Radiofrequency Exposure Levels in Greece.

Medical Physics Department (Medical School, University of Thessaly) participated in a Greek National EMF research program (EDBM34) with the scope to measure and evaluate radiofrequency (RF) exposure (27-3000 MHz) in areas of sensitive land use. A thousand (1000) measurements were carried out at two "metropolitan locations" (Athens and Thessaloniki: 624 points) and several rest urban/rural locations (376 points). SRM 3006 spectrum analyzer manufactured by Narda Safety Test Solutions was used. The broadband mean electric field in metropolitan areas was 0.41 V/m, while in the rest of Greece was 0.36 V/m. In metropolitan areas, the predominant RF source was the TV and Radio FM signals (36.2% mean contribution to the total RF exposure level). In the rest areas, the predominant source was the systems of the meteorological and military/defensive service (31.1%). The mobile sector contributed 14.9% in metropolitan areas versus 12.2% in the rest of Greece. The predominant mobile source was 900 MHz in both cases (4.5% in metropolitan areas vs. 3.3% in the rest of Greece). The total exposure from all RF sources complied with the International Commission on Non-Ionizing Radiation Protection (ICNIRP) 2020 safety guidelines [ICNIRP, 2020]. The maximum exposure level was 0.129% of the limit for the metropolitan areas vs. 0.110% for the rest of Greece. Nonremarkable differences between metropolitan areas' exposure and the rest of Greece. In most cases, new 5 G antennas will be added to the existing base stations. Thus, the total exposure may be increased, leading to higher safety distances. © 2023 Bioelectromagnetics Society.

A statistical analysis for RF-EMF exposure levels in sensitive land use: A novel study in Greek primary and secondary education schools.

BACKGROUND: The increasing popularity of mobile phones and the expansion of network infrastructure in Greece have given rise to public concerns about potential adverse health effects on sensitive groups, such as children, from long-term radio-frequency (RF) electromagnetic fields (EMFs) exposure. According to Greek law the RF limit values for sensitive land use (schools, hospitals, etc) have been set to 60% of those recommended by EU standard and 70% for the general population. AIMS: The objective of this study is to estimate mean RF-EMF exposure levels of Greek primary and secondary edu-cation schools located in urban environments. METHODS: In selecting the minimum sample size we observed that the variance of the random variable was unknown, as there has been no similar previous study in Greece with schools as the target population. For this reason, a pilot study was conducted in 65 schools in order to estimate the standard deviation of the population and use that value to calculate the minimum sample size. Using a random machine num-ber generator contracted in R based on pseudo-random number algorithms, we obtained a sample of 492 schools in order to estimate the mean value for RF-EMF radiation sources in the 27 MHz-3GHz range in schools within urban environments in Greece. RESULTS: We have performed the appropriate hypothesis test to get that there is sufficient evidence at the α = 0.05 level to conclude that the mean value for RF-EMF radiation sources in the 27 MHz-3GHz range, in schools within urban environments in Greece, is equal to 0.42 V/m, also a 95% confidence interval for the mean value is (0.4024, 0.4395)] with central value equal to the sample mean 0.4209. CONCLUSION: In conclusion, the exposure level in the locations tested are both below 60% of the highest limit set by ICNIRP (International Commision on Non-Ionizing Radiation Protection) regarding sensitive land use.

Application of Radiomics and Decision Support Systems for Breast MR Differential Diagnosis.

Over the years, MR systems have evolved from imaging modalities to advanced computational systems producing a variety of numerical parameters that can be used for the noninvasive preoperative assessment of breast pathology. Furthermore, the combination with state-of-the-art image analysis methods provides a plethora of quantifiable imaging features, termed radiomics that increases diagnostic accuracy towards individualized therapy planning. More importantly, radiomics can now be complemented by the emerging deep learning techniques for further process automation and correlation with other clinical data which facilitate the monitoring of treatment response, as well as the prediction of patient's outcome, by means of unravelling of the complex underlying pathophysiological mechanisms which are reflected in tissue phenotype. The scope of this review is to provide applications and limitations of radiomics towards the development of clinical decision support systems for breast cancer diagnosis and prognosis.

The role of diffusion and perfusion weighted imaging in the differential diagnosis of cerebral tumors: a review and future perspectives.

The role of conventional Magnetic Resonance Imaging (MRI) in the detection of cerebral tumors has been well established. However its excellent soft tissue visualization and variety of imaging sequences are in many cases non-specific for the assessment of brain tumor grading. Hence, advanced MRI techniques, like Diffusion-Weighted Imaging (DWI), Diffusion Tensor Imaging (DTI) and Dynamic-Susceptibility Contrast Imaging (DSCI), which are based on different contrast principles, have been used in the clinical routine to improve diagnostic accuracy. The variety of quantitative information derived from these techniques provides significant structural and functional information in a cellular level, highlighting aspects of the underlying brain pathophysiology. The present work, reviews physical principles and recent results obtained using DWI/DTI and DSCI, in tumor characterization and grading of the most common cerebral neoplasms, and discusses how the available MR quantitative data can be utilized through advanced methods of analysis, in order to optimize clinical decision making.

A review of PET normalization: striving for count rate uniformity.

The advent of PET instrumentation signaled the beginning of a new perspective in nuclear medicine diagnostic imaging. PET systems rely on several corrections that must be applied in order to establish accurate and reliable quantification. The inherent properties of PET detector architecture and the crystals themselves are sources of different types of systematic and random errors with subsequent count rate variability that should be accounted for. Normalization is the correction dealing with these errors. In this work, the reasons resulting in this variability are explored and the different normalization approaches are described. Special focus is paid to component-based normalization, with an attempt to describe the discrete factors and discuss the underlying mechanisms of their contribution to sensitivity variations of the lines of response.

Impact of beam quality on megavoltage radiotherapy treatment techniques utilizing gold nanoparticles for dose enhancement.

This study determines the optimal clinical scenarios for gold nanoparticle dose enhancement as a function of irradiation conditions and potential biological targets using megavoltage x-ray beams. Four hundred and eighty clinical beams were studied for different potential cellular or sub-cellular targets. Beam quality was determined based on a 6 MV linac with and without a flattening filter for various delivery conditions. Dose enhancement ratios DER = D(GNP)/D(water) were calculated for all cases using the GEANT4 Monte Carlo code and the CEPXS/ONEDANT radiation transport deterministic code. Dose enhancement using GEANT4 agreed with CEPXS/ONEDANT. DER for unflattened beams is ∼2 times larger than for flattened beams. The maximum DER values were calculated for split-IMRT fields (∼6) and for out-of-field areas of an unflattened linac (∼17). In-field DER values, at the surface of gold nanoparticles, ranged from 2.2 to 4.2 (flattened beam) and from 3 to 4.7 (unflattened beams). For a GNP cluster with thicknesses of 10 and 100 nm, the DER ranges from 14% to 287%. DER is the greatest for split-IMRT, larger depths, out-of-field areas and/or unflattened linac. Mapping of a GNP location in tumor and normal tissue is essential for efficient and safe delivery of nanoparticle-enhanced radiotherapy.

hTERT regulation by NF-κB and c-myc in irradiated HER2-positive breast cancer cells.

PURPOSE: Telomerase activity (TA), frequently observed in cancer, compensates for telomere shortening thus preventing cell senescence and conferring resistance to therapy. In the present study, we investigated the expression of human telomerase reverse transcriptase (hTERT) and TA and their regulation, as well as apoptotic rates and correlation with the presence of human epidermal growth factor receptor 2 (HER2), in irradiated tumour-derived breast cancer cells. MATERIALS AND METHODS: In 50 breast cancer tissue samples hTERT mRNA expression and TA were correlated with cell features (HER2, Estrogen and Progesterone Receptor status). Cells from six samples were then irradiated with 10 and 20 Gy; apoptotic rates were measured by flow cytometry, hTERT mRNA expression by real-time polymerase chain reaction and TA by telomeric repeat amplification protocol assay, at 24-144 h post-irradiation. Chromatin immunoprecipitation was performed to investigate hTERT and cellular-myelocytomatosis (c-myc) promoters' activity. HER2 gene knockdown was performed using small interfering RNA technology. RESULTS: hTERT/TA were found increased only in irradiated HER2-positive cells, which were found to be more radioresistant, while HER2 knockdown led to hTERT/TA downregulation. HER2 was found to mediate hTERT expression through activation of Nuclear Factor-kappa B (NF-κB) and c-myc. CONCLUSIONS: The present study suggests that following irradiation, HER2 receptor activates hTERT/telomerase, increasing the breast cancer cells' survival potential, through sequential induction of transcription factors NF-κΒ and c-myc.

Patient-specific internal radionuclide dosimetry.

The development of patient-specific treatment planning systems is of outmost importance in the development of radionuclide dosimetry, taking into account that quantitative three-dimensional nuclear medical imaging can be used in this regard. At present, the established method for dosimetry is based on the measurement of the biokinetics by serial gamma-camera scans, followed by calculations of the administered activity and the residence times, resulting in the radiation-absorbed doses of critical organs. However, the quantification of the activity in different organs from planar data is hampered by inaccurate attenuation and scatter correction as well as because of background and organ overlay. In contrast, dosimetry based on quantitative three-dimensional data can be more accurate and allows an individualized approach, provided that all effects that degrade the quantitative content of the images have been corrected for. In addition, inhomogeneous organ accumulation of the radionuclide can be detected and possibly taken into account. The aim of this work is to provide adequate information on internal emitter dosimetry and a state-of-the-art review of the current methodology and future trends.

A radionuclide dosimetry toolkit based on material-specific Monte Carlo dose kernels.

OBJECTIVE: We sought to develop a user-friendly dosimetry toolkit that should aid the improvement of the quality of radionuclide therapy, which is critically dependent on patient-specific planning of each treatment. METHODS: In this work, we present a new toolkit suitable for indicative radionuclide dose calculation. The software is built using open source tools and it uses dose kernels calculated using the Geant4 Application for Tomographic Emission simulation toolkit. In addition, a method that uses kernel data to extract a material-specific dose absorption factor is described and a proof of concept is given. In this work, time dependency and organ sensitivity are not modeled. RESULTS: The developed software utilizes Monte Carlo calculated dose kernels and proposes a fast dose calculation method. Using computed tomography or magnetic resonance imaging it can provide a more accurate and personalized indicative dose map. CONCLUSION: Dosimetry based on quantitative three-dimensional data is more accurate and allows a more individualized approach in patient therapy. Moreover, the use of this toolkit with the standardization for data collection and processing will increase the accuracy as well as the compatibility of radiation dose.

A free software for the evaluation and comparison of dose response models in clinical radiotherapy (DORES).

PURPOSE: The aim of this work was to develop a user-friendly and simple tool for fast and accurate estimation of Normal Tissue Complication Probabilities (NTCP) for several radiobiological models, which can be used as a valuable complement to the clinical experience. MATERIALS AND METHODS: The software which has been named DORES (Dose Response Evaluation Software) has been developed in Visual Basic, and includes three NTCP models (Lyman-Kuther-Burman (LKB), Relative Seriality and Parallel). Required input information includes the Dose-Volume Histogram (DVH) for the Organs at Risk (OAR) of each treatment, the number of fractions and the total dose of therapy. RESULTS: NTCP values are computed, and subsequently placed in a spreadsheet file for further analysis. A Dose Response curve for every model is automatically generated. Every patient of the study population can be found on the curve since by definition their corresponding dose-response points fall exactly on the theoretical dose-response curve, when plotted on the same diagram. CONCLUSION: Distributions of absorbed dose alone do not provide information on the biological response of tissues to irradiation, so the use of this software may aid in the comparison of outcomes for different treatment plans or types of treatment, and also aid the evaluation of the sensitivity of different model predictions to uncertainties in parameter values. This was illustrated in a clinical case of breast cancer radiotherapy.

Dosimetric and radiobiological evaluation of dose distribution perturbation due to head heterogeneities for Linac and Gamma Knife stereotactic radiotherapy.

INTRODUCTION: In SRT/SRS, dedicated treatment planning systems are used for the calculation of the dose distribution. The majority of these systems utilize the standard TMR/OAR formalism for dose calculation as well as they usually neglect any perturbation due to head heterogeneities. The aim of this study is to examine the errors due to head heterogeneities for both absolute and relative dose distributions in stereotactic radiotherapy. MATERIALS AND METHODS: Dosimetric measurements in phantoms have been made for linac stereotactic irradiation. CT-based phantoms have been used for Monte Carlo simulations for both linac-based stereotactic system and Gamma Knife unit. Absolute and relative dose distributions have been compared between homogeneous and heterogeneous media. DVH and TCP results are presented for all cases. RESULTS: The maximum absolute dose difference at the isocenter was 2.2% and 6.9% for the linac and Gamma Knife respectively. The impact of heterogeneity in the target DVH was minor for the linac technique whereas considerable difference was observed for the Gamma Knife treatment. This was reflected also to the radiobiological evaluation, where the maximum TCP difference for the linac system was 2.7% and for the Gamma Knife was 4%. DISCUSSION AND CONCLUSIONS: The errors rising from the existence of head heterogeneities are not negligible especially for the Gamma Knife which uses lower energy beams. The errors of the absolute dose calculation could be easily eliminated by implementing a simple heterogeneity correction algorithm at the TPS. Nevertheless, the errors for not taking into account the lateral electron transport would require a more sophisticated approach and even direct Monte Carlo calculation.

Geometrical pre-planning for conformal radiotherapy.

The optimum selection of beams and arcs in conformal techniques is of the outmost importance in modern radiotherapy. In this work we give a description of an analytic method to aid optimum selection, which is based on minimizing the intersection between beams and organs at risk (OAR) and on minimizing the intersection between the beam and the planning target volume (PTV). An arc-selection function that permits selection of irradiation arcs based on individual beam feasibility is introduce. The method simulates the treatment process by defining a computed beam feasibility, for every possible set of gantry-table angles, by taking into account accurately computer intersection volumes between the OAR and beams. The beams are shaped to conform the target using realistic parameters for the treatment process. The results are displayed on a virtual sphere centred at the isocenter with color-coded regions indicating beam feasibility. Arcs selections are performed by searching the map for successive gantry positions at a certain table angle, with feasibility values greater than a user-specified threshold. The accuracy of the method was confirmed by using geometrical regular shapes, as well as real clinical cases.

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.

Monte Carlo dosimetric evaluation of high energy vs low energy photon beams in low density tissues.

BACKGROUND AND PURPOSE: Low megavoltage photon beams are often the treatment choice in radiotherapy when low density heterogeneities are involved, because higher energies show some undesirable dosimetric effects. This work is aimed at investigating the effects of different energy selection for low density tissues. PATIENTS AND METHODS: BEAMnrc was used to simulate simple treatment set-ups in a simple and a CT reconstructed lung phantom and an air-channel phantom. The dose distribution of 6, 15 and 20 MV photon beams was studied using single, AP/PA and three-field arrangements. RESULTS: Our results showed no significant changes in the penumbra width in lung when a pair of opposed fields were used. The underdosage at the anterior/posterior tumor edge caused by the dose build-up at the lung-tumor interface reached 7% for a 5 x 5 cm AP/PA set-up. Shrinkage of the 90% isodose volume was noticed for the same set-up, which could be rectified by adding a lateral field. For the CT reconstructed phantom, the AP/PA set-up offered better tumor coverage when lower energies were used but for the three field set-up, higher energies resulted to better sparing of the lung tissue. For the air-channel set-up, adding an opposed field reduced the penumbra width. Using higher energies resulted in a 7% cold spot around the air-tissue interface for a 5 x 5 cm field. CONCLUSIONS: The choice of energy for treatment in the low density areas is not a straightforward decision but depends on a number of parameters such as the beam set-up and the dosimetric criteria. Updated calculation algorithms should be used in order to be confident for the choice of energy of treatment.

An inhomogeneity correction algorithm for irregular fields of high-energy photon beams based on Clarkson integration and the 3D beam subtraction method.

A number of treatment-planning systems still use conventional correction methods for body inhomogeneities. Most of these methods (power law method, tissue-air ratio (TAR), etc.) consider only on-axis points, rectangular fields, and inhomogeneous slabs covering the whole irradiating field. A new method is proposed that overcomes the above limitations. The new method uses the principle of the Clarkson method on sector integration to take into account the position and lateral extent of the inhomogeneity with respect to the point of calculation, as well as the shape of the irradiating field. The field is divided into angular sectors, and each sector is then treated separately for the presence of inhomogeneities using a conventional correction method. Applying this method, we can predict the correction factors for Co-60 and 6-MV photon beams for irregular fields that include inhomogeneities of lower or higher densities relative to water. Validation of the predicted corrections factors was made against Monte Carlo calculations for the same geometries. The agreement between the predicted correction factors and the Monte Carlo calculations was within 1.5%. In addition, the new method was able to predict the behavior of the correction factor when the point of calculation was approaching or moving away from the interface between two materials.

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.

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.