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Image quality of 68Ga Positron Emission Tomography (PET) studies is impacted by its relatively high positron range compared with 18F, thus limiting spatial resolution. This simulation study describes a post-reconstruction 2-dimensional (2D) positron range correction (post-PRC) using the Richardson-Lucy (RL) de-blurring method for 68Ga. The method proposed is based on a 2-dimensional de-blurring kernel derived in bone, soft-tissue and lung medium. and the kernel was applied to the simulated image of the NEMA Image Quality phantom geometry with a target-to-background ratio of 8:1. The post-PRC method can recover spatial resolution loss by approximately 1%, 9% and 56% in bone, water and lung medium, respectively. However, the proposed de-blurring method increases image noise, particularly in the lung medium. This convenient post-processing de-blurring approach does not require raw data or modification to the reconstruction algorithm allowing it to be adopted to the reconstructed volumes of any PET scanner.

Regional quantification is often considered the end-point of many studies in Positron Emission Tomography (PET). However, in neurological small animal imaging, features can be sufficiently small that device resolution and voxel granularity inhibit the definition of segmentation boundaries that closely conform to organs or regions of interest. Even if well defined, estimation of uncertainty over small regions is problematic, particularly given that in some cases — such as in awake animal imaging — studies are unique and non-repeatable. The Origin Ensembles algorithm is an approach to image reconstruction based on Bayesian inference which utilises Monte-Carlo driven sampling to determine the posterior distribution of the emission counts given the measured data. The algorithm explores the full posterior and so can be used to estimate measures of uncertainty in quantitative parameters drawn from the data. However, being inference based, Origin Ensembles is sensitive to the dimension of the parameter space over which estimates are made. In this investigation the dimension of the image space is reduced using a regional segmentation based on an initial MLEM reconstruction of detected data. Origin Ensembles is used to reconstruct data directly to the regions of interest over which quantification is desired providing estimation of the full posterior distribution for each region. Origin Ensembles sampling allows the uncertainty in quantitative values to be determined both in terms of parameter variance and the covariance between recovered regional intensities. Direct regional reconstruction was employed in this study using simulated data and was shown to enhance the precision and accuracy of recovered values.

Motion corrected images from awake and freely moving animals often exhibit reduced resolution when compared to their stationary counterparts. This could be attributed to the combination of brief periods of fast animal motion and insufficient motion sampling speed. In this paper we hypothesise that we can measure the motion dependent point spread function of a given study and mitigate the motion blurring artifacts in the reconstructed images, in a similar way that a measured system response point spread function can improve resolution due to geometric effects (e.g. parallax errors). We investigated this hypothesis on a set of experimentally measured phantom data, which underwent a series of distinctively different motion patterns, ranging from slow to fast. Preliminary results showed that motion corrected images have reduced resolution compared to the stationary image and noticeable motion blurring artefacts, particularly for fast speed/acceleration settings. In addition, images deconvolved after reconstruction with the measured motion dependent PSF appear to be sharper compared to their unprocessed counterparts, yet without completely eliminating the motion blurring artefacts. Work is in progress to refine the methodology, by decomposing the geometric and motion components of the PSF, as well as including the deconvolution within the reconstruction algorithm.

In order to remove the influence of anaesthetic agents on neurological function and to expand the range of imaging tasks available it is preferable to image small animals in an awake state. Accurate activity estimates in awake small animal Positron Emission Tomography rely on the measurement of animal head pose over the time-course of the scan. Pose measurements are then incorporated into the emission data during image reconstruction, compensating for animal motion. Uncertainty in pose measurement can impact reconstructed image quality by effectively degrading scanner resolution, and hence that of the reconstructed image. In small animal imaging, regions of interest can be small in comparison to image-space voxelisation so that the precision of estimates taken from a single reconstructed image can be difficult to gauge. Stochastic Origin Ensembles provides a means of estimating a more complete statistical description of the emission data than other methods of image reconstruction. In this investigation, rigid motion compensation is incorporated into the Stochastic Origin Ensembles algorithm and explored using simulated data. Realistic motion is modeled within a GATE simulation and measurement uncertainty is incorporated into the pose data using both simulated perturbations as well as experimental trials using a motion tracking system. Sampling from the posterior distribution is conducted using the Stochastic Origin Ensembles algorithm and compared to image reconstruction using the Maximum Likelihood-Expectation Maximisation algorithm. Using Stochastic Origin Ensembles both regional and single voxel parameters were investigated. The impact of varying levels of pose measurement uncertainty on image-space parameters was demonstrated and assessed.

The temporal characterisation of endogenous neurotransmitter release during a cognitive task or drug intervention is an important capability for studying the role of neuro-transmitters in normal and aberrant brain function, including disease. Advanced kinetic models, such as the linear parametric neurotransmitter PET (lp-ntPET) have been developed to appropriately model the transient changes in the model parameters, such as the radiotracer efflux from the target tissue, during endogenous neurotransmitter release. Incorporation of the kinetic model within the tomographic reconstruction algorithm may lead to improved parameter estimates, both in terms of precision and accuracy, compared to the conventional two-step post reconstruction approach. In this study, we evaluate a direct reconstruction approach that uses an expectation maximisation framework to transfer the 4D spatiotemporal maximum likelihood problem into an image-based weighted least squares problem. This framework allows the use of well established kinetic models, such as the lp-ntPET model, to estimate the endogenous neurotransmitter response directly from the dynamic PET data. Dynamic GATE simulations using a realistic digital rat brain phantom showed that the proposed direct reconstruction method can provide higher temporal accuracy and precision for the estimated neurotransmitter response at the voxel level, compared to the conventional post reconstruction modelling. In addition, we applied this methodology to a [11C]raclopride displacement study in an awake and freely moving rat and generated voxel-wise parametric maps illustrating ligand displacement from striatum.

A spatially variant resolution modelling technique for PET image reconstruction is presented which models the physical processes of the measurement during the iterative reconstruction. This is achieved by redistributing the line-of-response endpoints according to derived probability density functions describing the detector response function and photon acollinearity. When applying this technique it is shown that, to avoid mathematical inconsistencies and reconstruction artefacts, MLEM cannot be used for the reconstruction. The ISRA algorithm, after being adapted to a list-mode based implementation, is used instead since its structure is well-suited to this application. The Redistribution technique is shown to produce superior resolution recovery in off-centre phantom reconstructions than the standard stationary image-space Gaussian convolution approach, and it only requires approximately 35% more computation time.

Reliable interpretation of results from pre-clinical Emission Tomography studies is often hampered by the requirement that the animal be anesthetised, affecting certain neuro-transmission systems and cerebral blood flow. Animal tracking and motion compensation techniques have been exploited to account for that rigid motion associated with head movement - allowing brain imaging in small animals. However, rigid motion cannot be assumed for extra cranial activity. Tetrahedral mesh approaches have been applied in cardiac reconstruction to account for non-rigid motion in clinical environments. In this investigation a list-mode approach to calculation of the elements of the system matrix using a tetrahedral image space is developed and evaluated by applying rigid motion compensation to both simulated and experimental data. Experimental data for which only rigid motion was applied were used to demonstrate the application of variable voxel-size over the image space. A simple small animal model comprising rigid (head) and non-rigid (body) motion was developed and the resulting voxelised sources were simulated using GATE. Motion compensation based on rigid transforms allowed targeted voxel sampling and demonstrates the impact of the non-rigid motion of activity estimates. The tetrahedral mesh should allow future investigations to extend correction to also include non-rigid estimates of small animal motion.

Accurate motion compensated image reconstruction of freely moving small animals requires the exact calculation of the time-weighted sensitivity correction factors. Back-projection of all possible lines of response for every recorded pose is a computationally intensive task, which requires impractically long reconstruction times. In this work we investigated an approach to accelerate this task, by randomly sampling the lines of response and the poses that are used to calculate the time-averaged sensitivity image. Two phantom datasets, acquired on the microPET Focus220 scanner, were used to quantify errors introduced in the randomly sampled sensitivity images and propagated to the final reconstructed images. In addition, the qualitative performance of the proposed methodology was assessed by reconstructing a freely moving rat acquisition. Results showed that randomisation can severely amplify the noise in the reconstructed images, especially when few LORs are sampled. However, such errors can be suppressed by post-filtering the randomised sensitivity images prior to reconstruction (e.g. 2 mm FHWM). Such an approach can substantially reduce the computational time involved during the estimation of the time-averaged sensitivity image for motion compensated image reconstruction.

The kinetics of single photon emitting macromolecules (e.g. antibodies) are typically slower than small molecules, necessitating long or repeat acquisitions. We previously proposed the use of motion tracking and limited angle tomographic reconstruction to characterise tracer kinetics over extended periods in awake rodents. In this study, we explored this approach by imaging a contrast phantom, moved with 6 degrees of freedom, using a prototype preclinical SPECT scanner with parallel-hole collimation and a fixed detector located at 0 and 90 degrees. The position of the phantom was tracked and data were acquired in list mode. Each event was motion-corrected and reconstructed using LM-MLEM. Planar projections were created by summing the reconstructed volume along the x-axis. Line profiles of the contrast phantom were compared for a planar reference projection and projections generated from the motion-free, motion-corrupted and motion-corrected reconstructions. Projections created from the motion-corrected agreed well with the planar reference projection of the stationary object and exhibited similar contrast. Whilst this initial study was limited to rigid motion, it demonstrates the feasibility of motion-corrected planar projections of a moving object.

Hadron-therapy (HT) delivers high dose to the tumor, significantly sparing surrounding healthy tissues. Positron Emission Tomography (PET) can be used to image short-lived positron-emitters, produced by the hadron beam in the patient. PET is nowadays the most assessed imaging technique to monitor HT treatments. The number of positron-emitters produced is much lower than in conventional clinical scenarios, dedicated scanners and acquisition protocols are then required. Sensitivity becomes a crucial parameter since the duration of the acquisition is limited by the beam delivery during treatment (in-beam PET) as well as by the physiological wash-out of the radioisotopes after treatment (in-room PET). AX-PET, a novel PET concept with axially oriented crystals, provides a higher sensitivity almost fully decoupled from its 3D spatial resolution. The flexible design can overcome many of the geometrical constraints imposed by HT monitoring. This work presents a preliminary feasibility study of the application of AX-PET to the HT scenario in in-room modality.

A three layer Compton telescope for dose monitoring in hadron therapy is under development at IFIC - Valencia. It will consist of three detector layers and each layer will be made of a continuous LaBr 3 crystal coupled to four Silicon Photomultiplier (SiPM) arrays. A prototype made of two detector layers has already been assembled and tested. The detector layers consist of a 32×36×5 mm3 and 32×36×10 mm3 LaBr 3 crystal, each coupled to four SiPM arrays. The front-end electronics of each detector is based on the VATA64HDR16 application specific integrated circuit (ASIC). The gamma rays coming from a 22Na source have been detected with the two detector layers working in time coincidence, allowing energy and position estimation.

Hadron-therapy (HT) aims to treat tumors by maximizing the dose released to the target and sparing the dose to normal tissues. For a successful outcome it is very important to determine where the maximum dose is deposited; therefore range verification is necessary for treatment optimization and patient safety. Secondary positron emitting isotopes and prompt gamma radiation are produced after the hadron beam passage. This secondary radiation coming from tissue activation could be used for quality control of treatment, provided that it can be detected and employed to reconstruct the beam path using imaging techniques. This is one of the main goals of the ENVISION project: to evaluate and develop on-line monitoring devices for HT, like PET for detecting the annihilation photons from positrons and Compton Cameras (CCs) for prompt gamma radiation detection. In both technologies high sensitivity is required to increase the signal-to-noise ratio of the reconstructed image for a given therapeutic dose. This simulation study focuses on the sensitivity optimization of such devices, PET and CC, taking into account its use and constraints for on-line HT monitoring. Several configurations of both technologies have been investigated using sources generated from hadron beams. In the case of PET data, the time-of-flight (TOF) information has been included too. For individual hadron beams acquired after 5 minutes, differences in range of 3 mm are detected for all the PET configurations, except for the partial-ring of 60 cm diameter. In addition, patient data from a carbon ion treatment at GSI have been simulated and reconstructed. The system with higher sensitivity and angular sampling recovers more accurately areas with no activity (nasal cavity). In the case of the CC data, the quality of the reconstructed image when using 2-interaction events is notably improved when the detector layers are placed covering a larger solid angle.

Real-time monitoring techniques are receiving increased attention due to their great potential for improving the precision of treatment delivery for hadron-therapy (HT). The study of prompt-γ(PG) focuses on the energetic photon radiation exiting the patient few nanoseconds after the beam irradiation. Its high intensity compared to other similar technologies like in-beam Positron Emission Tomography (PET) and good correlation with the original dose deposition profile are promising features. On the other hand, the use of neutral particles to monitor the dose comes together with a high noise background, mainly due to neutrons and scattered γ, which are uncorrelated with the original dose map. The search of a robust detector that fully exploits the information from PG is still a matter of research.

The usage of long, axially oriented scintillator crystals in a PET scanner has been shown by the AX-PET Demonstrator as a possible solution for a high resolution and high sensitivity PET detector. In the AX-PET implementation, arrays of wavelength shifting (WLS) strips, placed orthogonally behind every crystal layer, are used to define the axial coordinate. After extensive characterization measurements, the AX-PET Demonstrator has been successfully used for the reconstruction of several phantoms and a few rodents. Possible extensions of the AX-PET concept towards Time Of Flight capabilities have been investigated, using Philips digital SiPMs as alternative photodetector. Promising CRT values equal to 211 ps have been demonstrated, using long crystals with dual sided readout and mean timing method. Finally, we report about an alternative way to reconstruct the axial coordinate: exploiting the light sharing of 100 mm long crystals with special surface treatment resulted in axial resolutions of the order of 4 mm FWHM.

A Compton telescope for dose delivery monitoring in hadron therapy is under development at IFIC Valencia within the European project ENVISION. The telescope will consist of three detector planes, each one composed of a LaBr3 continuous scintillator crystal coupled to four silicon photomultiplier (SiPM) arrays. After the development of a first prototype which served to assess the principle, a second prototype with larger crystals has been assembled and is being tested. The current version of the prototype consists of two detector layers, each one composed of a 32.5 × 35 mm2 crystal coupled to four SiPM arrays. The VATA64HDR16 ASIC has been employed as front-end electronics. The readout system consists of a custom made data acquisition board. Tests with point-like sources have been carried out in the laboratory, assessing the correct functioning of the device. The system optimization is ongoing.

The use of Silicon Photomultiplier (SiPM) arrays requires the use of multichannel data acquisition (DAQ) systems. For this reason a dedicated DAQ system has been developed for the read-out of several SiPM-based detector layers. The frontend of a system is based on the 64-channel ASIC V ATA64HDR16 from Gamma Medica - Ideas. As first application, the DAQ system will be employed in the construction of Compton telescope for dose monitoring in hadron therapy. However the designed system is suitable for any other devices that need to treat large number of SiPM channels. Tests are presented with SiPM matrix of 16 (4×4) elements each coupled to LYSO and LaBr3 continuous crystals. The complete characterization of the DAQ system and the obtained results are presented.

Image reconstruction for Compton camera data can be problematic due to the common trade-off between physically realistic models and speed of computation. In this investigation a novel method of system matrix calculation - Simulated One-Pass Listmode (SOPL) - is extended to incorporate Compton camera data. The method reduces the Cone Surface Response for the Compton camera to an ensemble of Siddon-rays and is conducted in two stages. As part of the ENVISION project for monitoring in hadron therapy, a continuous-crystal Lanthanum Bromide Compton camera has been developed and experimental data acquired. Continuous detection geometries are particularly susceptible to variation in both spatial and spectral resolution over the detection volume and so accurate yet flexible models of detection are particularly important. The SOPL-Compton method was applied via the Maximum Likelihood - Expectation Maximization algorithm to experimental data taken using the prototype device. In this investigation, detection modeling using SOPL-Compton in a two interaction Compton camera is validated and the incorporation of a shift-invariant image-space model confirmed as a useful modification to reduce computational expense. Finally experimental data taken using the prototype LaBr3 Compton camera provide confirmation of the SOPL-Compton approach to system modeling. Results indicate a fast, flexible and accurate algorithm that can easily be extended to alternate and novel detection geometries.

Increased sensitivity is one of the major challenges in novel detector development. While pixelated crystals are standard, the use of continuous crystals can provide increased active volume and thus sensitivity. Accurate estimation of the interaction positions of photons in continuous crystals requires a sophisticated algorithm. Additionally, including depth of interaction (Dol) in the reconstruction process can mitigate parallax effects near the edges of field of view, therefore Dol estimation is highly desirable. In this work, the interaction position coordinates in 3D are estimated adapting an already existing analytical model to our system with no additional hardware, training data sets or Monte Carlo simulations. The algorithm is implemented in a two-detector-head system comprised of continuous crystals coupled to SiPM arrays. Acquired data is stored in list-mode where the continuous nature of the interaction position is preserved. For image reconstruction, since the crystal is continuous, pre-computation of the system matrix elements would require discretization of the detected measurements. To avoid data discretization the system matrix elements are calculated on-the-fly. Spatial information is later on retained in the reconstruction algorithm by using a Siddon-like algorithm where the ray end-points correspond to the estimated interaction positions in continuous space, introducing the interaction position estimation uncertainty in the calculation of the system matrix elements. Reconstruction using continuous data is compared to reconstruction using artificially discretized data. Results show that the spatial resolution measured from a reconstructed point source using ML-EM obtained with a continuous crystal is superior to the spatial resolution obtained with a pixelated crystal.

In PET, as the spatial resolution of the measurement system is increased, multiple interactions of a single photon may be separately measured and such events are often removed from the data used in image reconstruction. While for some PET imaging tasks this effect is unimportant, for primate, brain and high-spatial-resolution imaging where sensitivity is important, such Inter Crystal Scattering (ICS) events may constitute a large fraction of the measured data. On-the-fly list-mode image reconstruction is generally required in order to use all the information provided by ICS. Simulated One-Pass List-mode image reconstruction is used in this investigation to study the inclusion of ICS information into the reconstructed image using data acquired with the AX-PET prototype. In almost all cases an increase in image quality was observed, particularly for larger features. A small resolution penalty was also observed.

The Axial PET (AX-PET) concept proposes a novel detection geometry for PET, based on layers of long scintillating crystals axially aligned with the bore axis. Arrays of wavelength shifting (WLS) strips are placed orthogonally and underneath the crystal layers; both crystals and strips are individually readout by G-APDs. The axial coordinate is obtained from the WLS signals by means of a Center-of-Gravity method combined with a cluster algorithm. This design allows spatial resolution and sensitivity to be decoupled and thus simultaneously optimized. In this work we present the latest results obtained with the 2-module AX-PET scanner prototype, which consists of 6 radial layers of 8 LYSO crystals each (crystal size: 3 × 3 × 100 mm3). The WLS arrays comprise 26 strips (3-mm wide) per layer. The estimated energy resolution from point-like measurements is 11.8% (FWHM at 511 keV). The intrinsic spatial resolution was measured for the two modules in coincidence at two different configurations using point-like sources, showing very little degradation when the modules were placed oblique to each other. The axial spatial resolution was 1.5 mm (FWHM) in all the studied cases. Tomographic data of extended phantoms filled with fluorine-18 have been acquired. Imaging a larger transaxial Field-of-View (when compared to the previous measurement campaign) was possible thanks to implementing secondary motion of one of the modules. We have also developed various reconstruction approaches which take into account the particular nature of AX-PET data, as well as a count rate model which allowed us to develop an acquisition protocol able to compensate for count losses. The reconstructed phantom images confirm the imaging capabilities of AX-PET, and the recent advancements in the DAQ let us expect significant improvements for future campaigns.

In hadron therapy particulate radiation is used to treat regions in close proximity to vital organs or tissue. Protons, or Carbon ions, provide enhanced treatment due to the characteristic Bragg peak structure of dose deposition, which constrains maximum dose deposition to a small volume of the patient. However, as there is no transmitted beam novel methods of beam monitoring must be developed to ensure accuracy in dose delivery. The particulate beam activates the target material giving rise to positrons, prompt gamma-rays and neutrons. While positron emission imaging is possible, Compton imaging has some distinct advantages in this role. The broad spectrum of prompt radiation means that incident photon energy is unknown. Unless incident photon energy can be determined, Compton imaging requires that either three or more interactions be measured or that the photon spectrum also be estimated during image reconstruction. However, the extension of the image space to include incident energy is inconvenient as the image space dimension is increased. Here pencil-beam therapy is considered, which allows the inclusion of beam information into the reconstruction algorithm. Coincident hodoscope information constrains the unknown spatial distribution of the emission field to a single dimension leaving one spatial and one spectral dimension. In this investigation hodoscope coincidence imaging using a Compton camera was explored using data simulated with GEANT4 and was shown to be a promising approach to the challenge of monitoring in hadron therapy.

In hadron therapy, a proton or carbon ion beam interacts with the tissue and prompt gamma rays are emitted from the excited nuclei that can be employed for dose monitoring. A Compton telescope makes it possible to locate the origin of these photons, allowing an indirect estimation of the delivered dose. The telescope prototype being developed at IFIC-Valencia within the ENVISION project will consist of three detector layers. Each layer will be composed of a continuous LaBr 3 crystal coupled to four Silicon Photomultiplier (SiPM) arrays. Coincidence tests have been carried out with a first layer of a 16 mm × 18 mm × 5 mm LaBr 3 crystal coupled to a 16 mm × 18 mm SiPM array and a second layer of a 12 mm × 12 mm × 5 mm LYSO crystal coupled to another 16 mm × 18 mm SiPM array. The test system is read out by two SPIROC1 boards working in time coincidence. First data have been taken and the results demonstrate the feasibility of operating the system.

Simulated One Pass List-mode is a means of image-reconstruction that distributes on-the-fly calculations of the full system matrix across multiple iterations during Maximum Likelihood-Expectation Maximization image reconstruction. On the fly list-mode processing of coincidence data provides a very flexible approach to image reconstruction that can be applied to many novel systems for Positron Emission Tomography. However, in addition to standard on-the-fly calculation and list-mode methods, Simulated One Pass List-mode provides for extra possibilities during image reconstruction. Two possibilities are investigated here: system modeling accuracy can be altered at each iteration and enhanced modeling can be conduced only for specific Regions of Interest. In this investigation simulated data from a simple two dimensional PET system is used to demonstrate these two advantages of Simulated One Pass List-mode image reconstruction for Positron Emission Tomography.

Monte Carlo based radiation transport modelling is a useful tool in evaluating the interaction and effect of radiation in a defined environment. The process of simulating Compton scattering is of interest in a large number of different fields. Of the range of available Monte Carlo radiation transport programs, Geant4, one of the most popular, integrated the effects of Doppler broadening into their standard low energy Compton scattering package in 2008. However, there still exists a significant limitation within this standard Compton scattering package regarding the algorithms that determine the emission direction of Compton electrons. Here we outline the development of the Monash University Low Energy Compton Scattering (MULECS) package. The package addresses the current limitation of Compton electron directionality of Geant4 through the inclusion of additional directional information of the pre-collision momentum. MULECS is intended to replace the standard Compton scattering package of Geant4 to improve the accuracy of emission imaging simulations below 2 MeV.

This is a preliminary study on the feasibility of using Resistive-Plate-Chambers (RPC) based Positron Emission Tomography (PET) for hadron-therapy monitoring. The imaging capabilities of the RPC gas detector are being investigated for PET. Their main advantages are excellent timing resolution, low cost and Depth Of Interaction information (DOI) due to their layered structure. Hadron-therapy (HT) aims at treating tumors by maximizing the dose released to the target and sparing healthy tissue. During irradiation with a hadron beam, fragments, positron emitting isotopes and gamma radiation are produced. This radiation coming from the tissue activation could be used for quality control of the treatment. Our work focuses on imaging the positron emitting isotopes using an RPC-based PET scanner. The low cost of RPC makes possible to enlarge the angular coverage of the scanner guaranteeing the higher sensitivity needed by the in-beam monitoring. In addition, the TOF capability and spatial resolution makes worth investigating it. A first protoype is currently under construction at CERN in the TERA group. For this study, Monte Carlo simulations by means of GATE were employed. Up on our knowledge, such gas detectors have not been simulated yet in GATE and the new version of GATE offers new tools for dosimetry. These are the main reasons of choosing GATE. A set of linear sources, simulating the delivery of a hadron beam, has proposed to evaluate the image quality for an ideal time resolution of the system and the TOF information is being considered in the reconstruction. For the full ring simulated system, no important differences were found between TOF and non-TOF images, only the contrast was always better for the TOF-images. However, further simulations should be performed adapting the system to the real situation (partial ring) for HT and lowering the detected events to a clinical number. Under these circumstances, we expect to be crucial the TOF capabilities of the RPC-PET.

Compton reconstruction requires the computationally intensive, yet highly parallelizable, task of Cone of Response (CoR) back-projection. The acceleration of CoR back-projection is of significant importance as a faster algorithm allows the user to increase either the size or resolution of the imaging volume. Such acceleration also lends itself to the realization of real-time reconstruction. The image estimate is formed by calculating and histogramming voxel-cone intersections in the imaging volume. As the level of computation increases with the cube of the length or resolution of the volume, the bottle-neck in processing the dataset is at the imaging-voxel level, as opposed to the event level. The reconstruction algorithm developed for the Pixelated Emission Detector for RadiOisotopes (PEDRO) system was optimized for threading at the voxel level and implemented in the C++ programming language. The benchmark C++ code was then extended with OpenCL to assess the acceleration that could be obtained by running the algorithm on a selection of commercially available Graphical Processing Units (GPUs). Increases of up to 102 times the bench-mark speed were achieved

The Pixelated Emission Detector for RadiOisotopes (PEDRO) is a hybrid imaging system designed for the measurement of single photon emission from small animal models. The proof-of-principle device consists of a Compton-camera situated behind a mechanical collimator and is intended to provide optimal detection characteristics over a broad spectral range, from 30 keV to 511 keV. An automated routine has been developed for the optimization of the mechanical collimator which consists of pinholes and open slits. The optimization was tested with a Geant4 model of the experimental prototype. The data were blurred with the expected position and energy resolution parameters and a Bayesian interaction ordering algorithm was applied. The results show that the optimization technique allows the large-area slits to sample fully the primary field of view (FoV). The slits were found to provide truncation of the back-projected cones of response and also an increase in the success rate of the interaction ordering algorithm. These factors resulted in an increase in the contrast and signal-to-noise ratios of the reconstructed image estimates.

A proof-of-principle Single Photon Emission Imaging (SPEI) system is being constructed and validated against Geant4 Monte-Carlo simulations, with the intention of determining the optimal detector configuration for imaging the evolution of induced matastices in small animals. This device consists of a Compton-camera situated behind a mechanical modulator. The combination of mechanical and electronic (hybrid) collimation should provide optimal detection characteristics over a broad spectral range (30 keV to 511 keV), through a reduction in the sensitivity-resolution trade-off, inherent in conventional mechanically collimated configurations. The Phase I imager has been constructed from a combination of off-the-shelf detectors and custom electronics to allow the experimental architecture and data processing algorithms to be tested. This paper presents the designs and preliminary results from the simulations.

The Pixelated Emission Detector for RadiOisotopes (PEDRO) is a hybrid emission imaging system designed for the measurement of single photon emission from small animals. The PEDRO is based on the combination of mechanical and electronic collimation (through the Compton effect). It utilizes a Compton-camera stack geometry situated behind an aperture array to modulate the incident radiation. The geometry is intended to maximize detection efficiency over a wide range of photon energies whilst maintaining the enhanced resolution of Single Photon Emission Imaging (SPEI). Geant4 simulations have been performed to allow validation of the model with experimental and theoretical data. This paper presents a preliminary validation of the simulation and an investigation into the effects of detector spacing for a multi-plane detector geometry.

Image reconstruction from Compton camera data is a complex problem requiring investigation. Generally reconstruction is conducted using iterative reconstruction methods such as Maximum Likelihood - Expectation Maximization (MLEM). However, iterative reconstruction into volumetric grids is a computational burden. Analytic methods of image reconstruction have been proposed which relieve the computational expense. However, such methods usually have unrealistic sampling assumptions or are not directly extendable to situations where the scattering detector is extended when compared to the detector-source distance. Starting from a standard inversion technique, a generic method of filtering inversion co-efficients is developed. By dynamically assigning the strength of co-efficients on an event-by-event basis, artifacts arising from the difference between assumed and actual forward transform may be reduced. Dynamic assignment allows inversion of single cone-surfaces, so that the generic technique may be implemented in volumetric reconstruction. Results are compared to direct-back-projection in a limited-angle tomography context. The ability to apply event-by-event analytic image reconstruction provides many advantages when compared to standard iterative techniques.

The evolution of germanium detectors over the last decade has lead to the possibility that they can be used in medical imaging and security scanning. The potential of increased sensitivity and energy resolution that germanium affords takes away the necessity of mechanical collimators that would be required in a gamma camera. Without mechanical collimation the resulting increase in statistics leads to the possibility of decreased patient dose or increased system throughput. In terms of security imaging segmented germanium provides directionality and excellent spectroscopic information for nuclide identification.

The performance of Compton imaging systems is limited by the angular uncertainty arising from the detector geometry and spatial resolution [Ordonez et al., 1997 amd 1999], When closely spaced multiple interactions are incorrectly recorded as a single event [Solomon and Ott, 1988], termed "interaction packing", the system response has considerable angular and directional uncertainty. In this situation, we test two methods for assigning the event location; binning the combined interaction to a central location, and sub-sampling to an energy weighted centroid. We considered a dual layer camera geometry containing two SmartPET detectors [Hall et al., 2003], and employed Geant4 [Agostinelli et al., 2003] to simulate the response to 662 keV photons. A cone-intersection algorithm [Wilderman et al., 2000] is utilised to reconstruct the activity distribution. The major findings are as follows. Interaction packing in the scatter detector leads to an increase in reconstructed background levels. Interaction packing in the absorption detector leads to a broader point spread function, but this is only observed using the energy centroid approximation. While both of these effects are small for the SmartPET based geometry, they may lead to image degradation when using different detection geometries, such as more closely spaced detection volumes.

Developments in position-sensitive spectroscopic detector systems resulting from work undertaken in the fields of astrophysics, high energy physics and medical imaging provide an opportunity for the synchrotron physics community to look at possible improvements to synchrotron studies. Specifications of the detector designed by the smartPET collaboration are outlined; a brief comparison with current options presented and possible applications to X-ray imaging, protein and macromolecular crystallography and X-ray fluorescence holography are introduced.

The Compton camera, a method of electronic collimation, introduces angular resolution into a gamma-ray imaging system without the need of a collimating device. Compton kinematics are used to deduce the incident trajectory of the photon, resulting in a cone-surface of possible source locations. So far this type of system has been successfully employed only as a single photon detection device. However, it has been proposed that positron emission tomography may also be enhanced by implementing the Compton camera. Cone-surfaces acquired from the collinear gamma rays produced in positron annihilation may be used to validate the resulting line of response. Moreover, single sided detections need no longer be redundant in image reconstruction due to the ability to perform cone-surface reconstruction in tandem with reconstruction from LoRs