Biomedical subjects

Constantin Kappas

Publications and source records attributed to Constantin Kappas.

9 recordsLinked to original sources

PubMed2006

Monte Carlo dosimetric evaluation of high energy vs low energy photon beams in low density tissues.

BACKGROUND AND PURPOSE: Low megavoltage photon beams are often the treatment choice in radiotherapy when low density heterogeneities are involved, because higher energies show some undesirable dosimetric effects. This work is aimed at investigating the effects of different energy selection for low density tissues. PATIENTS AND METHODS: BEAMnrc was used to simulate simple treatment set-ups in a simple and a CT reconstructed lung phantom and an air-channel phantom. The dose distribution of 6, 15 and 20 MV photon beams was studied using single, AP/PA and three-field arrangements. RESULTS: Our results showed no significant changes in the penumbra width in lung when a pair of opposed fields were used. The underdosage at the anterior/posterior tumor edge caused by the dose build-up at the lung-tumor interface reached 7% for a 5 x 5 cm AP/PA set-up. Shrinkage of the 90% isodose volume was noticed for the same set-up, which could be rectified by adding a lateral field. For the CT reconstructed phantom, the AP/PA set-up offered better tumor coverage when lower energies were used but for the three field set-up, higher energies resulted to better sparing of the lung tissue. For the air-channel set-up, adding an opposed field reduced the penumbra width. Using higher energies resulted in a 7% cold spot around the air-tissue interface for a 5 x 5 cm field. CONCLUSIONS: The choice of energy for treatment in the low density areas is not a straightforward decision but depends on a number of parameters such as the beam set-up and the dosimetric criteria. Updated calculation algorithms should be used in order to be confident for the choice of energy of treatment.

Algorithms↗

PubMed2006

An inhomogeneity correction algorithm for irregular fields of high-energy photon beams based on Clarkson integration and the 3D beam subtraction method.

A number of treatment-planning systems still use conventional correction methods for body inhomogeneities. Most of these methods (power law method, tissue-air ratio (TAR), etc.) consider only on-axis points, rectangular fields, and inhomogeneous slabs covering the whole irradiating field. A new method is proposed that overcomes the above limitations. The new method uses the principle of the Clarkson method on sector integration to take into account the position and lateral extent of the inhomogeneity with respect to the point of calculation, as well as the shape of the irradiating field. The field is divided into angular sectors, and each sector is then treated separately for the presence of inhomogeneities using a conventional correction method. Applying this method, we can predict the correction factors for Co-60 and 6-MV photon beams for irregular fields that include inhomogeneities of lower or higher densities relative to water. Validation of the predicted corrections factors was made against Monte Carlo calculations for the same geometries. The agreement between the predicted correction factors and the Monte Carlo calculations was within 1.5%. In addition, the new method was able to predict the behavior of the correction factor when the point of calculation was approaching or moving away from the interface between two materials.

Algorithms↗

PubMed2006

Clinical validation of the LKB model and parameter sets for predicting radiation-induced pneumonitis from breast cancer radiotherapy.

The choice of the appropriate model and parameter set in determining the relation between the incidence of radiation pneumonitis and dose distribution in the lung is of great importance, especially in the case of breast radiotherapy where the observed incidence is fairly low. From our previous study based on 150 breast cancer patients, where the fits of dose-volume models to clinical data were estimated (Tsougos et al 2005 Evaluation of dose-response models and parameters predicting radiation induced pneumonitis using clinical data from breast cancer radiotherapy Phys. Med. Biol. 50 3535-54), one could get the impression that the relative seriality is significantly better than the LKB NTCP model. However, the estimation of the different NTCP models was based on their goodness-of-fit on clinical data, using various sets of published parameters from other groups, and this fact may provisionally justify the results. Hence, we sought to investigate further the LKB model, by applying different published parameter sets for the very same group of patients, in order to be able to compare the results. It was shown that, depending on the parameter set applied, the LKB model is able to predict the incidence of radiation pneumonitis with acceptable accuracy, especially when implemented on a sub-group of patients (120) receiving [see text]|EUD higher than 8 Gy. In conclusion, the goodness-of-fit of a certain radiobiological model on a given clinical case is closely related to the selection of the proper scoring criteria and parameter set as well as to the compatibility of the clinical case from which the data were derived.

Abnormalities, Radiation-Induced↗

PubMed2005

Evaluation of dose-response models and parameters predicting radiation induced pneumonitis using clinical data from breast cancer radiotherapy.

The purpose of this work is to evaluate the predictive strength of the relative seriality, parallel and LKB normal tissue complication probability (NTCP) models regarding the incidence of radiation pneumonitis, in a large group of patients following breast cancer radiotherapy, and furthermore, to illustrate statistical methods for examining whether certain published radiobiological parameters are compatible with a clinical treatment methodology and patient group characteristics. The study is based on 150 consecutive patients who received radiation therapy for breast cancer. For each patient, the 3D dose distribution delivered to lung and the clinical treatment outcome were available. Clinical symptoms and radiological findings, along with a patient questionnaire, were used to assess the manifestation of radiation-induced complications. Using this material, different methods of estimating the likelihood of radiation effects were evaluated. This was attempted by analysing patient data based on their full dose distributions and associating the calculated complication rates with the clinical follow-up records. Additionally, the need for an update of the criteria that are being used in the current clinical practice was also examined. The patient material was selected without any conscious bias regarding the radiotherapy treatment technique used. The treatment data of each patient were applied to the relative seriality, LKB and parallel NTCP models, using published parameter sets. Of the 150 patients, 15 experienced radiation-induced pneumonitis (grade 2) according to the radiation pneumonitis scoring criteria used. Of the NTCP models examined, the relative seriality model was able to predict the incidence of radiation pneumonitis with acceptable accuracy, although radiation pneumonitis was developed by only a few patients. In the case of modern breast radiotherapy, radiobiological modelling appears to be very sensitive to model and parameter selection giving clinically acceptable results in certain cases selectively (relative seriality model with Seppenwoolde et al and Gagliardi et al parameter sets). The use of published parameters should be considered as safe only after their examination using local clinical data. The variation of inter-patient radiosensitivity seems to play a significant role in the prediction of such low incidence rate complications. Scoring grades were combined to give stronger evidence of radiation pneumonitis since their differences could not be strictly associated with dose. This obviously reveals a weakness of the scoring related to this endpoint, and implies that the probability of radiation pneumonitis induction may be too low to be statistically analysed with high accuracy, at least with the latest advances of dose delivery in breast radiotherapy.

Adult↗

PubMed2005

Dose-response relations for anal sphincter regarding fecal leakage and blood or phlegm in stools after radiotherapy for prostate cancer. Radiobiological study of 65 consecutive patients.

BACKGROUND: The estimation of the parameters that describe the dose-response relations of anal sphincter regarding the clinical endpoints of fecal leakage and blood or phlegm in stools is important in the optimization of prostate cancer radiotherapy. Also, the validity of the relative seriality model for this clinical case needs to be examined by associating the clinical follow-up results with the predicted complication rates. PATIENTS AND METHODS: In this study, 65 patients who received radiation therapy for clinically localized prostate adenocarcinoma are analyzed. The clinical treatment outcome and the three-dimensional dose distribution delivered to anal sphincter were available for each patient. A questionnaire was used for assessing the clinical bowel and urinary symptoms. A maximum likelihood fitting was performed to calculate the best estimates of the parameters used by the relative seriality model. The clinical utilization of the calculated parameters in predicting anal sphincter complication probabilities was illustrated by applying the best estimate of the parameters to a subset of the patient population. RESULTS: The estimated values of the parameters for the two clinical endpoints are D (50) = 70.2 Gy, gamma = 1.22, s = 0.35 for fecal leakage and D (50) = 74.0 Gy, gamma = 0.75, s approximately 0 for blood or phlegm in stools. The standard deviations of the parameters were also calculated together with the confidence intervals of the dose-response curves. The analysis proved that the treatment outcome pattern of the patient material can suitably be reproduced by the relative seriality model (probability of finding a worse fit = 60.2%, the area under the receiver operating characteristic curve = 0.72 and 0.69 and chi(2)-test = 0.97 and 0.86, respectively). CONCLUSION: Fecal leakage is characterized by a medium relative seriality whereas blood or phlegm in stools was found to have strong volume dependence (low relative seriality). Diminishing the biologically effective uniform dose to anal sphincter < 40-45 Gy may significantly reduce the risk of fecal leakage or blood or phlegm in stools for patients irradiated for prostate cancer.

Aged↗

PubMed2004

Statistical methods for clinical verification of dose-response parameters related to esophageal stricture and AVM obliteration from radiotherapy.

The purpose of this work is to provide some statistical methods for evaluating the predictive strength of radiobiological models and the validity of dose-response parameters for tumour control and normal tissue complications. This is accomplished by associating the expected complication rates, which are calculated using different models, with the clinical follow-up records. These methods are applied to 77 patients who received radiation treatment for head and neck cancer and 85 patients who were treated for arteriovenous malformation (AVM). The three-dimensional dose distribution delivered to esophagus and AVM nidus and the clinical follow-up results were available for each patient. Dose-response parameters derived by a maximum likelihood fitting were used as a reference to evaluate their compatibility with the examined treatment methodologies. The impact of the parameter uncertainties on the dose-response curves is demonstrated. The clinical utilization of the radiobiological parameters is illustrated. The radiobiological models (relative seriality and linear Poisson) and the reference parameters are validated to prove their suitability in reproducing the treatment outcome pattern of the patient material studied (through the probability of finding a worse fit, area under the ROC curve and chi2 test). The analysis was carried out for the upper 5 cm of the esophagus (proximal esophagus) where all the strictures are formed, and the total volume of AVM. The estimated confidence intervals of the dose-response curves appear to have a significant supporting role on their clinical implementation and use.

Angiography↗

PubMed2004

Analysis of the penumbra enlargement in lung versus the quality index of photon beams: a methodology to check the dose calculation algorithm.

It is well known that considerable underdosage can occur at the edges of a tumor inside the lung because of the degradation of penumbra due to lack of lateral electronic equilibrium. Although present even at smaller energies, this phenomenon is more pronounced for higher energies. Apart from Monte Carlo calculation, most of the existing Treatment Planning Systems (TPSs) cannot deal at all, or with acceptable accuracy, with this effect. A methodology has been developed for assessing the dose calculation algorithms in the lung region where lateral electronic disequilibrium exists, based on the Quality Index (QI) of the incident beam. A phantom, consisting of layers of polystyrene and lung material, has been irradiated using photon beams of 4, 6, 15, and 20 MV. The cross-plane profiles of each beam for 5x5, 10x10, and 25x10 fields have been measured at the middle of the phantom with the use of films. The penumbra (20%-80%) and fringe (50%-90%) enlargement was measured and the ratio of the widths for the lung to that of polystyrene was defined as the Correction Factor (CF). Monte Carlo calculations in the two phantoms have also been performed for energies of 6, 15, and 20 MV. Five commercial TPS's algorithms were tested for their ability to predict the penumbra and fringe enlargement. A linear relationship has been found between the QI of the beams and the CF of the penumbra and fringe enlargement for all the examined fields. Monte Carlo calculations agree very well (less than 1% difference) with the film measurements. The CF values range between 1.1 for 4 MV (QI 0.620) and 2.28 for 20 MV (QI 0.794). Three of the tested TPS's algorithms could not predict any enlargement at all for all energies and all fields and two of them could predict the penumbra enlargement to some extent. The proposed methodology can help any user or developer to check the accuracy of its algorithm for lung cases, based on a simple phantom geometry and the QI of the incident beam. This check is very important especially when higher energies are used, as the inaccuracies in existing algorithms can lead to an incorrect choice of energy for lung treatment and consequently to a failure in tumor control.

Algorithms↗

PubMed2003

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↗

PubMed2002

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↗