Table of contents

GATE (Geant4 Application for Emission Tomography) is a Monte Carlo simulation platform developed by the OpenGATE collaboration since 2001 and first publicly released in 2004. Dedicated to the modelling of planar scintigraphy, single photon emission computed tomography (SPECT) and positron emission tomography (PET) acquisitions, this platform is widely used to assist PET and SPECT research. A recent extension of this platform, released by the OpenGATE collaboration as GATE V6, now also enables modelling of x-ray computed tomography and radiation therapy experiments. This paper presents an overview of the main additions and improvements implemented in GATE since the publication of the initial GATE paper (Jan et al 2004 Phys. Med. Biol.49 4543–61). This includes new models available in GATE to simulate optical and hadronic processes, novelties in modelling tracer, organ or detector motion, new options for speeding up GATE simulations, examples illustrating the use of GATE V6 in radiotherapy applications and CT simulations, and preliminary results regarding the validation of GATE V6 for radiation therapy applications. Upon completion of extensive validation studies, GATE is expected to become a valuable tool for simulations involving both radiotherapy and imaging.

The GEANT4-based GATE Monte Carlo (MC) platform was initially focused on PET and SPECT simulations. The new release v6.0 (February 2010) proposes new tools dedicated for radiation therapy simulations. In this work, we investigated some part of this extension and proposed a general methodology for Linac simulations. Details of the modeling of a 6 MV photon beam delivered by an Elekta Precise Linac, with radiation fields ranging from 5 × 5 to 30 × 30 cm² at the isocenter are presented. Comparisons were performed with measurements in water. The simulations were performed in two stages: first, the patient-independent part was simulated and a phase space (PhS) was built above the secondary collimator. Then, a multiple source model (MSM) derived from the PhS was proposed to simulate the photon fluence interacting with the patient-dependent part. The selective bremsstrahlung splitting (SBS) variance reduction technique proposed in GATE was used in order to speed up the accelerator head simulation. Further investigations showed that the SBS can be safely used without biasing the simulations. Additional comparisons with full simulations performed on the EGEE grid, in a single stage from the electron source to the water phantom, allowed the evaluation of the MSM. The proposed MSM allowed for calculating depth dose and transverse profiles in 48 hours on a single 2.8 GHz CPU, with a statistical uncertainty of 0.8% for a 10 × 10 cm² radiation field, using voxels of 5 × 5 × 5 mm³. Good agreement between simulations and measurements in water was observed, with dose differences of about 1% and 2% for depth doses and dose profiles, respectively. Additional gamma index comparisons were performed; more than 90% of the points for all simulations passed the 3%/3 mm gamma criterion. To our knowledge, this feasibility study is the first one illustrating the potential of GATE for external radiotherapy applications.

The ability to accurately and non-invasively characterize breast lesions and their vasculature would greatly limit the number of unneeded biopsies performed annually. Subharmonic ultrasound imaging (SHI) allows exclusive imaging of vasculature in real time, while completely suppressing tissue signals. Previously, cumulative maximum intensity (CMI) projections of SHI data were shown to be useful for characterization, but lacked means of quantification. In this study we investigate three potential thinning algorithms for defining breast lesion architecture. Sequential thinning, parallel thinning, and distance transformation algorithms were compared using 40 in vitro test images. Sequential thinning was selected due to superior connectivity, minimal rotational variance, and sufficient data reduction. This algorithm was then applied to 16 CMI SHI images of breast lesions, out of which 13 were successfully skeletonized. Average bifurcations were 9.8 ± 8.18 and 6.9 ± 6.50 in malignant and benign lesions, respectively (p > 0.60). Average vessel-chain length was 88.9 ± 79.10 pixels versus 63.2 ± 45.65 pixels in malignant versus benign lesions (p > 0.40). While the sequential thinning algorithm was promising for quantifying breast vasculature, its ability to significantly differentiate between malignant and benign lesions in this study was limited by a high degree of variability and limited sample size.

Iterative image reconstruction methods such as ordered-subset expectation maximization (OSEM) are widely used in PET. Reconstructions via OSEM are however reported to be biased for low-count data. We investigated this and considered the impact for dynamic PET. Patient listmode data were acquired in [¹¹C]DASB and [¹⁵O]H₂O scans on the HRRT brain PET scanner. These data were subsampled to create many independent, low-count replicates. The data were reconstructed and the images from low-count data were compared to the high-count originals (from the same reconstruction method). This comparison enabled low-statistics bias to be calculated for the given reconstruction, as a function of the noise-equivalent counts (NEC). Two iterative reconstruction methods were tested, one with and one without an image-based resolution model (RM). Significant bias was observed when reconstructing data of low statistical quality, for both subsampled human and simulated data. For human data, this bias was substantially reduced by including a RM. For [¹¹C]DASB the low-statistics bias in the caudate head at 1.7 M NEC (approx. 30 s) was −5.5% and −13% with and without RM, respectively. We predicted biases in the binding potential of −4% and −10%. For quantification of cerebral blood flow for the whole-brain grey- or white-matter, using [¹⁵O]H₂O and the PET autoradiographic method, a low-statistics bias of <2.5% and <4% was predicted for reconstruction with and without the RM. The use of a resolution model reduces low-statistics bias and can hence be beneficial for quantitative dynamic PET.

Non-thermal irreversible electroporation (NTIRE) is a biophysical phenomenon which involves application of electric field pulses to cells or tissues, causing certain rearrangements in the membrane structure leading to cell death. The treated tissue ac impedance changes induced by electroporation were shown to be the indicators for NTIRE efficiency. In a previous study we characterized in vitro tissue galvanic apparent internal resistance (GAIR) changes due to NTIRE. Here we describe an in vivo study in which we monitored the GAIR changes of a rat liver treated by NTIRE. Electrical pulses were delivered through the same Zn/Cu electrodes by which GAIR was measured. GAIR was measured before and for 3 h after the treatment at 15 min intervals. The results were compared to the established ac bioimpedance measurement method. A decrease of 33% was measured immediately after the NTIRE treatment and a 40% decrease was measured after 3 h in GAIR values; in the same time 40% and 47% decrease respectively were measured by ac bioimpedance analyses. The temperature increase due to the NTIRE was only 0.5 °C. The results open the way for an inexpensive, self-powered in vivo real-time NTIRE effectiveness measurement.

A feasibility study of a novel PET-based molecular image guided radiation therapy (m-IGRT) system was conducted by comparing PET-based digitally reconstructed planar image (PDRI) registration with radiographic registration. We selected a pair of opposing parallel-plane PET systems for the practical implementation of this system. Planar images along the in-plane and cross-plane directions were reconstructed from the parallel-plane PET data. The in-plane and cross-plane FWHM of the profile of 2 mm diameter sources was approximately 1.8 and 8.1 mm, respectively. Therefore, only the reconstructed in-plane image from the parallel-plane PET data was used in the PDRI registration. In the image registration, five different sizes of ¹⁸F cylindrical sources (diameter: 8, 12, 16, 24, 32 mm) were used to determine setup errors. The data acquisition times were 1, 3 and 5 min. Image registration was performed by five observers to determine the setup errors from PDRI registration and radiographic registration. The majority of the mean registration errors obtained from the PDRI registration were not significantly different from those obtained from the radiographic registration. Acquisition time did not appear to result in significant differences in the mean registration error. The mean registration error for the PDRI registration was found to be 0.93 ± 0.33 mm. This is not statistically different from the radiographic registration which had a mean registration error of 0.92 ± 0.27 mm. Our results suggest that m-IGRT image registration using PET-based reconstructed planar images along the in-plane direction is feasible for clinical use if PDRI registration is performed at two orthogonal gantry angles.

This paper describes a digital radiography (DR) quality control protocol for DR detectors from the forthcoming report from the Institute of Physics and Engineering in Medicine (IPEM). The protocol was applied to a group of six identical caesium iodide (CsI) digital x-ray detectors to assess reproducibility of methods, while four further detectors were assessed to examine the wider applicability. Twelve images with minimal spatial frequency processing are required, from which the detector response, lag, modulation transfer function (MTF), normalized noise power spectrum (NNPS) and threshold contrast-detail (c-d) detectability are calculated. The x-ray spectrum used was 70 kV and 1 mm added copper filtration, with a target detector air kerma of 2.5 µGy for the NNPS and c-d results. In order to compare detector performance with previous imaging technology, c-d data from four screen/film systems were also acquired, at a target optical density of 1.5 and an average detector air kerma of 2.56 µGy. The DR detector images were typically acquired in 20 min, with a further 45 min required for image transfer and analysis. The average spatial frequency for the 50% point of the MTF for six identical detectors was 1.29 mm⁻¹ ± 0.05 (3.9% coefficient of variation (cov)). The air kerma set for the six systems was 2.57 µGy ± 0.13 (5.0% cov) and the NNPS at this air kerma was 1.42 × 10⁻⁵ mm² (6.5% cov). The detective quantum efficiency (DQE) measured for the six identical detectors was 0.60 at 0.5 mm⁻¹, with a maximum cov of 10% at 2.9 mm⁻¹, while the average DQE was 0.56 at 0.5 mm⁻¹ for three CsI detectors from three different manufacturers. Comparable c-d performance was found for these detectors (5.9% cov) with an average threshold contrast of 0.46% for 11 mm circular discs. The average threshold contrast for the S/F systems was 0.70% at 11 mm, indicating superior imaging performance for the digital systems. The protocol was found to be quick, reproducible and gave an in-depth assessment of performance for a range of digital x-ray detectors.

Curative breast radiotherapy typically leaves patients with varying degrees of cosmetic damage. One problem interfering with cosmetically acceptable breast radiotherapy is the external contour for large pendulous breasts which often results in high doses to skin folds. Thermoplastic casts are often employed to secure the breasts to maintain setup reproducibility and limit the presence of skin folds. This paper aims to determine changes in surface dose that can be attributed to the use of thermoplastic immobilization casts. Skin dose for a clinical hybrid conformal/IMRT breast plan was measured using radiochromic film and MOSFET detectors at a range of water equivalent depths representative of the different skin layers. The radiochromic film was used as an integrating dosimeter, while the MOSFETs were used for real-time dosimetry to isolate the contribution of skin dose from individual IMRT segments. Strips of film were placed at various locations on the breast and the MOSFETs were used to measure skin dose at 16 positions spaced along the film strips for comparison of data. The results showed an increase in skin dose in the presence of the immobilization cast of up to 45.7% and 62.3% of the skin dose without the immobilization cast present as measured with Gafchromic EBT film and MOSFETs, respectively. The increase in skin dose due to the immobilization cast varied with the angle of beam incidence and was greatest when the beam was normally incident on the phantom. The increase in surface dose with the immobilization cast was greater under entrance dose conditions compared to exit dose conditions.

X-ray scatter is a significant problem in cone-beam computed tomography when thicker objects and larger cone angles are used, as scattered radiation can lead to reduced contrast and CT number inaccuracy. Advances have been made in x-ray computed tomography (CT) by incorporating a high quality prior image into the image reconstruction process. In this paper, we extend this idea to correct scatter-induced shading artifacts in cone-beam CT image-guided radiation therapy. Specifically, this paper presents a new scatter correction algorithm which uses a prior image with low scatter artifacts to reduce shading artifacts in cone-beam CT images acquired under conditions of high scatter. The proposed correction algorithm begins with an empirical hypothesis that the target image can be written as a weighted summation of a series of basis images that are generated by raising the raw cone-beam projection data to different powers, and then, reconstructing using the standard filtered backprojection algorithm. The weight for each basis image is calculated by minimizing the difference between the target image and the prior image. The performance of the scatter correction algorithm is qualitatively and quantitatively evaluated through phantom studies using a Varian 2100 EX System with an on-board imager. Results show that the proposed scatter correction algorithm using a prior image with low scatter artifacts can substantially mitigate scatter-induced shading artifacts in both full-fan and half-fan modes.

Spatial and soft tissue information provided by magnetic resonance imaging can be very valuable during image-guided procedures, where usually only real-time two-dimensional (2D) x-ray images are available. Registration of 2D x-ray images to three-dimensional (3D) magnetic resonance imaging (MRI) data, acquired prior to the procedure, can provide optimal information to guide the procedure. However, registering x-ray images to MRI data is not a trivial task because of their fundamental difference in tissue contrast. This paper presents a technique that generates pseudo-computed tomography (CT) data from multi-spectral MRI acquisitions which is sufficiently similar to real CT data to enable registration of x-ray to MRI with comparable accuracy as registration of x-ray to CT. The method is based on a k-nearest-neighbors (kNN)-regression strategy which labels voxels of MRI data with CT Hounsfield Units. The regression method uses multi-spectral MRI intensities and intensity gradients as features to discriminate between various tissue types. The efficacy of using pseudo-CT data for registration of x-ray to MRI was tested on ex vivo animal data. 2D–3D registration experiments using CT and pseudo-CT data of multiple subjects were performed with a commonly used 2D–3D registration algorithm. On average, the median target registration error for registration of two x-ray images to MRI data was approximately 1 mm larger than for x-ray to CT registration. The authors have shown that pseudo-CT data generated from multi-spectral MRI facilitate registration of MRI to x-ray images. From the experiments it could be concluded that the accuracy achieved was comparable to that of registering x-ray images to CT data.

Local motions and deformations of organs between treatment fractions introduce geometrical uncertainties into radiotherapy. These uncertainties are generally taken into account in the treatment planning by enlarging the radiation target by a margin around the clinical target volume. However, a practical method to fully include these uncertainties is still lacking. This paper proposes a model based on the principal component analysis to describe the patient-specific local probability distributions of voxel motions so that the average values and variances of the dose distribution can be calculated and fully used later in inverse treatment planning. As usually only a very limited number of data for new patients is available; in this paper the analysis is extended to use population data. A basic assumption (which is justified retrospectively in this paper) is that general movements and deformations of a specific organ are similar despite variations in the shapes of the organ over the population. A proof of principle of the method for deformations of the prostate and the seminal vesicles is presented.

The purpose of this work was to compare the clinical adaptation of prompt gamma (PG) imaging and positron emission tomography (PET) as independent tools for non-invasive proton beam range verification and treatment validation. The PG range correlation and its differences with PET have been modeled for the first time in a highly heterogeneous tissue environment, using different field sizes and configurations. Four patients with different tumor locations (head and neck, prostate, spine and abdomen) were chosen to compare the site-specific behaviors of the PG and PET images, using both passive scattered and pencil beam fields. Accurate reconstruction of dose, PG and PET distributions was achieved by using the planning computed tomography (CT) image in a validated GEANT4-based Monte Carlo code capable of modeling the treatment nozzle and patient anatomy in detail. The physical and biological washout phenomenon and decay half-lives for PET activity for the most abundant isotopes such as ¹¹C, ¹⁵O, ¹³N, ³⁰P and ³⁸K were taken into account in the data analysis. The attenuation of the gamma signal after traversing the patient geometry and respective detection efficiencies were estimated for both methods to ensure proper comparison. The projected dose, PG and PET profiles along many lines in the beam direction were analyzed to investigate the correlation consistency across the beam width. For all subjects, the PG method showed on average approximately 10 times higher gamma production rates than the PET method before, and 60 to 80 times higher production after including the washout correction and acquisition time delay. This rate strongly depended on tissue density and elemental composition. For broad passive scattered fields, it was demonstrated that large differences exist between PG and PET signal falloff positions and the correlation with the dose distribution for different lines in the beam direction. These variations also depended on the treatment site and the particular subject. Thus, similar to PET, direct range verification with PG in passive scattering is not easily viable. However, upon development of an optimized 3D PG detector, indirect range verification by comparing measured and simulated PG distributions (currently being explored for the PET method) would be more beneficial because it can avoid the inherent biological challenges of the PET imaging. The improved correlation of PG and PET with dose when using pencil beams was evident. PG imaging was found to be potentially advantageous especially for small tumors in the presence of high tissue heterogeneities. Including the effects of detector acceptance and efficiency may hold PET superior in terms of the amplitude of the detected signal (depending on the future development of PG detection technology), but the ability to perform online measurements and avoid signal disintegration (due to washout) with PG are important factors that can outweigh the benefits of higher detection sensitivity.

Iterative reconstruction algorithms have been widely used in PET and SPECT emission tomography. Accurate modeling of photon noise propagation is crucial for quantitative tomography applications. Iteration-based noise propagation methods have been developed for only a few algorithms that have explicit multiplicative update equations. And there are discrepancies between the iteration-based methods and Fessler's fixed-point method because of improper approximations. In this paper, we present a unified theoretical prediction of noise propagation for any penalized expectation maximization (EM) algorithm where the EM approach incorporates a penalty term. The proposed method does not require an explicit update equation. The update equation is assumed to be implicitly defined by a differential equation of a surrogate function. We derive the expressions using the implicit function theorem, Taylor series and the chain rule from vector calculus. We also derive the fixed-point expressions when iterative algorithms converge and show the consistency between the proposed method and the fixed-point method. These expressions are solely defined in terms of the partial derivatives of the surrogate function and the Fisher information matrices. We also apply the theoretical noise predictions for iterative reconstruction algorithms in emission tomography. Finally, we validate the theoretical predictions for MAP-EM and OSEM algorithms using Monte Carlo simulations with Jaszczak-like and XCAT phantoms, respectively.

We describe a fibre-based variable-incidence angle (VIA) polarization-sensitive swept-source optical coherence tomography (PS-SS-OCT) system to determine the 3D optical axis of birefringent biological tissues. Single-plane VIA-PS-OCT is also explored which requires measurement of the absolute fast-axis orientation. A state-of-the-art PS-SS-OCT system with some improvements both in hardware and software was used to determine the apparent optical birefringence of equine tendon for a number of different illumination directions. Polar and azimuthal angles of cut equine tendon were produced by the VIA method and compared with the nominal values. A quarter waveplate (QWP) and equine tendon were used as test targets to validate the fast-axis measurements using the system. Polar and azimuthal angles of cut equine tendon broadly agreed with the expected values within about 8% of the nominal values. A theoretical and experimental analysis of the effect of the sample arm fibre on determination of optical axis orientation using a proposed definition based on the orientation of the eigenpolarization ellipse experimentally confirms that this algorithm only works correctly for special settings of the sample arm fibre. A proposed algorithm based on the angle between Stokes vectors on the Poincaré sphere is confirmed to work for all settings of the sample arm fibre. A calibration procedure is proposed to remove the sign ambiguity of the measured orientation and was confirmed experimentally by using the QWP.

The OpenPET geometry is our new idea to visualize a physically opened space between two detector rings. In this paper, we developed the first small prototype to show a proof-of-concept of OpenPET imaging. Two detector rings of 110 mm diameter and 42 mm axial length were placed with a gap of 42 mm. The basic imaging performance was confirmed through phantom studies; the open imaging was realized at the cost of slight loss of axial resolution and 24% loss of sensitivity. For a proof-of-concept of PET image-guided radiation therapy, we carried out the in-beam tests with ¹¹C radioactive beam irradiation in the heavy ion medical accelerator in Chiba to visualize in situ distribution of primary particles stopped in a phantom. We showed that PET images corresponding to dose distribution were obtained. For an initial proof-of-concept of real-time multimodal imaging, we measured a tumor-inoculated mouse with ¹⁸F-FDG, and an optical image of the mouse body surface was taken during the PET measurement by inserting a digital camera in the ring gap. We confirmed that the tumor in the gap was clearly visualized. The result also showed the extension effect of an axial field-of-view (FOV); a large axial FOV of 126 mm was obtained with the detectors that originally covered only an 84 mm axial FOV. In conclusion, our initial imaging studies showed promising performance of the OpenPET.

This study aims to develop a new computer-aided detection (CAD) scheme to detect early interstitial lung disease (ILD) using low-dose computed tomography (CT) examinations. The CAD scheme classifies each pixel depicted on the segmented lung areas into positive or negative groups for ILD using a mesh-grid-based region growth method and a multi-feature-based artificial neural network (ANN). A genetic algorithm was applied to select optimal image features and the ANN structure. In testing each CT examination, only pixels selected by the mesh-grid region growth method were analyzed and classified by the ANN to improve computational efficiency. All unselected pixels were classified as negative for ILD. After classifying all pixels into the positive and negative groups, CAD computed a detection score based on the ratio of the number of positive pixels to all pixels in the segmented lung areas, which indicates the likelihood of the test case being positive for ILD. When applying to an independent testing dataset of 15 positive and 15 negative cases, the CAD scheme yielded the area under receiver operating characteristic curve (AUC = 0.884 ± 0.064) and 80.0% sensitivity at 85.7% specificity. The results demonstrated the feasibility of applying the CAD scheme to automatically detect early ILD using low-dose CT examinations.

The capability of currently available echocardiography-based strain estimation techniques to fully map myocardial abnormality at early stages of myocardial ischemia is yet to be investigated. In this study, myocardial elastography (ME), a radio-frequency (RF)-based strain imaging technique that maps the full 2D transmural angle-independent strain tensor in standard echocardiographic views at both high spatial and temporal resolution is presented. The objectives were to (1) evaluate the performance of ME on mapping the onset, extent and progression of myocardial ischemia at graded coronary constriction levels (from partial to complete coronary flow reduction), and (2) validate the accuracy of the strain estimates against sonomicrometry (SM) measurements. A non-survival canine ischemic model (n = 5) was performed by gradually constricting the left anterior descending (LAD) coronary blood flow from 0% (baseline blood flow) to 100% (zero blood flow) at 20% increments. An open-architecture ultrasound system was used to acquire RF echocardiograms in a standard full short-axis view at the frame rate of 211 fps, at least twice higher than what is typically used in conventional echocardiographic systems, using a previously developed, fully automated composite technique. Myocardial deformation was estimated by ME and validated against sonomicrometry. ME estimates and maps transmural (1) 2D displacements using RF cross-correlation and recorrelation; and (2) 2D polar (radial and circumferential) strains, derived from 2D (i.e. both lateral and axial) displacement components, at high accuracy. Full-view strain images were shown and found to reliably depict decreased myocardial function in the region at risk at increased levels of coronary flow reduction. The ME radial strain was deemed to be a more sensitive, quantitative, regional measure of myocardial ischemia as a result of coronary flow reduction when compared to the conventional wall motion score index and ejection fraction. Good agreement (0.22% strain bias, 95% limits of agreement) using Bland–Altman analysis and good correlation (r = 0.84) were found between the ME and SM measurements. These findings demonstrate for the first time that ME could map angle-independent strains to non-invasively detect, localize and characterize the early onset of myocardial ischemia, i.e. at 40%, and possibly as low as 20%, LAD flow reduction, which could be further associated with the severity of coronary stenosis.

In this paper, we present a Bayesian maximum a posteriori method for multi-slice helical CT reconstruction based on an L0-norm prior. It makes use of a very low number of projections. A set of surrogate potential functions is used to successively approximate the L0-norm function while generating the prior and to accelerate the convergence speed. Simulation results show that the proposed method provides high quality reconstructions with highly sparse sampled noise-free projections. In the presence of noise, the reconstruction quality is still significantly better than the reconstructions obtained with L1-norm or L2-norm priors.

Dual-energy chest radiography has the potential to provide better diagnosis of lung disease by removing the bone signal from the image. Dynamic dual-energy radiography is now possible with the introduction of digital flat-panel detectors. The purpose of this study is to evaluate the feasibility of using dynamic dual-energy chest radiography for functional lung imaging and tumor motion assessment. The dual-energy system used in this study can acquire up to 15 frames of dual-energy images per second. A swine animal model was mechanically ventilated and imaged using the dual-energy system. Sequences of soft-tissue images were obtained using dual-energy subtraction. Time subtracted soft-tissue images were shown to be able to provide information on regional ventilation. Motion tracking of a lung anatomic feature (a branch of pulmonary artery) was performed based on an image cross-correlation algorithm. The tracking precision was found to be better than 1 mm. An adaptive correlation model was established between the above tracked motion and an external surrogate signal (temperature within the tracheal tube). This model is used to predict lung feature motion using the continuous surrogate signal and low frame rate dual-energy images (0.1–3.0 frames per second). The average RMS error of the prediction was (1.1 ± 0.3) mm. The dynamic dual energy was shown to be potentially useful for lung functional imaging such as regional ventilation and kinetic studies. It can also be used for lung tumor motion assessment and prediction during radiation therapy.

A novel transmission detector (IBA Dosimetry, Germany) developed as an IMRT quality assurance tool, intended for in vivo patient dose measurements, is studied here. The goal of this investigation is to use Monte Carlo techniques to characterize treatment beam parameters in the presence of the detector and to compare to those of a plastic block tray (a frequently used clinical device). Particular attention is paid to the impact of the detector on electron contamination model parameters of two commercial dose calculation algorithms. The linac head together with the COMPASS transmission detector (TRD) was modeled using BEAMnrc code. To understand the effect of the TRD on treatment beams, the contaminant electron fluence, energy spectra, and angular distributions at different SSDs were analyzed for open and non-open (i.e. TRD and block tray) fields. Contaminant electrons in the BEAMnrc simulations were separated according to where they were created. Calculation of surface dose and the evaluation of contributions from contaminant electrons were performed using the DOSXYZnrc user code. The effect of the TRD on contaminant electrons model parameters in Eclipse AAA and Pinnacle³ dose calculation algorithms was investigated. Comparisons of the fluence of contaminant electrons produced in the non-open fields versus open field show that electrons created in the non-open fields increase at shorter SSD, but most of the electrons at shorter SSD are of low energy with large angular spread. These electrons are out-scattered or absorbed in air and contribute less to surface dose at larger SSD. Calculated surface doses with the block tray are higher than those with the TRD. Contribution of contaminant electrons to dose in the buildup region increases with increasing field size. The additional contribution of electrons to surface dose increases with field size for TRD and block tray. The introduction of the TRD results in a 12% and 15% increase in the Gaussian widths used in the contaminant electron source model of the Eclipse AAA dose algorithm. The off-axis coefficient in the Pinnacle³ dose calculation algorithm decreases in the presence of TRD compared to without the device. The electron model parameters were modified to reflect the increase in electron contamination with the TRD, a necessary step for accurate beam modeling when using the device.

The derivative at constant direction is frequently used in inversion of cone-beam data. Several algorithms for computing the derivative have been proposed in the literature. The best algorithm to date has been proposed recently by Noo et al (2007 Phys. Med. Biol.52 5393–414). In this note we propose a new, simple and efficient formula for computing the derivative. Numerical experiments with helical CT show that our formula and the one of Noo et al provide fairly similar spatial resolution and noise stability, even though the new formula is more efficient and easier to implement.

In this study, we investigated the in vivo application of an integrated small-animal magnetic resonance (MR) and gamma-ray imaging system that consists of a semiconductor-based radiation detector, a parallel-hole collimator, and a specialized radiofrequency coil. Gadodiamide and ^99mTc sestimibi agents were injected simultaneously into a mouse, and simultaneous dynamic contrast-enhanced MR and scintigraphic images of the kidneys were acquired. The time curves of both the MR signal intensity and radioactivity indicate a rapid uptake of the agents followed by a more gradual excretion, consistent with the previously reported literature. Our results demonstrate the feasibility of measuring multiple biological processes at the same time using both MR contrast agents and radiotracers.

While intensity-modulated proton therapy (IMPT) has great potential to improve the therapeutic efficacy of radiotherapy, IMPT optimization can be computationally demanding, particularly for large and complex tumors. Here we propose a dose calculation strategy to accelerate IMPT optimization while reducing memory requirements. By using two adjustable threshold parameters, our method separates dose contributions from proton beamlets into major and minor components for each dose voxel. The optimization proceeds with two levels of iterations: in inner iterations, doses are updated in correspondence with changes in beamlet intensities from only the major contributions while keeping the portions from the minor contributions constant; in outer iterations, doses are recalculated exactly by considering both major and minor contributions. Since the number of elements in the influence matrix for major contributions is relatively small, each inner iteration proceeds quickly. Each outer iteration requires a longer computation time, but only a few such iterations are needed. Our study shows that the proposed strategy leads to nearly identical dose distributions as those optimized with the full influence matrix, but reducing computing time by at least a factor of 3 and internal memory requirements by a factor of 10 or more. In addition, we show that the proposed approach could enhance other optimization-related applications such as optimizing beam angles. By using an advanced lung cancer case that would demand large computing resources by conventional optimization approach, we show how our method may potentially help improve IMPT treatment planning in real clinical situations.