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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.

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.

Purpose: BioSuite is a program developed to help clinicians to identify cases eligible for dose escalation and/or altered fractionation and to quantify this potential using biological models of normal tissue and tumour response to EBRT. Materials: BioSuite consists in a single executable file developed in C++. The input data are DVHs from a TPS (Philips Pinnacle) as well as a more general DVH format. Plans are defined by parameters such as the number of fractions or a default prescription dose. These DVHs are in turn associated with an endpoint defined by a biological model and a set of parameters. From these models (LKB, Relative Seriality and enhanced LQ Poisson TCP), evaluation of NTCP or TCP can be performed forwardly or inversely. The forward evaluation is made in real-time as the operator modifies plan or endpoint parameters. The inverse evaluation (or optimisation) finds the "dose multiplication factor" (DMP) rescaling the DVH or number of fractions of a given size which take the complication risk to a prior set level. An "isotoxic optimisation" can also be done, which consists of computing for a fraction-number range the highest DMP (and thus TCP) for a constant NTCP. An upper TCP limit can be set (e.g. 99%) to avoid excessive doses in particular cases. The operator can finally generate dose-response curves to visually assess plan quality. Isotoxic optimisation was applied to 33 plans from our institution whose DVHs were exported to BIOSUITE. Results: For most of these plans, scope for dose escalation and/or altered fractionation was found, suggesting these patients were "undertreated". In cases with a very small tumour and consequently small volume of irradiated normal tissue, the models implemented in BioSuite suggested treatments very similar to those currently done in SBRT i.e. TCP close to 100% for as low as 3 fractions. Serial organ DVHs in the plan can drastically affect the BIOSUITE fractionation strategy, making hypofractionation no longer viable.

Purpose: BioSuite is a program developed to help clinicians to identify cases eligible for dose escalation and/or altered fractionation and to quantify this potential using biological models of normal tissue and tumour response to EBRT. Materials: BioSuite consists in a single executable file developed in C++. The input data are DVHs from a TPS (Philips Pinnacle) as well as a more general DVH format. Plans are defined by parameters such as the number of fractions or a default prescription dose. These DVHs are in turn associated with an endpoint defined by a biological model and a set of parameters. From these models (LKB, Relative Seriality and enhanced LQ Poisson TCP), evaluation of NTCP or TCP can be performed forwardly or inversely. The forward evaluation is made in real-time as the operator modifies plan or endpoint parameters. The inverse evaluation (or optimisation) finds the "dose multiplication factor" (DMP) rescaling the DVH or number of fractions of a given size which take the complication risk to a prior set level. An "isotoxic optimisation" can also be done, which consists of computing for a fraction-number range the highest DMP (and thus TCP) for a constant NTCP. An upper TCP limit can be set (e.g. 99%) to avoid excessive doses in particular cases. The operator can finally generate dose-response curves to visually assess plan quality. Isotoxic optimisation was applied to 33 plans from our institution whose DVHs were exported to BIOSUITE. Results: For most of these plans, scope for dose escalation and/or altered fractionation was found, suggesting these patients were "undertreated". In cases with a very small tumour and consequently small volume of irradiated normal tissue, the models implemented in BioSuite suggested treatments very similar to those currently done in SBRT i.e. TCP close to 100% for as low as 3 fractions. Serial organ DVHs in the plan can drastically affect the BIOSUITE fractionation strategy, making hypofractionation no longer viable.

Biological treatment optimization aim at improving radiation therapy by accounting for the radiobiological tumour and normal tissues response properties when optimizing the dose delivery. Generally traditional methods, using only dosimetrical measures, disregard the nonlinear radiation response of different tumours and normal tissues. The accumulated knowledge on tissue response to radiation, in the form of more accurate dose response relations, cell survival models and their associated biological parameters, alongside with the tools for biological treatment plan optimization, has allowed the present investigation on the potential merits of biologically based treatment optimization in radiation therapy.With a more widespread implementation of intensity modulated radiation therapy in the clinic, there is an increasing demand for faster and safer treatment delivery techniques. In this thesis biological treatment plan optimization, using the probability to achieve complication free tumour control as the quantifier for treatment outcome, was applied to radiation therapy of early breast cancer and advanced cervix cancer. It is shown that very conformal dose distributions can generally be produced with 3 or 4 optimally orientated coplanar intensity modulated beams, without having clinically significant losses in treatment outcome from the optimal dose distribution.By using exhaustive search methods, the optimal coplanar beam directions for intensity modulated photon beams for early breast cancer and the optimal non-coplanar directions for an advanced cervix cancer were investigated. Although time consuming, exhaustive search methods have the advantage of revealing most features involving interactions between a small number of beams and how this may influence the treatment outcome. Thus phase spaces may serve as a general database for selecting an almost optimal treatment configuration for similar patients. Previous knowledge acquired with physically optimized uniform beam radiation therapy may not apply when intensity modulated biological optimization is used. Thus unconventional treatment directions were sometimes found.