Biomedical subjects

Martin Soukup

Publications and source records attributed to Martin Soukup.

4 recordsLinked to original sources

PubMed2007

Influence of dose engine accuracy on the optimum dose distribution in intensity-modulated proton therapy treatment plans.

Analytical dose computation algorithms like pencil beam algorithms (PB) are presently used for clinical treatment planning in intensity-modulated proton therapy. PB offer fast computation times, but are based on substantial approximations. Monte Carlo algorithms (MC) offer better accuracy, but are slower. We present a comparison of optimized treatment plans for six patients computed either with PB or MC. Both PB and MC are used during optimization, plus MC is used to recompute PB results. PB is used with different accuracy settings that define the coarseness of approximation. We evaluate the errors of PB optimized treatment plans via comparison with MC optimized plans (convergence errors) and MC recomputed plans (systematic errors) occurring for different accuracy settings of the PB. The level of lateral heterogeneities, being one of the main sources of inaccuracies of the PB, is quantified by a formula. In geometries with high levels of lateral heterogeneities, the shortcomings of PB are most obvious. For these geometries, simple PB lead to clinically significant differences and more accurate PB settings have to be used to diminish the error. The most accurate PB settings lead however to longer computing times by approximately a factor of 2 to 4 compared to PB with simple settings. Although the errors can be diminished, they cannot be fully eliminated even with sophisticated PB. Further gain in accuracy can therefore only be reached with MC in optimization. The use of MC in optimization is technically feasible, the computing times are however about 25 to 50 times longer compared to PB with most accurate settings.

Algorithms↗

PubMed2007

Conversion of CT numbers into tissue parameters for Monte Carlo dose calculations: a multi-centre study.

The conversion of computed tomography (CT) numbers into material composition and mass density data influences the accuracy of patient dose calculations in Monte Carlo treatment planning (MCTP). The aim of our work was to develop a CT conversion scheme by performing a stoichiometric CT calibration. Fourteen dosimetrically equivalent tissue subsets (bins), of which ten bone bins, were created. After validating the proposed CT conversion scheme on phantoms, it was compared to a conventional five bin scheme with only one bone bin. This resulted in dose distributions D(14) and D(5) for nine clinical patient cases in a European multi-centre study. The observed local relative differences in dose to medium were mostly smaller than 5%. The dose-volume histograms of both targets and organs at risk were comparable, although within bony structures D(14) was found to be slightly but systematically higher than D(5). Converting dose to medium to dose to water (D(14) to D(14wat) and D(5) to D(5wat)) resulted in larger local differences as D(5wat) became up to 10% higher than D(14wat). In conclusion, multiple bone bins need to be introduced when Monte Carlo (MC) calculations of patient dose distributions are converted to dose to water.

Biophysical Phenomena↗

PubMed2005

A pencil beam algorithm for intensity modulated proton therapy derived from Monte Carlo simulations.

A pencil beam algorithm as a component of an optimization algorithm for intensity modulated proton therapy (IMPT) is presented. The pencil beam algorithm is tuned to the special accuracy requirements of IMPT, where in heterogeneous geometries both the position and distortion of the Bragg peak and the lateral scatter pose problems which are amplified by the spot weight optimization. Heterogeneity corrections are implemented by a multiple raytracing approach using fluence-weighted sub-spots. In order to derive nuclear interaction corrections, Monte Carlo simulations were performed. The contribution of long ranged products of nuclear interactions is taken into account by a fit to the Monte Carlo results. Energy-dependent stopping power ratios are also implemented. Scatter in optional beam line accessories such as range shifters or ripple filters is taken into account. The collimator can also be included, but without additional scattering. Finally, dose distributions are benchmarked against Monte Carlo simulations, showing 3%/1 mm agreement for simple heterogeneous phantoms. In the case of more complicated phantoms, principal shortcomings of pencil beam algorithms are evident. The influence of these effects on IMPT dose distributions is shown in clinical examples.

Algorithms↗

PubMed2004

A Monte Carlo dose calculation algorithm for proton therapy.

A Monte Carlo (MC) code (VMCpro) for treatment planning in proton beam therapy of cancer is introduced. It is based on ideas of the Voxel Monte Carlo algorithm for photons and electrons and is applicable to human tissue for clinical proton energies. In the present paper the implementation of electromagnetic and nuclear interactions is described. They are modeled by a Class II condensed history algorithm with continuous energy loss, ionization, multiple scattering, range straggling, delta-electron transport, nuclear elastic proton nucleus scattering and inelastic proton nucleus reactions. VMCpro is faster than the general purpose MC codes FLUKA by a factor of 13 and GEANT4 by a factor of 35 for simulations in a phantom with inhomogeneities. For dose calculations in patients the speed improvement is larger, because VMCpro has only a weak dependency on the heterogeneity of the calculation grid. Dose distributions produced with VMCpro are in agreement with GEANT4 results. Integrated or broad beam depth dose curves show maximum deviations not larger than 1% or 0.5 mm in regions with large dose gradients for the examples presented here.

Algorithms↗