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We designed a dedicated multi-detector multi-pinhole brain SPECT scanner to generate images of higher quality compared to general-purpose systems. The system, AdaptiSPECT-C, is intended to adapt its sensitivity-resolution trade-off by varying its aperture configurations allowing both high-sensitivity dynamic and high-spatial-resolution static imaging. The current system design consists of 23 detector heads arranged in a truncated spherical geometry. In this work, we investigated the axial and angular sampling capability of the current stationary system design. Two data acquisition schemes using limited rotation of the gantry and two others using axial translation of the imaging bed were also evaluated concerning their impact on image quality through improved sampling. Increasing both angular and axial sampling in the current prototype system resulted in quantitative improvements in image quality metrics and qualitative appearance of the images as determined in studies with specifically selected phantoms. Visual improvements for the brain phantoms with clinical distributions were less pronounced but presented quantitative improvements in the fidelity (normalized root-mean-square error (NRMSE)) and striatal specific binding ratio (SBR) for a dopamine transporter (DAT) distribution, and in NRMSE and activity recovery for a brain perfusion distribution. More pronounced improvements with increased sampling were seen in contrast recovery coefficient, bias, and coefficient of variation for a lesion in the brain perfusion distribution. The negligible impact of the most cranial ring of detectors on axial sampling, but its significant impact on sensitivity and angular sampling in the cranial portion of the imaging volume-of-interest were also determined.

Single photon emission tomography imaging of dopamine transporters (DATs) in the brain is a widely utilized study to improve the diagnosis of Parkinsonian syndromes, where conventional (parallel-hole and fan-beam) collimators on dual-head scanners are commonly employed. We have designed a multipinhole (MPH) collimator to improve the performance of DAT imaging. The MPH collimator focuses on the striatum and hence offers a better tradeoff for sensitivity and spatial resolution than the conventional collimators within this clinically most relevant region for DAT imaging. Our original MPH design consisted of 9 pinholes with a background-to-striatal (Bkg/Str) projection multiplexing of 1% only. In this simulation study, we investigated whether further improvements in the performance of MPH imaging could be obtained by increasing the number of pinholes, hence by enhancing the sensitivity and sampling, despite the ambiguity in reconstructing images due to increased multiplexing. We performed analytic simulations of the MPH configurations with 9, 13, and 16 pinholes (aperture diameters: 4–6 mm) using a digital phantom modeling DAT imaging. Our quantitative analyses indicated that using 13 (Bkg/Str: 12%) and 16 (Bkg/Str: 22%) pinholes provided better performance than the original 9-pinhole configuration for the acquisition with two or four angular views, but a similar performance with 8 and 16 views.

Stationary single photon emission computed tomography (SPECT) systems offer numerous advantages over rotating-head systems, but have one notable drawback in that the array of relatively smaller cameras contains more edges and gaps than clinical two headed systems. Scintillation events occurring at the edges of traditional photomultiplier-tube (PMT)-based SPECT cameras lose spatial resolution due to loss of light-sampling. Simulations using customized non-sequential raytracing scripts to model and analyze mean detector response functions (MDRFs) showed significant improvement in spatial resolution for hybrid-sensor cameras employing both silicon photomultipliers (SiPMs) and PMTs. The results inform the hardware design of AdaptiSPECT-C: a stationary clinical whole-brain SPECT imager with adaptive apertures for selective dynamic or high spatial resolution imaging. Its modular hybrid cameras use SiPMs to augment the PMTs and improve spatial resolution for position estimation tasks. SiPMs, having a small pitch and efficient fill factor, are employed as a border around the edges of each detector area. PMTs, being low cost and reliable, are packed in the center. The front end electronics are split into two main boards: one to drive and provide signal conditioning for the PMTs, and the other performing a similar function for the SiPMs. Ultimately, 81 total signal channels leave each camera as negative voltage pulses. AdaptiSPECT-C will have two equatorial rings of 10 cameras each and a quasi-vertex ring of 4 cameras, totaling 24. Modularity is the guiding design principle for the mechanical components of the cameras and ensures ease of assembly and field service in the completed system.

An adaptive-stationary-modular multi-pinhole (MPH) brain SPECT, AdaptiSPECT-C is being developed by the University of Arizona and University of Massachusetts Medical School to meet static and dynamic brain SPECT imaging needs. Salient features of the ASC include the use of adjustable pinhole apertures to dynamically adapt to imaging task needs, improved light measuring around the edge of the scintillator crystal, plus motion tracking and correction with attenuation correction enabled by usage of depth-sensing (DS)-cameras. For a target system spatial resolution of 8 mm at the focal point of the apertures, selected to enable comparison to current 2-headed commercial (2HC) SPECT imaging, we report investigation of aperture layout designs for a system with 3 rings of 18.4 cm flat square detector modules. We investigated sensitivity at the focal point in comparison to 2HC for usage of 1 versus 5 apertures per module, and variation in the extent of truncation and multiplexing of the irradiation fields by adjustment of the aperture location between the detector and focal point. For a system with one aperture per module and minor truncation we determined a sensitivity of 2.7x that of 2HC; whereas, with use of 4 oblique apertures with minor truncation and moderate multiplexing we determined the sensitivity was 4.6x, and with all 5 apertures resulting in significant multiplexing the sensitivity was 5.7x. We also determined through simulation better visualization of the rods of a Derenzo phantom, and perfusion distribution of XCAT brain phantom with the 5 pinhole design, using solely the 4 oblique pinholes. We thus believe that this design with 5 pinholes per detector module is an excellent candidate for use in construction of the AdaptiSPECT-C system.

We are designing AdaptiSPECT-C, a novel, multiple-detector, adaptive-aperture single-photon emission, tomographic (SPECT) system dedicated to brain imaging. This system is designed to change sensitivity and spatial resolution in realtime to address the needs of dynamic imaging[1]. The aim of this work is to document the creation of a manufacturable aperture design including hardware, electronics and software that effectively adapt in real-time spatial resolution and sensitivity functions to the needs of a dynamically changing subject. We accomplish these goals through metal printing of apertures and with custom control boards based on the Arduino microcontroller. With this design we are able to precisely control each aperture motion with a step resolution of 0.20 millimeters, which is within our required tolerances.

A next-generation multi-pinhole system dedicated to brain SPECT imaging is being constructed by our research team, which we call AdaptiSPECT-C. The system prototype used herein consists of 25 square detector modules and a total of 100 apertures grouped by 4 per module. The system is specifically designed for multi-purpose brain imaging and capable of adapting in real-time each aperture size and whether it is open or shuttered closed. The use of such system would provide optimum high-performance patient-personalized imaging for a wide range of brain imaging tasks. In this work we investigated the effect of pinhole diameter variation on spherical tumor quantification for the promising brain tumor imaging agent 123I-CLINDE. To assess the quality of the images reconstructed for the different aperture sizes, we used a customized multiple-sphere tumor phantom derived from the XCAT software with a tumor size of 1 cm in diameter. Our results suggest through quantification and visual inspection that an aperture diameter in the range of 2 to 5 mm in diameter for the adaptive AdaptiSPECT-C system is likely the most suited for high performance brain tumor 123I-CLINDE imaging. In addition, our study concludes that a 4 mm pinhole diameter given its excellent spatial-resolution-to-sensitivity trade-off is promising for scout acquisition in localizing target tumor regions within the brain. We have initiated a task-based performance on the tumor detection and localization accuracy for a range of simulated tumor sizes using the channelized non-pre-whitening (CNPW) matched-filter scanning-observer.

With brain-dedicated multi-detector systems employing pinhole apertures the usage of detectors facing the top of the patient’s head (i.e. quasi-vertex (QV) views) can provide the advantage of additional viewing from close to the brain for improved detector coverage. In this paper, we report the results of simulation and reconstruction studies to investigate the impact of the QV views on the imaging performance of AdaptiSPECT-C, a brain-dedicated stationary SPECT system under development. In this design, both primary and scatter photons from regions located inferior to the brain can contribute to SPECT projections acquired by the QV views, and thus degrade AdaptiSPECT-C imaging performance. In this work, we determined the proportion, origin, and nature (i.e. primary, scatter, and multiple-scatter) of counts emitted from structures within the head and throughout the body contributing to projections from the different AdaptiSPECT-C detector rings, as well as from a true vertex view detector. We simulated phantoms used to assess different aspects of image quality (i.e. uniform activity concentration sphere, and Derenzo), as well as anthropomorphic phantoms with different count levels emulating clinical 123I activity distributions (i.e. DaTscan and perfusion). We determined that attenuation and scatter in the patient’s body greatly diminish the probability of the photons emitted outside the volume of interest reaching to detectors and being recorded within the 15% photopeak energy window. In addition, we demonstrated that the inclusion of the residual of such counts in the system acquisition does not degrade visual interpretation or quantitative analysis. The addition of the QV detectors improves volumetric sensitivity, angular sampling, and spatial resolution leading to significant enhancement in image quality, especially in the striato-thalamic and superior regions of the brain. Besides, the use of QV detectors improves the recovery of clinically relevant metrics such as the striatal binding ratio and mean activity in selected cerebral structures. Our findings proving the usefulness of the QV ring for brain imaging with 123I agents can be generalized to other commonly used SPECT imaging agents labelled with isotopes, such as 99mTc and likely 111In.

Application of multi-pinhole collimator in pinhole-based SPECT increases detection sensitivity. The presence of multiplexing in projection images due to the usage of multiple pinholes can further improve the sensitivity at the cost of adding data ambiguity. We are developing a next-generation adaptive brain-dedicated SPECT system –AdaptiSPECT-C. The AdaptiSPECT-C can adapt the multiplexing level and system sensitivity using adaptable pinhole modules. In this study, we investigated the performance of 4 data acquisition schemes with different multiplexing levels and sensitivities on cerebral SPECT imaging. Schemes #1, #2, and #3 have

A next-generation, adaptive, multi-pinhole system, AdaptiSPECT-C, dedicated to SPECT brain imaging is currently under development in our research team. Attenuation and scatter correction have proven to be critical to enhance image quality and quantification for brain imaging. The motivation for this investigation was to determine the enhancement in image quality by adding scatter correction strategy in addition to attenuation correction for brain imaging with AdaptiSPECT-C. An ideal scatter correction strategy was investigated in this GATE simulation study using a brain perfusion phantom and compared to the reference case for which an air attenuation medium was considered. We demonstrated that the use of the attenuation and the ideal scatter correction strategy significantly enhanced the imaging performance of AdaptiSPECT-C in case of clinical I-123 brain perfusion imaging. In addition, our study concluded that the use of an attenuation correction without compensating for scatter strongly degrades the contrast of the reconstruction, despite a quantitative improvement compared to the case for which no correction was used.

Patient motion and its deteriorating effects in medical imaging is well known. Likewise, head rigid-body motion degrades the image quality in brain SPECT. We developed an algorithm to compensate the head motion in multi-pinhole SPECT systems within a statistical iterative image reconstruction algorithm. Previously, volunteer’s head motion was recorded by Vicon MX visual tracking system for 10 minutes while laying inside a SPECT/CT gantry. We then divided the motion into 120 intervals, each 5 seconds long. AdaptiSPECT-C, a multi-pinhole multi-detector stationary SPECT system, we are developing for dedicated brain imaging was used for this study. We generated an XCAT voxelized brain phantom emulating the activity distribution of Iodine-123 N-isopropyl-4-iodoamphetamine (IMP) for brain perfusion scan. To simulate the data acquisition with head motion, we used generic analytic simulation software we developed for multi-pinhole SPECT systems. The 6-degrees-offreedom (6-DOF) motion was incorporated into the simulation software to realistically simulate the data acquisition with motion. Our previously developed graphics-processing-unit (GPU)-based iterative reconstruction software was augmented to incorporate motion compensation using 3D Gaussian interpolation. The rigidbody (i.e. 6-DOF) head motion was input to the reconstruction software through 120 motion intervals. For comparison, we reconstructed the motion corrupted SPECT data without motion compensation and a motion-free acquisition as ground truth. The results show that our proposed motion compensation method provides a significantly better SPECT reconstruction when compared to no motion compensation. The developed software can be applied for any scan duration with any number of motion intervals.

AdaptiSPECT-C (ASC) is being designed as an adaptive multi-pinhole SPECT imaging system with multiple detectors arranged in sphere-like geometry in three rings (Caudal, Middle, and Quasi-Vertex (QV)). Herein we investigate the usage of rotated square detectors for the first two rings, and hexagonal detectors for QV ring. We compare designs for different levels of temporal shuttering of the multiple apertures irradiating each detector. We assess image quality for a variety of phantoms assessing uniformity, axial sampling, and brain perfusion imaging. We determine that rotated square detectors can provide good uniformity, the axial sampling we have observed thus far based on reconstruction of a tailored Defrise Phantom and reconstructions of the brain phantom modeling perfusion distribution.

We introduce a generic analytic simulation and image reconstruction software platform for multi-pinhole (MPH) SPECT systems. The platform is capable of modeling common or sophisticated MPH designs as well as complex data acquisition schemes. Graphics processing unit (GPU) acceleration was utilized to make a high-performance computing software. Herein, we describe the software platform and provide verification studies of the simulation and image reconstruction software.

We report our investigation of system designs and 3D reconstruction for a dedicated brain-imaging SPECT system using multiple square or square and hexagonal detector modules. The system employs shuttering to vary which of multiple pinhole apertures are enabled to pass photons through to irradiate the detectors. Both multiplexed and nonmultiplexed irradiation by the pinholes are investigated. Sampling is assessed by simulated imaging of a uniform activity concentration in a spherical tub filling the VOI and a tailored Defrise phantom consisting of a series of activity containing slabs aligned axially. Potential image quality for clinical imaging is assessed through simulated imaging of an XCAT brain phantom with an activity distribution simulating perfusion imaging.

The use of accurate system response modeling has been proven to be an essential key of SPECT image reconstruction, with its usage leading to overall improvement of image quality. The aim of this work was to investigate the imaging performance using an XCAT brain perfusion phantom of two modeling strategies, one based on analytic techniques and the other one based on GATE Monte-Carlo simulation. In addition, an efficient forced detection approach to improve the overall simulation efficiency was implemented and its performance was evaluated. We demonstrated that accurate modeling of the system matrix generated by Monte-Carlo simulation for iterative reconstruction leads to superior performance compared to analytic modeling in the case of clinical I-123 brain imaging. It was also shown that the use of the forced detection approach provided a quantitative and qualitative enhancement of the reconstruction.

Multi-pinhole (MPH) collimators are known to provide better trade-off between sensitivity and resolution for preclinical, as well as for smaller regions in clinical SPECT imaging compared to conventional collimators. In addition to this geometric advantage, MPH plates typically offer better stopping power for penetration than the conventional collimators, which is especially relevant for I-123 imaging. The I-123 emits a series of high-energy (>300 keV, similar to 2.5% abundance) gamma photons in addition to the primary emission (159 keV, 83% abundance). Despite their low abundance, high-energy photons penetrate through a low-energy parallel-hole (LEHR) collimator much more readily than the 159 keV photons, resulting in large downscatter in the photopeak window. In this work, we investigate the primary, scatter, and penetration characteristics of a single pinhole collimator that is commonly used for I-123 thyroid imaging and our two MPH collimators designed for I-123 DaTscan imaging for Parkinson's Disease, in comparison to three different parallel-hole collimators through a series of experiments and Monte Carlo simulations. The simulations of a point source and a digital human phantom with DaTscan activity distribution showed that our MPH collimators provide superior count performance in terms of high primary counts, low penetration, and low scatter counts compared to the parallel-hole and single pinhole collimators. For example, total scatter, multiple scatter, and collimator penetration events for the LEHR were 2.5, 7.6 and 14 times more than that of MPH within the 15% photopeak window. The total scatter fraction for LEHR was 56% where the largest contribution came from the high-energy scatter from the back compartments (31%). For the same energy window, the total scatter for MPH was 21% with only 1% scatter from the back compartments. We therefore anticipate that using MPH collimators, higher quality reconstructions can be obtained in a substantially shorter acquisition time for I-123 DaTscan and thyroid imaging.

We are developing a multi-detector pinhole-based stationary brain-dedicated SPECT system: AdaptiSPECT-C. In this work, we introduced a new design prototype with multiple adaptable pinhole apertures for each detector to modulate the multiplexing by employing temporal shuttering of apertures. Temporal shuttering of apertures over the scan time provides the AdaptiSPECT-C with the capability of multiple-frame acquisition. We investigated, through analytic simulation, the impact of projection multiplexing on image quality using several digital phantoms and a customized anthropomorphic phantom emulating brain perfusion clinical distribution. The 105 pinholes in the collimator of the system were categorized into central, axial, and lateral apertures. We generated, through simulation, collimators of different multiplexing levels. Several data acquisition schemes were also created by changing the imaging time share of the acquisition frames. Sensitivity increased by 35% compared to the single-pinhole-per-detector base configuration of the AdaptiSPECT-C when using the central, axial, and lateral apertures with equal acquisition time shares within a triple-frame scheme with a high multiplexing scenario. Axial and angular sampling of the base configuration was enhanced by adding the axial and lateral apertures. We showed that the temporal shuttering of apertures can be exploited, trading the sensitivity, to modulate the multiplexing and to acquire a set of non-multiplexed non-truncated projections. Our results suggested that reconstruction benefited from utilizing both non-multiplexed projections and projections with modulated multiplexing resulting in a noticeably reduction in the multiplexing-induced image artefacts. Contrast recovery factor improved by 20% (9%) compared to the base configuration for a Defrise (hot-rod) phantom study when the central and axial (lateral) apertures with equal time shares were combined. The results revealed that, as an overall trend at each simulated multiplexing level, lowest normalized root-mean-square errors for the brain gray-matter regions were achieved with the combined usage of the central apertures and axial/lateral apertures.

Simulation studies have been essential for development of SPECT imaging systems. GATE is one of the most commonly used simulation toolkits in nuclear medicine. This software package allows the users to build system geometries and phantoms based on primitive objects such as cylinder, sphere, and cube. However, modeling systems with complex geometry is challenging, if not impossible using these primitive volumes. The latest GATE release addressed this issue by allowing the users to import surface meshes created in a computer aided design software thus enabling accurate simulation of complex system or phantom geometries. In this study we present our GATE mesh-based simulations of a next-generation multi-pinhole SPECT system for the clinical brain imaging, called AdaptiSPECT-C. An additional challenge with the AdaptiSPECT-C is that the volume of the standard voxelized XCAT phantom overlaps with the spherical collimator plate. In order to address this issue, we developed a mesh modeling of the XCAT human phantom by directly using the native XCAT nurbs data, which also provided a more accurate representation of the anatomy. Two approaches for simulating mesh-based activity source were developed and evaluated. The first method consisted of using an acceptance/rejection criterion confining a cubical source into the mesh object and the second one was based on a conversion of a mesh-based volume into a voxelized object. Although the two strategies led to very similar results, the voxelized-mesh approach was significantly faster in computation time. We successfully imported and simulated in GATE a complete SPECT acquisition incorporating an STL representation of system, phantom anatomy, and activity source.

A joint research program at the universities of Arizona and Massachusetts (Medical school) is designing a next-generation, adaptive, dedicated brain-imaging, single photon emission computed tomography (SPECT) system. It consists of multi-pinhole, modular gamma cameras arrayed around a hemisphere that encloses the volume of interest. The adaptive feature of the system stems from the capability of shuttering selected pinholes for each module. Critical to the design process is the ability to vary parameters such as the number, location and size of the pinholes and quantify their effects on system performance. One approach is to use the Fourier-crosstalk matrix (FXM) which is derived from the system matrix and can provide a modulation transfer function (MTF)-type measure of system resolution. An FXM-based study has been initiated to answer some of the questions regarding pinhole/detector placement in the proposed SPECT system. The initial work has entailed obtaining system matrices for individual detector modules and then deriving the FXM from it (via a multidimensional discrete Fourier transform (DFT)).

Collimator penetration, down-scatter related to 123I high energy photons, and scatter within detectors can significantly degrade the imaging performance of any system. Precise selection of pinhole and collimator parameters using simulation studies has the potential to considerably reduce these effects. This type of investigation, thus represents an essential step in system development. An innovative multi-pinhole system, AdaptiSPECT-C, dedicated to clinical brain SPECT imaging, is currently under development at the universities of Massachusetts and Arizona. The aim of this work was to determine the system parameters which considerably improve AdaptiSPECT- C imaging performance for the criteria of sensitivity and relative amounts of scatter and penetration. A 20 mm thick, tungsten alloy collimator leads to the best trade-off between performance and price in case of 123I imaging. Tungsten alloy provided performance relatively close to that of gold in terms of stopping power as compared to lead alloy. A pinhole center distance of 0.5 cm to the aperture entry port led to the best compromise for locating the aperture within the aperture plate in terms of sensitivity and relative amounts of scatter and penetration.

A next-generation, adaptive, dynamic multi-pinhole system, AdaptiSPECT-C, dedicated to clinical brain SPECT imaging, is currently under development as part of a collaboration between the universities of Arizona and Massachusetts. It has been shown that accurate modeling of the system matrix is a key aspect of SPECT image reconstruction as it has the potential to improve the imaging performance of any system. A straight-forward approach to modeling is based on the use of Monte Carlo simulation to pre-compute and store the system matrix. Generally, in clinical imaging, given the large sizes of detectors and volume of interests this approach faces critical memory storage issues despite the use of sparse structures to store the system matrix. The aim of this work was to investigate the feasibility of a Monte Carlo simulation pre-computed system matrix approach for 123I clinical brain SPECT imaging with the AdaptiSPECT-C system. Our efficient method was evaluated using an XCAT brain perfusion phantom. The present approach’s feasibility was fully demonstrated in case of clinical 123I brain imaging.

We present a full-year on-line global simulation of tropospheric chemistry (158 coupled species) at cubed-sphere c720 (12.5 x 12.5 km2) resolution in the NASA GEOS Earth System Model, Version 5 (GEOS-5 ESM) with GEOS-Chem as a chemical module (G5NR-chem). The GEOS-Chem module within GEOS uses the exact same code as the off-line GEOS-Chem chemical transport model (CTM) developed by a large atmospheric chemistry research community. In this way, continual updates to the GEOS-Chem CTM by that community can be seamlessly passed on to the GEOS chemical module, which remains state-of-the-science and referenceable to the latest version of GEOS-Chem. The 1-year G5NR-chem simulation was conducted to serve as Nature Run for observing system simulation experiments (OSSEs) in support of the future geostationary satellite constellation for tropospheric chemistry. It required 31 walltime days on 4707 compute cores with only 24 \\% of the time spent on the GEOS-Chem chemical module. Results from the GEOS-5 Nature Run with GEOS-Chem chemistry were shown to be consistent to the off-line GEOS-Chem CTM and were further compared to global and regional observations. The simulation shows no significant global bias for tropospheric ozone relative to the Ozone Monitoring Instrument (OMI) satellite, and is highly correlated with observations spatially and seasonally. It successfully captures the ozone vertical distributions measured by ozonesondes over different regions of the world, as well as observations for ozone and its precursors from the Aug-Sep 2013 SEAC4RS aircraft campaign over the Southeast US. It systematically overestimates surface ozone concentrations by 10 ppbv at sites in the US and Europe, a problem currently being addressed by the GEOS-Chem CTM community and from which the GEOS ESM will benefit through the seamless update of the on-line code.

International audience; In small animal Single Photon Emission Computed Tomography (SPECT), attenuation and scatter introduce important artifacts in the reconstructed images, which could lead to misdiagnosis for subject's follow-up. Gold standard Monte Carlo Simulation (MCS) is one of the well-established tools that has been used in SPECT image reconstruction due to its ability to accurately model photon transport. However, MCS requires extensive computation time to obtain a low noise system matrix and are therefore inappropriate for the rate of daily exams performed in both clinical and preclinical routine: an improvement in simulation speed is thus mandatory. In this work, we validated, compared to a state of the art approach and by using a modified NU-4 IQ phantom, our efficient and simplified modeling of the physical phenomena occurring in the subject. Our approach based on a system matrix decomposition, associated to a scatter pre-calculated database method, demonstrated an acceptable time on a standard computer for daily imaging small animal follow-up (around 1h), leading to a personalized image reconstruction. The reconstruction workflow leads to significant image artifacts reduction as well as a 13% (on average) improvement in terms of recovery coefficients. Results presented in this study, conduct to the validation of the developed approach in comparison with a state of the art one which appears to be far too long for a daily exam perspective.

International audience; Nowadays, the use of gold standard Monte Carlo Simulation (MCS) based modeling of the acquisition process in a way to compute the System Matrix (SM) is one of the well-established methods that has been used in small animal SPECT image reconstruction. However, MCS requires extensive computation time to obtain a low noise SM. Such reconstruction methods are therefore largely penalized by the huge time consumption required for the SM generation since a large number of photons has to be generated: an improvement in simulation speed is thus mandatory. Simplified analytical approach has the potential to lead to efficient SM computation, in a reduced time while requiring neither particular computing skills nor heavy informatics resources (cluster). In this work, we proposed to evaluate several modeling types (analytical and MCS) of the acquisition process of a pinhole SPECT system available at our institute. Secondly, various complexity degrees of an efficient and simplified analytical modeling of the physical effects occurring into the detector during SPECT examinations will be investigated. The two-developed analytical modeling of detector response represent some fast and efficient alternatives strategies to the implemented MCS based one. Although, even if they are less accurate, they allow coherent estimation while overcoming the disadvantages of the MCS like excessive computation time, high technical complexity and heavy computation infrastructures. However, the performance obtained, both qualitatively and quantitatively, do not allow their use in a quantitative reconstruction process. Nevertheless, recovery coefficient divergences with respect to the MCS reference modeling are on average of the order of ~ 6%.

Most brain SPECT imaging procedures are currently being performed using general-purpose systems which are unable to fully take advantage of the use of clinically available agents. We are designing a novel multi-detector, multi-pinhole modular dedicated brain SPECT imaging system called AdaptiSPECT-C to improve sensitivity and resolution, and address the static and dynamic imaging needs. The aim of this study was to evaluate the axial and angular sampling sufficiency of a preliminary design of the system using simulation of the XCAT and a customized Defrise phantom. The simulator as well as image reconstruction projector is based on analytical modeling. The results provided an insight into the axial and angular sampling of the region-ofinterest of the AdaptiSPECT-C system and possible approaches to enhance the image quality in this regard showing that the application of approaches for increasing axial and angular samples including multipinhole shattering concept can enhance the quality of the reconstructed images.

A next-generation, adaptive, brain-imaging, single photon emission computed tomography system is currently under development at the Universities of Arizona and Massachusetts. The proposed multi-pinhole based modular gamma camera configuration enables the acquisition of “quasi-vertex” views i.e., views close to the vertex. This study is concerned with understanding how activity inferior to the brain will influence these views and ultimately, the reconstruction of the volume of interest. Analytical models can provide some measure of the detected primary gamma radiation originating in an organ or tissue outside the region of interest. Scattered gamma radiation will be detected as well but given the difficulty in modeling such phenomena, Monte Carlo simulations are used to quantify its effect. Using computer generated phantoms, the influence of activity from organs and tissues in the thorax, neck and lower head as compared to that from brain structures in the quasivertex views, will be detected, identified and quantified. The simulation consists of two components: detectors and sources. The detectors were simulated gamma camera modules consisting of a tungsten pinhole collimator, an air gap, and a NaI(Tl) scintillator surrounded by lead shielding. The sources were phantoms with activity (I-123, primary gamma photons at 159 keV) set in the liver, lungs, striatum, salivary glands and the thyroid.