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The purpose of this paper is to use an animal model to quantify the spatial displacement uncertainties and test the fundamental assumptions of an imagebased 4D-CT algorithm in vivo. Six female Landrace cross pigs were ventilated and imaged using a 64-slice CT scanner (GE Healthcare) operating in axial cine mode. The breathing amplitude pattern of the pigs was varied by periodically crimping the ventilator gas return tube during the image acquisition. The image data were used to determine the displacement uncertainties that result from matching CT images at the same respiratory phase using normalized cross correlation (NCC) as the matching criteria. Additionally, the ability to match the respiratory phase of a 4.0 cm subvolume of the thorax to a reference subvolume using only a single overlapping 2D slice from the two subvolumes was tested by varying the location of the overlapping matching image within the subvolume and examining the effect this had on the displacement relative to the reference volume. The displacement uncertainty resulting from matching two respiratory images using NCC ranged from 0.54 ± 0.10 mm per match to 0.32 ± 0.16 mm per match in the lung of the animal. The uncertainty was found to propagate in quadrature, increasing with number of NCC matches performed. In comparison, the minimum displacement achievable if two respiratory images were matched perfectly in phase ranged from 0.77 ± 0.06 to 0.93 ± 0.06 mm in the lung. The assumption that subvolumes from separate cine scan could bematched by matching a single overlapping 2D image between to subvolumes was validated. An in vivo animal model was developed to test an image-based 4D-CT algorithm. The uncertainties associated with usingNCC to match the respiratory phase of two images were quantified and the assumption that a 4.0 cm 3D subvolume can by matched in respiratory phase by matching a single 2D image from the 3D subvolume was validated. The work in this paper shows the image-based 4D-CT algorithm to be a promising method for producing 4D-CT images for radiotherapy. [ABSTRACT FROM AUTHOR]

The aim of radiation dosimetry is to evaluate, under specific conditions, absorbed dose in a medium of interest using a detection device. In comparison to what is meant to be evaluated, the distinctive composition of the detector causes particle fluence perturbation and shifted absorbed-dose response, both effects depending on beam quality. For electron and megavoltage photon beams, Spencer-Attix cavity theory further adapted by Nahum remains the accepted standard method used to convert absorbed dose in a wall-less detector to absorbed dose in the medium of interest. For several decades, the approach has been widely used in protocols to generate data for ionization chamber dosimetry. As a considerable effort was made towards accurate Monte Carlo methods, computation techniques are nowadays available to determine absorbed dose accurately in complex geometries, including radiation detectors. In the development of nonstandard beam protocols, direct Monte Carlo dose calculations using realistic models are being suggested and used to generate data for ionization chamber dosimetry. This indicates that for a general dosimetric context, including nonstandard beams, a more general cavity theory in agreement with what is currently being done could be adopted. Not only this could be of interest in the dosimetry standards community, but also for educational purposes. This paper re-examines Spencer-Attix theory from first principles, using a new general cavity theory rigorously derived from radiation transport equations. The approach is based on the same schematization as for Spencer-Attix's (i.e. groups of slow and fast electrons) and yields a general expression of absorbed dose for suitably implemented Monte Carlo methods. The Spencer-Attix-Nahum formulation is shown to be a special case of the presented model, outlining specific issues of the standardmethod. By providing an expression of absorbed dose which reflects the gold standard calculation method (i.e. Monte Carlo), the proposed theory could be adopted by the radiation dosimetry community. [ABSTRACT FROM AUTHOR]

The aim of this paper is to determine the dosimetric impact of trace elements in human tissues for low-energy photon sources used in brachytherapy. Monte Carlo dose calculations were used to investigate the dosimetric effect of trace elements present in normal or cancerous human tissues. The effect of individual traces (atomic number Z = 11-30) was studied in soft tissue irradiated by low-energy brachytherapy sources. Three other tissue types (prostate, adipose and mammary gland) were also simulated with varying trace concentrations to quantify the contribution of each trace to the dose distribution. The dose differences between cancerous and healthy prostate tissues were calculated in single- and multi-source geometries. The presence of traces in a tissue produces a difference in the dose distribution that is dependent on Z and the concentration of the trace. Low-Z traces (Na) have a negligible effect (<0.3%) in all tissues, while higher Z (K) had a larger effect (>3%). There is a potentially significant difference in the dose distribution between cancerous and healthy prostate tissues (4%) and even larger if compared to the trace-free composition (15%) in both single- and multi-sourced geometries. Trace elements have a non-negligible (up to 8%in prostate D90) effect on the dose in tissues irradiated with low-energy photon sources. This study underlines the need for further investigation into accurate determination of the trace composition of tissues associated with low-energy brachytherapy. Alternatively, trace elements could be incorporated as a source of uncertainty in dose calculations. [ABSTRACT FROM AUTHOR]

In this paper, we study the feasibility of using the stochastic origin ensemble (SOE) algorithm for reconstructing images of secondary gammas emitted during proton radiotherapy from data measured with a three-stage Compton camera. The purpose of this study was to evaluate the quality of the images of the gamma rays emitted during proton irradiation produced using the SOE algorithm and to measure how well the images reproduce the distal falloff of the beam. For our evaluation, we performed a Monte Carlo simulation of an ideal three-stage Compton camera positioned above and orthogonal to a proton pencil beam irradiating a tissue phantom. Scattering of beam protons with nuclei in the phantom produces secondary gamma rays, which are detected by the Compton camera and used as input to the SOE algorithm. We studied the SOE reconstructed images as a function of the number of iterations, the voxel probability parameter, and the number of detected gammas used by the SOE algorithm. We quantitatively evaluated the capabilities of the SOE algorithm by calculating and comparing the normalized mean square error (NMSE) of SOE reconstructed images. We also studied the ability of the SOE reconstructed images to predict the distal falloff of the secondary gamma production in the irradiated tissue. Our results show that the images produced with the SOE algorithm converge in ∼10 000 iterations, with little improvement to the image NMSE for iterations above this number. We found that the statistical noise of the images is inversely proportional to the ratio of the number of gammas detected to the SOE voxel probability parameter value. In our study, the SOE predicted distal falloff of the reconstructed images agrees with the Monte Carlo calculated distal falloff of the gamma emission profile in the phantom to within ±0.6 mm for the positions of maximum emission (100%) and 90%, 50% and 20% distal falloff of the gamma emission profile. We conclude that the SOE algorithm is an effective method for reconstructing images of a proton pencil beam from the data collected by an ideal Compton camera and that these images accurately model the distal falloff of secondary gamma emission during proton irradiation. [ABSTRACT FROM AUTHOR]

Task group 43 (TG43)-based dosimetry algorithms are efficient for brachytherapy dose calculation inwater. However, human tissues have chemical compositions and densities different thanwater. Moreover, themutual shielding effect of seeds on each other (interseed attenuation) is neglected in the TG43- based dosimetry platforms. The scientific community has expressed the need for an accurate dosimetry platform in brachytherapy. The purpose of this paper is to present ALGEBRA, a Monte Carlo platform for dosimetry in brachytherapy which is sufficiently fast and accurate for clinical and research purposes. ALGEBRA is based on the GEANT4 Monte Carlo code and is capable of handling the DICOM RT standard to recreate a virtual model of the treated site. Here, the performance of ALGEBRA is presented for the special case of LDR brachytherapy in permanent prostate and breast seed implants. However, the algorithm is also capable of handling other treatments such as HDR brachytherapy. [ABSTRACT FROM AUTHOR]

Magnetic resonance electrical impedance tomography (MREIT) is a noninvasive method to visualize cross-sectional electrical conductivity and/or current density by measuring a magnetic flux density signal when an electrical current is injected into a subject. In the MREIT system, it is crucial to reduce the scan duration while maintaining spatial resolution and contrast for practical in vivo implementation. The purpose of the study is to optimize the measured magnetic flux density using an interleaved multiple-echo pulse sequence (injected current nonlinear encoding) that acquires each spatial position multiple times, although these pixels vary between echoes in their signal-tonoise ratio due to (a) T*2 2 decay and (b) the current density passing through the pixel. Using the acquired multiple measured magnetic flux densities, the noise level for the measured magnetic flux density Bz at each pixel is estimated using the relationship between the intensity of the magnitude and the width of the injected current. We determine an optimal combination of the multiply acquired magnetic flux densities, which optimally reduces the random noise artifacts. We develop a new denoising technique and apply it to a recovered conductivity distribution with a known noise level of the recovered magnetic flux density, which is designed to provide a stable internal conductivity distribution, while sustaining resolution. The proposed method uses three key steps: the first step is optimizing the magnetic flux density by using the multiple-echo magnetic flux densities at each pixel, the second step is estimating the noise level of this optimized magnetic flux density and the third step is applying a denoising technique using the pixel-specific estimated noise level. Numerical simulation experiments using a three-dimensional cylindrical phantom model validated the proposed method. Multiple-echo Bz data were generated, including in short T*2 or low spin-density regions, as a function of T*2 and the temporal extent of the injected current. In the simulation experiment, comparing between an equally averaged and the optimized Bz methods, relative L2-mode errors were 0.053 and 0.024, respectively. In an actual imaging experiment of an agarose gel filled with objects of various conductivities and shapes, we acquired six echoes per repetition time. The optimal weighting factorsminimized the effects of noise in Bz, and provided reconstructed conductivity maps that suppressed noise artifacts that normally accumulate in the low signal-to-noise-ratio defect regions. [ABSTRACT FROM AUTHOR]

The Akaike information criterion and the associated Akaike weights (AW) rank pharmacokinetic models on the basis of goodness-of-fit and number of parameters. The usefulness of this information for improving the haemodynamic parameter estimates from DCE-MRI was investigated through two examples. In each of these, the estimates from the two-compartment exchange model (2CXM) were combined on the basis of the AW with those of a simplified model (either the uptake model or the extended Tofts model). Data were simulated using the 2CXM for a range of experimental and tissue conditions. Two multimodel approaches exploiting the AW were investigated: the 'bestmodel' approach which selects the parameter estimates from themodel with highest AW and the 'weighted model' approach in which AW-weighted averages of the estimates from the competing models are calculated. Although these approaches were shown to be beneficial in some cases, they were found to frequently lead to unexpected increases in the bias and/or uncertainty of the resulting parameter estimates. Within the limited scope of this simulation study, the use of the Akaike criterion showed no systematic benefit over a fitting strategy involving only the more complex model. [ABSTRACT FROM AUTHOR]

The understanding of large biophysical systems at the systems level often depends on a precise knowledge of their microstructure. This is difficult to obtain, especially in vivo, because most imaging methods are either limited in terms of achievable field of view, or make use of penetrating ionizing radiations such as x-rays, in which case the resolution is severely limited by the deposited dose. Here, we describe a new method, x-ray vector radiography (XVR), which yields various types of information about the local orientation, anisotropy and average size of the sample microstructures. We demonstrate the feasibility by showing first experimental XVRs of human vertebra bone samples, giving information on the trabecular structures even with a pixel resolution of half a millimetre, much larger than the structures themselves. This last point is critical for the development of low-dose measurement methods which will allow for in vivo studies and potentially in the future for new medical diagnostics methods of bone metabolic disorder diseases such as osteoporosis. [ABSTRACT FROM AUTHOR]

Image-guided adaptive radiotherapy requires deformable image registration to map radiation dose back and forth between images. The purpose of this study is to develop a novel method to improve the accuracy of an intensity-based image registration algorithm in low-contrast regions. A computational framework has been developed in this study to improve the quality of the 'demons' registration. For each voxel in the registration's target image, the standard deviation of image intensity in a neighborhood of this voxel was calculated. A mask for high-contrast regions was generated based on their standard deviations. In the masked regions, a tetrahedral mesh was refined recursively so that a sufficient number of tetrahedral nodes in these regions can be selected as driving nodes. An elastic system driven by the displacements of the selected nodes was formulated using a finite element method (FEM) and implemented on the refined mesh. The displacements of these driving nodes were generated with the 'demons' algorithm. The solution of the system was derived using a conjugated gradient method, and interpolated to generate a displacement vector field for the registered images. The FEM correction method was compared with the 'demons' algorithm on the computed tomography (CT) images of lung and prostate patients. The performance of the FEM correction relating to the 'demons' registration was analyzed based on the physical property of their deformation maps, and quantitatively evaluated through a benchmark model developed specifically for this study. Compared to the benchmark model, the 'demons' registration has themaximum error of 1.2 cm, which can be corrected by the FEM to 0.4 cm, and the average error of the 'demons' registration is reduced from 0.17 to 0.11 cm. For the CT images of lung and prostate patients, the deformation maps generated by the 'demons' algorithm were found unrealistic at several places. In these places, the displacement differences between the 'demons' registrations and their FEM corrections were found in the range of 0.4 and 1.1 cm. The mesh refinement and FEM simulation were implemented in a single thread application which requires about 45 min of computation time on a 2.6 GHz computer. This study has demonstrated that the FEM can be integrated with intensity-based image registration algorithms to improve their registration accuracy, especially in low-contrast regions. [ABSTRACT FROM AUTHOR]

We present a stored system matrix (SM) approach for iterative x-ray CT image reconstruction with helical cone-beam geometry. Because of the symmetry of a helical source trajectory, it is sufficient to calculate and store the SM entries for one transaxial slice only and for all source positions illuminating the slice. This is made possible by (1) selecting the reconstruction slice thickness to be an integer multiple of the source translation per projection view, and (2) discretizing the 3D reconstruction volume on a rotated stack of slices. Using the proposed method, thememory requirement for reconstructing a full field-ofview of clinical scanners is manageable on current computing platforms. The same storage principle can be generalized and applied to volume-of-interest (VOI) image reconstruction for helical cone-beam CT. In this case, the stored SM entries correspond to a partial- or full-ring region on one transaxial slice, and for all source positions illuminating the ring. The size and location of the ring depend on the size and the location of the VOI and the scan geometry. We demonstrate by both computer simulations and clinical patient data the speed and efficacy of iterative image reconstruction using the stored SM approach. [ABSTRACT FROM AUTHOR]

The aim of this study is to design and test a new high-resolution hybrid depth of interaction (DOI) detector for a dedicated breast PET/CT scanner. Two detectors have been designed and built. The completed detectors are based on a 14 × 14 array of 1.5 × 1.5 × 20 mm3 unpolished lutetium orthosilicate scintillation crystals, with each element coated in a 50 µm layer of reflective material. The detector is read out from both ends using a positionsensitive photomultiplier tube (PSPMT) and a large active area (20 × 20 mm2) avalanche photodiode (APD) to enable acquisition of DOI information. Nuclear instrumentationmodules were used to characterize the detectors' performances in terms of timing, intrinsic spatial resolution (ISR) and energy resolution, as well as DOI resolution with a dual-ended readout configuration. Measurements with the APD were performed at a temperature of 10 °C. All crystals were identified at all depths, even though the signal amplitude from the PSPMT decreases with depth away from it. We measured a timing resolution of 2.4 ns, and an average energy resolution of 19%. The mean ISR was measured to be 1.2 mm for crystals in the central row of the array for detectors in the faceto- face position. Two off-center positions were measured corresponding to 26? and 51? oblique photon incidence, and the mean ISR at these positions was 1.5 and 1.7 mm, respectively. The average DOI resolution across all crystals and depths was measured to be 2.9 mm (including the beam width of 0.6 mm). This detector design shows good promise as a high-resolution detector for a dedicated breast PET/CT scanner. [ABSTRACT FROM AUTHOR]

The absorbed dose distribution at sub-millimeter distances from the Best single 192Ir intravascular brachytherapy seed was measured using a high-spatialresolution gel dosimetry system. Two gel phantoms from the same batch were used; one for the seed irradiation and one for calibration. Since the response of this gel is energy independent for photons between 20 and 1250 keV, the gel was calibrated using a narrowly collimated 60Co gamma-ray beam (crosssectional area ¡«1 cm2). A small format laser computed tomography scanner was used to acquire the data. The measurements were carried out with a spatial resolution of 100 Ìm in all dimensions. The seed was calibrated at NIST in terms of air-kerma strength. The absorbed dose rate as well as the radial dose function, gL(r), was measured for radial distances between 0.6 and 12.6 mm from the seed center. The dose rate constant was measured, yielding a value of &Lgr; = (1.122 ± 0.032) cGy h-1 U-1, which agrees with published data within the measurement uncertainty. For distances between 0.6 and 1.5 mm, gL(r) decreases from a maximum value of 1.06 down to 1.00; between 1.5 and 6.7 mm, an enhancement is clearly observed with a maximum value around 1.24 and beyond 6.7 mm, gL(r) has an approximately constant value around 1.0, which suggests that this seed can be considered as a point source only at distances larger than 6.7 mm. This latter observation agrees with data for the same seed reported previously using Gafchromic film MD-55-2. Additionally, published Monte Carlo (MC) calculations have predicted the observed behavior of the radial dose function resulting from the absorbed dose contributions of beta particles and electrons emitted by the 192Ir seed. Nonetheless, in the enhancement region, MC underestimates the dose by approximately 20%. This work suggests that beta particles and electrons emitted from the seed make a significant contribution to the total absorbed dose delivered at distances near the seed center (less than 6 mm) and therefore cannot be neglected, given the dimensions of blood vessel walls. [ABSTRACT FROM AUTHOR]

Treatments delivered by proton therapy are affected by uncertainties on the range of the beam within the patient, requiring medical physicists to add safety margins on the penetration depth of the beam. To reduce these margins and deliver safer treatments, different projects are currently investigating real-time range control by imaging prompt gammas emitted along the proton tracks in the patient. This study reports on the feasibility, development and test of a new concept of prompt gamma camera using a slit collimator to obtain a one-dimensional projection of the beam path on a scintillation detector. This concept was optimized, using the Monte Carlo code MCNPX version 2.5.0, to select high energy photons correlated with the beam range and detect them with both high statistics and sufficient spatial resolution. To validate the Monte Carlo model, spectrometry measurements of secondary particles emitted by a PMMAtarget during proton irradiation at 160 MeV were realized. An excellent agreement with the simulations was observed when using subtraction methods to isolate the gammas in direct incidence. A first prototype slit camera using the HiCam gamma detector was consequently prepared and tested successfully at 100 and 160 MeV beam energies. Results confirmed the potential of this concept for real-time range monitoring with millimetre accuracy in pencil beam scanning mode for typical clinical conditions. If we neglect electronic dead times and rejection of detected events, the current solution with its collimator at 15 cm from the beam axis can achieve a 1-2 mm standard deviation on range estimation in a homogeneous PMMA target for numbers of protons that correspond to doses in water at the Bragg peak as low as 15 cGy at 100 MeV and 25 cGy at 160 MeV assuming pencil beams with a Gaussian profile of 5 mm sigma at target entrance. [ABSTRACT FROM AUTHOR]

A key task within all Monte Carlo particle transport codes is 'navigation', the calculation to determine at each particle step what volume the particle may be leaving and what volume the particle may be entering. Navigation should be optimized to the specific geometry at hand. For patient dose calculation, this geometry generally involves voxelized computed tomography (CT) data. We investigated the efficiency of navigation algorithms on currently available voxel geometry parameterizations in the Monte Carlo simulation package Geant4: G4VPVParameterisation, G4V Nested Parameterisation and G4P hantom Parameterisation, the last with and without boundary skipping, a method where neighboring voxels with the same Hounsfield unit are combined into one larger voxel. A fourth parameterization approach (MGHParameterization), developed inhouse before the latter two parameterizations became available in Geant4, was also included in this study. All simulations were performed using TOPAS, a tool for particle simulations layered on top of Geant4. Runtime comparisons were made on three distinct patient CT data sets: a head and neck, a liver and a prostate patient. We included an additional version of these three patients where all voxels, including the air voxels outside of the patient, were uniformly set to water in the runtime study. The G4VPVParameterisation offers two optimization options. One option has a 60-150 times slower simulation speed. The other is compatible in speed but requires 15-19 times more memory compared to the other parameterizations. We found the average CPU time used for the simulation relative to G4V Nested Parameterisation to be 1.014 for G4 Phantom Parameterisation without boundary skipping and 1.015 for MGH Parameterization. The average runtime ratio for G4P hantom Parameterisation with and without boundary skipping for our heterogeneous data was equal to 0.97 : 1. The calculated dose distributions agreed with the reference distribution for all but the G4PhantomParameterisation with boundary skipping for the head and neck patient. The maximum memory usage ranged from 0.8 to 1.8 GB depending on the CT volume independent of parameterizations, except for the 15-19 times greater memory usage with the G4VPVParameterisation when using the option with a higher simulation speed. The G4VNestedParameterisation was selected as the preferred choice for the patient geometries and treatment plans studied. [ABSTRACT FROM AUTHOR]