Biomedical subjects

R Jeraj

Publications and source records attributed to R Jeraj.

8 recordsLinked to original sources

PubMed2005

Optimization of intensity-modulated radiation therapy with biological objectives.

IMRT treatment planning via biological objectives gives rise to constrained nonlinear optimization problems. We consider formulations with nonlinear objectives based on the equivalent uniform dose (EUD), with bound constraints on the beamlet weights, and describe fast, flexible variants of the two-metric gradient-projection approach for solving them efficiently and in a mathematically sound manner. We conclude that an approach that calculates the Newton component of the step iteratively, by means of the conjugate-gradient algorithm and an implicit representation of the Hessian matrix, is most effective. We also present an efficient heuristic for obtaining an approximate solution with a smoother distribution of beamlet weights. The effectiveness of the methods is verified by testing on a medium-scale clinical case.

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PubMed2005

The helical tomotherapy thread effect.

Inherent to helical tomotherapy is a dose variation pattern that manifests as a "ripple" (peak-to-trough relative to the average). This ripple is the result of helical beam junctioning, completely unique to helical tomotherapy. Pitch is defined as in helical CT, the couch travel distance for a complete gantry rotation relative to the axial beam width at the axis of rotation. Without scattering or beam divergence, an analytical posing of the problem as a simple integral predicts minima near a pitch of 1/n where n is an integer. A convolution-superposition dose calculator (TomoTherapy, Inc.) included all the physics needed to explore the ripple magnitude versus pitch and beam width. The results of the dose calculator and some benchmark measurements demonstrate that the ripple has sharp minima near p=0.86(1/n). The 0.86 factor is empirical and caused by a beam junctioning of the off-axis dose profiles which differ from the axial profiles as well as a long scatter tail of the profiles at depth. For very strong intensity modulation, the 0.86 factor may vary. The authors propose choosing particular minima pitches or using a second delivery that starts 180 deg off-phase from the first to reduce these ripples: "Double threading." For current typical pitches and beam widths, however, this effect is small and not clinically important for most situations. Certain extremely large field or high pitch cases, however, may benefit from mitigation of this effect.

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PubMed2002

Monte Carlo study of a highly efficient gas ionization detector for megavoltage imaging and image-guided radiotherapy.

The imaging characteristics of an arc-shaped xenon gas ionization chamber for the purpose of megavoltage CT imaging were investigated. The detector consists of several hundred 320 microm thick gas cavities separated by thin tungsten plates of the same thickness. Dose response, efficiency and resolution parameters were calculated using Monte Carlo simulations. The calculations were compared to measurements taken in a 4 MV photon beam, assuming that the measured signal in the chambers corresponds to the therein absorbed dose. The measured response profiles for narrow and broad incident photon beams could be well reproduced with the Monte Carlo calculations. They show, that the quantum efficiency is 29.2% and the detective quantum efficiency at zero frequency DQE(0) is 20.4% for the detector arc placed in focus with the photon source. For a detector placed out of focus, these numbers even increase. The efficiency of this kind of radiation detector for megavoltage radiation therefore surpasses the reported efficiency of existing detector technologies. The resolution of the detector is quantified with calculated and measured line spread functions. The corresponding modulation transfer functions were determined for different thicknesses of the tungsten plates. They show that the resolution is only slightly dependent on the plate thickness but is predominantly determined by the cell size of the detector. The optimal plate thickness is determined by a tradeoff between quantum efficiency, total signal generation and resolution. Thicker plates are more efficient but the total signal and the resolution decrease with plate thickness. In conclusion, a gas ionization chamber of the described type is a highly efficient megavoltage radiation detector, allowing to obtain CT images with very little dose for a sufficient image quality for anatomy verification. This kind of detector might serve as a model for a future generation of highly efficient radiation detectors.

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PubMed2002

Parameter dependence of the MCNP electron transport in determining dose distributions.

In this paper, a detailed study of the electron transport in MCNP is performed, separating the effects of the energy binning technique on the energy loss rate, the scattering angles, and the sub-step length as a function of energy. As this problem is already well known, in this paper we focus on the explanation as to why the default mode of MCNP can lead to large deviations. The resolution dependence was investigated as well. An error in the MCNP code in the energy binning technique in the default mode (DBCN 18 card = 0) was revealed, more specific in the updating of cross sections when a sub-step is performed corresponding to a high-energy loss. This updating error is not present in the ITS mode (DBCN 18 card = 1) and leads to a systematically lower dose deposition rate in the default mode. The effect is present for all energies studied (0.5-10 MeV) and depends on the geometrical resolution of the scoring regions and the energy grid resolution. The effect of the energy binning technique is of the same order of that of the updating error for energies below 2 MeV, and becomes less important for higher energies. For a 1 MeV point source surrounded by homogeneous water, the deviation of the default MCNP results at short distances attains 9% and remains approximately the same for all energies. This effect could be corrected by removing the completion of an energy step each time an electron changes from an energy bin during a sub-step. Another solution consists of performing all calculations in the ITS mode. Another problem is the resolution dependence, even in the ITS mode. The higher the resolution is chosen (the smaller the scoring regions) the faster the energy is deposited along the electron track. It is proven that this is caused by starting a new energy step when crossing a surface. The resolution effect should be investigated for every specific case when calculating dose distributions around beta sources. The resolution should not be higher than 0.85*(1-EFAC)*CSDA, where EFAC is the energy loss per energy step and CSDA a continuous slowing down approximation range. This effect could as well be removed by determining the cross sections for energy loss and multiple scattering at the average energy of an energy step and by sampling the cross sections for each sub-step. Overall, we conclude that MCNP cannot be used without a caution due to possible errors in the electron transport. When care is taken, it is possible to obtain correct results that are in agreement with other Monte Carlo codes.

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PubMed2000

The effect of statistical uncertainty on inverse treatment planning based on Monte Carlo dose calculation.

The effect of the statistical uncertainty, or noise, in inverse treatment planning for intensity modulated radiotherapy (IMRT) based on Monte Carlo dose calculation was studied. Sets of Monte Carlo beamlets were calculated to give uncertainties at Dmax ranging from 0.2% to 4% for a lung tumour plan. The weights of these beamlets were optimized using a previously described procedure based on a simulated annealing optimization algorithm. Several different objective functions were used. It was determined that the use of Monte Carlo dose calculation in inverse treatment planning introduces two errors in the calculated plan. In addition to the statistical error due to the statistical uncertainty of the Monte Carlo calculation, a noise convergence error also appears. For the statistical error it was determined that apparently successfully optimized plans with a noisy dose calculation (3% 1sigma at Dmax), which satisfied the required uniformity of the dose within the tumour, showed as much as 7% underdose when recalculated with a noise-free dose calculation. The statistical error is larger towards the tumour and is only weakly dependent on the choice of objective function. The noise convergence error appears because the optimum weights are determined using a noisy calculation, which is different from the optimum weights determined for a noise-free calculation. Unlike the statistical error, the noise convergence error is generally larger outside the tumour, is case dependent and strongly depends on the required objectives.

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PubMed2000

The effect of dose calculation uncertainty on the evaluation of radiotherapy plans.

Monte Carlo dose calculations will potentially reduce systematic errors that may be present in currently used dose calculation algorithms. However, Monte Carlo calculations inherently contain random errors, or statistical uncertainty, the level of which decreases inversely with the square root of computation time. Our purpose in this study was to determine the level of uncertainty at which a lung treatment plan is clinically acceptable. The evaluation methods to decide acceptability were visual examination of both isodose lines on CT scans and dose volume histograms (DVHs), and reviewing calculated biological indices. To study the effect of systematic and/or random errors on treatment plan evaluation, a simulated "error-free" reference plan was used as a benchmark. The relationship between Monte Carlo statistical uncertainty and dose was found to be approximately proportional to the square root of the dose. Random and systematic errors were applied to a calculated lung plan, creating dose distributions with statistical uncertainties of between 0% and 16% (1 s.d.) at the maximum dose point and also distributions with systematic errors of -16% to 16% at the maximum dose point. Critical structure DVHs and biological indices are less sensitive to calculation uncertainty than those of the target. Systematic errors affect plan evaluation accuracy significantly more than random errors, suggesting that Monte Carlo dose calculation will improve outcomes in radiotherapy. A statistical uncertainty of 2% or less does not significantly affect isodose lines, DVHs, or biological indices.

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PubMed1999

Comparisons between MCNP, EGS4 and experiment for clinical electron beams.

Understanding the limitations of Monte Carlo codes is essential in order to avoid systematic errors in simulations, and to suggest further improvement of the codes. MCNP and EGS4, Monte Carlo codes commonly used in medical physics, were compared and evaluated against electron depth dose data and experimental backscatter results obtained using clinical radiotherapy beams. Different physical models and algorithms used in the codes give significantly different depth dose curves and electron backscattering factors. The default version of MCNP calculates electron depth dose curves which are too penetrating. The MCNP results agree better with experiment if the ITS-style energy-indexing algorithm is used. EGS4 underpredicts electron backscattering for high-Z materials. The results slightly improve if optimal PRESTA-I parameters are used. MCNP simulates backscattering well even for high-Z materials. To conclude the comparison, a timing study was performed. EGS4 is generally faster than MCNP and use of a large number of scoring voxels dramatically slows down the MCNP calculation. However, use of a large number of geometry voxels in MCNP only slightly affects the speed of the calculation.

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PubMed1999

Monte Carlo-based inverse treatment planning.

A Monte Carlo based inverse treatment planning system (MCI) has been developed which combines arguably the most accurate dose calculation method (Monte Carlo particle transport) with a 'guaranteed' optimization method (simulated annealing). A distribution of photons is specified in the tumour volume; they are transported using an adjoint calculation method to outside the patient surface to build up an intensity distribution. This intensity distribution is used as the initial input into an optimization algorithm. The dose distribution from each beam element from a number of fields is pre-calculated using Monte Carlo transport. Simulated annealing optimization is then used to find the weighting of each beam element, to yield the optimal dose distribution for the given criteria and constraints. MCI plans have been generated in various theoretical phantoms and patient geometries. These plans show conformation of the dose to the target volume and avoidance of critical structures. To verify the code, an experiment was performed on an anthropomorphic phantom.

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