4 research outputs found
Are IMRT treatments in the head and neck region increasing the risk of secondary cancers?
<div><p></p><p><b>Background.</b> Intensity-modulated radiation therapy (IMRT) has been increasingly employed for treating head and neck (H&N) tumours due to its ability to produce isodoses suitable for the complex anatomy of the region. The aim of this study was to assess possible differences between IMRT and conformal radiation therapy (CRT) with regard to risk of radiation-induced secondary malignancies for H&N tumours.</p><p><b>Material and methods.</b> IMRT and CRT plans were made for 10 H&N adult patients and the resulting treatment planning data were used to calculate the risk of radiation-induced malignancies in four different tissues. Three risk models with biologically relevant parameters were used for calculations. The influence of scatter radiation and repeated imaging sessions has also been investigated.</p><p><b>Results.</b> The results showed that the total lifetime risks of developing radiation-induced secondary malignancies from the two treatment techniques, CRT and IMRT, were comparable and in the interval 0.9–2.5%. The risk contributions from the primary beam and scatter radiation were comparable, whereas the contribution from repeated diagnostic imaging was considerably smaller.</p><p><b>Conclusion.</b> The results indicated that the redistribution of the dose characteristic to IMRT leads to a redistribution of the risks in individual tissues. However, the total levels of risk were similar between the two irradiation techniques considered.</p></div
Survival and tumour control probability in tumours with heterogeneous oxygenation: A comparison between the linear-quadratic and the universal survival curve models for high doses
<div><p></p><p><b>Background.</b> The validity of the linear-quadratic (LQ) model at high doses has been questioned due to a decreasing agreement between predicted survival and experimental cell survival data. A frequently proposed alternative is the universal survival curve (USC) model, thought to provide a better fit in the high-dose region. The comparison between the predictions of the models has mostly been performed for uniform populations of cells with respect to sensitivity to radiation. This study aimed to compare the two models in terms of cell survival and tumour control probability (TCP) for cell populations with mixed sensitivities related to their oxygenation.</p><p><b>Methods.</b> The study was performed in two parts. For the first part, cell survival curves were calculated with both models assuming various homogeneous populations of cells irradiated with uniform doses. For the second part, a realistic three-dimensional (3D) model of complex tumour oxygenation was used to study the impact of the differences in cell survival on the modelled TCP. Cellular response was assessed with the LQ and USC models at voxel level and a Poisson TCP model at tumour level.</p><p><b>Results.</b> For hypoxic tumours, the disputed continuous bend of the LQ survival curve was counteracted by the increased radioresistance of the hypoxic cells and the survival curves started to diverge only at much higher doses than for oxic tumours. This was also reflected by the TCP curves for hypoxic tumours for which the difference in <i>D</i><sub>50</sub> values for the LQ and USC models was reduced from 5.4 to 0.2 Gy for 1 and 3 fractions, respectively, in a tumour with only 1.1% hypoxia and from 9.5 to 0.4 Gy in a tumour with 11.1% hypoxia.</p><p><b>Conclusions.</b> For a large range of fractional doses including hypofractionated schemes, the difference in predicted survival and TCP between the LQ and USC models for tumours with heterogeneous oxygenation was found to be negligible.</p></div
The influence of breathing motion and a variable relative biological effectiveness in proton therapy of left-sided breast cancer
<p><b>Background:</b> Proton breast radiotherapy has been suggested to improve target coverage as well as reduce cardiopulmonary and integral dose compared with photon therapy. This study aims to assess this potential when accounting for breathing motion and a variable relative biological effectiveness (RBE).</p> <p><b>Methods:</b> Photon and robustly optimized proton plans were generated to deliver 50 Gy (RBE) in 25 fractions (RBE = 1.1) to the CTV (whole left breast) for 12 patients. The plan evaluation was performed using the constant RBE and a variable RBE model. Robustness against breathing motion, setup, range and RBE uncertainties was analyzed using CT data obtained at free-breathing, breath-hold-at-inhalation and breath-hold-at-exhalation.</p> <p><b>Results:</b> All photon and proton plans (RBE = 1.1) met the clinical goals. The variable RBE model predicted an average RBE of 1.18 for the CTVs (range 1.14–1.21) and even higher RBEs in organs at risk (OARs). However, the dosimetric impact of this latter aspect was minor due to low OAR doses. The normal tissue complication probability (NTCP) for the lungs was low for all patients (<1%), and similar for photons and protons. The proton plans were generally considered robust for all patients. However, in the most extreme scenarios, the lowest dose received by 98% of the CTV dropped from 96 to 99% of the prescribed dose to around 92–94% for both protons and photons. Including RBE uncertainties in the robustness analysis resulted in substantially higher worst-case OAR doses.</p> <p><b>Conclusions:</b> Breathing motion seems to have a minor effect on the plan quality for breast cancer. The variable RBE might impact the potential benefit of protons, but could probably be neglected in most cases where the physical OAR doses are low. However, to be able to identify outlier cases at risk for high OAR doses, the biological evaluation of proton plans taking into account the variable RBE is recommended.</p
Defining the hypoxic target volume based on positron emission tomography for image guided radiotherapy – the influence of the choice of the reference region and conversion function
<p><b>Background:</b> Hypoxia imaged by positron emission tomography (PET) is a potential target for optimization in radiotherapy. However, the implementation of this approach with respect to the conversion of intensities in the images into oxygenation and radiosensitivity maps is not straightforward. This study investigated the feasibility of applying two conversion approaches previously derived for <sup>18</sup>F-labeled fluoromisonidazole (<sup>18</sup>F-FMISO)-PET images for the hypoxia tracer <sup>18</sup>F-flortanidazole (<sup>18</sup>F-HX4).</p> <p><b>Material and methods:</b> Ten non-small-cell lung cancer patients imaged with <sup>18</sup>F-HX4 before the start of radiotherapy were considered in this study. PET image uptake was normalized to a well-oxygenated reference region and subsequently linear and non-linear conversions were used to determine tissue oxygenations maps. These were subsequently used to delineate hypoxic volumes based partial oxygen pressure (pO<sub>2</sub>) thresholds. The results were compared to hypoxic volumes segmented using a tissue-to-background ratio of 1.4 for <sup>18</sup>F-HX4 uptake.</p> <p><b>Results:</b> While the linear conversion function was not found to result in realistic oxygenation maps, the non-linear function resulted in reasonably sized sub-volumes in good agreement with uptake-based segmented volumes for a limited range of pO<sub>2</sub> thresholds. However, the pO<sub>2</sub> values corresponding to this range were significantly higher than what is normally considered as hypoxia. The similarity in size, shape, and relative location between uptake-based sub-volumes and volumes based on the conversion to pO<sub>2</sub> suggests that the relationship between uptake and pO<sub>2</sub> is similar for <sup>18</sup>F-FMISO and <sup>18</sup>F-HX4, but that the model parameters need to be adjusted for the latter.</p> <p><b>Conclusions:</b> A non-linear conversion function between uptake and oxygen partial pressure for <sup>18</sup>F-FMISO-PET could be applied to <sup>18</sup>F-HX4 images to delineate hypoxic sub-volumes of similar size, shape, and relative location as based directly on the uptake. In order to apply the model for e.g., dose-painting, new parameters need to be derived for the accurate calculation of dose-modifying factors for this tracer.</p