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PurposeRecent studies have suggested significant variations in radiotherapy schedules used to treat advanced non-small-cell lung cancer (NSCLC), both between different centers in one country as well as between countries. In this study, different treatment methodologies have been explored using management plans proposed by radiation oncologists regarding general questions and theoretical case histories for patients with advanced NSCLC.Materials and methodsThe survey was conducted by sending a questionnaire to 24 radiotherapy centers in Europe. The questionnaire was composed of two sections. The first section concerned reasons for giving radiotherapy, parameters that influence the choice of total dose and fractionation for radiotherapy and kind of equipment used. The second section concerned the management of five theoretical patients (A–E) regarding the selection of the radiotherapy technique and the aim of treatment (radical or palliative). Furthermore, 19 trials comparing different regimens of palliative radiotherapy in patients with NSCLC were reviewed. There were marked differences in the doses of the investigated radiotherapy schemes, the patient characteristics and the assessed outcome measures.Results70% of the responders answered that the most important factors for deciding what dose and fractionation scheme to use were: metastases, performance status (PS) of the patient, lung function and size of the primary tumour. The most common reasons for giving the treatment were symptom relief, prolongation of life and, in some cases, possibly cure. More than 95% of the responders stated that they would give radiotherapy in each of these cases. The total doses proposed where 20 Gy in five fractions or 30 Gy in ten fractions in 2 weeks for the cases A and D. If the previous two schemes were converted to a fractionation scheme delivering 2 Gy per fraction, the equivalent doses would be 23 and 33 Gy, respectively. For the cases B, C and E, the proposed fractionation schemes were 2 Gy daily to 60–68 Gy in 6 weeks or 2 Gy daily to 68 Gy in 7 weeks. For the case E, 20% of the responders suggested Stereotactic Body Radiotherapy (SBRT) giving 21 Gy three times a week with a day apart to 63 Gy. The total dose and number of fractions of radiotherapy are related to the perceived aims and expectations of treatment. Those aiming at extending life would give significantly higher total doses in a larger number of fractions, whereas those aiming at relieving symptoms would give significantly lower total doses. There is evidence for an increase in survival, in patients who are given higher radiotherapy doses, especially in those patients with better PS.ConclusionsThis survey demonstrates a range of treatment strategies for advanced and inoperable NSCLC within Europe. There are a number of factors that influence the perceived aims of treatment and treatment planning. These factors should be taken into account when evaluating the effectiveness of different irradiation techniques, especially in the determination of radiobiological parameters and dose–response relations. The majority of patients should be treated with short courses of palliative radiotherapy, of one or two fractions. The use of high-dose palliative regimens using many fractions or SBRT should be considered for selected patients with good PS.

For many years the linear-quadratic (LQ) model has been widely used to describe the effects of total dose and dose per fraction at low-to-intermediate doses in conventional fractionated radiotherapy. Recent advances in stereotactic radiosurgery (SRS) and stereotactic radiotherapy (SRT) have increased the interest in finding a reliable cell survival model, which will be accurate at high doses, as well. Different models have been proposed for improving descriptions of high dose survival responses, such as the Universal Survival Curve (USC), the Kavanagh-Newman (KN) and several generalizations of the LQ model, e.g. the Linear-Quadratic-Linear (LQL) model and the Padé Linear Quadratic (PLQ) model. The purpose of the present study is to compare a number of models in order to find the best option(s) which could successfully be used as a fractionation correction method in SRT. In this work, six independent experimental data sets were used: CHOAA8 (Chinese hamster fibroblast), H460 (non-small cell lung cancer, NSLC), NCI-H841 (small cell lung cancer, SCLC), CP3 and DU145 (human prostate carcinoma cell lines) and U1690 (SCLC). By detailed comparisons with these measurements, the performance of nine different radiobiological models was examined for the entire dose range, including high doses beyond the shoulder of the survival curves. Using the computed and measured cell surviving fractions, comparison of the goodness-of-fit for all the models was performed by means of the reduced χ2-test with a 95% confidence interval. The obtained results indicate that models with dose-independent final slopes and extrapolation numbers generally represent better choices for SRT. This is especially important at high doses where the final slope and extrapolation numbers are presently found to play a major role. The PLQ, USC and LQL models have the least number of shortcomings at all doses. The extrapolation numbers and final slopes of these models do not depend on dose. Their asymptotes for the cell surviving fractions are exponentials at low as well as high doses, and this is in agreement with the behaviour of the corresponding experimental data. This is an important improvement over the LQ model which predicts a Gaussian at high doses. Overall and for the highlighted reasons, it was concluded that the PLQ, USC and LQL models are theoretically well-founded. They could prove useful compared to the other proposed radiobiological models in clinical applications for obtaining uniformly accurate cell surviving fractions encountered in stereotactic high-dose radiotherapy as well as at medium and low doses.

In breast cancer radiotherapy, significant discrepancies in dose delivery can contribute to underdosage of the tumor or overdosage of normal tissue, which is potentially related to a reduction of local tumor control and an increase of side effects. To study the impact of these factors in breast cancer radiotherapy, a meta analysis of the clinical data reported by Mavroidis et al. (2002) in Acta Oncol (41:471–85), showing the patient setup and breathing uncertainties characterizing three different irradiation techniques, were employed. The uncertainties in dose delivery are simulated based on fifteen breast cancer patients (5 mastectomized, 5 resected with negative node involvement (R-) and 5 resected with positive node involvement (R+)), who were treated by three different irradiation techniques, respectively. The positioning and breathing effects were taken into consideration in the determination of the real dose distributions delivered to the CTV and lung in each patient. The combined frequency distributions of the positioning and breathing distributions were obtained by convolution. For each patient the effectiveness of the dose distribution applied is calculated by the Poisson and relative seriality models and a set of parameters that describe the dose-response relations of the target and lung. The three representative radiation techniques are compared based on radiobiological measures by using the complication-free tumor control probability, P+ and the biologically effective uniform dose, D̿ concepts. For the Mastectomy case, the average P+ values of the planned and delivered dose distributions are 93.8% for a D̿CTV of 51.8 Gy and 85.0% for a D̿CTV of 50.3 Gy, respectively. The respective total control probabilities, PB values are 94.8% and 92.5%, whereas the corresponding total complication probabilities, PI values are 0.9% and 7.4%. For the R- case, the average P+ values are 89.4% for a D̿CTV of 48.9 Gy and 88.6% for a D̿CTV of 49.0 Gy, respectively. The respective PB values are 89.8% and 89.9%, whereas the corresponding PI values are 0.4% and 1.2%. For the R+ case, the average P+ values are 86.1% for a D̿CTV of 49.2 Gy and 85.5% for a D̿CTV of 49.1 Gy, respectively. The respective PB values are 90.2% and 90.1%, whereas the corresponding PI values are 4.1% and 4.6%. The combined effects of positioning uncertainties and breathing can introduce a significant deviation between the planned and delivered dose distributions in lung in breast cancer radiotherapy. The positioning and breathing uncertainties do not affect much the dose distribution to the CTV. The simulated delivered dose distributions show larger lung complication probabilities than the treatment plans. This means that in clinical practice the true expected complications are underestimated. Radiation pneumonitis of Grade 1–2 is more frequent and any radiotherapy optimization should use this as a more clinically relevant endpoint.

The aim of this study was to investigate what bowel organ and delivered dose levels are most relevant for the development of 'emptying of all stools into clothing without forewarning' so that the related dose-responses could be derived as an aid in avoiding this distressing symptom in the future.Of the 77 gynecological cancer survivors treated with radiotherapy (RT) for gynecological cancer, 13 developed the symptom. The survivors were treated between 1991 and 2003. The anal-sphincter region, the rectum, the sigmoid and the small intestines were all delineated and the dose-volume histograms were exported for each patient. The dose-volume parameters were estimated fitting the data to the Relative Seriality (RS), the Lyman and the generalized Equivalent Uniform Dose (gEUD) model.The dose-response parameters for all three models and four organs at risk (OARs) were estimated. The data from the sigmoid fits the studied models best: D50 was 58.8 and 59.5 Gy (RS, Lyman), γ50 was 1.60 and 1.57 (RS, Lyman), s was 0.32, n was 0.13 and a was 7.7 (RS, Lyman, gEUD). The estimated volume parameters indicate that the investigated OARs behave serially for this endpoint. Our results for the three models studied indicate that they have the same predictive power (similar LL values) for the symptom as a function of the dose for all investigated OARs.In our study, the anal-sphincter region and sigmoid fit our data best, but all OARs were found to have steep dose-responses for 'emptying of all stools into clothing without forewarning' and thus, the outcome can be predicted with an NTCP model. In addition, the dose to the four studied OARs may be considered when minimizing the risk of the symptom.

Theoretical modelling of tumour control probability (TCP) with respect to non-uniformity in the dose to the tumour, alternate fractionation schemes and tumour kinetics is a very useful tool for assessment of the influence of changes in dosimetric or radiobiological factors on the outcome of the treatment. Various attempts have been made to also include effects from non-uniform dose to the tumour volume, but the problem has not been fully solved and many factors were totally neglected or not accurately taken into account. This paper presents derivations of analytical expressions of TCP for macroscopic inter-cell dose variations and for random inter-fractional variations in average tumour dose, based on binomial statistics for the TCP and the well-known linear quadratic model for the cell survival. Numerical calculations have been performed to validate the analytical expressions. An analysis of the influence of the deterministic and stochastic heterogeneity in dose delivery on the TCP was performed. The precision requirements in dose delivery are discussed briefly with the support of the presented results. The main finding of this paper is that it is primarily the shape of the cell survival curve that governs how the response is affected by macroscopic dose variations. The analytical expressions for TCP accounting for heterogeneity in dose can quite well describe the TCP for varying dose from cell to cell and random dose in each fraction. An increased TCP is seen when a large number of fractions are used and the variations in dose to the cells are rather high for tissues with low α/β.

To outline the limitations of PENELOPE (acronym of PENetration and Energy LOss of Positrons and Electrons) as a track-structure code, and to comment on modifications that enable its fruitful use in certain microdosimetry and nanodosimetry applications.Attention is paid to the way in which inelastic collisions of electrons are modelled and to the ensuing implications for microdosimetry analysis.Inelastic mean free paths and collision stopping powers calculated with PENELOPE and two well-known optical-data models are compared. An ad hoc modification of PENELOPE is summarized where ionization and excitation of liquid water by electron impact is simulated using tables of realistic differential and total cross sections.PENELOPE can be employed advantageously in some track-structure applications provided that the default model for inelastic interactions of electrons is replaced by suitable tables of differential and total cross sections.

Seven different radiobiological dose-response models have been compared with regard to their ability to describe experimental data. The first four models, namely the critical volume, the relative seriality, the inverse tumor and the critical element models are mainly based on cell survival biology. The other three models: the Lyman (Gaussian distribution), the parallel architecture and the Weibull distribution models are semi-empirical and rather based on statistical distributions. The maximum likelihood estimation was used to fit the models to experimental data and the χ2-distribution, AIC criterion and F-test were applied to compare the goodness-of-fit of the models. The comparison was performed using experimental data for rat spinal cord injury. Both the shape of the dose-response curve and the ability of handling the volume dependence were separately compared for each model. All the models were found to be acceptable in describing the present experimental dataset (p > 0.05). For the white matter necrosis dataset, the Weibull and Lyman models were clearly superior to the other models, whereas for the vascular damage case, the Relative Seriality model seems to have the best performance although the Critical volume, Inverse tumor, Critical element and Parallel architecture models gave similar results. Although the differences between many of the investigated models are rather small, they still may be of importance in indicating the advantages and limitations of each particular model. It appears that most of the models have favorable properties for describing dose-response data, which indicates that they may be suitable to be used in biologically optimized intensity modulated radiation therapy planning, provided a proper estimation of their radiobiological parameters had been performed for every tissue and clinical endpoint.

A Monte Carlo code for the event-by-event simulation of electron transport in liquid water is presented. The code, written in C++, can accommodate different interaction models. Currently it implements cross sections for ionizing collisions calculated with the model developed by Dingfelder et al (1998 Radiat. Phys. Chem. 53 1-18, 2008 Radiat. Res. 169 584-94) and cross sections for elastic scattering computed within the static-exchange approximation (Salvat et al 2005 Comput. Phys. Commun. 165 157-90). The latter cross sections coincide with those recommended in ICRU Report 77 (2007). Other included interaction mechanisms are excitation by electron impact and dissociative attachment. The main characteristics of the code are summarized. Various track penetration parameters, including the detour factor, are defined as useful tools to quantify the geometrical extent of electron tracks in liquid water. Results obtained with the present microdosimetry code are given in the form of probability density functions for initial electron kinetic energies ranging from 0.1 to 10 keV. The sensitivity of the simulated distributions to the choice of alternative physics models has been briefly explored. The discrepancies with equivalent simulations reported by Wilson et al (2004 Radiat. Res. 161 591-6) stem from the adopted cross sections for elastic scattering, which determine largely the spatial evolution of low-energy electron tracks.

Objectives: The aim of this study was to compare three-dimensional (3D) conformal radiotherapy and the two different forms of IMRT in lung cancer radiotherapy. Methods: Cases of four lung cancer patients were investigated by developing a 3D conformal treatment plan, a linac MLC-based step-and-shoot IMRT plan and an HT plan for each case. With the use of the complication-free tumour control probability (P+) index and the uniform dose concept as the common prescription point of the plans, the different treatment plans were compared based on radiobiological measures. Results: The applied plan evaluation method shows the MLC-based IMRT and the HT treatment plans are almost equivalent over the clinically useful dose prescription range; however, the 3D conformal plan inferior. At the optimal dose levels, the 3D conformal treatment plans give an average P+ of 48.1% for a effective uniform dose to the internal target volume (ITV) of 62.4 Gy, whereas the corresponding MLC-based IMRT treatment plans are more effective by an average DP+ of 27.0% for a D effective uniform dose of 16.3 Gy. Similarly, the HT treatment plans are more effective than the 3D-conformal plans by an average DP+ of 23.8% for a D effective uniform dose of 11.6 Gy. Conclusion: A radiobiological treatment plan evaluation can provide a closer association of the delivered treatment with the clinical outcome by taking into account the dose–response relations of the irradiated tumours and normal tissues. The use of P – effective uniform dose diagrams can complement the traditional tools of evaluation to compare and effectively evaluate different treatment plans.

Determination of the dose-response relations for oesophageal stricture after radiotherapy of the head and neck.In this study 33 patients who developed oesophageal stricture and 39 patients as controls are included. The patients received radiation therapy for head and neck cancer at Karolinska University Hospital, Stockholm, Sweden. For each patient the 3D dose distribution delivered to the upper 5 cm of the oesophagus was analysed. The analysis was conducted for two periods, 1992-2000 and 2001-2005, due to the different irradiation techniques used. The fitting has been done using the relative seriality model.For the treatment period 1992-2005, the mean doses were 49.8 and 33.4 Gy, respectively, for the cases and the controls. For the period 1992-2000, the mean doses for the cases and the controls were 49.9 and 45.9 Gy and for the period 2001-2005 were 49.8 and 21.4 Gy. For the period 2001-2005 the best estimates of the dose-response parameters are D(50)=61.5 Gy (52.9-84.9 Gy), γ=1.4 (0.8-2.6) and s=0.1 (0.01-0.3).Radiation-induced strictures were found to have a dose response relation and volume dependence (low relative seriality) for the treatment period 2001-2005. However, no dose response relation was found for the complete material.

Radiation treatment of arteriovenous malformations (AVMs) has a slow and progressive vaso-occlusive effect. Some studies suggested the possible role of vascular structure in this process. A detailed biomathematical model has been used, where the morphological, biophysical and hemodynamic characteristics of intracranial AVM vessels are faithfully reproduced. The effect of radiation on plexiform and fistulous AVM nidus vessels was simulated using this theoretical model. The similarities between vascular and electrical networks were used to construct this biomathematical AVM model and provide an accurate rendering of transnidal and intranidal hemodynamics. The response of different vessels to radiation and their obliteration probability as a function of different angiostructures were simulated and total obliteration was defined as the probability of obliteration of all possible vascular pathways. The dose response of the whole AVM is observed to depend on the vascular structure of the intra-nidus AVM. Furthermore, a plexiform AVM appears to be more prone to obliteration compared with an AVM of the same size but having more arteriovenous fistulas. Finally, a binomial model was introduced, which considers the number of crucial vessels and is able to predict the dose response behavior of AVMs with a complex vascular structure.

During the last 20 years, the field of cellular and not least molecular radiation biology has been developed substantially and can today describe the response of heterogeneous tumors and organized normal tissues to radiation therapy quite well. An increased understanding of the sub-cellular and molecular response is leading to a more general systems biological approach to radiation therapy and treatment optimization. It is interesting that most of the characteristics of the tissue infrastructure, such as the vascular system and the degree of hypoxia, have to be considered to get an accurate description of tumor and normal tissue responses to ionizing radiation. In the limited space available, only a brief description of some of the most important concepts and processes is possible, starting from the key functional genomics pathways of the cell that are not only responsible for tumor development but also responsible for the response of the cells to radiation therapy. The key mechanisms for cellular damage and damage repair are described. It is further more discussed how these processes can be brought to inactivate the tumor without severely damaging surrounding normal tissues using suitable radiation modalities like intensity-modulated radiation therapy (IMRT) or light ions. The use of such methods may lead to a truly scientific approach to radiation therapy optimization, particularly when invivo predictive assays of radiation responsiveness becomes clinically available at a larger scale. Brief examples of the efficiency of IMRT are also given showing how sensitive normal tissues can be spared at the same time as highly curative doses are delivered to a tumor that is often radiation resistant and located near organs at risk. This new approach maximizes the probability to eradicate the tumor, while at the same time, adverse reactions in sensitive normal tissues are as far as possible minimized using IMRT with photons and light ions.

The investigation of the clinical efficacy and effectiveness of Intensity Modulated Radiotherapy (IMRT) using Multileaf Collimators (MLC) and Helical Tomotherapy (HT) has been an issue of increasing interest over the past few years. In order to assess the suitability of a treatment plan, dosimetric criteria such as dose-volume histograms (DVH), maximum, minimum, mean, and standard deviation of the dose distribution are typically used. Nevertheless, the radiobiological parameters of the different tumors and normal tissues are often not taken into account. The use of the biologically effective uniform dose (D̿) together with the complication-free tumor control probability ( P+) were applied to evaluate the two radiation modalities. Two different clinical cases of brain and cranio-spinal axis cancers have been investigated by developing a linac MLC-based step-and-shoot IMRT plan and a Helical Tomotherapy plan. The treatment plans of the MLC-based IMRT were developed on the Philips treatment planning station using the Pinnacle 7.6 software release while the dedicated Tomotherapy treatment planning station was used for the HT plan. With the use of the P+ index and the D̿ concept as the common prescription point, the different treatment plans were compared based on radiobiological measures. The tissue response probabilities were plotted against D̿ for a range of prescription doses. The applied plan evaluation method shows that in the brain cancer, the HT treatment gives slightly better results than the MLC-based IMRT in terms of optimum expected clinical outcome ( P+ of 66.1% and 63.5% for a D̿ to the PTV of 63.0 Gy and 62.0 Gy, respectively). In the cranio-spinal axis cancer, the HT plan is significantly better compared to the MLC-based IMRT plan over the clinically useful dose prescription range ( P+ of 84.1% and 28.3% for a D̿ to the PTV of 50.6 Gy and 44.0 Gy, respectively). If a higher than 5% risk for complications could be allowed, the complication-free tumor control could be increased by almost 30% compared to the initial dose prescription. In comparison to MLC based-IMRT, HT can better encompass the often large PTV while minimizing the volume of the OARs receiving high dose. A radiobiological treatment plan evaluation can provide a closer association of the delivered treatment with the clinical outcome by taking into account the dose-response relations of the irradiated tumors and normal tissues. The use of P — D̿ diagrams can complement the traditional tools of evaluation such as DVHs, in order to compare and effectively evaluate different treatment plans.

In IMRT treatment plan optimization there are various methods that try to regularize the variation of dose nonuniformity using purely dosimetric measures. However, although these methods can help in finding a good dose distribution, they do not provide any information regarding the expected treatment outcome. When a treatment plan optimization is performed using biological measures, the final goal should be some indication about the expected tumor control or normal tissue complications, which is the primary goal of treatment planning (the association of treatment configurations and dose prescription with the treatment outcome). In this study, this issue is analyzed distinguishing the dose-oriented treatment plan optimization from the response-oriented optimization. Three different dose distributions were obtained by using a dose-based optimization technique, an EUD-based optimization without applying any technique for regularizing the nonuniformity of the dose distribution, and an EUD-based optimization using a variational regularization technique, which controls dose nonuniformity. The clinical effectiveness of the three dose distributions was investigated by calculating the response probabilities of the tumors and organs-at-risk (OARs) involved in two head and neck and prostate cancer cases. The radiobiological models used are the linear-quadratic-Poisson and the Relative Seriality models. Furthermore, the complication-free tumor control probability and the biologically effective uniform dose (D) were used for treatment plan evaluation and comparison. The radiobiological comparison shows that the EUD-based optimization using L-curve regularization gives better results than the EUD-based optimization without regularization and dose-based optimization in both clinical cases. Concluding, it appears that the applied dose nonuniformity regularization technique is expected to improve the effectiveness of the optimized IMRT dose distributions. However, more patient cases are needed to validate the statistical significance of the results and conclusions presented in this paper.

The full potential of biologically optimized radiation therapy can only be maximized with the prediction of individual patient radiosensitivity prior to treatment. Unfortunately, the available biological parameters, derived from clinical trials, reflect an average radiosensitivity of the examined populations. In the present study, a breast cancer patient of stage I-II with positive lymph nodes was chosen in order to analyse the effect of the variation of individual radiosensitivity on the optimal dose distribution. Thus, deviations from the average biological parameters, describing tumour, heart and lung response, were introduced covering the range of patient radiosensitivity reported in the literature. Two treatment configurations of three and seven biologically optimized intensity-modulated beams were employed. The different dose distributions were analysed using biological and physical parameters such as the complication-free tumour control probability (P(+)), the biologically effective uniform dose (D), dose volume histograms, mean doses, standard deviations, maximum and minimum doses. In the three-beam plan, the difference in P(+) between the optimal dose distribution (when the individual patient radiosensitivity is known) and the reference dose distribution, which is optimal for the average patient biology, ranges up to 13.9% when varying the radiosensitivity of the target volume, up to 0.9% when varying the radiosensitivity of the heart and up to 1.3% when varying the radiosensitivity of the lung. Similarly, in the seven-beam plan, the differences in P(+) are up to 13.1% for the target, up to 1.6% for the heart and up to 0.9% for the left lung. When the radiosensitivity of the most important tissues in breast cancer radiation therapy was simultaneously changed, the maximum gain in outcome was as high as 7.7%. The impact of the dose-response uncertainties on the treatment outcome was clinically insignificant for the majority of the simulated patients. However, the jump from generalized to individualized radiation therapy may significantly increase the therapeutic window for patients with extreme radio sensitivity or radioresistance, provided that these are identified. Even for radiosensitive patients a simple treatment technique is sufficient to maximize the outcome, since no significant benefits were obtained with a more complex technique using seven intensity-modulated beams portals.

Haptic technology enables us to incorporate the sense of touch into computer applications, providing an additional input/ output channel. The purpose of this study was to examine if haptic feedback can help physicians and other practitioners to interact with medical imaging and treatment planning systems. A haptic application for outlining target areas (a key task in radiation therapy treatment planning) was implemented and then evaluated via a controlled experiment with ten subjects. Even though the sample size was small, and the application only a prototype, results showed that haptic feedback can significantly increase (p0.05) the speed of outlining target volumes and organs at risk. No significant differences were found regarding precision or perceived usability. This promising result warrants further development of a full haptic application for this task. Improvements to the usability of the application as well as to the forces generated have been implemented and an experiment with more subjects is planned.

This work aims to evaluate the predictive strength of the relative seriality, parallel and Lyman-Kutcher-Burman (LKB) normal tissue complication probability (NTCP) models regarding the incidence of radiation pneumonitis (RP), in a group of patients following lung cancer radiotherapy and also to examine their correlation with pulmonary function tests (PFTs). The study was based on 47 patients who received radiation therapy for stage III non-small-cell lung cancer. For each patient, lung dose volume histograms (DVHs) and the clinical treatment outcome were available. Clinical symptoms, radiological findings and pulmonary function tests incorporated in a post-treatment follow-up period of 18 months were used to assess the manifestation of radiation induced complications. Thirteen of the 47 patients were scored as having radiation induced pneumonitis, with RTOG criteria grade 3 and 28 of the 47 with RTOG criteria grade 2. Using this material, different methods of estimating the likelihood of radiation effects were evaluated, by analysing patient data based on their full dose distributions and associating the calculated complication rates with the clinical follow-up records. Lungs were evaluated as a paired organ as well as individual lungs. Of the NTCP models examined in the overall group considering the dose distribution in the ipsilateral lung, all models were able to predict radiation induced pneumonitis only in the case of grade 2 radiation pneumonitis score, with the LKB model giving the best results (chi2-test: probability of agreement between the observed and predicted results Pchi(chi2)=0.524 using the 0.05 significance level). The NTCP modelling considering lungs as a paired organ did not give statistically acceptable results. In the case of lung cancer radiotherapy, the application of different published radiobiological parameters alters the NTCP results, but not excessively as in the case of breast cancer radiotherapy. In this relatively small group of lung cancer patients, no positive statistical correlation could be established between the incidence of radiation pneumonitis as estimated by NTCP models and the pulmonary function test evaluation. However, the use of PFTs as markers or predictors for the incidence or severity of radiation induced pneumonitis must be investigated further.

Background and purpose To investigate the dose-response relation between the dose to the vagina and the patient-reported symptom ‘absence of vaginal elasticity’ and how time to follow-up influences this relation. Materials and methods The study included 78 long-term gynecological cancer survivors treated between 1991 and 2003 with external beam radiation therapy. Of those, 24 experienced absence of vaginal elasticity. A normal tissue complication model is introduced that takes into account the influence of time to follow-up on the dose-response relation and the patient’s age. The best estimates of the dose-response parameters were calculated using Probit, Probit-Relative Seriality (RS) and Probit-time models. Log likelihood (LL) values and the Akaike Information Criterion (AIC) were used to evaluate the model fit. Results The dose-response parameters for ‘absence of vaginal elasticity’ according to the Probit and Probit-time models with the 68% Confidence Intervals (CI) were: LL=−39.8, D50 = 49.7 (47.2–52.4) Gy, γ 50 = 1.40 (1.12–1.70) and LL = −37.4, D50 = 46.9 (43.5–50.9) Gy, γ 50 = 1.81(1.17–2.51) respectively. Conclusions The proposed model, which describes the influence of time to follow-up on the dose-response relation, fits our data best. Our data indicate that the steepness of the dose-response curve of the dose to the vagina and the symptom ‘absence of vaginal elasticity’ increases with time to follow-up, while D50decreases. • Alevronta E, Avall-Lundqvist E, Al-Abany M, et al. Time-dependent dose-response relation for absence of vaginal elasticity after gynecological radiation therapy. Radiother Oncol 2016. http://dx.doi.org/10.1016/j.radonc.2016.02.013 .

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.

Comprehensive atlases of lymph node topography are necessary tools to provide a detailed description of the lymphatic distribution in relation to other organs and structures. Despite the recent developments of atlases and guidelines focusing on definitions of lymphatic regions, a comprehensive and detailed description of the three-dimensional (3D) nodal distribution is lacking. This article describes a new 3D atlas of lymph node topography based on the digital images of the Visible Human Male Anatomical (VHMA) data set. About 1,200 lymph nodes were localized in the data set and their distribution was compared with data from current cross-sectional lymphatic atlases. The identified nodes were delineated and then labeled with different colors that corresponded to their anatomical locations. A series of 2D illustrations, showing discrete locations, description, and distribution of major lymph nodes, was compiled to form a cross-sectional atlas. The resultant contours of all localized nodes in the VHMA data set were superimposed to develop a volumetric model. A 3D reconstruction was generated for the lymph nodes and surrounding structures. The volumetric lymph node topography was also integrated into the existing VOXEL-MAN digital atlas to obtain an interactive and photo-realistic visualization of the lymph nodes showing their proximity to blood vessels and surrounding organs. The lymph node topography forms part of our whole body atlas database, which includes organs, definitions, and parameters that are related to radiation therapy. The lymph node topography atlas could be utilized for visualization and exploration of the 3D lymphatic distribution to assist in defining the target volume for treatment based on the lymphatic spread surrounding the primary tumor.

The purpose of this study was to investigate the optimal coplanar beam directions when treating an early breast cancer with locoregional lymphatic spread with a few radiobiologically optimized intensity modulated beams. Also to determine the increase in the probability of complication-free cure with the number of beam portals and the smallest number required to perform a close to optimal treatment for this tumour site. Four test patients with stage II left-sided breast cancer were studied with heart, lung and contralateral breast as principal organs at risk. The clinical target volume consisted of the breast tissue remaining after surgery, the axillary, the internal mammary as well as the supraclavicular lymph nodes. Through an exhaustive search of all possible beam directions the most effective coplanar beams with one to four intensity modulated photon beam portals were investigated. Comparisons with uniform beam treatment techniques and up to 12 intensity modulated beams were also made. The different plans were optimized using the probability of complication-free tumour cure, P(+), as biological objective function. When using two intensity modulated beam directions three major sets of suitable directions were identified denoted by A, P and T. A corresponds to an anterior oblique pair of beams around 25 degrees and 325 degrees , P is a perpendicular lateral pair at around 50 degrees and 130 degrees whereas T is a more conventional tangential pair at around 155 degrees and 300 degrees . Interestingly, these configurations identify simply three major effective beam directions namely at 30 degrees +/-20 degrees , 145 degrees +/-20 degrees and 310 degrees +/-15 degrees . For the three intensity modulated beam technique a combination of these three effective beam directions generally covered the global maximum of the probability of complication-free tumour control. The improvement in complication-free cure probability with two optimally selected intensity modulated beams is around 10% when compared to a uniform beam technique with three to four beam portals. This increase is mainly due to a reduction by almost 1% in the probability of injury to the heart and an increase of 6% in the probability of local tumour control. When three or four biologically optimized beam portals are used a further increase in the probability of complication-free cure of about 6% can often be obtained. This improvement is caused by a small decrease in the probability of injury to the heart, left lung and other surrounding normal tissue, as well as a slight further increase in the probability of tumour control. The increase in the treatment outcome is minimal when more than four intensity modulated beams are employed. A small increase in dose homogeneity in the target volume and a slight decrease in the normal tissue volume receiving high dose may be seen, but without appreciably improving the complication-free cure probability. For a stage II breast cancer, three and in more complex cases four optimally oriented beams are sufficient to reach close to the maximum probability of complication-free tumour control when biologically optimized intensity modulated dose delivery is used. Angle of incidence optimization may then be advantageous starting from the given most effective three beam directions.

Purpose: The aim of that work is to study the theoretical behavior and merits of the Generalized Gamma (generalized dose response gradient) as well as to investigate the usefulness of this concept in practical radiobiological treatment planning.Methods: In this study, the treatment planning system RayStation 1.9 (Raysearch Laboratories AB, Stockholm, Sweden) was used. Furthermore, radiobiological models that provide the tumor control probability (TCP), normal tissue complication probability (NTCP), complication-free tumor control probability (P+) and the Generalized Gamma were employed. The Generalized Gammas of TCP and NTCP, respectively were calculated for given heterogeneous dose distributions to different organs in order to verify the TCP and NTCP computations of the treatment planning system. In this process, a treatment plan was created, where the target and the organs at risk were included in the same ROI in order to check the validity of the system regarding the objective function P+ and the Generalized Gamma. Subsequently, six additional treatment plans were created with the target organ and the organs at risk placed in the same or different ROIs. In these plans, the mean dose was increased in order to investigate the behavior of dose change on tissue response and on Generalized Gamma before and after the change in dose. By theoretically calculating these quantities, the agreement of different theoretical expressions compared to the values that the treatment planning system provides could be evaluated. Finally, the relative error between the real and approximate response values using the Poisson and the Probit models, for the case of having a target organ consisting of two compartments in a parallel architecture and with the same number of clonogens could be investigated and quantified. Results: The computations of the RayStation regarding the values of the Generalized Gamma and the objective function (P+) were verified by using an independent software. Furthermore, it was proved that after a small change in dose, the organ that is being affected most is the organ with the highest Generalized Gamma. Apart from that, the validity of the theoretical expressions that describe the change in response and the associated Generalized Gamma was verified but only for the case of small change in dose. Especially for the case of 50% TCP and NTCP, the theoretical values (ΔPapprox.) and those calculated by the RayStation show close agreement, which proves the high importance of the D50 parameter in specifying clinical response levels. Finally, the presented findings show that the behavior of ΔPapprox. looks sensible because, for both of the models that were used (Poisson and Probit), it significantly approaches the real ΔP around the region of 37% and 50% response. The present study managed to evaluate the mathematical expression of Generalized Gamma for the case of non-uniform dose delivery and the accuracy of the RayStation to calculate its values for different organs. Conclusion: A very important finding of this work is the establishment of the usefulness and clinical relevance of Generalized Gamma. That is because it gives the planner the opportunity to precisely determine which organ will be affected most after a small increase in dose and as a result an optimal treatment plan regarding tumor control and normal tissue complications can be found.

The aim was to investigate and compare the influence of linear energy transfer (LET), dose and time on the induction of apoptosis in a human melanoma cell line exposed to accelerated light boron ((10)B) ions and photons. Cells were exposed in vitro to doses up to 6 Gy accelerated boron ions (40, 80, 125 and 160 eV nm(-1)) and up to 12 Gy photons (0.2 eV nm(-1)). The induction of apoptosis was measured up to 9 days after irradiation using morphological characterization of apoptotic cells and bodies. In parallel, measurements of cell-cycle distribution, monitored by DNA flow cytometry, and cell survival based on the clonogenic cell survival assay, were performed. In addition, the induction and repair of DNA double-strand breaks (DSB), using pulsed-field gel electrophoresis (PFGE) were studied. Accelerated boron ions induced a significant increase in apoptosis as compared with photons at all time points studied. At 1-5 h the percentage of radiation-induced apoptotic cells increased with both dose and LET. At the later time points (24-216 h) the apoptotic response was more complex and did not increase in a strictly LET-dependent manner. The early premitotic apoptotic cells disappeared at 24 h following exposure to the highest LET (160 eV nm(-1)). A postmitotic apoptotic response was seen after release of the dose-, time- and LET-dependent G2/M accumulations. The loss of clonogenic ability was dose- and LET-dependent and the fraction of un-rejoined DSB increased with increasing LET. Despite the LET-dependent clonogenic cell killing, it was not possible to measure quantitatively a LET-dependent apoptotic response. This was due to the different time course of appearance and disappearance of apoptotic cells.

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.

Based on irradiation with 45 MeV/u N and B ions and with Co-60 gamma rays, cellular parameters of Katz's track structure model have been fitted for the survival of V79-379A Chinese hamster lung fibroblasts. Cellular parameters representing neoplastic transformations in C3H10T/1/2 cells after their irradiation with heavy ion beams, taken from earlier work, were also used to model the radiation hazard in deep space, following the system for evaluating, summing and reporting occupational exposures proposed in 1967 by a subcommittee of NCRP. We have performed model calculations of the number of transformations in surviving cells, after a given fluence of heavy charged particles of initial energy 500 MeV/u, penetrating thick layers of cells. We take the product of cell transformation and survival probabilities, calculated along the path lengths of charged particles using cellular survival and transformation parameters, to represent a quantity proportional to the "radiation risk factor" discussed in the NCRP document. The "synergistic" effect of simultaneous charged particle transfers is accounted for by the "track overlap" mode inherent in the model of Katz.

The advent of intensity-modulated radiation therapy makes it increasingly important to model the response accurately when large volumes of normal tissues are irradiated by controlled graded dose distributions aimed at maximizing tumor cure and minimizing normal tissue toxicity. The cell survival model proposed here is very useful and flexible for accurate description of the response of healthy tissues as well as tumors in classical and truly radiobiologically optimized radiation therapy. The repairable-conditionally repairable (RCR) model distinguishes between two different types of damage, namely the potentially repairable, which may also be lethal, i.e. if unrepaired or misrepaired, and the conditionally repairable, which may be repaired or may lead to apoptosis if it has not been repaired correctly. When potentially repairable damage is being repaired, for example by nonhomologous end joining, conditionally repairable damage may require in addition a high-fidelity correction by homologous repair. The induction of both types of damage is assumed to be described by Poisson statistics. The resultant cell survival expression has the unique ability to fit most experimental data well at low doses (the initial hypersensitive range), intermediate doses (on the shoulder of the survival curve), and high doses (on the quasi-exponential region of the survival curve). The complete Poisson expression can be approximated well by a simple bi-exponential cell survival expression, S(D) = e(-aD) + bDe(-cD), where the first term describes the survival of undamaged cells and the last term represents survival after complete repair of sublethal damage. The bi-exponential expression makes it easy to derive D(0), D(q), n and alpha, beta values to facilitate comparison with classical cell survival models.

To the Editor,Cancer is a leading cause of death worldwide, including developing countries [1,2]. In Mozambique, because of the high prevalence of infectious diseases such as malaria and later HIV ...

The clinical implementation of radiobiological models is a prerequisite for an accurate optimization of radiotherapy. However, to achieve this goal, a number of factors have to be considered and procedural steps to be taken. This chapter examines methods for extracting dose–response relations for tumor and normal tissues from clinical patient data. In order to demonstrate the practical aspects of those methods, different clinical examples are employed such as that of anal sphincter regarding determination of the dose–response relations for the end points of fecal leakage and blood or phlegm in stools. One aspect of the quality assurance of radiobiological treatment plan optimization is the validation of the determined dose–response relations. In the literature, different statistical methods have been utilized for this purpose (e.g., maximum likelihood method, Pearson’s test, and receiver operating characteristic curves), which are demonstrated here for validating the dose–response relations of the lung regarding the end point of radiation pneumonitis. Apart from the methodology by which the radiobiological parameters are determined, the predictive strength of the different models depends on their inherent structure to account for the relevant biological factors that are related to the treatment outcome. Such factors that are examined here are (a) volume effect, (b) different fractionation correction approaches, (c) the generalization of the normalized dose–response gradient to nonuniform dose delivery and multiple target volumes and normal tissues, (d) factors affecting the clinically observed patient radiosensitivity variation, and (e) the impact of inter- and intrapatient radiosensitivity variation on treatment plan evaluation and radiotherapy optimization.

Developments in radiation therapy planning have improved the information about the three-dimensional dose distribution in the patient. Isodose graphs, dose volume histograms and most recently radiobiological models can be used to evaluate the dose distribution delivered to the irradiated organs and volumes of interest. The concept of a biologically effective uniform dose (D) assumes that any two dose distributions are equivalent if they cause the same probability for tumour control or normal tissue complication. In the present paper the D concept both for tumours and normal tissues is presented, making use of the fact that probabilities averaged over both dose distribution and organ radiosensitivity are more relevant to the clinical outcome than the expected number of surviving clonogens or functional subunits. D can be calculated in complex target volumes or organs at risk either from the 3D dose matrix or from the corresponding dose volume histograms of the dose plan. The value of the D concept is demonstrated by applying it to two treatment plans of a cervix cancer. Comparison is made of the D concept with the effective dose (Deff) and equivalent uniform dose (EUD) that have been suggested in the past. The value of the concept for complex targets and fractionation schedules is also pointed out.

A generalization of the standard dose-response gradient to arbitrarily heterogeneous dose distributions has been developed. The generalized dose-response gradient is the scalar product of the vector representing the dose distribution and the gradient of the dose-response relation with respect to that dose vector. It is shown that, for a tumor, the individual &#110 -values for each portion of the tumor divided by the corresponding local tumor control probability should be added to get the total value for the heterogeneously irradiated tumor. This corresponds to summing up the contributions of all tumor volumes so that the total value of the gradient is related to the logarithm of the total tumor clonogen number. General expressions are also derived for the change in the dose-response relation as a function of a change in the delivered dose distribution.

The objective of the dynamic radiotherapy project 'Dynarad' within the European Community has been to compare and grade treatment techniques that are currently applied or being developed at the participating institutions. Cervical cancer was selected as the tumour site on the grounds that the involved organs at risk, mainly the rectum and the bladder, are very close to the tumour and partly located inside the internal target volume. In this work, a solid phantom simulating the pelvic anatomy was used by institutions in Belgium, France, Greece, Holland, Italy, Sweden and the United Kingdom. The results were evaluated using both biological and physical criteria. The main purpose of this parallel evaluation is to test the value of biological and physical evaluations in comparing treatment techniques. It is demonstrated that the biological objective functions allow a much higher conformality and a more clinically relevant scoring of the outcome. Often external beam treatment techniques have to be combined with intracavitary therapy to give clinically acceptable results. However, recent developments can reduce or even eliminate this need by delivering more conformal dose distributions using intensity modulated external dose delivery. In these cases the reliability of the patient set-up procedure becomes critical for the effectiveness of the treatment.

Purpose : (a) To assess the increased risk of death due to ischemic heart disease (IHD) in a group of patients treated for Hodgkin's disease (HD) with radiation therapy (RT) as the primary treatment. (b) To quantify the dose response of IHD using a biophysical model. Materials and methods : Patient material consisted of 157 patients diagnosed for HD between 1972 and 1985 who received RT as the primary treatment at Radiumhemmet, Karolinska Hospital. The general population formed the control group. The RT treatments were reconstructed based on the individual treatment data and simulator films. Individual clinical and dosimetrical data were analyzed with the relative seriality model. The material was also analyzed grouping the material according to dose-volume constraints. Results : Of the 157 patients, 13 (8.3%) died due to IHD. The standardized mortality ratio (SMR) was 5.0 (95% CI, 2.7–8.6). Analysis of dose-volume histograms (DVH) showed an increasing risk with increasing dose to a larger volume fraction. The observed individual clinical complication data could not be modeled unambiguously. The group analysis resulted in the dose-response parameters: D 50 =71 Gy, γ =0.96 and s =1.0. Conclusions : A significantly increased risk of death due to IHD following RT for HD was found. The risk was found to increase with higher dose and larger volume fraction irradiated.

The aim of the present work is to better account for the known uncertainties in radiobiological response parameters when optimizing radiation therapy. The radiation sensitivity of a specific patient is usually unknown beyond the expectation value and possibly the standard deviation that may be derived from studies on groups of patients. Instead of trying to find the treatment with the highest possible probability of a desirable outcome for a patient of average sensitivity, it is more desirable to maximize the expectation value of the probability for the desirable outcome over the possible range of variation of the radiation sensitivity of the patient. Such a stochastic optimization will also have to consider the distribution function of the radiation sensitivity and the larger steepness of the response for the individual patient. The results of stochastic optimization are also compared with simpler methods such as using biological response `margins' to account for the range of sensitivity variation. By using stochastic optimization, the absolute gain will typically be of the order of a few per cent and the relative improvement compared with non-stochastic optimization is generally less than about 10 per cent. The extent of this gain varies with the level of interpatient variability as well as with the difficulty and complexity of the case studied. Although the dose changes are rather small (

A new general beam optimization algorithm for inverse treatment planning is presented. It utilizes a new formulation of the probability to achieve complication-free tumour control. The new formulation explicitly describes the dependence of the treatment outcome on the incident fluence distribution, the patient geometry, the radiobiological properties of the patient and the fractionation schedule. In order to account for both measured and non-measured positioning uncertainties, the algorithm is based on a combination of dynamic and stochastic optimization techniques. Because of the difficulty in measuring all aspects of the intra- and interfractional variations in the patient geometry, such as internal organ displacements and deformations, these uncertainties are primarily accounted for in the treatment planning process by intensity modulation using stochastic optimization. The information about the deviations from the nominal fluence profiles and the nominal position of the patient relative to the beam that is obtained by portal imaging during treatment delivery, is used in a feedback loop to automatically adjust the profiles and the location of the patient for all subsequent treatments. Based on the treatment delivered in previous fractions, the algorithm furnishes optimal corrections for the remaining dose delivery both with regard to the fluence profile and its position relative to the patient. By dynamically refining the beam configuration from fraction to fraction, the algorithm generates an optimal sequence of treatments that very effectively reduces the influence of systematic and random set-up uncertainties to minimize and almost eliminate their overall effect on the treatment. Computer simulations have shown that the present algorithm leads to a significant increase in the probability of uncomplicated tumour control compared with the simple classical approach of adding fixed set-up margins to the internal target volume.

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Sublethal damage after radiation exposure may become lethal or be repaired according to repair kinetics. This is a well-established concept in conventional radiotherapy. It also plays an important role in single-dose stereotactic radiotherapy treatments, often called stereotactic radiosurgery, when duration of treatment is extended due to source decay or treatment planning protocol. The purpose of this study is to look into the radiobiological characteristics of normal brain tissue and treatment protocols and find a way to optimize the time course of these protocols. The general problem is nonlinear and can be solved numerically. For numerical optimization of the time course of radiation protocol, a biexponential repair model with slow and fast components was considered. With the clinically imposed constraints of a fixed total dose and total treatment time, three parameters for each fraction (dose-rate, fraction duration, time of each fraction) were simultaneously optimized. A biological optimization can be performed by maximizing the therapeutic difference between tumor control probability and normal tissue complication probability. Specifically, for gamma knife radiosurgery, this approach can be implemented for normal brain tissue or tumor voxels separately in a treatment plan. Differences in repair kinetics of normal tissue and tumors can be used to find clinically optimized protocols. Thus, in addition to considering the physical dose in tumor and normal tissue, we also account for repair of sublethal damage in both these tissues.

An efficient algorithm has been developed to estimate the relative biological effectiveness (RBE) from experimental RBE data and measured single-event energy deposition spectra. As benchmarks for the calculations well established RBE data for crypt cell survival and associated microdosimetric distributions from a number of therapeutic high- and low-LET beams was used. As a by-product of the calculations the RBE for this system was determined for the lineal energy range 0.1-5000 keV microns-1 in very good agreement with experimental data. These data have been applied to estimate the biological effectiveness of therapeutic high-energy bremsstrahlung beams characterized by microdosimetric measurements with a wall-less proportional counter. The absorbed dose component due to photoneutrons and charged particles from photonuclear reactions in scanned 50 MV bremsstrahlung beams was measured to be about 2% of the total absorbed dose. The RBE of 50 MV scanned bremsstrahlung beams was estimated to be 1.09 for jejunum crypt cell survival as the biological endpoint at absorbed doses of the order of 10 Gy, in fair agreement with reported results based on radiobiological experiments. The RBE is fairly independent of the bremsstrahlung target used. Using the estimated increase in the RBE of neutrons compared to photons for absorbed dose levels applied in clinical fractionation schedules increases the RBE further to 1.13 at absorbed doses per fraction of the order of 2 Gy.

Over the last decade a large number of new treatment techniques have been developed to allow a true optimization of the delivered dose distribution in radiation therapy. The most important clinical requirement of most optimization techniques is to be able to deliver strongly nonuniform beams on the patient from arbitrary directions. For very complex tumors the number of beams required to eradicate the tumor without severe injury to normal tissues is quite high, to accurately make the three dimensional dose distribution conform to the target volume. For more simple target geometries fewer beams are sufficient, and in many cases with small tumors the classical uniform rectangular beams will do nicely. A number of new treatment techniques, from narrow beam robot mounted linear accelerators through fan beam devices using linear multileaf collimation in rotary gantries, to the most flexible external beam devices with scanned electron and photon beams and/or dynamic multileaf collimation available over the whole treatment field, are now rapidly coming into clinical use.

The purpose of this study was to quantify and model various types of cell death for a small-cell lung cancer (SCLC) cell line (U1690) after exposure to a 137Cs source and as well as to compare the linear-quadratic (LQ) and repairable-conditionally repairable model (RCR). This study is based on four different experiments that were taken place at Cancer Centrum Karolinska (CCK). A human small-cell lung cancer (SCLC) cell line after the exposure to a 137Cs source was used for the extraction of the clonogenic cell survival curve. Additionally, for the determination and quantification of various modes of cell death the method of fluorescence staining was implemented, where the cell deaths were categorized based on morphological characteristics. The percentage of cells in each phase of the cell cycle was investigated with flow cytometry analysis. The quantification of senescent cells was performed by staining the samples with senescence-associated β-galactosidase (SA-β-Gal) solution and then scoring as senescent cells those that had incorporated the substance. These data were introduced into a maximum likelihood fitting to calculate the best estimates of the parameters used by the examined model. In this model, the modes of cell death are divided into three categories: apoptotic, senescent and other types of cell death (necrotic/apoptotic, necrotic, micronuclei and giant). In the clonogenic cell survival assay, the fitting of the RCR model gives a χ(2)-value of 6.10 whereas for the LQ model became 9.61. In the fluorescence microscopy and senescence assay, the probability of the three different modes of cell death on day 2 seems to increases with a dose up to about 10 Gy where there is saturation. On day 7 a significant induction of apoptosis in a dose- and time-dependent manner was evident, whereas senescence was slightly increased in response to dose but not to time. As for the 'other types of cell death' mode on day 7 showed a higher probability than the one on day 2 and as well as a prominent dose-dependence. The RCR model fits better to the experimental data than the LQ model. On day 2 there is a slight increase of the apoptotic and senescent probability with dose. On the other hand, on day 7 the shape of the curve of apoptosis differs and a sigmoidal increase with dose is observed. At both time-points, the present model fits the data reasonably well. Due to the fact that the clonogenic survival does not coincide with the one extracted from the fluorescence microscopy, a more accurate way to quantify cell death needs to be used, e.g. computerized video time-lapse (CVTL).

The biological effects of particles are often expressed in relation to that of photons through the concept of relative biological effectiveness, RBE. In proton radiotherapy, a constant RBE of 1.1 is usually assumed. However, there is experimental evidence that RBE depends on various factors. The aim of this study is to develop a model to predict the RBE based on linear energy transfer (LET), dose, and the tissue specific parameter α/β of the linear-quadratic model for the reference radiation. Moreover, the model should capture the basic features of the RBE using a minimum of assumptions, each supported by experimental data.The α and β parameters for protons were studied with respect to their dependence on LET. An RBE model was proposed where the dependence of LET is affected by the (α/β)phot ratio of photons. Published cell survival data with a range of well-defined LETs and cell types were selected for model evaluation rendering a total of 10 cell lines and 24 RBE values.A statistically significant relation was found between α for protons and LET. Moreover, the strength of that relation varied significantly with (α/β)phot. In contrast, no significant relation between β and LET was found. On the whole, the resulting RBE model provided a significantly improved fit (p-value0.01) to the experimental data compared to the standard constant RBE. By accounting for the α/β ratio of photons, clearer trends between RBE and LET of protons were found, and our results suggest that late responding tissues are more sensitive to LET changes than early responding tissues and most tumors. An advantage with the proposed RBE model in optimization and evaluation of treatment plans is that it only requires dose, LET, and (α/β)phot as input parameters. Hence, no proton specific biological parameters are needed.

There are many tools available that are used to evaluate a radiotherapy treatment plan, such as isodose distribution charts, dose volume histograms (DVH), maximum, minimum and mean doses of the dose distributions as well as DVH point dose constraints. All the already mentioned evaluation tools are dosimetric only without taking into account the radiobiological characteristics of tumors or OARs. It has been demonstrated that although competing treatment plans might have similar mean, maximum or minimum doses they may have significantly different clinical outcomes (Mavroidis et al. 2001). For performing a more complete treatment plan evaluation and comparison the complication-free tumor control probability (P+) and the biologically effective uniform dose (D ) have been proposed (Kallman et al. 1992a, Mavroidis et al. 2000). The D concept denotes that any two dose distributions within a target or OAR are equivalent if they produce the same probability for tumor control or normal tissue complication, respectively (Mavroidis et al. 2001)...

In order to apply highly conformal dose distributions, which are characterized by steep dose fall-offs, it is necessary to know the exact target location and extension. This study aims at evaluating the impact of using combined CT-MRI images in organ delineation compared to using CT images alone, on the clinical results. For 10 prostate cancer patients, the respective CT and MRI images at treatment position were acquired. The CTV was delineated using the CT and MRI images, separately, whereas bladder and rectum were delineated using the CT images alone. Based on the CT and MRI images, two CTVs were produced for each patient. The mutual information algorithm was used in the fusion of the two image sets. In this way, the structures drawn on the MRI images were transferred to the CT images in order to produce the treatment plans. For each set of structures of each patient, IMRT and 3D-CRT treatment plans were produced. The individual treatment plans were compared using the biologically effective uniform dose ([Formula: see text]) and the complication-free tumor control probability ( P+) concepts together with the DVHs of the targets and organs at risk and common dosimetric criteria. For the IMRT treatment, at the optimum dose level of the average CT and CT-MRI delineated CTV dose distributions, the P+ values are 74.7% in both cases for a [Formula: see text] of 91.5 Gy and 92.1 Gy, respectively. The respective average total control probabilities, PB are 90.0% and 90.2%, whereas the corresponding average total complication probabilities, PI are 15.3% and 15.4%. Similarly, for the 3D-CRT treatment, the average P+ values are 42.5% and 46.7%, respectively for a [Formula: see text] of 86.4 Gy and 86.7 Gy, respectively. The respective average PB values are 80.0% and 80.6%, whereas the corresponding average PI values are 37.4% and 33.8%, respectively. For both radiation modalities, the improvement mainly stems from the better sparing of rectum. According to these results, the expected clinical effectiveness of IMRT can be increased by a maximum Δ P+ of around 0.9%, whereas of 3D-CRT by about 4.2% when combined CT-MRI delineation is performed instead of using CT images alone. It is apparent that in both IMRT and 3D-CRT radiation modalities, the better knowledge of the CTV extension improved the produced dose distribution. It is shown that the CTV is irradiated more effectively, while the complication probabilities of bladder and rectum, which is the principal organs at risk, are lower in the CT-MRI based treatment plans.

The often large uncertainties that exist in beam patient alignment during radiation therapy may require modification of the incident beams to ensure an optimal delivered dose distribution to the target volume. This problem becomes increasingly severe when the required dose distribution of the incident beams becomes more heterogeneous. A simple analytical formula is derived for the case when the fraction number is high, and the desired relative dose variations are small. This formula adjusts the fluence distribution of the incident beam so that the resultant dose distribution will be as close as possible to the desired one considering the uncertainties in beam patient alignment. When sharp dose gradients are important, for instance at the border of the target volume, the problem is much more difficult. It is shown here that, if the tumor is surrounded by organs at risk, it is generally best to open up the field by about one standard deviation of the positional uncertainty--that is sigma/2 on each side of the target volume. In principle it is simultaneously desirable to increase the prescribed dose by a few per cent compared to the case where the positional uncertainty is negligible, in order to compensate for the rounded shoulders of the delivered dose distribution. When the tissues surrounding the tumor no longer are dose limiting even larger increases in field size may be advantageous. For more critical clinical situations the positional uncertainty may even limit the success of radiotherapy. In such cases one generally wants to create a steeper dose distribution than the underlying random Gaussian displacement process allows. The problem is then best handled by quantifying the treatment outcome under the influence of the stochastic process of patient misalignment. Either the coincidence with the desired dose distribution, or the expectation value of the probability of achieving complication-free tumor control is maximized under the influence of this stochastic process. It is shown that the most advantageous treatment is to apply beams that are either considerably widened or slightly widened and over flattened near the field edges for small and large fraction numbers respectively.

Accurately determined dose-response relations of the different tumors and normal tissues should be estimated and used in the clinic. The aim of this study is to demonstrate developed tools that are necessary for determining the dose-response parameters of tumors and normal tissues, for clinically verifying already published parameter sets using local patient materials and for making use of all this information in the optimization and comparison of different treatment plans and radiation techniques. One of the software modules (the Parameter Determination Module) is designed to determine the dose-response parameters of tumors and normal tissues. This is accomplished by performing a maximum likelihood fitting to calculate the best estimates and confidence intervals of the parameters used by different radiobiological models. Another module of this software (the Parameter Validation Module) concerns the validation and compatibility of external or reported dose-response parameters describing tumor control and normal tissue complications. This is accomplished by associating the expected response rates, which are calculated using different models and published parameter sets, with the clinical follow-up records of the local patient population. Finally, the last module of the software (the Radiobiological Plan Evaluation Module) is used for estimating and optimizing the effectiveness a treatment plan in terms of complication-free tumor control, P+. The use of the Parameter Determination Module is demonstrated by deriving the dose-response relation of proximal esophagus from head & neck cancer radiotherapy. The application of the Parameter Validation Module is illustrated by verifying the clinical compatibility of those dose-response parameters with the examined treatment methodologies. The Radiobiological Plan Evaluation Module is demonstrated by evaluating and optimizing the effectiveness of head & neck cancer treatment plans. The results of the radiobiological evaluation are compared against dosimetric criteria. The presented toolkit appears to be very convenient and efficient for clinical implementation of radiobiological modeling. It can also be used for the development of a clinical data and health information database for assisting the performance of epidemiological studies and the collaboration between different institutions within research and clinical frameworks.