A model for the relative biological effectiveness of protons: the tissue specific parameter α/ß of photons is a predictor for the sensitivity to LET changes.

BACKGROUND: 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/ß 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. MATERIAL AND METHODS: The α and ß 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/ß)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. RESULTS AND CONCLUSION: A statistically significant relation was found between α for protons and LET. Moreover, the strength of that relation varied significantly with (α/ß)phot. In contrast, no significant relation between ß and LET was found. On the whole, the resulting RBE model provided a significantly improved fit (p-value < 0.01) to the experimental data compared to the standard constant RBE. By accounting for the α/ß 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/ß)phot as input parameters. Hence, no proton specific biological parameters are needed.

Dose-response relationships for an atomized symptom of fecal incontinence after gynecological radiotherapy.

PURPOSE: 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. MATERIAL AND METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

A systems biology approach to radiation therapy optimization.

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.

Comparison of the helical tomotherapy and MLC-based IMRT radiation modalities in treating brain and cranio-spinal tumors.

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 (D=) 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 D(=) concept as the common prescription point, the different treatment plans were compared based on radiobiological measures. The tissue response probabilities were plotted against D(=) 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 D(=) 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 D(=) 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 - (D=) diagrams can complement the traditional tools of evaluation such as DVHs, in order to compare and effectively evaluate different treatment plans.

Radial secondary electron dose profiles and biological effects in light-ion beams based on analytical and Monte Carlo calculations using distorted wave cross sections.

To speed up dose calculation, an analytical pencil-beam method has been developed to calculate the mean radial dose distributions due to secondary electrons that are set in motion by light ions in water. For comparison, radial dose profiles calculated using a Monte Carlo technique have also been determined. An accurate comparison of the resulting radial dose profiles of the Bragg peak for (1)H(+), (4)He(2+) and (6)Li(3+) ions has been performed. The double differential cross sections for secondary electron production were calculated using the continuous distorted wave-eikonal initial state method (CDW-EIS). For the secondary electrons that are generated, the radial dose distribution for the analytical case is based on the generalized Gaussian pencil-beam method and the central axis depth-dose distributions are calculated using the Monte Carlo code PENELOPE. In the Monte Carlo case, the PENELOPE code was used to calculate the whole radial dose profile based on CDW data. The present pencil-beam and Monte Carlo calculations agree well at all radii. A radial dose profile that is shallower at small radii and steeper at large radii than the conventional 1/r(2) is clearly seen with both the Monte Carlo and pencil-beam methods. As expected, since the projectile velocities are the same, the dose profiles of Bragg-peak ions of 0.5 MeV (1)H(+), 2 MeV (4)He(2+) and 3 MeV (6)Li(3+) are almost the same, with about 30% more delta electrons in the sub keV range from (4)He(2+)and (6)Li(3+) compared to (1)H(+). A similar behavior is also seen for 1 MeV (1)H(+), 4 MeV (4)He(2+) and 6 MeV (6)Li(3+), all classically expected to have the same secondary electron cross sections. The results are promising and indicate a fast and accurate way of calculating the mean radial dose profile.

Interpretation of the dosimetric results of three uniformity regularization methods in terms of expected treatment outcome.

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.

Variation in radiation sensitivity and repair kinetics in different parts of the spinal cord.

BACKGROUND: The spinal cord, known for its strongly serial character and high sensitivity to radiation even when a small segment is irradiated, is one of the most critical organs at risk to be spared during radiation therapy. To compare the sensitivity of different parts of the spinal cord, data for radiation myelopathy have been used. MATERIAL AND METHODS: In the present study, the relative seriality model was fitted to two different datasets of clinical radiation myelitis concerning cervical spinal cord after treating 248 patients for head and neck cancer and thoracic spinal cord after treating 43 patients with lung carcinoma. The maximum likelihood method was applied to fit the clinical data. The model parameters and their 68% confidence intervals were calculated for each dataset. The alpha/beta ratio for the thoracic cord was also was also found to be 0.9 (0-3.0) Gy. RESULTS: The dose-response curve for the more sensitive cervical myelopathy is well described by the parameters D(50)=55.9 (54.8-57.1) Gy, gamma=6.9 (5.0-9.2), s=0.13 (0.07-0.24), whereas the thoracic myelopathy is described by the parameters D(50)=75.5 (70.5-80.8) Gy, gamma=1.1 (0.6-1.6), s=36 (3.3-infinity). DISCUSSION AND CONCLUSIONS: Large differences in radiation response between the cervical and thoracic region of spinal cord are thus observed: cervical myelopathy seems to be characterized by medium seriality, while thoracic spinal cord is characterized by a highly serial dose-response. The much steeper dose-response curve for cervical spinal cord myelopathy can be interpreted as a higher number of functional subunits consistent with a higher amount of white matter close to the brain.

The dose--response relation for rat spinal cord paralysis analyzed in terms of the effective size of the functional subunit.

Radiobiological models for estimating normal tissue complication probability (NTCP) are increasingly used in order to quantify or optimize the clinical outcome of radiation therapy. A good NTCP model should fulfill at least the following two requirements: (a) it should predict the sigmoid shape of the corresponding dose-response curve and (b) it should accurately describe the probability of a specified response for arbitrary non-uniform dose delivery for a given endpoint as accurately as possible, i.e. predict the volume dependence. In recent studies of the volume effect of a rat spinal cord after irradiation with narrow and broad proton beams the authors claim that none of the existing NTCP models is able to describe their results. Published experimental data have been used here to try to quantify the change in the effective dose (D(50)) causing 50% response for different field sizes. The present study was initiated to describe the induction of white matter necrosis in a rat spinal cord after irradiation with narrow proton beams in terms of the mean dose to the effective volume of the functional subunit (FSU). The physically delivered dose distribution was convolved with a function describing the effective size or, more accurately, the sensitivity distribution of the FSU to obtain the effective mean dose deposited in it. This procedure allows the determination of the mean D(50) value of the FSUs of a certain size which is of interest for example if the cell nucleus of the oligodendrocyte is the sensitive target. Using the least-squares method to compare the effective doses for different sizes of the functional subunits with the experimental data the best fit was obtained with a length of about 9 mm. For the non-uniform dose distributions an effective FSU length of 8 mm gave the optimal fit with the probit dose-response model. The method could also be used to interpret the so-called bath and shower experiments where the heterogeneous dose delivery was used in the convolution process. The assumption of an effective FSU size is consistent with most of the effects seen when different portions of the rat spinal cord are irradiated to different doses. The effective FSU length from these experiments is about 8.5 +/- 0.5 mm. This length could be interpreted as an effective size of the functional subunits in a rat spinal cord, where multiple myelin sheaths are connected by a single oligodendrocyte and repair is limited by the range of oligodendrocyte progenitor cell diffusion. It was even possible to suggest a more likely than uniform effective FSU sensitivity distribution from the experimental data.

The impact of different dose-response parameters on biologically optimized IMRT in breast cancer.

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.

Treatment plan comparison between helical tomotherapy and MLC-based IMRT using radiobiological measures.

The rapid implementation of advanced treatment planning and delivery technologies for radiation therapy has brought new challenges in evaluating the most effective treatment modality. Intensity-modulated radiotherapy (IMRT) using multi-leaf collimators (MLC) and helical tomotherapy (HT) are becoming popular modes of treatment delivery and their application and effectiveness continues to be investigated. Presently, there are several treatment planning systems (TPS) that can generate and optimize IMRT plans based on user-defined objective functions for the internal target volume (ITV) and organs at risk (OAR). However, the radiobiological parameters of the different tumours and normal tissues are typically not taken into account during dose prescription and optimization of a treatment plan or during plan evaluation. The suitability of a treatment plan is typically decided based on dosimetric criteria such as dose-volume histograms (DVH), maximum, minimum, mean and standard deviation of the dose distribution. For a more comprehensive treatment plan evaluation, the biologically effective uniform dose (D) is applied together with the complication-free tumour control probability (P(+)). Its utilization is demonstrated using three clinical cases that were planned with two different forms of IMRT. In this study, three different cancer types at different anatomical sites were investigated: head and neck, lung and prostate cancers. For each cancer type, a linac MLC-based step-and-shoot IMRT plan and a HT plan were developed. The MLC-based IMRT treatment plans were developed on the Philips treatment-planning platform, using the Pinnacle 7.6 software release. For the tomotherapy HiArt plans, the dedicated tomotherapy treatment planning station was used, running version 2.1.2. By using D as the common prescription point of the treatment plans and plotting the tissue response probabilities versus D for a range of prescription doses, a number of plan trials can be compared based on radiobiological measures. The applied plan evaluation method shows that in the head and neck cancer case the HT treatment gives better results than MLC-based IMRT in terms of expected clinical outcome P(+) of 62.2% and 46.0%, D to the ITV of 72.3 Gy and 70.7 Gy, respectively). In the lung cancer and prostate cancer cases, the MLC-based IMRT plans are better over the clinically useful dose prescription range. For the lung cancer case, the HT and MLC-based IMRT plans give a P(+) of 66.9% and 72.9%, D to the ITV of 64.0 Gy and 66.9 Gy, respectively. Similarly, for the prostate cancer case, the two radiation modalities give a P(+) of 68.7% and 72.2%, D to the ITV of 86.0 Gy and 85.9 Gy, respectively. If a higher risk of complications (higher than 5%) could be allowed, the complication-free tumour control could increase by over 40%, 2% and 30% compared to the initial dose prescription for the three cancer cases, respectively. Both MLC-based IMRT and HT can encompass the often-large ITV required while they minimize the volume of the organs at risk receiving high doses. Radiobiological evaluation of treatment plans may provide an improved correlation of the delivered treatment with the clinical outcome by taking into account the dose-response characteristics of the irradiated targets and normal tissues. There may exist clinical cases, which may look dosimetrically similar but in radiobiological terms may be quite different. In such situations, traditional dose-based evaluation tools can be complemented by the use of P(+)--D diagrams to effectively evaluate and compare treatment plans.

NTCP modelling and pulmonary function tests evaluation for the prediction of radiation induced pneumonitis in non-small-cell lung cancer radiotherapy.

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.

The radiation response of heterogeneous tumors.

Heterogeneous tumors often have a wide spectrum of radiation sensitivities due to factors like their genetic make up, clonal distribution and degree of genetic instability, as well as gradients of oxygen and nutrients. Recent studies demonstrate that the radiation response of heterogeneous tumors can be rather well described by a single effective clonogen compartment when the dose-response relation at high doses is of main interest. When a correct description of the clonogen survival is important at both low and high doses, a description based on one sensitive and one resistant clonogen compartment will be necessary and generally sufficient and surprisingly accurate. Such a description is valuable for example when in vivo PET-CT data are acquired early in the treatment to predict the required curative radiation dose. Methods are given for derivation of the sensitive and resistant cell compartments based on clinically observed dose-response relations and the degree of hypoxia. Principal characteristics of heterogeneous tumors are derived, such as the dose D(t) describing the transition when sensitive cells are lost and resistant cells start to dominate the response resulting in a fast change in slope of the cell survival curve. Since the effective compartments are based on the whole spectrum of radiation resistance, they will take both low intermediate and high sensitivity values into account, thus providing an accurate description of the radiation response over the entire range of clinically relevant doses.

Comments on 'Reconsidering the definition of a dose-volume histogram'--dose-mass histogram (DMH) versus dose-volume histogram (DVH) for predicting radiation-induced pneumonitis.

In a recently published paper (Nioutsikou et al 2005 Phys. Med. Biol. 50 L17) the authors showed that the use of the dose-mass histogram (DMH) concept is a more accurate descriptor of the dose delivered to lung than the traditionally used dose-volume histogram (DVH) concept. Furthermore, they state that if a functional imaging modality could also be registered to the anatomical imaging modality providing a functional weighting across the organ (functional mass) then the more general and realistic concept of the dose-functioning mass histogram (D[F]MH) could be an even more appropriate descriptor. The comments of the present letter to the editor are in line with the basic arguments of that work since their general conclusions appear to be supported by the comparison of the DMH and DVH concepts using radiobiological measures. In this study, it is examined whether the dose-mass histogram (DMH) concept deviated significantly from the widely used dose-volume histogram (DVH) concept regarding the expected lung complications and if there are clinical indications supporting these results. The problem was investigated theoretically by applying two hypothetical dose distributions (Gaussian and semi-Gaussian shaped) on two lungs of uniform and varying densities. The influence of the deviation between DVHs and DMHs on the treatment outcome was estimated by using the relative seriality and LKB models using the Gagliardi et al (2000 Int. J. Radiat. Oncol. Biol. Phys. 46 373) and Seppenwoolde et al (2003 Int. J. Radiat. Oncol. Biol. Phys. 55 724) parameter sets for radiation pneumonitis, respectively. Furthermore, the biological equivalent of their difference was estimated by the biologically effective uniform dose (D) and equivalent uniform dose (EUD) concepts, respectively. It is shown that the relation between the DVHs and DMHs varies depending on the underlying cell density distribution and the applied dose distribution. However, the range of their deviation in terms of the expected clinical outcome was proven to be very large. Concluding, the effectiveness of the dose distribution delivered to the patients seems to be more closely related to the radiation effects when using the DMH concept.

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.

Three-dimensional atlas of lymph node topography based on the visible human data set.

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.

Time-dependent dose-response relation for absence of vaginal elasticity after gynecological radiation therapy.

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. MATERIAL 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, γ50=1.40 (1.12-1.70) and LL=-37.4, D50=46.9 (43.5-50.9) Gy, γ50=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 D50 decreases.

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.

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.