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A Greek version of the reserch scientific activities of this topic can be found in odf.pdf  format.

State of the art

Humans are being constantly exposed to electromagnetic radiation (EMR), including sunlight, cosmic rays and terrestrial radiation. However, a substantial increase in exposure to non-ionizing radiation and especially to low frequency electromagnetic radiation (LF-EMR), started in the early 20^th century with the generation of artificial electromagnetic fields and continued with the development of power stations, radios, radars, televisions, computers, mobile phones, microwave ovens and numerous devices used in medicine, industry and home. These technological advances have aroused concerns about the potential health risks associated with unprecedented levels of EMR exposure (Ahlbom et al 2008; HPA 2004a, 2004b; NRPB 2003; SCENIHR 2007, 2009; Valberg et al 2007).

The amount of energy deposited by EMR and the nature of its absorption are determined by the frequency and type of incident radiation and by the type of tissue that absorbs it. Exposure to multiple sources of non-ionizing radiation (Table 1), including residential exposure to high-voltage power lines, transformers, and domestic electrical installations, varies in duration and depends on the distance from the source. Exposure is usually due to low-frequency (LF) or extremely low- frequency (ELF) EMR radiation, it is continuous and rises among populations of the industrialized world. Exposures to ELF electric and magnetic fields emanating from generation, transmission and uses of electricity constitute a ubiquitous part of modern life (CENELEC 2008; EU 1999). Besides LF-EMR and ELF-EMR radiation, individuals are increasingly exposed to radio frequencies (RF) from television (TV) towers, radio stations, mobile phone/wi-fi systems and personal computers. In contrast to ionizing radiation, where natural sources contribute the largest proportion to population exposure, man-made non-ionizing sources tend to dominate the human exposure to electromagnetic fields. In all cases of EMR, exposure depends not only on the strength of the field but also on the distance from the source and, in the case of directional antennas, on the proximity to the main beam. The field strength often decreases rapidly with distance (IEC 2005; IEEE 2004, 2005a, 2005b; WHO 2002, 2006, 2010, 2011). There exist several possible sources of RF fields to which people may be exposed. Within the frequency band from 3 kHz to 300 GHz the sources include those used for telecommunications or security. Communications equipment cover most of the frequency range with TV and radio transmissions frequencies from about 200 kHz to 900 MHz. Personal telecommunication devices operate over the range of frequencies from 100 MHz to 3 GHz. Table 1 summarises the different types, frequency ranges and sources of non-ionizing radiation, the energy of which, even at 300 GHz, is still around three orders of magnitude smaller than the ionization threshold in matter (EPA 2013). Application and rapid development of technologies using radiofrequencies (RFs) induced a substantial increase in exposure among the general population, especially over the last 20 years. RFs are emitted by numerous sources operating in different frequency bands (Table 2). These sources can be subdivided in two broad categories: (a) ambient sources, such as broadcast transmitters (radio, TV), or mobile phone base stations and (b) personal sources, such as mobile phones, in-house bases for cordless phones (DECT – Digital enhanced cordless telephony), microwave ovens, wireless networks. Consequently, exposure to RF varies considerably across persons, space and time (Frei et al 2009a, 2009b; Viel et al 2009a). There are, therefore, significant challenges in assessing the sources of variation and related uncertainty, but also in identifying exposure relevant factors (Ahlbom et al 2004; Joseph et al 2009, 2010b, 2012; Joseph and Verloock 2010a, Mann et al 2005; Röösli et al 2008, 2010; Viel et al 2009a, 2009b; Vrijheid et al 2008).

The signals generated by various sources may be different in type. The underlying waveform from a source is usually sinusoidal, the signal however may then be amplitude modulated (AM), frequency modulated (FM), pulse modulated (e.g. radar) or modulated in a more complex way (e.g. digital radio) (CENELEC 2008; ECC 2006; NRPB 2003). Exposure to EMR sources is commonly described by electric and magnetic field strength, which is however measured around the subject. Any biological effects would be the result of the exposure within the body and this is difficult to be measured directly. As it is already mentioned, the nature of the field and the characteristics of the source differ considerably from each other (Frei et al 2009a, 2009b; HPA 2004a,2004b, 2004c, 2012). At frequencies below 100 kHz, the physical quantity associated with most biological effects is the electric field strength in tissue (ICNIRP 1998, 2009). More appropriate quantity at higher frequencies is the specific absorption rate, SAR, which is related to the second power of the electric field strength in tissue (IEC 2005;NRPB 2003; SAR Database 2012). At frequencies above about 1 MHz, the orientation of the body with respect to the incident field becomes increasingly important, because the body behaves as an antenna (Fig.1), absorbing energy in a resonant manner (for standing adults the maximum absorption occurs when frequency varies between 70-80 MHz, a value that depends on the isolation status relative to the ground). As frequency increases above the resonance region, energy absorption becomes confined to the surface layers of the body, limited to the skin when frequency reaches a few tens of GHz (Ahlbom et al 2004, 2008; HPA 2012; ICNIRP 2009; NRPB 2003; SCENIHR 2007, 2009).

Electric field can be measured using suitable sensors such as small dipoles. Studies to evaluate internal exposure are carried out either by using computational methods or by conducting measurements in phantoms. Computational methods rely on the detailed anatomical information, in addition to information on the electrical properties of the different tissues for each frequency regime. The electric field at various points inside simple phantoms is usually measured via a robotically positioned probe, small enough to minimise the changes in the fields produced by its presence. In simple cases, estimation of the internal exposure can rely on measurement of the field outside the body accompanied by reasonable approximations (HPA 2012; NRPB 2003; WHO 2002, 2006, 2010, 2011). The strength of the electric or magnetic field can be indicated by its peak value, although it is often denoted by the rms value. For a sinusoidally varying field, the rms value equals to the peak value divided by 1.4. The power density represents the intensity of the electromagnetic field and is determined by the amount of electromagnetic energy passing through a point per unit area perpendicular to the direction of propagation (NRPB 2003). The power density of an electromagnetic wave is equal to the product of the electric and magnetic fields, although this is not true in near-field regions, i.e. when the distance from the source is comparable to the wavelength. In the near-field region the electric and magnetic fields are neither perpendicular to each other nor in phase. In general, the fields can be divided into two components: radiative and reactive (NRPB 2003). The radiative component is that part of the field which propagates energy away from the source, while the reactive component can be thought of as relating to energy stored in the region around the source. The reactive component dominates close to the source and the stored energy can be absorbed by people standing in the near-field region. However, any measurement in the near-field region is particularly difficult since, even the introduction of a small probe, can substantially alter the field. Magnetic field is measured with small loop sensors. The boundary radius depends on wavelength. Distances of about one-sixth of a wavelength from the source, define approximately the near-field boundary. The frequency range of 3 kHz to 300 GHz corresponds to the wavelength range of 100 km to 1 mm (HPA 2012; ICNIRP 2009; Lauer et al 2013; NRPB 2003;Valberg et al 2007).

Antennas generate electromagnetic fields across the spectrum. At very low frequencies the structures are massive with support towers 200-250 m high and the fields may be extensive over the site area. Electric field strengths of several hundred Vm^-1 and magnetic field strengths in the range 2-15 Am^-1 (52 Am^-1 close to low frequency towers) may be encountered. The currents induced in body (Fig. 1) flow to ground through the feet and can reach a theoretical maximum of 10-12 mA per Vm^-1 at a resonance frequency for an electrically grounded adult (the current is reduced to half of these values when the adult is wearing shoes) (IEEE 2005b; National Academy of Sciences 2006; Neubauer et al 2007; SCENIHR 2007, 2009). Nevertheless, the average magnetic flux density (in µT) is, generally, considered to be below maximum exposure limits established by different organizations, such as the International Council of Non-Ionizing Radiation Protection (ICNIRP, 1998) or the National Radiological Protection Board (NRPB 2003). The International Commission on Non-Ionizing Radiation Protection and the UK's National Radiological Protection Board, together with the Health Protection Agency (HPA), the Institute of Electrical and Electronics Engineers (IEEE), the International Telecommunication Union Recommendation (ITU-R 2005) and European Union committees, reviewed many relevant studies and recommended guidelines on restrictions for exposure to electromagnetic fields.

Recommended restrictions are based on biological data relating to thresholds for adverse direct and indirect effects of acute exposure. Direct effects are those resulting from the interactions of electromagnetic fields with the human body (basic restrictions). Indirect effects are those resulting from an interaction between electromagnetic fields, an external object and the human body (e.g. to avoid burns). As compliance with the basic restrictions cannot be easily determined, ICNIRP recommends reference levels as values of measurable field quantities for assessing whether compliance with the basic restrictions is achieved (ICNIRP 1998; NRPB 2003). Table 3 summarises the reference levels for electric field intensity (in V/m), magnetic flux density (in µT) and power density (in W/m²). Corresponding values for occupational exposure are about five times higher (HPA 2012; ICNIRP 1998; NRPB 2003). Radiocommunications Agency (now Ofcom: http://www.ofcom.org.uk/) supported in 2003 measurements in the UK that gave range and geometric mean (in parenthesis) of power density values in μW m^-2 from all signals: (a) indoor 2-1000 (75), (b) outdoor 50-1700 (240) and (c) all locations 3.5-1100 (110) (HPA 2004c; NRPB 2003).

Since the introduction of mobile phones in the early 90s, there has been a constant and rapid increase in the number of base stations. Joseph et al (2010b) compared the total radio frequency electromagnetic field (RF-EMF) exposure in five European countries and found that in outdoor urban environments mobile phone base stations are a major, if not the largest, source of environmental RF-EMF. There has been concern about potential health effects of the electromagnetic waves emitted by these base stations (Neubauer et al 2007; Valberg et al 2007), which have led to studies assessing the relationship between RF-EMF and the health impact on the general population. To date, no consistent health effect has been found (HPA 2012; NRPB 2003; Röösli et al 2010). However, if there are health effects, they are likely to be small and subtle and, as such, large population samples and a reliable exposure assessment are needed to confirm or reject the hypothesis of a certain health effect, minimizing statistical uncertainties (Briggs et al 2012; NRPB 2003; SCENIHR 2007, 2009). In general, in the last few years, several countries have performed measurement studies using exposimeters and some of the results have already been published (Bolte et al 2008; EU 1999; Frei et al 2009a; Joseph et al 2009, 2010b, 2012; Joseph and Verloock 2010a, Röösli et al 2008; Thomas et al 2008a, 2008b; Thuróczy et al 2008; Trcek et al 2007; Viel et al 2009a, 2009b). In some of these studies, measurements were performed in different microenvironments such as offices or outdoor urban areas, to characterize typical exposure levels in these places (microenvironmental studies). Other studies, were population surveys where the personal exposure distribution in the population of interest was determined. The strategies for the recruitment of the study participants as well as the data analysis methods differed between these studies and therefore, a direct comparison of their results is difficult.

In Table 4, Reference Levels for exposure to Electric Field, Magnetic Field and Wave Power Density are shown for mobile phones, as well as Wi-Fi frequencies for general population and workers (in parenthesis), according to ICNIRP and NRPB guidance. The Greek Atomic Energy Agency, according to EU recommendations, made a series of electromagnetic field measurements in selected Greek regions. Table 5 gives average and maximum values of Electric Field, Magnetic Field and Wave Power Density measured, together with the Reference Levels estimated for Greek environment, for mobile phones frequencies. Depending on the particular environmental situation, two groups of Reference Levels are established in Greece: (a) 70 per cent of the proposed values for general purpose and (b) 60 per cent of the proposed values for regions with more sensitive population (GAEA 2010). In Table 5 the 70 per cent Reference Levels are given.

Regarding non-ionizing electromagnetic radiation, the energy carried (and potentially transferred) is measured in electrovolts (eV). Biological tissues exposed to radiofrequencies absorb energy and develop an induced current density from the external field. Specific absorption rate (SAR) is the quantity showing the rate at which energy is absorbed by a particular mass of tissue and depends on the density and the electrical conductivity of the tissue, as well as on the electric field strength (second power) (IEC 2005; NRPB 2003; SAR Database 2012). SAR is measured in watts per kilogram. As SAR varies from point to point, may be ascertained by averaging over a small mass or over the whole body mass. The most commonly used methods for experimental measurement of SAR involve measurement of the internal electric field strength or the rate of temperature rise, both methods however, being very difficult in practice (NRPB 2003).Thermal effects from RF electric fields occur because most biological tissues are electrically conducting. Electric fields inside human tissue generate currents and their dissipation leads to energy absorption and, hence, to increase in temperature. The latter is considered as a cause leading to biological effects. Except thermal effects, non-thermal effects are associated with changes in protein conformation (different dipole moment and energy, transitions that would result in changes in protein folding), conformational changes in the ATPases associated with cell membrane ion channels (ion pumping across membranes produced by RF fields), heat shock proteins (an increase in unfolded protein produces an increase in aggregation), changes in binding ability of Ca ions to cell receptor proteins. In general, the interaction of RF magnetic fields with tissue would be expected to be much weaker than that of RF electric fields. Possible exceptions might be expected to include interaction with tissues like human brain, containing particles of magnetite. RF magnetic fields could interact either by ferromagnetic resonance or by mechanical activation of cellular ion channels. Positive findings are not yet confirmed. The literature on non-thermal effects is inconsistent (Ahlbom et al 2004, 2008; HPA 2004a, 2004b, 2004c, 2012; ICNIRP 2009; NRPB 2003; WHO 2002, 2006, 2011). With regard to the effects of RF radiation on the nervous system, IEGMP (Independent Expert Group on Mobile Phones) concluded that changes in neuronal excitability will occur when exposure induces significant heating by about 1 grad or more (NRPB 2003; SCENIHR 2007, 2009).

Despite the rapid growth of new technologies using RFs, information on the exposure of individual persons for these and older RF sources is scarce and even less is known about the relative importance of different sources. Existing RF sources are operated in different frequency bands and can be subdivided in two broad categories: (a) external sources, such as broadcast transmitters (radio,TV) or mobile phone base stations, and (b) internal sources, such as mobile phones, in-house bases for cordless phones (DECT), or microwave ovens. The relative contribution of these sources to exposure depends on individual home and workplace circumstances. For a given source, the actual exposure to RF depends on a number of factors. Regarding mobile phones, the characteristics of a certain phone (particularly type and location of the antenna), the way the phone is handled, the distance from the base station, the frequency of handovers and RF traffic conditions are of prime importance (Ahlbom et al 2004, 2008; Briggs et al 2012; Inyang et al 2008). Similarly, RF fields from mobile phone base stations also exhibit a complex pattern, influenced by numerous factors, such as, the output power of the antenna, the direction of transmission, the attenuation due to obstacles or walls, and any existing scattering from buildings and trees (Joseph et al 2009, 2010b, 2012; Joseph and Verloock 2010a, Mann et al 2005; Neubauer et al 2007). There are, therefore, significant challenges in assessing the exposure of individuals in the general population to RF signals, including the number and range of sources involved and the effect of the environment on signal's strength, as people move around. In principle, two different types of RF-EMF exposure sources can be distinguished: (a) sources which are applied close to the human body usually causing high and periodic short-term exposure mainly to the head (e.g. mobile phones) and (b) environmental sources which, in general, cause lower but relatively continuous whole-body exposure (e.g. mobile phone base stations). While exposure from mobile phones can be assessed using self-reported mobile phone use or operator data (Vrijheid et al 2008), valid assessment of exposure to environmental fields is more challenging. Frei et al (2009a) studied temporal and spatial variabilities of personal exposure to radio frequency electromagnetic fields. They concluded that exposure to RF-EMF varied considerably between persons and locations but was fairly consistent within persons. Mobile phone handsets, mobile phone base stations and cordless phones were important sources of exposure in urban Switzerland. Their results revealed mean weekly exposure values to all RF-EMF sources equal to 0.13 mW/m² (0.22 V/m) with the range of individual means between 0.014–0.881 mW/m²). Exposure was mainly due to mobile phone base stations (32.0%), mobile phone handsets (29.1%) and digital enhanced cordless telecommunications (DECT) phones (22.7%). Persons owning DECT phones (total mean 0.15 mW/m²) or mobile phones (0.14 mW/m²) were exposed more than those not owning DECT or mobile phones (0.10 mW/m²). Mean values were highest in trains (1.16 mW/m²), airports (0.74 mW/m²) and tramways or buses (0.36 mW/m²) and higher during daytime (0.16 mW/m²) than night-time (0.08 mW/m²). However Frei et al (2010) claim that “exposure to RF-EMF in everyday life is highly temporally and spatially variable due to various emitting sources like broadcast transmitters or wireless local area networks (W-LAN). The use of personal exposure meters (exposimeters) has been recommended in order to characterize personal exposure to RF-EMFs (Neubauer et al 2007). Several exposure assessment studies have been conducted so far using exposimeters (Joseph et al 2008; Kühnlein et al 2009; Thomas et al 2008a; Thuróczy et al 2008; Viel et al 2009b), which allow capture of exposure from all relevant RF-EMF sources in the different environments where a study participant spends time (Neubauer et al 2007; Radon et al 2006). They are suitable for measuring RF-EMF from environmental far-field sources like mobile phone base stations, but are less able to accurately measure exposure to personal mobile or cordless phones (Inyang et al 2008) because measurements during personal phone calls are dependent on the distance between the emitting device and the exposimeter”.Joseph et al reported their research (2012) about in situ electromagnetic radio frequency exposure to existing and emerging wireless technologies by using spectrum analyzer measurements at 311 locations (68 indoor, 243 outdoor), subdivided into six different categories (rural, residential, urban, suburban, office and industrial), geographically spread across Belgium, The Netherlands and Sweden. The maximal total value was measured in a residential environment and found to be equal to 3.9 Vm^-1, mainly due to the GSM900 signal (11 times below the ICNIRP reference levels). Exposure ratios for maximal electric field values ranged from 0.5% (WiMAX – Worldwide Interoperability for Microwave Access) to 9.3% (GSM900) for the 311 measurement locations. The exposure ratios for total exposures varied from 3.1% for the rural environment to 9.4% for the residential environment. Exposures were log-normally distributed and were in general the lowest in rural environments and the highest in urban environments. The dominating outdoor source was GSM900 (95th percentile of 1.9 Vm^-1) while indoor DECT dominated (95th percentile 1.5 V m^-1 ) if present. The average contribution to the total electric field was more than 60% for GSM. Except for the rural environment, average contributions of UMTS-HSPA (High Speed Packet Access) were more than 3%. The contributions of LTE (Long Term Evolution) and WiMAX were on average less than 1%.

As far as exposure to non-ionizing radiation is concerned, absorbed energy from human body is very low, but becomes significant if it is continuous for very long periods of time accounting the fact that the related effects are not yet well known.

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52. UNSCEAR United Nations Scientific Committee on the Effects of Atomic Radiation, 2009. http://www.unscear.org/docs/Radon-distrib.pdf. Accessed May 2013.

53. Valberg,PA, van Deventer, TE, Repacholi,MH., 2007. Workgroup report: base stations and wireless networks-radiofrequency (RF) exposures and health consequences. Environ Health Perspect 115, 416–424.

54. Viel,J.F., Cardis,E., Moissonnier,M., deSeze,R., Hours,M., 2009a. Radiofrequency exposure in the French general population: band, time, location and activity variability. Environ. Int. 35, 1150–1154.

55. Viel,J.F., Clerc,S., Barrera,C., Rymzhanova,R., Moissonnier,M., Hours,M., Cardis, E., 2009b. Residential exposure to radiofrequency fields from mobile phone base stations, and broadcast transmitters: a population-based survey with personal meter. Occup. Environ. Med. 66, 550–556.

56. Vrijheid,M., Armstrong,B.K., Bedard,D., Brown,J., Deltour,I., Iavarone,I., et al., 2008. Recall bias in the assessment of exposure to mobile phones. J.Expo.Sci. Environ.Epidemiol. 19, 369-381.

57. Wahl E.L., 2010. Environmental Radiation, Lawrence Berkeley National Laboratory, Fact Sheet http://hps.org/documents/environmental_radiation_fact_sheet.pdf. Accessed May 2013.

58. WHO World Health Organization, 2002. Establishing a dialogue on risks from electromagnetic fields. Geneva, Switzerland

59. http://www.who.int/peh- emf/publications/en/emf_final_300dpi_ALL.pdf. Accessed May 2013.

60. WHO World Health Organization, 2006. Electromagnetic fields and public health: base stations and wireless technologies http://www.who.int/peh-emf/publications/factsheets/en/index.html. Accessed May 2013.

61. WHO World Health Organization, 2010. WHO Research Agenda for Radiofrequency Fields. Geneva, Switzerland http://apps.who.int/iris/bitstream/10665/44396/1/9789241599948_eng.pdf. Accessed May 2013.

62. WHO World Health Organization, 2011. Electromagnetic fields and public health: mobile phones. June 2011. Fact sheet N°193. http://www.who.int/mediacentre/factsheets/fs193/en/index.html. Accessed May 2013.

Table1

Frequencies and sources of non-ionizing radiation

High frequency ultraviolet (UV) is considered as ionizing radiation

Table 2

Personal exposure meter frequency bands (EME SPY 120, Satimo, France)

a Global System for Mobile Communications

b Transmitted radio signal from the point of view of a mobile phone

c Received radio signal from the point of view of a mobile phone

d Digital Communication System

e Digital Enhanced Cordless Telephone

f Universal Mobile Telecommunication System

Table 3

ICNIRP reference levels for general public exposure to time-varying electric and magnetic fields (rms values)

f: frequencies as indicated in the column of frequency range

Table 4

Reference Levels for exposure to Electric Field, Magnetic Field and Wave Power Density for mobile phones, as well as Wi-Fi frequencies for general population and workers (in parenthesis), according to ICNIRP and NRPB guidance.

Table 5

Average and maximum values of Electric Field, Magnetic Field and Wave Power Density measured, together with the Reference Levels estimated for Greek environment, for mobile phones frequencies, according to the Greek Atomic Energy Agency.

A Greek version of the reserch scientific activities of this topic can be found in odf.pdf format.

OVERVIEW

Monte Carlo methods have been employed in the study of the X-ray absorption and fluorescence properties of medical imaging scintillator detectors. The X-ray properties are studied as a function of the detector's thickness and the incident photon energy or energy spectrum. Several detector materials have been examined such as Gd₂O₂S, (GOS) Gd₂SiO₅ (GSO) YAlO₃ (YAP), Y₃Al₅O₁₂ (YAG), LuSiO₅ (LSO), LuAlO₃ (LuAP) and ZnS. The spectral or monoenergetic photon exposures are modelled in the range from 10 keV to 25 MeV, covering the energies involved in the Medical Imaging Detectors, namely energies in the X-ray Mammography, X-ray Radiography, X-ray Scintigraphy, CT, Nuclear Medicine, PET/SPECT Scanning and Radiotherapy. Modelling and simulation utilise custom-developed MS-Fortran, GNU-gfortran and GNU-c++ codes and codes in EGCnrcMP, MCNP and GATE/GEANT4.

OVERVIEW

Medical Imaging (MI) has affected diagnostic accuracy in diverging fields of Medicine. Despite the on-going progress of MI, it is still an open issue to achieve low-cost designs with enhanced image quality and reduced human burden. Computational techniques support innovative MI design especially for modalities utilising phosphors/scintillators, viz., materials that emit light when excited by radiation. There is considerable interest nowadays onflat-panel x-ray imaging detectors. Novel technologies are related to new materials in conjunction with state-of-the art optical sensors Interesting approaches concern (I) investigating new nanophosphors with enhanced characteristics and (II) modern Complementary Metal Oxide Semiconductor (CMOS) optical-sensor technology. Any new approach prerequisites intensive research prior to adoption in commercial MI systems.

The research aims in (a) investigating new phosphor and nanophosphor detectors for modern MI systems in combination with different optical sensors, and, (b) developing computational Monte Carlo (MC) methods targeted to the applicability of phosphor and nanophosphor detectors in MI. The outcomesenable (1) the suggestion of optimum phosphor detector-optical sensor combinations under various conditions, and, (2) suggestion of newMI detector designs especially with nanophosphors coupled to CMOS sensors. Whole activity is expected to affect (i) industrial MI applications, and (ii) research of biomedical nanomaterial technology. These will benefit MI industry, health care services, clinical applications and research.

INTRODUCTION

Non invasive MI techniques have developed widely. Related diagnosis refers to structural, functional and physiological processes. Principal branches are (a) transmission and (b) emission imaging. First branch refers to x-rays, transmitted through human body or, diffracted by macromolecules. Characteristic applications are diagnostic radiology, x-ray radiography, fluoroscopy, angiography, computed tomography (CT), portal imaging and protein crystallography. Second branch includes two large categories, namely Single Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET). SPECT and PET utilise radiation emitted by nuclides administered in human body. Administered nuclides trace biochemical and physiological processes as they label critical substrates, ligands, drugs, antibodies, neurotransmitters and other compounds. Through this way functional and physiological information are provided, especially regarding cancer tumours.

Intensive research is implemented in enhancing characteristics of MI systems Special is the concern on investigating new-novel fluorescent materials and nanomaterials emphasising on the optimisation of new detector configurations. Fluorescent materials are widely used in several MI detectors as converters of x-rays to light (van Eijk 2002, Nikl 2006). They include scintillators, phosphors and nanophosphors. They are employed in form of screens or crystals, coupled to optical sensors, as e.g. CCDs, photodiodes and flat panels. Alternative detector configurations utilise photoconductors, which convert x-rays to charge. All types provide the electric signals that are necessary for image formation (van Eijk 2002). Phosphors and scintillators are discriminated according to the time needed for the emission of light. Nevertheless, in MI this time is incorporated in material's properties. Therefore MI phosphors and scintillators are referred altogether. For detection, scintillators are incorporated in suitable designs (van Eijk 2002).The spectral emission properties are important in selecting the appropriate fluorescent material .For example, the distribution of wavelengths of scintillation light is critical for matching a scintillator with available optical sensors. New promising materials and detector geometries have shown very interesting results both in enhancing detector performance and reducing overall cost; the latter rendering systems attractive for commercial production.

Especially regarding emission imaging, considerable is the effort towards non-invasive, high-resolution, small animal imaging technologies. Nonetheless, significant challenges remain to be overcome when, for example, attempting to image a 30-g mouse as compared with a 70-kg human. It is however still difficult to include enough spatial information to obtain meaningful anatomical and functional data. Multiple imaging modalities are available for small-animal molecular imaging including micro-PET, micro-CT, micro-SPECT. State-of-the art instrumentation uses advances in detector technology, including exploitation of solid-state detector technology and modern image-reconstruction techniques. The investigation in this field renders newer generations of scanners of high resolution, sensitivity, and sthroughput time. On the other hand, standard SPECT cameras still use NaI(Tl) single crystals. However, there are some prototypes of small field of view, where other crystals have been tested. Characteristic examples are the YAP, BGO, BaF and CsI(Tl) scintillators. In addition, some detectors employed solid-state detectors-usually CdZnTe- with excellent results. PET cameras are based mainly on BGO, GSO and LSO single crystals. Other scintillators are also proposed for PET prototypes. Mixed scintillators designs, the so called phoswitch detectors, are also under investigation.

Nowadays, special is the interest on flat panels. These are large area x-ray detectors that are position sensitive, i.e., they provide electric signals depending on the interaction site. Due to this fact they exhibit high image quality. For example, in x-ray projection imaging flat panel arrays with phosphor screens or photoconductors, detect attenuation profiles of human body's parts and produce accurate images. Mammography utilises thin phosphor screens or photoconductors which slot scanning devices based on phosphor-CCD detectors (van Eijk 2002). Chest Radiography employes large area flat panel arrays with thick phosphor screens. Fluoroscopy uses flat panels or image intensifiers with phosphor screens of fast response. In this manner, fast real-time images are produced (van Eijk 2002). In CT, ceramic scintillators or crystals are used, while portal imaging employes flat panels of very thick phosphor screens.

It becomes evident that scintillators constitute critical structural parts of detectors of MI systems. International research in the field of MI is focused on optimising performance of detectors involved. Investigations refer to optimization of detectors' geometry, material- for example, type of crystals, collimator and position-sensitive photomultiplier tubes-, electronics readout, data acquisition and image reconstruction. Since detector design affects resolution and sensitivity of the total system, many groups and companies evaluate a number of new materials for specific applications. It is this fact, that renews the necessity for investigating and evaluating new phosphors and nanophosphors for MI. Optimisation of existing MI materials can be achieved by improving their structural elements or image characteristics. Improvement in structure refers to thickness, grain size and columnar structure. Improvement in characteristics refers to enhancement of absorption and intrinsic efficiency and by providing better optical properties. Apart, brandnew designs can be suggested from modelling or experimental results. In addition to phosphors, novel CMOS technologies are under investigation to develop high resolution and low noise optical sensors with “system on chip” properties(Arvanitis et al 2009)In conclusion, further research is still needed in the field of detector optimisation.

Powder scintillator materials have been previously assessed in many fields of diagnostic radiology, namely in general radiography, mammography and computed tomograph. Additionally several single crystal scintillators have been studied for gamma-ray imaging. However, restrictions exist because (1) very limited number of studies are concerned with powder scintillators that might be employed in ring type SPECT detectors; (2) the response of powder scintillators has not been extensively studied in a wide range coating thickness values nor at exposure conditions corresponding to nuclear medicine modalities; (3) only restricted output image properties have been extensively studied, namely the spatial resolution, luminescence emission efficiency (LE), noise, and contrast; (4) physical properties such as the spectral compatibility and intrinsic optical properties like the optical absorption and scattering coefficients, light reflectivity, intrinsic conversion efficiency etc. have not been adequately investigated. Under investigation is also their relationship to image quality; (5) limited number of single crystal scintillators have been extensively investigated, principally those employed in commercial systems. Still, crystal treatment, on micro level, can possibly improve the performance of already existing materials.

Currently, powder scintillators are mainly ceramic phosphor materialsunder reduced porosity. Phosphor grains are glued through binding material in close packed spatial distribution (Nagarkar et al 2004; Blasse and Grabmeier 1994).Similarstructures are also addressed in nanophosphors. Ceramic phosphors and nanophosphors provide high detection efficiency and high image quality(Zych et al 2003, Liaparinos and Kandarakis 2009). Intrinsic and physical imaging properties of powder scintillators have been investigated through experimental and theoreticalmethods (Yaffe and Rowlands 1997), however for imaging systems of previous decades. To-date performance of detectors is evaluated in space andspatial frequency domains through frequency dependent parameters as e.g. Modulation Transfer Function (MTF), Noise Power Spectrum (NPS) and Detective Quantum Efficiency (DQE). MTF is measured frequently using the slanted-edge method to avoid aliasing while the Normalized NPS (NNPS) is determined by two-dimensional (2D) Fourier transforming of uniformly exposed images. Both measurements are performed under the representative radiation quality (RQA) settings, RQA-5 (70kVp digital-radiography) and RQA-M2 (28kVp digital-mammography) recommended by the International Electrotechnical Commission Reports 62220-1 and 62220-1-2 respectively. Detective Quantum Efficiency (DQE) can be assessed from the measured MTF, NPS and the entrance surface air-Kerma (ESAK) obtained from X-ray spectra measurement, normally with cadmium telluride (CdTe) detector.(IEC, 2005; Michail et al. 2011).

Scintillators of MIhave been successfully modelled through Monte Carlo methods. These were proven to be by far the most successful technique for the simulation of the stochastic processes involved in radiation detection (Nikolopoulos et al., 2006). Monte Carlo techniques have been successfully applied to medical physics, and particularly in evaluating MI detectors. Monte Carlo methods constitute, in principle, numerical-statistical approximations. Key-success, is the quantification of random processes in physical phenomena that are difficult, or even impossible, to determine experimentally.During the last decade, various Monte Carlo simulation packages have become commercially available. Some research groups have reported results on application of such packages in studies of photon transport phenomena in scintillators employed in x-ray medical imaging (e.g Nikolopoulos et al, 2006; Liaparinos and Kandarakis 2009 and references therein). However, commercially available Monte Carlo simulation packages are general and for this reason, their application is constrained by their expediency and feasibility in specialising to firm situations. The most popular packages i.e. EGSnrcMP, GEANT4 and PENELOPE, have been developed and verified for studies mainly in the field of nuclear and high energy physics (Nikolopoulos et al., 2006). Nevertheless, even such platforms may aid in finding significant information for effects within material's structure and the intrinsic properties of MI scintillators. In this sense, Monte Carlo simulation is very useful for complex problems that cannot be modeled by computer codes using deterministic methods (Badano and Sempau 2006). Results obtained by the Monte Carlo simulations can contribute to x-ray detector optimisation, toward improving whole imaging processes. This can be achieved by simulating (a) new efficient MI detectors, (b) novel advances in MI acquisition in conjunction with (c) lower patient doses.

OBJECTIVES

The objectives of the present research are:

1. The evaluation of the performance of powder scintillator radiation detectors under irradiation with various gamma-ray sources. Powder radiation scintillators are used in the form of thin layers (i.e. phosphor screens), which are prepared in laboratory. Various layers from various materials and with various thicknesses are prepared and experimentally studied. Under these conditions a number of physical quantities, related to the light emission and imaging performance of scintillators, are experimentally determined for various photon energies and scintillator detector thickness values. These quantities are as follows: a) The spatial resolution, b) The energy resolution, c) The detector sensitivity-expressed by the emitted light per unit of radiation exposure (uminescence emission efficiency), d) The light emission spectrum and the spectral compatibility to various optical sensors, e) The light transparency and the attenuation of the generated light (light losses) within the scintillator mass and f) The intrinsic light yield (conversion of the absorbed radiation energy into light within the scintillator material). In addition the scintillator behaviour will be modeled using theoretical models describing radiation and light transport within the scintillator mass. Modelling will allow for prediction of scintillator performance under conditions different to those experimentally available in our laboratories (e.g. very high or very low photon energies, very thick layers etc).

2. The comparison of the performance of powder vs. single crystal scintillators under identical irradiation conditions. This comparison is expected to provide useful data concerning possible applications of powder scintillators, especially in ring type SPECT detectors. Since powder scintillators are much cheaper and easier to manufacture - when compared to single crystals - the possibility of obtaining similar results between these to alternative scintillator forms will be of a great significance, especially in the design and implementation of low cost imaging systems. Such ring type detector systems already exist (microSPECT and microPET), but their cost do not allow their use in a number of dedicated imaging applications. Thus, the minimization of their cost is one of the main goals of this project.

3. The evaluation of the imaging properties of crystals in single form, after crystal treatment on micro level, using a high-resolution gamma camera. The surface and the exit window of the scintillator affect the light output and its optical properties. Detailed signal analysis will be carried out and phantom tests will be performed. The possibility of optimizing the performance of commercially available scintillators by performing an additional low cost entrance or output layer treatment and edge processing on micro-level may provide significantly important results. Recent studies have shown that the continuous crystals, used today in Nuclear Medicine, can be further processed and their performance can be further improved. The most promising geometries will be studied, since improvement of detectors performance on the crystal level is considered of high importance and may lead to significant innovations, with commercial applications.

4. The development of well proofed Monte Carlo simulation packages of the optical properties of single crystals and powder screens. Monte Carlo simulation packages and custom simulation codes will be employed and the experimental results will be used to evaluate the Monte Carlo simulation models. Original simulation models will be developed and evaluated, which will be further used in future studies. Since simulation is an important tool in the study of scintillator materials, the implementation of a well-tested simulation code, is scientifically very important.

Expected Results

The results expected from the proposed project allow for the following:

1. The estimation of the thickness and the type of a powder scintillator layer with emission efficiency and imaging properties approximating the efficiency of a single crystal layer.

2. The establishment of the developing procedures for manufacturing powder screens using new promising materials.

3. The selection of the scintillator materials, which are most suitable for each imaging application (i.e. exhibiting high light emission efficiency and optimized imaging performance).

4. The selection of the optimal crystal geometries for gamma ray imaging applications, which will provide a compromise between cost and performance.

5. The implementation of a well-tested simulation code, for studying optical phenomena in single and powder crystals.

In addition, important exchange of knowledge and experience from the collaboration of the proposing institutions is gained and subparts of this work lead to scientifically interesting results.

METHODS

The scintillator materials are commercially supplied n various physical forms (powders, single crystals and, if available, in ceramic form). In the case of powder scintillators, phosphor screens of various coating thicknesses will be prepared in the leader Institution by employing sedimentation techniques. Manufacturing of crystals surface or edges, is carried out by experienced personnel with associated infrastructure.

Evaluation of the performance of the scintillators is accomplished by determining the following parameters using experimental and theoretical methods:

1. Absolute luminescence efficiency (AE). This efficiency is defined as the ratio of the light energy flux emitted by an irradiated scintillator over the exposure rate characterizing the incident radiation. AE expresses the sensitivity of a scintillator and is of importance when the final image brightness with respect to the patient radiation dose is considered. The emitted light flux will be experimentally determined under x-ray and gamma-ray irradiation conditions. In addition, theoretical models, describing the radiation and light transmission through a scintillator material, will be employed to fit theoretical curves to experimental data. This technique will allow for estimation of a number of intrinsic material properties related to the light generation and the light attenuation within the mass of the scintillator.

2. Energy resolution (ER). This parameter expresses the ability of a scintillator to discern X-ray or gamma-ray photons of different energies. Detectors with good energy resolution produce high information diagnostic images and can be utilized in gamma-ray spectroscopy measurements

3. Optical spectrum (OS) emitted by an irradiated scintillator and the spectral compatibility (SC) of this spectrum with the spectral sensitivity of various optical sensors (photocathodes, photodiodes, films etc) used currently used in MI. SC is very important for estimating the efficiency of the detection of the emitted light of a new scintillator by existing optical sensors. A high value of SC ensures a lower dose to the patient and a faster Nuclear Medicine examination.

4. Modulation transfer function (MTF). This is an imaging parameter, which describes the image contrast and spatial resolution in the spatial frequency domain. Methods (SWRF response, ESF, etc) have been developed for measuring MTF of screen shaped scintillators (i.e. thin layers). In addition theoretical models, describing the radiation and light transmission through a scintillator material, will be employed to predict the MTF curves of the scintillator in various coating thicknesses and X-ray or gamma ray energies.

5. Noise power spectrum (NPS) or Wiener spectrum, which describes the noise contained ίn the final image. NPS can be calculated as the Fourier Transform of the autocorrelation function of the output signal of the scintillator detector under uniform X-ray or gamma-ray excitation. As in the case of MTF, theoretical models will be employed predict the NPS curves of the scintillator in various coating thicknesses and X-ray or gamma ray energies.

6. Detective quantum efficiency (DQE) describing the efficiency of an imaging system to transfer the input signal to noise ratio to its output. DQE values in the spatial frequency domain are a function of the MTF and the NPS of the scintillation detector. Since, DQE incorporates both signal and noise transfer it can be used as a single parameter for evaluating the performance of scintillators.

7. Measurement of the temporal response of certain scintillators and the effects of screen preparations upοn this process. Scintillators with a fast temporal response are of great value in the design of a ring type SPECT detector, especially in dynamic imaging, where the patient’s internal organs (i.e. heart) are moving.

8. Spatial resolution (SR). This parameter expresses the minimum distance that two X-ray or gamma-ray photons must have in order to be detected as two separate events by a scintillator. Detectors with good spatial resolution produce detailed images and can be utilized in gamma-ray imaging in order to identify small tumours.

The aforementioned parameters are determined under different exposure conditions used in variοus x-ray imaging techniques such as mammography, general radiography and fluoroscopy, computed tomography etc.

EXPERIENCE

The research group has a considerably long experience in investigating the role of powder (granular) and single crystal scintillators in the performance of radiation detectors of MI systems. More than 100 scientific papers, relevant to this field, have been published in international journals and conference proceedings. Various commercially available scintillator materials (terbium, europium and cerium activated rare earth materials as well as cesium iodide crystals) have been evaluated under x-ray and gamma-ray exposure conditions using experimental, theoretical as well as Monte Carlo techniques. Powder scintillators are employed in the form of thin screens prepared in laboratory with various thicknesses. Various properties related to optical characteristics (luminescence emission efficiency, light emission spectrum etc) and to the role of scintillators in the imaging performance (MTF, NPS, SNR, DQE etc) of imaging systems have been investigated. However the TEI group is not yet experienced in the development of imaging hardware and in incorporating scintillator materials in real detector systems. Taking into consideration the experience of ICCS in developing integrated imaging devices and the experience of the USA partner in producing and treatment novel scintillators, the present collaboration will clearly lead to benefits for all participating institutions by combining their complementary experiences.

DISSEMINATION AND EXPLOITATION OF RESEARCH RESULTS

The present research covers a variety of fields related to crystal evaluation, nano-technology, signal processing and MI. Since the techniques to be used are rather new and promising, a number of publications are expected to result from this collaboration. The results are related to the following: 1) Comparative evaluation of commercial used crystal materials in powder and single crystal form in x-ray and gamma-ray radiation, 2) evaluation of novel materials in powder and single crystal form, 3) Crystal treatment on micro-level, 4) Results from Monte Carlo studies and comparison with experimental ones.

REFERENCES

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Arvanitis C D, Bohndiek S E, Royle G, Blue A, Liang H X, Clark A, Prydderch M, Turchetta R, Speller R, “Empirical electro-optical and x-ray performance evaluation of CMOS active pixels sensor for low dose, high resolution x-ray medical imaging,” Med. Phys. 34 (2007) 4612-4625.

Badano A. and Sempau J., “MANTIS: combined x-ray, electron and optical Monte Carlo simulations of indirect radiation imaging systems” Phys. Med. Biol. 51(2006) 1545-1561.

Blasse G. and Grabmaier B. C., Luminescent materials (Spinger, Berlin, 1994).

Bohren C. F. and Huffman D. R., Absorption and Scattering of Light by Small Particles (Wiley, New York, 1983).

David S., Michail C., Valais I., Toutountzis A., Liaparinos P., Cavouras D., Kandarakis I., and Panayiotakis G., ‘Investigation of luminescence properties of Lu2SiO5:Ce (LSO) powder scintillator in the x-ray radiography energy range’, IEEE Transactions on Nuclear Science, 46, 474-478, 2007.

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Liaparinos P. and Kandarakis I., ‘The imaging performance of compact Lu₂O₃:Eu phosphor screens: Monte Carlo simulation for applications in mammography,’ Med.Phys., 36, 1985-1997, 2009,

Liaparinos P. and Kandarakis I., ‘The Monte Carlo evaluation of noise and resolution properties of granular phosphor screens,’ Phys. Med. Biol., 54, 859-874, 2009.

Michail C., David S., Liaparinos P., Valais I., Nikolopoulos D., Kalivas N., Toutountzis A., Sianoudis I., Cavouras D., Dimitropoulos N., Nomicos C. D., Kourkoutas K., Kandarakis I., Panayiotakis G. S., ‘Evaluation of the imaging performance of LSO powder scintillator for use in x-ray mammography’, Nucl. Instrum. Methods A, 580, 719-727, 2007.

Michail C, Spyropoulou V, Fountos G, Kalyvas N, I. G. Valais, I. S. Kandarakis and G. S. Panayiotakis,Experimental and theoretical evaluation of a high resolution CMOS based detector under X-ray imaging conditions, ΙΕΕΕTransactions on Nuclear Science (TNS), 58 (2011), 314-322.

Nagarkar V. V., Miller S. R., Tipnis S. V., Lempicki A., Brecher C., Lingertat H., “A new large area scintillator screen for X-ray imaging”, Nucl. Instr. and Meth. B. 213, (2004) 250-254.

Nikl M., “Scintillation detectors for x-rays,”Meas. Sci. Technol., vol. 17, pp.R37-R54, 2006.

Nikolopoulos D, Kandarakis I, CavourasD, Louizi A, Nomicos C. Investigation of radiation absorption and x-ray fluorescence of medical imaging scintillators by Monte Carlo Methods, Nucl.Instr.Method.(A) 2006; 565:821-832.

Valais I., Kandarakis I., Nikolopoulos D., Sianoudis I., Dimitropoulos N., Cavouras D., Nomicos C. D., and Panayiotakis G. S., “Luminescence efficiency of Gd2SiO5:Ce scintillator under x-ray excitation,” IEEE Trans. Nucl. Sci. 52 (2005) 1830-1835.

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A Greek version of the reserch scientific activities of this topic can be found in odf.pdf and tex.pdf formats.

OVERVIEW

The environmental exposure to radon is a public health problem. This is considered as the second cause of lung cance incidencer, after smoking. Radon in the human environment is an important research topic worldwide. Parts of regions are affected by residuals/wastes of increased natural radioactivity from the mining industry. In the same time radon issue is still not addressed in this area.

The targets of this research include the: a.spatial and seasonal variations of radon in dwellings and the environment; b.study of the effect of geological, hydrographic, meteorological factors, buildings design, type of building materials and other related factors that affect radon concentration; c.assessment of the radiological risk of the population under various conditions and exposure scenaria. d.modelling of radon and progeny generation and concentration peaks; e.focused measrements of radon and progeny in spas; f.special investigations in areas of concern; g.recommendations for minimisation of the radiological risk; h.generation of databases and maps of radon distribution in geographical zones of interest.

Towards the objectives measurements of radon in soil, surface and tap water, outdoor and indoor air are continiously conducted and the corresponding radiological risk of the exposed population is estimated. Specific measurements related to earthquacke prepatory activity from Geosystems are presented under the next topic of this category.

The main research directions are the following: 1.Selection of representative list of sampling points for field research and laboratory investigation; 2.Analysis of geological, hydrographic and building characteristics of specific regions;3.Study of spatial, temporal and seasonal radon variations; 4.Study of factors that affect radon concentrations; 5.Advanced statistical data analysis; 6.Chaotic and Hurst analysis; 7.Indexing areas of high radon potential; 8.SSNTD investigations; 9.Monte-Carlo modelling; 10.Dynamical modelling; 11..Estimation of radiation doses of population groups; 12.Recommendations for remediation;