An investigation into factors affecting electron density calibration for a megavoltage cone-beam CT system

There is a growing interest in the use of megavoltage cone-beam computed tomography (MV CBCT) data for radiotherapy treatment planning. To calculate accurate dose distributions, knowledge of the electron density (ED) of the tissues being irradiated is required. In the case of MV CBCT, it is necessary to determine a calibration-relating CT number to ED, utilizing the photon beam produced for MV CBCT. A number of different parameters can affect this calibration. This study was undertaken on the Siemens MV CBCT system, MVision, to evaluate the effect of the following parameters on the reconstructed CT pixel value to ED calibration: the number of monitor units (MUs) used (5, 8, 15 and 60 MUs), the image reconstruction filter (head and neck, and pelvis), reconstruction matrix size (256 by 256 and 512 by 512), and the addition of extra solid water surrounding the ED phantom. A Gammex electron density CT phantom containing EDs from 0.292 to 1.707 was imaged under each of these conditions. The linear relationship between MV CBCT pixel value and ED was demonstrated for all MU settings and over the range of EDs. Changes in MU number did not dramatically alter the MV CBCT ED calibration. The use of different reconstruction filters was found to affect the MV CBCT ED calibration, as was the addition of solid water surrounding the phantom. Dose distributions from treatment plans calculated with simulated image data from a 15 MU head and neck reconstruction filter MV CBCT image and a MV CBCT ED calibration curve from the image data parameters and a 15 MU pelvis reconstruction filter showed small and clinically insignificant differences. Thus, the use of a single MV CBCT ED calibration curve is unlikely to result in any clinical differences. However, to ensure minimal uncertainties in dose reporting, MV CBCT ED calibration measurements could be carried out using parameter-specific calibration measurements.

Effect of CT electron density identification on Monte Carlo simulations of radiotherapeutic treatments

Introduction: The accurate identification of tissue electron densities is of great importance for Monte Carlo (MC) dose calculations. When converting patient CT data into a voxelised format suitable for MC simulations, however, it is common to simplify the assignment of electron densities so that the complex tissues existing in the human body are categorized into a few basic types. This study examines the effects that the assignment of tissue types and the calculation of densities can have on the results of MC simulations, for the particular case of a Siemen’s Sensation 4 CT scanner located in a radiotherapy centre where QA measurements are routinely made using 11 tissue types (plus air). Methods: DOSXYZnrc phantoms are generated from CT data, using the CTCREATE user code, with the relationship between Hounsfield units (HU) and density determined via linear interpolation between a series of specified points on the ‘CT-density ramp’ (see Figure 1(a)). Tissue types are assigned according to HU ranges. Each voxel in the DOSXYZnrc phantom therefore has an electron density (electrons/cm3) defined by the product of the mass density (from the HU conversion) and the intrinsic electron density (electrons /gram) (from the material assignment), in that voxel. In this study, we consider the problems of density conversion and material identification separately: the CT-density ramp is simplified by decreasing the number of points which define it from 12 down to 8, 3 and 2; and the material-type-assignment is varied by defining the materials which comprise our test phantom (a Supertech head) as two tissues and bone, two plastics and bone, water only and (as an extreme case) lead only. The effect of these parameters on radiological thickness maps derived from simulated portal images is investigated. Results & Discussion: Increasing the degree of simplification of the CT-density ramp results in an increasing effect on the resulting radiological thickness calculated for the Supertech head phantom. For instance, defining the CT-density ramp using 8 points, instead of 12, results in a maximum radiological thickness change of 0.2 cm, whereas defining the CT-density ramp using only 2 points results in a maximum radiological thickness change of 11.2 cm. Changing the definition of the materials comprising the phantom between water and plastic and tissue results in millimetre-scale changes to the resulting radiological thickness. When the entire phantom is defined as lead, this alteration changes the calculated radiological thickness by a maximum of 9.7 cm. Evidently, the simplification of the CT-density ramp has a greater effect on the resulting radiological thickness map than does the alteration of the assignment of tissue types. Conclusions: It is possible to alter the definitions of the tissue types comprising the phantom (or patient) without substantially altering the results of simulated portal images. However, these images are very sensitive to the accurate identification of the HU-density relationship. When converting data from a patient’s CT into a MC simulation phantom, therefore, all possible care should be taken to accurately reproduce the conversion between HU and mass density, for the specific CT scanner used. Acknowledgements: This work is funded by the NHMRC, through a project grant, and supported by the Queensland University of Technology (QUT) and the Royal Brisbane and Women's Hospital (RBWH), Brisbane, Australia. The authors are grateful to the staff of the RBWH, especially Darren Cassidy, for assistance in obtaining the phantom CT data used in this study. The authors also wish to thank Cathy Hargrave, of QUT, for assistance in formatting the CT data, using the Pinnacle TPS. Computational resources and services used in this work were provided by the HPC and Research Support Group, QUT, Brisbane, Australia.

Pixel value to electron density conversion for a Megavoltage Cone Beam CT System

Introduction: The motivation for developing megavoltage (and kilovoltage) cone beam CT (MV CBCT) capabilities in the radiotherapy treatment room was primarily based on the need to improve patient set-up accuracy. There has recently been an interest in using the cone beam CT data for treatment planning. Accurate treatment planning, however, requires knowledge of the electron density of the tissues receiving radiation in order to calculate dose distributions. This is obtained from CT, utilising a conversion between CT number and electron density of various tissues. The use of MV CBCT has particular advantages compared to treatment planning with kilovoltage CT in the presence of high atomic number materials and requires the conversion of pixel values from the image sets to electron density. Therefore, a study was undertaken to characterise the pixel value to electron density relationship for the Siemens MV CBCT system, MVision, and determine the effect, if any, of differing the number of monitor units used for acquisition. If a significant difference with number of monitor units was seen then pixel value to ED conversions may be required for each of the clinical settings. The calibration of the MV CT images for electron density offers the possibility for a daily recalculation of the dose distribution and the introduction of new adaptive radiotherapy treatment strategies. Methods: A Gammex Electron Density CT Phantom was imaged with the MVCB CT system. The pixel value for each of the sixteen inserts, which ranged from 0.292 to 1.707 relative electron density to the background solid water, was determined by taking the mean value from within a region of interest centred on the insert, over 5 slices within the centre of the phantom. These results were averaged and plotted against the relative electron densities of each insert with a linear least squares fit was preformed. This procedure was performed for images acquired with 5, 8, 15 and 60 monitor units. Results: The linear relationship between MVCT pixel value and ED was demonstrated for all monitor unit settings and over a range of electron densities. The number of monitor units utilised was found to have no significant impact on this relationship. Discussion: It was found that the number of MU utilised does not significantly alter the pixel value obtained for different ED materials. However, to ensure the most accurate and reproducible MV to ED calibration, one MU setting should be chosen and used routinely. To ensure accuracy for the clinical situation this MU setting should correspond to that which is used clinically. If more than one MU setting is used clinically then an average of the CT values acquired with different numbers of MU could be utilized without loss in accuracy. Conclusions: No significant differences have been shown between the pixel value to ED conversion for the Siemens MV CT cone beam unit with change in monitor units. Thus as single conversion curve could be utilised for MV CT treatment planning. To fully utilise MV CT imaging for radiotherapy treatment planning further work will be undertaken to ensure all corrections have been made and dose calculations verified. These dose calculations may be either for treatment planning purposes or for reconstructing the delivered dose distribution from transit dosimetry measurements made using electronic portal imaging devices. This will potentially allow the cumulative dose distribution to be determined through the patient’s multi-fraction treatment and adaptive treatment strategies developed to optimize the tumour response.

The dependence of computed tomography number to relative electron density conversion on phantom geometry and its impact on planned dose

A computed tomography number to relative electron density (CT-RED) calibration is performed when commissioning a radiotherapy CT scanner by imaging a calibration phantom with inserts of specified RED and recording the CT number displayed. In this work, CT-RED calibrations were generated using several commercially available phantoms to observe the effect of phantom geometry on conversion to electron density and, ultimately, the dose calculation in a treatment planning system. Using an anthropomorphic phantom as a gold standard, the CT number of a material was found to depend strongly on the amount and type of scattering material surrounding the volume of interest, with the largest variation observed for the highest density material tested, cortical bone. Cortical bone gave a maximum CT number difference of 1,110 when a cylindrical insert of diameter 28 mm scanned free in air was compared to that in the form of a 30 × 30 cm2 slab. The effect of using each CT-RED calibration on planned dose to a patient was quantified using a commercially available treatment planning system. When all calibrations were compared to the anthropomorphic calibration, the largest percentage dose difference was 4.2 % which occurred when the CT-RED calibration curve was acquired with heterogeneity inserts removed from the phantom and scanned free in air. The maximum dose difference observed between two dedicated CT-RED phantoms was ±2.1 %. A phantom that is to be used for CT-RED calibrations must have sufficient water equivalent scattering material surrounding the heterogeneous objects that are to be used for calibration.

Influence of electrolyte cations on electron transport and electron transfer in dye-sensitized solar cells

The influence of different electrolyte cations ((Li+, Na+, Mg2+, tetrabutyl ammonium (TBA+)) on the TiO2 conduction band energy (Ec) the effective electron lifetime (τn), and the effective electron diffusion coefficient (Dn) in dye-sensitized solar cells (DSCs) was studied quantitatively. The separation between Ec and the redox Fermi level, EF,redox, was found to decrease as the charge/radius ratio of the cations increased. Ec in the Mg2+ electrolyte was found to be 170 meV lower than that in the Na+ electrolyte and 400 meV lower than that in the TBA+ electrolyte. Comparison of Dn and τn in the different electrolytes was carried out by using the trapped electron concentration as a measure of the energy difference between Ec and the quasi-Fermi level, nEF, under different illumination levels. Plots of Dn as a function of the trapped electron density, nt, were found to be relatively insensitive to the electrolyte cation, indicating that the density and energetic distribution of electron traps in TiO2 are similar in all of the electrolytes studied. By contrast, plots of τn versus nt for the different cations showed that the rate of electron back reaction is more than an order of magnitude faster in the TBA+ electrolyte compared with the Na+ and Li+ electrolytes. The electron diffusion lengths in the different electrolytes followed the sequence of Na+ > Li+ > Mg2+ > TBA+. The trends observed in the AM 1.5 current–voltage characteristics of the DSCs are rationalized on the basis of the conduction band shifts and changes in electron lifetime.

Adatom CCV Auger rates via the local density of states

In this letter the core-core-valence Auger transitions of an atomic impurity, both in bulk or adsorbed on a jellium-like surface, are computed within a DFT framework. The Auger rates calculated by the Fermi golden rule are compared with those determined by an approximate and simpler expression. This is based on the local density of states (LDOS) with a core hole present, in a region around the impurity nucleus. Different atoms, Na and Mg, solids, Al and Ag, and several impurity locations are considered. We obtain an excellent agreement between KL1V and KL23V rates worked out with the two approaches. The radius of the sphere in which we calculate the LDOS is the relevant parameter of the simpler approach. Its value only depends on the atomic species regardless of the location of the impurity and the type of substrate. (C) 2003 Elsevier B.V. All rights reserved.

Effective control of nanostructured phases in rapid, room-temperature synthesis of nanocrystalline Si in high-density plasmas

An innovative and effective approach based on low-pressure, low-frequency, thermally nonequilibrium, high-density inductively coupled plasmas is proposed to synthesize device-quality nanocrystalline silicon (nc-Si) thin films at room temperature and with very competitive growth rates. The crystallinity and microstructure properties (including crystal structure, crystal volume fraction, surface morphology, etc.) of this nanostructured phase of Si can be effectively tailored in broad ranges for different device applications by simply varying the inductive rf power density from 25.0 to 41.7 mW/cm3. In particular, at a moderate rf power density of 41.7 mW/cm3, the nc-Si films feature a very high growth rate of 2.37 nm/s, a high crystalline fraction of 86%, a vertically aligned columnar structure with the preferential (111) growth orientation and embedded Si quantum dots, as well as a clean, smooth and defect-free interface. We also propose the formation mechanism of nc-Si thin films which relates the high electron density and other unique properties of the inductively coupled plasmas and the formation of the nanocrystalline phase on the Si surface.

Behavior of the electron temperature in nonuniform complex plasmas

The response of complex ionized gas systems to the presence of nonuniform distribution of charged grains is investigated using a kinetic model. Contrary to an existing view that the electron temperature inevitably increases in the grain-occupied region because of enhanced ionization to compensate for the electrons lost to the grains, it is shown that this happens only when the ionizing electric field increases in the electron depleted region. The results for two typical plasma systems suggest that when the ionizing electric field depends on the spatially averaged electron density, the electron temperature in the grain containing region can actually decrease.

Nano-scale morphology and electron spectrum of defect states in low-k SiOCH films

Results of experimental investigations on the relationship between nanoscale morphology of carbon doped hydrogenated silicon-oxide (SiOCH) low-k films and their electron spectrum of defect states are presented. The SiOCH films have been deposited using trimethylsilane (3MS) - oxygen mixture in a 13.56 MHz plasma enhanced chemical vapor deposition (PECVD) system at variable RF power densities (from 1.3 to 2.6 W/cm2) and gas pressures of 3, 4, and 5 Torr. The atomic structure of the SiOCH films is a mixture of amorphous-nanocrystalline SiO2-like and SiC-like phases. Results of the FTIR spectroscopy and atomic force microscopy suggest that the volume fraction of the SiC-like phase increases from ∼0.2 to 0.4 with RF power. The average size of the nanoscale surface morphology elements of the SiO2-like matrix can be controlled by the RF power density and source gas flow rates. Electron density of the defect states N(E) of the SiOCH films has been investigated with the DLTS technique in the energy range up to 0.6 eV from the bottom of the conduction band. Distinct N(E) peaks at 0.25 - 0.35 eV and 0.42 - 0.52 eV below the conduction band bottom have been observed. The first N(E) peak is identified as originated from E1-like centers in the SiC-like phase. The volume density of the defects can vary from 1011 - 1017 cm-3 depending on specific conditions of the PECVD process.

Photo-ionization and residual electron effects in guided streamers

Complementary experiments and numerical modeling reveal the important role of photo-ionization in the guided streamer propagation in helium-air gas mixtures. It is shown that the minimum electron concentration ∼108 cm−3 is required for the regular, repeated propagation of the plasma bullets, while the streamers propagate in the stochastic mode below this threshold. The stochastic-to-regular mode transition is related to the higher background electron density in front of the propagating streamers. These findings help improving control of guided streamer propagation in applications from health care to nanotechnology and improve understanding of generic pre-breakdown phenomena.

Vapour phase assembly of a halogen bonded complex of an isoindoline nitroxide and 1,2-diiodotetrafluorobenzene

Vapour phase assembly has been used for the first time to prepare co-crystals in which the primary intermolecular interaction is halogen bonding. Co-crystals of the nitroxide 1,1,3,3-tetramethylisoindolin-2-yloxyl (TMIO) and 1,2-diiodotetrafluorobenzene (1,2-DITFB) are readily formed under standard sublimation conditions. Single crystal X-ray diffraction confirmed the structure of a 2:2 cyclic tetramer, (TMIO)2·(1,2-DITFB)2, which exhibits a new halogen bonding motif, with each nitroxide oxygen atom accepting two halogen bonds. Powder X-ray diffraction confirmed the homogeneity of the bulk sample. The crystalline complex was further characterized in the solid state using thermal analysis and vibrational spectroscopy (infrared and Raman). Density functional theory calculations were also used to evaluate the enthalpy of formation, electrostatic potential and unpaired electron density of the complex. These findings illustrate the preparation of co-crystals where solution state methodology is problematic and the potential of this approach for the formation of novel organic spin systems.

Ruthenium(II) dichloro or dithiocyanato complexes with 4,4′:2′,2″:4″,4‴-quaterpyridinium ligands : towards photosensitisers with enhanced low-energy absorption properties

Fourteen new complexes of the form cis-\[RuIIX2(R2qpy2+)2]4+ (R2qpy2+ = a 4,4′:2′,2″:4″,4‴-quaterpyridinium ligand, X = Cl− or NCS−) have been prepared and isolated as their PF6− salts. Characterisation involved various techniques including 1H NMR spectroscopy and +electrospray or MALDI mass spectrometry. The UV–Vis spectra display intense intraligand π → π∗ absorptions, and also metal-to-ligand charge-transfer (MLCT) bands with two resolved maxima in the visible region. Red-shifts in the MLCT bands occur as the electron-withdrawing strength of the pyridinium groups increases, while replacing Cl− with NCS− causes blue-shifts. Cyclic voltammograms show quasi-reversible or reversible RuIII/II oxidation waves, and several ligand-based reductions that are irreversible. The variations in the redox potentials correlate with changes in the MLCT energies. A single-crystal X-ray structure has been obtained for a protonated form of a proligand salt, \[(4-(CO2H)Ph)2qpyH3+]\[HSO4]3·3H2O. Time-dependent density functional theory calculations give adequate correlations with the experimental UV–Vis spectra for the two carboxylic acid-functionalised complexes in DMSO. Despite their attractive electronic absorption spectra, these dyes are relatively inefficient photosensitisers on electrodes coated with TiO2 or ZnO. These observations are attributed primarily to weak electronic coupling with the surfaces, since the DFT-derived LUMOs include no electron density near the carboxylic acid anchors.

The appearance and effects of metallic implants in CT images

Contemporary 3D radiotherapy treatment planning relies upon the use of 3D electron density maps derived from computed tomography (CT) scans of patient anatomy, to evaluate the effects of that anatomy on radiation dose distributions. Production of these electron density maps requires that the CT numbers (Hounsfield units) that quantify the attenuation of the x-ray beam by the patient’s anatomy must be reliably converted into electron densities, using a stable calibration relationship. This study investigates the fidelity of electron density assignment in the presence of metallic prostheses and implants.

Segmentation of cone-beam CT using a hidden Markov random field with informative priors

Purpose: Flat-detector, cone-beam computed tomography (CBCT) has enormous potential to improve the accuracy of treatment delivery in image-guided radiotherapy (IGRT). To assist radiotherapists in interpreting these images, we use a Bayesian statistical model to label each voxel according to its tissue type. Methods: The rich sources of prior information in IGRT are incorporated into a hidden Markov random field (MRF) model of the 3D image lattice. Tissue densities in the reference CT scan are estimated using inverse regression and then rescaled to approximate the corresponding CBCT intensity values. The treatment planning contours are combined with published studies of physiological variability to produce a spatial prior distribution for changes in the size, shape and position of the tumour volume and organs at risk (OAR). The voxel labels are estimated using the iterated conditional modes (ICM) algorithm. Results: The accuracy of the method has been evaluated using 27 CBCT scans of an electron density phantom (CIRS, Inc. model 062). The mean voxel-wise misclassification rate was 6.2%, with Dice similarity coefficient of 0.73 for liver, muscle, breast and adipose tissue. Conclusions: By incorporating prior information, we are able to successfully segment CBCT images. This could be a viable approach for automated, online image analysis in radiotherapy.

Segmentation of cone-beam CT using a hidden Markov random field with informative priors

Cone-beam computed tomography (CBCT) has enormous potential to improve the accuracy of treatment delivery in image-guided radiotherapy (IGRT). To assist radiotherapists in interpreting these images, we use a Bayesian statistical model to label each voxel according to its tissue type. The rich sources of prior information in IGRT are incorporated into a hidden Markov random field model of the 3D image lattice. Tissue densities in the reference CT scan are estimated using inverse regression and then rescaled to approximate the corresponding CBCT intensity values. The treatment planning contours are combined with published studies of physiological variability to produce a spatial prior distribution for changes in the size, shape and position of the tumour volume and organs at risk. The voxel labels are estimated using iterated conditional modes. The accuracy of the method has been evaluated using 27 CBCT scans of an electron density phantom. The mean voxel-wise misclassification rate was 6.2\%, with Dice similarity coefficient of 0.73 for liver, muscle, breast and adipose tissue. By incorporating prior information, we are able to successfully segment CBCT images. This could be a viable approach for automated, online image analysis in radiotherapy.