BackgroundPurpose of the present work was to investigate thermoluminescent dosimeters (TLDs) response to intraoperative electron radiation therapy (IOERT) beams. In an IOERT treatment, a large single radiation dose is delivered with a high dose-per-pulse electron beam (2–12 cGy/pulse) during surgery. To verify and to record the delivered dose, in vivo dosimetry is a mandatory procedure for quality assurance. The TLDs feature many advantages such as a small detector size and close tissue equivalence that make them attractive for IOERT as in vivo dosimeters.MethodsLiF:Mg,Ti dosimeters (TLD-100) were irradiated with different IOERT electron beam energies (5, 7 and 9 MeV) and with a 6 MV conventional photon beam. For each energy, the TLDs were irradiated in the dose range of 0–10 Gy in step of 2Gy. Regression analysis was performed to establish the response variation of thermoluminescent signals with dose and energy.ResultsThe TLD-100 dose-response curves were obtained. In the dose range of 0–10 Gy, the calibration curve was confirmed to be linear for the conventional photon beam. In the same dose region, the quadratic model performs better than the linear model when high dose-per-pulse electron beams were used (F test; p<0.05).ConclusionsThis study demonstrates that the TLD dose response, for doses ≤10Gy, has a parabolic behavior in high dose-per-pulse electron beams. TLD-100 can be useful detectors for IOERT patient dosimetry if a proper calibration is provided.

Hypofractionation for localized prostate cancer treatment is rapidly spreading in the medical community and it is supported by radiobiological evidences (lower α/β ratio compared with surrounding tissues). Stereotactic body radiation therapy (SBRT) is a technique to administer high doses with great precision, which is commonly performed with CyberKnife (CK) in prostate cancer treatment. Since the CyberKnife (CK) is not available at all radiotherapy center, alternative SBRT techniques are available such as Volumetric Modulated Arc Therapy (VMAT) and Helical Tomotherapy (HT). The aim of the present study was to compare the dosimetric differences between the CK, VMAT, and HT plans for localized prostate cancer treatment. Seventeenpatients have been recruited and replanned using VMAT and HT to this purpose: they received the treatment using the CK with a prescription of 36.25 Gy in 5 fractions; bladder, rectum and penis bulb were considered as organs at risk (OAR). In order to compare the techniques, we considered DVHs, PTV coverage, Conformity Index and new Conformity Index, Homogeneity Index, beam-on time and OARs received dose. The 3 treatments methods showed a comparable coverage of the lesion (PTV 95%: 99.8 ± 0.4% CK; 98.5 ± 0.8% VMAT; 99.4 ± 0.5% HT. P < .05) and good sparing of OARs. Nevertheless, the beam-on time showed a significant difference (37 ± 9 m CK; 7.1 ± 0.3 m VMAT; 17 ± 2 m HT. P < .05). Our results showed that, although CK is the best SBRT technique for prostate cancer treatment, in case this technology is not available, it can be replaced by a similar treatment delivered by VMAT technique. VMAT can be administrated only if it has an appropriate Image Guided Radiation Therapy (IGRT) tracking system.

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Radon is a major source of ionizing radiation exposure for the general population. It is known that exposure to radon is a risk factor for the onset of lung cancer. In this study, the results of a radon survey conducted in all districts of a Public Healthcare in Italy, are reported. Measurements of indoor radon were performed using nuclear track detectors, CR-39. The entire survey was conducted according to a well-established quality assurance program. The annual effective dose and excess lifetime cancer risk were also calculated. Results show that the radon concentrations varied from 7 ± 1 Bq/m3 and 5148 ± 772 Bq/m3, with a geometric mean of 67 Bq/m3 and geometric standard deviation of 2.5. The annual effective dose to workers was found to be 1.6 mSv/y and comparable with the worldwide average. In Italy, following the transposition of the European Directive 59/2013, great attention was paid to the radon risk in workplaces. The interest of the workers of the monitored sites was very high and this, certainly contributed to the high return rate of the detectors after exposure and therefore, to the presence of few missing data. Although it was not possible to study the factors affecting radon concentrations, certainly the main advantage of this study is that it was the first in which an entire public health company was monitored in regards to all the premises on the underground and ground floor.

AbstractThe population is continuously exposed to a background level of ionizing radiation due to the natural radioactivity and, in particular, with radon (222Rn). Radon gas has been classified as the second leading cause of lung cancer after tobacco smoke [1]. In the confined environment, radon concentration can reach harmful level and vary accordingly to many factors. Since the primary source of radon in dwellings is the subsurface, the risk assessment and reduction cannot disregard the identification of the local geology and the environmental predisposing factors. In this article, we propose a new methodology, based on the computation of the Gini coefficients at different spatial scales, to estimate the spatial correlation and the geographical variability of radon concentrations. This variability can be interpreted as a signature of the different subsurface geological conditions. The Gini coefficient computation is a statistical tool widely used to determine the degree of inhomogeneity of different kinds of distributions. We generated several simulated radon distributions, and the proposed tool has been validated by comparing the variograms based on the semi-variance computation with those ones based on the Gini coefficient. The Gini coefficient variogram is shown to be a good estimator of the inhomogeneity degree of radon concentration. Indeed, it allows to better constrain the critical distance below which the radon geological source can be considered as uniform at least for the investigated length scales of variability; it also better discriminates the fluctuations due to the environmental predisposing factors from those ones due to the random spatially uncorrelated noise.