open field profile shapes of up to 7% were reduced to less than 3% with the modifications, even for varying depths and off-axis distances. The necessary measurements are simple to perform, and hence this technique could be applied to improve wedged field dose distributions in other radiotherapy departments.

Biophysical Phenomena↗