PubMed Health⌕ Search

Biomedical subjects

Constantin Kappas

Publications and source records attributed to Constantin Kappas.

2 recordsLinked to original sources

A geometry based optimization algorithm for conformal external beam radiotherapy.

A geometric solution of the problem of optimal orientation of beams in conformal external radiotherapy is presented. The method uses geometric derived quantities which consider the intersection volume between organs at risk (OAR) and the beam shape. In comparison to previous geometric methods a true 3D volume computation is used which takes into account beam divergence, concave shapes, as well as treatment settings such as individual beam shaping by blocks or multi-leaf collimators. For standard dosimetric cost functions used by dose optimization algorithms a corresponding set of geometric objective functions is proposed. We compare the correlations between geometric and dosimetric cost functions for two clinical cases, a prostate and a head tumour case. A correlation is observed for the prostate case, whereas for the head case it is less pronounced due to the larger part of overlapping volumes between the beams which cannot be considered by the used objectives. In comparison to not-optimized beam directions the dose distribution is significantly better for the beam directions found by the optimization of a geometric multi-objective cost function. An optimal dose distribution can easily be achieved using the geometric model. This is shown by comparing for the two cases the dose-volume histograms (DVH) of manually optimized plans by experienced planners and the DVHs of the geometrically found optimal solutions. In comparison to the manually optimized plans the solutions found by the geometric method significantly reduce the average dose in the OARs and NT, while maintaining the same PTV coverage. The optimization requires only a few seconds and could be used to improve the performance of inverse planning algorithms in radiotherapy for the determination of the optimal direction of beams.

Algorithms↗

Prediction of AVM obliteration after stereotactic radiotherapy using radiobiological modelling.

This study was carried out in order to derive the radiobiological parameters of the dose-response relation for the obliteration of arteriovenous malformation (AVM) following single fraction stereotactic radiotherapy. Furthermore, the accuracy by which the linear Poisson model predicts the probability of obliteration and how the haemorrhage history, location and volume of the AVM influence its radiosensitivity are investigated. The study patient material consists of 85 patients who received radiation for AVM therapy. Radiation-induced AVM obliterations were assessed on the basis of post-irradiation angiographies and other radiological findings. For each patient the dose delivered to the clinical target volume and the clinical treatment outcome were available. These data were used in a maximum likelihood analysis to calculate the best estimates of the parameters of the linear Poisson model. The uncertainties of these parameters were also calculated and their individual influence on the dose-response curve was studied. AVM radiosensitivity was assumed to be the same for all the patients. The radiobiological model used was proved suitable for predicting the treatment outcome pattern of the studied patient material. The radiobiological parameters of the model were calculated for different AVM locations, bleeding histories and AVM sizes. The range of parameter variability had considerable effect on the dose-response curve of AVM. The correlation between the dosimetric data and their corresponding clinical effect could be accurately modelled using the linear Poisson model. The derived response parameters can be introduced into the clinical routine with the calculated accuracy assuming the same methodology in target definition and delineation. The known volume dependence of AVM radiosensitivity was confirmed. Moreover, a trend relating AVM location with its radiosensitivity was observed.

Adolescent↗