Single Photon Emission Computed Tomography System Research Articles

Correction of multiplexing artefacts in multi-pinhole SPECT through temporal shuttering, de-multiplexing of projections, and alternating reconstruction

Objective. Single-photon emission computed tomography (SPECT) with pinhole collimators can provide high-resolution imaging, but is often limited by low sensitivity. Acquiring projections simultaneously through multiple pinholes affords both high resolution and high sensitivity. However, the overlap of projections from different pinholes on detectors, known as multiplexing, has been shown to cause artefacts which degrade reconstructed images. Approach. Multiplexed projection sets were considered here using an analytic simulation model of AdaptiSPECT-C—a brain-dedicated multi-pinhole SPECT system. AdaptiSPECT-C has fully adaptable aperture shutters, so can acquire projections with a combination of multiplexed and non-multiplexed frames using temporal shuttering. Two strategies for reducing multiplex artefacts were considered: an algorithm to de-multiplex projections, and an alternating reconstruction strategy for projections acquired with a combination of multiplexed and non-multiplexed frames. Geometric and anthropomorphic digital phantoms were used to assess a number of metrics. Main results. Both de-multiplexing strategies showed a significant reduction in image artefacts and improved fidelity, image uniformity, contrast recovery and activity recovery (AR). In all cases, the two de-multiplexing strategies resulted in superior metrics to those from images acquired with only mux-free frames. The de-multiplexing algorithm provided reduced image noise and superior uniformity, whereas the alternating strategy improved contrast and AR. Significance. The use of these de-multiplexing algorithms means that multi-pinhole SPECT systems can acquire projections with more multiplexing without degradation of images.

Improvement of Basal Ganglia Detectability in Brain Single Photon Emission Computerized Tomography by Wavelet Transformation in Image Processing Domain: A XCAT Phantom Study

Purpose: Noise in brain Single Photon Emission Computed Tomography (SPECT) images limits an early diagnosis of Parkinson's Disease (PD). To overcome the limitation, as an image processing approach, wavelet transformation was used to denoising the images also with a segmentation method to differentiate the basal ganglia in brain SPECT.
 Materials and Methods: The brain scans of the human 4D Extended Cardiac Torso (XCAT) phantom through the Simulating Medical Imaging Nuclear Detectors (SIMIND) simulated SPECT system were imported to the MATLAB toolkit for image processing. The reconstructed brain images by iterative reconstruction were de-noised through 9 methods of wavelet transformation at different levels, and then six segmentation methods were applied to differentiate the caudate and putamen. The Dice coefficient, Specificity, and Sensitivity evaluation criteria were calculated based on the adaptive thresholding of the selected images from segmentation. A ground truth image was manually marked by a clinical nuclear medicine specialist.
 Results: The dice coefficient was obtained in a range from 0.3979 to 0.6299, as well as the specificity criterion from 0.7682 to 0.8168 and the sensitivity from 0.9049 to 0.9871.
 The results from adaptive threshold segmentation and the evaluation criteria showed that the best levels of the nucleuses detectability were provided by level 7 of Biorthogonal, levels 4 and 7 of Coiflet, level 6 of Daubechies, level 5 of Haar, level 6 of Morlet and level 6 of Symlet methods.
 Conclusion: Parkinson’s disease may be diagnosed in the early stage by an image processing approach to improve the quality of brain SPECT images.

The Challenge of Single-Photon Emission Computed Tomography Image Segmentation in the Internal Dosimetry of 177Lu Molecular Therapies.

The aim of this article is to review the single photon emission computed tomography (SPECT) segmentation methods used in patient-specific dosimetry of 177Lu molecular therapy. Notably, 177Lu-labelled radiopharmaceuticals are currently used in molecular therapy of metastatic neuroendocrine tumours (ligands for somatostatin receptors) and metastatic prostate adenocarcinomas (PSMA ligands). The proper segmentation of the organs at risk and tumours in targeted radionuclide therapy is an important part of the optimisation process of internal patient dosimetry in this kind of therapy. Because this is the first step in dosimetry assessments, on which further dose calculations are based, it is important to know the level of uncertainty that is associated with this part of the analysis. However, the robust quantification of SPECT images, which would ensure accurate dosimetry assessments, is very hard to achieve due to the intrinsic features of this device. In this article, papers on this topic were collected and reviewed to weigh up the advantages and disadvantages of the segmentation methods used in clinical practice. Degrading factors of SPECT images were also studied to assess their impact on the quantification of 177Lu therapy images. Our review of the recent literature gives an insight into this important topic. However, based on the PubMed and IEEE databases, only a few papers investigating segmentation methods in 177Lumolecular therapy were found. Although segmentation is an important step in internal dose calculations, this subject has been relatively lightly investigated for SPECT systems. This is mostly due to the inner features of SPECT. What is more, even when studies are conducted, they usually utilise the diagnostic radionuclide 99mTc and not a therapeutic one like 177Lu, which could be of concern regarding SPECT camera performance and its overall outcome on dosimetry.

Deep learning approach using SPECT-to-PET translation for attenuation correction in CT-less myocardial perfusion SPECT imaging

ObjectiveDeep learning approaches have attracted attention for improving the scoring accuracy in computed tomography-less single photon emission computed tomography (SPECT). In this study, we proposed a novel deep learning approach referring to positron emission tomography (PET). The aims of this study were to analyze the agreement of representative voxel values and perfusion scores of SPECT-to-PET translation model-generated SPECT (SPECTSPT) against PET in 17 segments according to the American Heart Association (AHA).MethodsThis retrospective study evaluated the patient-to-patient stress, resting SPECT, and PET datasets of 71 patients. The SPECTSPT generation model was trained (stress: 979 image pairs, rest: 987 image pairs) and validated (stress: 421 image pairs, rest: 425 image pairs) using 31 cases of SPECT and PET image pairs using an image-to-image translation network. Forty of 71 cases of left ventricular base-to-apex short-axis images were translated to SPECTSPT in the stress and resting state (stress: 1830 images, rest: 1856 images). Representative voxel values of SPECT and SPECTSPT in the 17 AHA segments against PET were compared. The stress, resting, and difference scores of 40 cases of SPECT and SPECTSPT were also compared in each of the 17 segments.ResultsFor AHA 17-segment-wise analysis, stressed SPECT but not SPECTSPT voxel values showed significant error from PET at basal anterior regions (segments #1, #6), and at mid inferoseptal regions (segments #8, #9, and #10). SPECT, but not SPECTSPT, voxel values at resting state showed significant error at basal anterior regions (segments #1, #2, and #6), and at mid inferior regions (segments #8, #9, and #11). Significant SPECT overscoring was observed against PET in basal-to-apical inferior regions (segments #4, #10, and #15) during stress. No significant overscoring was observed in SPECTSPT at stress, and only moderate over and underscoring in the basal inferior region (segment #4) was found in the resting and difference states.ConclusionsOur PET-supervised deep learning model is a new approach to correct well-known inferior wall attenuation in SPECT myocardial perfusion imaging. As standalone SPECT systems are used worldwide, the SPECTSPT generation model may be applied as a low-cost and practical clinical tool that provides powerful auxiliary information for the diagnosis of myocardial blood flow.

Quantitative validation of Monte Carlo SPECT simulation: application to a Mediso AnyScan GATE simulation

BackgroundMonte Carlo (MC) simulations are used in nuclear medicine imaging as they provide unparalleled insight into processes that are not directly experimentally measurable, such as scatter and attenuation in an acquisition. Whilst MC is often used to provide a ‘ground-truth’, this is only the case if the simulation is fully validated against experimental data. This work presents a quantitative validation for a MC simulation of a single-photon emission computed tomography (SPECT) system.MethodsAn MC simulation model of the Mediso AnyScan SCP SPECT system installed at the UK National Physical Laboratory was developed in the GATE (Geant4 Application for Tomographic Emission) toolkit. Components of the detector head and two collimator configurations were modelled according to technical specifications and physical measurements. Experimental detection efficiency measurements were collected for a range of energies, permitting an energy-dependent intrinsic camera efficiency correction function to be determined and applied to the simulation on an event-by-event basis. Experimental data were collected in a range of geometries with ^{99text {m}}Tc for comparison to simulation. The procedure was then repeated with ^{177}Lu to determine how the validation extended to another isotope and set of collimators.ResultsThe simulation’s spatial resolution, sensitivity, energy spectra and the projection images were compared with experimental measurements. The simulation and experimental uncertainties were determined and propagated to all calculations, permitting the quantitative agreement between simulated and experimental SPECT acquisitions to be determined. Statistical agreement was seen in sinograms and projection images of both ^{99text {m}}Tc and ^{177}Lu data. Average simulated and experimental sensitivity ratios of (0.991 pm 0.011) were seen for emission and scatter windows of ^{99text {m}}Tc, and (0.897 pm 0.014) and (0.839 pm 0.014) for the 113 and 208 keV emissions of ^{177}Lu, respectively.ConclusionsMC simulations will always be an approximation of a physical system and the level of agreement should be assessed. A validation method is presented to quantify the level of agreement between a simulation model and a physical SPECT system.

High-sensitivity cardiac SPECT system design with collimator-less interspaced mosaic-patterned scintillators.

Single-photon emission computed tomography (SPECT) is an important tool for myocardial perfusion imaging (MPI). Mechanical collimators cause the resolution-sensitivity trade-off in the existing cardiac SPECT systems, which hinders fast cardiac scan capability. In this work, we propose a novel collimator-less cardiac SPECT system with interspaced mosaic-patterned scintillators, aiming to significantly improve sensitivity and reduce scan time without trading-off image resolution. We propose to assemble a collimator-less cardiac SPECT with 7 mosaic-patterned detector modules forming a half-ring geometry. The detector module consists of 10 blocks, each of which is assembled with 768 sparsely distributed scintillators with a size of 1.68 mm × 1.68 mm × 20 mm, forming a mosaic pattern in the trans-axial direction. Each scintillator bar contains 5 GAGG(Ce) scintillators and 5 optical-guide elements, forming a mosaic pattern in the axial direction. In the Monte Carlo simulations, the in-plane resolution and axial resolution are evaluated using a hot-rod phantom and 5 disk phantoms, respectively. We simulate a cardiac phantom that is placed in a water-filled cylinder and evaluate the image performance with different data acquisition time. We perform image reconstruction with the expectation-maximization algorithm using system matrices derived from the simulation of a uniform cylindrical source filling the field-of-view (FOV). Besides, a 2-D prototype system is designed to demonstrate the feasibility of the collimator-less imaging concept. In the simulation system, the sensitivity is 16.31% ± 8.85% in a 180 mm (Φ) × 100 mm (L) FOV. The 6-mm rods in the hot rod phantom and the 5-mm disks in the disk phantom are clearly separable. Satisfactory MPI image quality is achieved in the cardiac phantom study with an acquisition time of 30 s. In prototype experiments, the point sources with an 8 mm center-to-center distance are clearly separable at different positions across the FOV. The study reveals a promising approach to high-sensitivity SPECT imaging without a heavy-metal collimator. In cardiac imaging, this approach opens the way to a very fast cardiac scan with good resolution. Further works are ongoing to build a practical 3-D imaging system based on the existing design.

State-of-the-art challenges and emerging technologies in radiation detection for nuclear medicine imaging: A review

Single photon emission computed tomography (SPECT) and positron emission tomography (PET) are established medical imaging modalities that have been implemented for decades, but improvements in detector design and camera electronics are needed for advancement of both imaging technologies. Detectors are arguably the most important aspect of the systems. Similar to SPECT, PET typically relies on indirect conversion of gamma radiation via scintillators coupled with photosensors used to convert optical photons produced by the scintillator into an electrical signal. PET detectors are defined by their energy resolution, timing resolution, and spatial resolution, all of which affect and determine the image quality. Improvements in energy resolution have been shown by increasing the brightness of the scintillator utilizing materials like cerium bromide (CeBr3) or switching to a direct conversion detector, such as cadmium zinc telluride (CZT) or thallium bromide (TlBr). Timing resolution for PET is a focal point of the current research. Improving the timing resolution improves the signal-to-noise of the PET system and is integral to the implementation of time-of-flight PET. By utilizing novel configurations, such as side readouts on scintillators, timing resolution has been improved dramatically. Similarly, metascintillators, which use complex combinations for the scintillator material, have also shown improvements to the timing resolution. Additional research has focused on using Cherenkov light emission in scintillators to further improve the timing resolution. Other research is focused on using convolutional neural networks and other signal processing to enhance timing resolution. Lastly, aside from acollinearity and positron range, spatial resolution is impacted by the PET detector, therefore improving the intrinsic spatial resolution of the detector will allow for smaller features to be imaged. One method for improving the spatial resolution is to use unique configurations with layered scintillators. Additionally, monolithic scintillators have also been shown to have reduced spatial resolution. The future for both SPECT and PET image system advancement will depend on continued development of the detectors via many different pathways including materials, signal processing, physics, and novel configurations. In this review article, we will discuss challenges and emerging technologies for state-of-the-art radiation detectors utilized in PET and SPECT.

Integration of advanced 3D SPECT modelling for pinhole collimators into the open-source STIR framework

Single-photon emission computed tomography (SPECT) systems with pinhole collimators are becoming increasingly important in clinical and preclinical nuclear medicine investigations as they can provide a superior resolution-sensitivity trade-off compared to conventional parallel-hole and fanbeam collimators. Previously, open-source software did not exist for reconstructing tomographic images from pinhole-SPECT datasets. A 3D SPECT system matrix modelling library specific for pinhole collimators has recently been integrated into STIR—an open-source software package for tomographic image reconstruction. The pinhole-SPECT library enables corrections for attenuation and the spatially variant collimator–detector response by incorporating their effects into the system matrix. Attenuation correction can be calculated with a simple single line-of-response or a full model. The spatially variant collimator–detector response can be modelled with point spread function and depth of interaction corrections for increased system matrix accuracy. In addition, improvements to computational speed and memory requirements can be made with image masking. This work demonstrates the flexibility and accuracy of STIR’s support for pinhole-SPECT datasets using measured and simulated single-pinhole SPECT data from which reconstructed images were analysed quantitatively and qualitatively. The extension of the open-source STIR project with advanced pinhole-SPECT modelling will enable the research community to study the impact of pinhole collimators in several SPECT imaging scenarios and with different scanners.

Development and task-based evaluation of a scatter-window projection and deep learning-based transmission-less attenuation compensation method for myocardial perfusion SPECT.

Attenuation compensation (AC) is beneficial for visual interpretation tasks in single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI). However, traditional AC methods require the availability of a transmission scan, most often a CT scan. This approach has the disadvantage of increased radiation dose, increased scanner costs, and the possibility of inaccurate diagnosis in cases of misregistration between the SPECT and CT images. Further, many SPECT systems do not include a CT component. To address these issues, we developed a Scatter-window projection and deep Learning-based AC (SLAC) method to perform AC without a separate transmission scan. To investigate the clinical efficacy of this method, we then objectively evaluated the performance of this method on the clinical task of detecting perfusion defects on MPI in a retrospective study with anonymized clinical SPECT/CT stress MPI images. The proposed method was compared with CT-based AC (CTAC) and no-AC (NAC) methods. Our results showed that the SLAC method yielded an almost overlapping receiver operating characteristic (ROC) plot and a similar area under the ROC (AUC) to the CTAC method on this task. These results demonstrate the capability of the SLAC method for transmission-less AC in SPECT and motivate further clinical evaluation.

Mesh modeling of system geometry and anatomy phantoms for realistic GATE simulations and their inclusion in SPECT reconstruction

Objective. Monte-Carlo simulation studies have been essential for advancing various developments in single photon emission computed tomography (SPECT) imaging, such as system design and accurate image reconstruction. Among the simulation software available, Geant4 application for tomographic emission (GATE) is one of the most used simulation toolkits in nuclear medicine, which allows building systems and attenuation phantom geometries based on the combination of idealized volumes. However, these idealized volumes are inadequate for modeling free-form shape components of such geometries. Recent GATE versions alleviate these major limitations by allowing users to import triangulated surface meshes. Approach. In this study, we describe our mesh-based simulations of a next-generation multi-pinhole SPECT system dedicated to clinical brain imaging, called AdaptiSPECT-C. To simulate realistic imaging data, we incorporated in our simulation the XCAT phantom, which provides an advanced anatomical description of the human body. An additional challenge with the AdaptiSPECT-C geometry is that the default voxelized XCAT attenuation phantom was not usable in our simulation due to intersection of objects of dissimilar materials caused by overlap of the air containing regions of the XCAT beyond the surface of the phantom and the components of the imaging system. Main results. We validated our mesh-based modeling against the one constructed by idealized volumes for a simplified single vertex configuration of AdaptiSPECT-C through simulated projection data of 123I-activity distributions. We resolved the overlap conflict by creating and incorporating a mesh-based attenuation phantom following a volume hierarchy. We then evaluated our reconstructions with attenuation and scatter correction for projections obtained from simulation consisting of mesh-based modeling of the system and the attenuation phantom for brain imaging. Our approach demonstrated similar performance as the reference scheme simulated in air for uniform and clinical-like 123I-IMP brain perfusion source distributions. Significance. This work enables the simulation of complex SPECT acquisitions and reconstructions for emulating realistic imaging data close to those of actual patients.

Simulation studies of a full-ring, CZT SPECT system for whole-body imaging of 99m Tc and 177 Lu.

Single photon emission computed tomography (SPECT) is an imaging modality that has demonstrated its utility in a number of clinical indications. Despite this progress, a high sensitivity, high spatial resolution, multi-tracer SPECT with a large field of view suitable for whole-body imaging of a broad range of radiotracers for theranostics is not available. With the goal of filling this technological gap, we have designed a cadmium zinc telluride (CZT) full-ring SPECT scanner instrumented with a broad-energy tungsten collimator. The final purpose is to provide a multi-tracer solution for brain and whole-body imaging. Our static SPECT does not rely on the dual- and the triple-head rotational SPECT standard paradigm, enabling a larger effective area in each scan to increase the sensitivity. We provide a demonstration of the performance of our design using a realistic model of our detector with simulated body-sized phantoms filled with 99m Tc and 177 Lu. We create a realistic model of our detector by using a combination of a Geant4 Application for Tomographic Emission (GATE) Monte Carlo simulation and a finite element model for the CZT response, accounting for low-energy tail effects in CZT that affects the sensitivity and the scatter correction. We implement a modified dual-energy-window scatter correction adapted for CZT. Other corrections for attenuation, detector and collimator response, and detector gaps and edges are also included. The images are reconstructed using the maximum-likelihood expectation-maximization. Detector and reconstruction performance are characterized with point sources, Derenzo phantoms, and a body-sized National Electrical Manufacturers Association (NEMA) Image Quality (IQ) phantom for both 99m Tc and 177 Lu. Our SPECT design can resolve 7.9mm rods for 99m Tc (140keV) and 9.5mm for 177 Lu (208keV) in a hot-rod Derenzo phantom with a 3-min exposure and reach an image contrast of 78% for 99m Tc and 57% for 177 Lu using the NEMA IQ phantom with a 6-min exposure. Our modified scatter correction shows an improved contrast-recovery ratio compared to a standard correction. In this paper, we demonstrate the good performance of our design for whole-body imaging purposes. This adds to our previous demonstration of improved qualitative and quantitative 99m Tc imaging of brain perfusion and 123 I imaging of dopamine transport with respect to state-of-the-art NaI dual-head cameras. We show that our design provides similar IQ and contrast to the commercial full-ring SPECT VERITON for 99m Tc. Regarding 177 Lu imaging of the 208keV emissions, our design provides similar contrast to that of other state-of-the-art SPECTs with a significant reduction in exposure. The high sensitivity and extended energy range up to 250keV makes our SPECT design a promising alternative for clinical imaging and theranostics of emerging radionuclides.

Tomographic image reconstruction techniques for accurate spent fuel assembly verification

Non-proliferation and the security of nuclear materials are essential. The international atomic energy agency (IAEA) considers a tomographic image acquisition technique of spent fuel assemblies a promising technique to accurately verify the rod-by-rod spent fuel conditions stored in a water pool. Researchers at Yonsei University in Korea developed the bismuth germanate (BGO) scintillator-based Yonsei Single-photon Emission Computed Tomography (YSECT). Previous research validated the YSECT system experimentally to quickly evaluate the radioactivity distribution of test fuel rods in the Korea Institute of Nuclear Nonproliferation and Control (KINAC). Quick verification of the fuel assembly requires the development of a high-quality image reconstruction algorithm that enables image acquisition within a short time. This study examined various tomographic image reconstruction techniques to identify patterns of missing fuel rods accurately. Rotational projection image data sets were obtained for 15 patterns of test fuel rods for 900 seconds using the single-photon emission computed tomography (SPECT) system installed at KINAC. The projection images were acquired every 5° while four 64-channel detectors rotated 90°. The acquired images were reconstructed using the following methods: filtered back-projection, simultaneous iterative reconstruction technique, order-subset simultaneous algebraic reconstruction technique, maximum likelihood expectation maximization (MLEM), and Fast-Iterative Shrinkage-Thresholding algorithm (FISTA). Among the reconstruction algorithms used in this study, the image quality of MLEM showed the best performance, and the image contrast of FISTA showed the highest result. Therefore, the signal-to-noise ratio of the tomographic image was improved using the image reconstruction technique optimized for the YSECT system to verify the patterns of fuel rods. Hence, even for the low-quality measured data with the short-time scan of the SPECT system, this advanced technique is expected to show better discriminability of the patterns of fuel rods in the assembly.

Monte Carlo Simulation and Reconstruction: Assessment of Myocardial Perfusion Imaging of Tracer Dynamics With Cardiac Motion Due to Deformation and Respiration Using Gamma Camera With Continuous Acquisition.

PurposeMyocardial perfusion imaging (MPI) with single photon emission computed tomography (SPECT) is routinely used for stress testing in nuclear medicine. Recently, our group extended its potential going from 3D visual qualitative image analysis to 4D spatiotemporal reconstruction of dynamically acquired data to capture the time variation of the radiotracer concentration and the estimated myocardial blood flow (MBF) and coronary flow reserve (CFR). However, the quality of reconstructed image is compromised due to cardiac deformation and respiration. The work presented here develops an algorithm that reconstructs the dynamic sequence of separate respiratory and cardiac phases and evaluates the algorithm with data simulated with a Monte Carlo simulation for the continuous image acquisition and processing with a slowly rotating SPECT camera.MethodsA clinically realistic Monte Carlo (MC) simulation is developed using the 4D Extended Cardiac Torso (XCAT) digital phantom with respiratory and cardiac motion to model continuous data acquisition of dynamic cardiac SPECT with slowly rotating gamma cameras by incorporating deformation and displacement of the myocardium due to cardiac and respiratory motion. We extended our previously developed 4D maximum-likelihood expectation-maximization (MLEM) reconstruction algorithm for a data set binned from a continuous list mode (LM) simulation with cardiac and respiratory information. Our spatiotemporal image reconstruction uses splines to explicitly model the temporal change of the tracer for each cardiac and respiratory gate that delineates the myocardial spatial position as the tracer washes in and out. Unlike in a fully list-mode data acquisition and reconstruction the accumulated photons are binned over a specific but very short time interval corresponding to each cardiac and respiratory gate. Reconstruction results are presented showing the dynamics of the tracer in the myocardium as it continuously deforms. These results are then compared with the conventional 4D spatiotemporal reconstruction method that models only the temporal changes of the tracer activity. Mean Stabilized Activity (MSA), signal to noise ratio (SNR) and Bias for the myocardium activities for three different target-to-background ratios (TBRs) are evaluated. Dynamic quantitative indices such as wash-in (K1) and wash-out (k2) rates at each gate were also estimated.ResultsThe MSA and SNR are higher with higher TBRs while biases were improved with higher TBRs to less than 10%. The correlation between exhalation-inhalation sequence with the ground truth during respiratory cycle was excellent. Our reconstruction method showed better resolved myocardial walls during diastole to systole as compared to the ungated 4D image. Estimated values of K1 and k2 were also consistent with the ground truth.ConclusionThe continuous image acquisition for dynamic scan using conventional two-head gamma cameras can provide valuable information for MPI. Our study demonstrated the viability of using a continuous image acquisition method on a widely used clinical two-head SPECT system. Our reconstruction method showed better resolved myocardial walls during diastole to systole as compared to the ungated 4D image. Precise implementation of reconstruction algorithms, better segmentation techniques by generating images of different tissue types and background activity would improve the feasibility of the method in real clinical environment.

Selection of photodetectors in nuclear medical imaging using MCDM methods

Photodetectors used in nuclear medical imaging such as single photon emission computed tomography (SPECT) and positron emission tomography (PET) are an important element of radiation detection systems. Selecting the photodetector depends on many physical criteria including quantum efficiency (QE) and gain. The aim of this study is to apply multi-criteria decision-making (MCDM) methods to determine the optimum photodetector based on the evaluation and comparison of complex and multiple criteria. The photodetectors investigated in this study are photomultiplier tube (PMT), avalanche photodiode (APD) and silicon photomultiplier (SiPM). The bias voltage, gain, rise time, and QE were selected since they are considered as the key criteria for the photodetectors. Then, the corresponding values of each criteria were defined and preferred weights were assigned to each criteria based on the desired outcome. The fuzzy preference ranking organization method for enrichment of evaluations (PROMETHEE) and fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) methods were used to evaluate the alternatives. The results showed that conventional PMT came first in the ranking, followed by SiPM, while APD was the least desirable photodetector according to the fuzzy PROMETHEE and fuzzy TOPSIS methods based on the selected criteria and assigned weights. MCDM methods were used to select photodetectors used in PET and SPECT systems. One can incorporate as many alternatives and criteria as needed and assign the weights accordingly.

Preliminary results of a single photon emission computed tomography (SPECT) detector for inspection of spent fuel assembly

SPECT systems are being used by international safeguards organizations for the measurement for structural evaluation of spent fuel assemblies. However, the low sensitivity still limits the verification of spent fuel assemblies within a short measurement time (1–2 h per assembly). In this study, the SPECT detector was optimized and evaluated to identify the structure of spent fuel. The detector module consists of 64 one-dimensional (1-D) multi-slit collimators and 1-D pixelated scintillators coupled to SiPMs. We evaluated and optimized the light collection efficiency and energy resolution according to the shape of scintillator (Trapezoid, Rectangular), and reflector materials (Paint, Teflon tape, BaSO4) by Geant4 Application for Tomographic Emission (GATE) simulation and experiment. As a result, the trapezoidal scintillator coated with BaSO4 showed the highest light collection efficiency among the six models in GATE simulation and in experiments. The spent fuel rods were imaged using trapezoidal scintillator coated with BaSO4, and 1-D projections and line profiles were obtained in order to distinguish the source location. In this study, the scintillator structure and reflector material variables were optimized using Monte Carlo simulation to measure 662 keV gamma-ray of 137Cs for inspection of spent fuel assembly using the SPECT system. In order to confirm the imaging potential of the spent fuel assembly, the detector performance was evaluated using unused fuel rods for testing. The performance of the detector for fuel rod identification has been proven, and we expect that the optimized detector module will contribute to the rapid verification of the spent fuel assembly compared to conventional systems.

Investigating the limited performance of a deep-learning-based SPECT denoising approach: An observer-study-based characterization.

Multiple objective assessment of image-quality (OAIQ)-based studies have reported that several deep-learning (DL)-based denoising methods show limited performance on signal-detection tasks. Our goal was to investigate the reasons for this limited performance. To achieve this goal, we conducted a task-based characterization of a DL-based denoising approach for individual signal properties. We conducted this study in the context of evaluating a DL-based approach for denoising single photon-emission computed tomography (SPECT) images. The training data consisted of signals of different sizes and shapes within a clustered-lumpy background, imaged with a 2D parallel-hole-collimator SPECT system. The projections were generated at normal and 20% low-count level, both of which were reconstructed using an ordered-subset-expectation-maximization (OSEM) algorithm. A convolutional neural network (CNN)-based denoiser was trained to process the low-count images. The performance of this CNN was characterized for five different signal sizes and four different signal-to-background ratio (SBRs) by designing each evaluation as a signal-known-exactly/background-known-statistically (SKE/BKS) signal-detection task. Performance on this task was evaluated using an anthropomorphic channelized Hotelling observer (CHO). As in previous studies, we observed that the DL-based denoising method did not improve performance on signal-detection tasks. Evaluation using the idea of observer-study-based characterization demonstrated that the DL-based denoising approach did not improve performance on the signal-detection task for any of the signal types. Overall, these results provide new insights on the performance of the DL-based denoising approach as a function of signal size and contrast. More generally, the observer study-based characterization provides a mechanism to evaluate the sensitivity of the method to specific object properties, and may be explored as analogous to characterizations such as modulation transfer function for linear systems. Finally, this work underscores the need for objective task-based evaluation of DL-based denoising approaches.

Development of a high-resolution SSR-SPECT system for preclinical imaging and neuroimaging

Techniques like single photon emission computed tomography (SPECT) show high potential in small animals in vivo imaging framework. In this context, the spatial resolution represents an important parameter influencing scanner design, given the small size of the anatomical structures to be investigated. The purpose of the present work was to assess the performance of a scintigraphic system with an improved spatial resolution by applying the previously described Super Spatial Resolution (SSR) method. Our dual-head SPECT system is composed of gamma cameras based on the Hamamatsu H13700 position-sensitive photomultiplier tube (PSPMT). In each detector head, the PSPMT is coupled to a 28 × 28 array of CRY018 scintillation crystals. The pure Tungsten parallel square hole collimator ensures the position sensitivity, and a dedicated resistive chain readout so as an ADC board have been proprietary designed.To finalize the mechanical development of the SSR-SPECT system several tests were carried out. Based on the results obtained in the test phase, a partial review of the mechanical design was performed. Then a dedicated mechanical motion software was developed, and in particular, a kinematic software debugging and testing was assessed. Several experiments were carried out by using Derenzo phantoms and capillaries filled with radioactive sources. Finally, the performance of our system was evaluated by performing small animal imaging studies.The SPECT spatial resolution was experimentally determined to be about 1.6 mm. We reach a resolution of 1.18 mm by applying the SSR based on two images.The results of this study demonstrated the good capability of the system as a suitable tool for preclinical imaging especially in fields like neuroscience for the study of small brain structures.

Simultaneous in vivo imaging with PET and SPECT tracers using a Compton-PET hybrid camera

Positron-emission tomography (PET) and single-photon-emission computed tomography (SPECT) are well-established nuclear-medicine imaging methods used in modern medical diagnoses. Combining PET with 18F-fluorodeoxyglucose (FDG) and SPECT with an 111In-labelled ligand provides clinicians with information about the aggressiveness and specific types of tumors. However, it is difficult to integrate a SPECT system with a PET system because SPECT requires a collimator. Herein, we describe a novel method that provides simultaneous imaging with PET and SPECT nuclides by combining PET imaging and Compton imaging. The latter is an imaging method that utilizes Compton scattering to visualize gamma rays over a wide range of energies without requiring a collimator. Using Compton imaging with SPECT nuclides, instead of the conventional SPECT imaging method, enables PET imaging and Compton imaging to be performed with one system. In this research, we have demonstrated simultaneous in vivo imaging of a tumor-bearing mouse injected with 18F-FDG and an 111In-antibody by using a prototype Compton-PET hybrid camera. We have succeeded in visualizing accumulations of 18F-FDG and 111In-antibody by performing PET imaging and Compton imaging simultaneously. As simultaneous imaging utilizes the same coordinate axes, it is expected to improve the accuracy of diagnoses.

Head-to-head comparison of diagnostic accuracy of stress-only myocardial perfusion imaging with conventional and cadmium-zinc telluride single-photon emission computed tomography in women with suspected coronary artery disease

BackgroundBreast attenuation may impact the diagnostic accuracy of stress myocardial perfusion imaging (MPI) with single-photon emission computed tomography (SPECT). We compared the performance of conventional (C)-SPECT and cadmium-zinc-telluride (CZT)-SPECT systems in women with low-intermediate likelihood of coronary artery disease (CAD). Methods and ResultsA total of 109 consecutive women underwent stress-optional rest MPI by both C-SPECT and CZT-SPECT. In the overall study population, a weak albeit significant correlation between total perfusion defect (TPD) measured by C-SPECT and CZT-SPECT was observed (r = 0.38, P < .001) and at Bland-Altman analysis the mean difference in TPD (C-SPECT minus CZT-SPECT) was 2.40% (P < .001). Overall concordance of semi-quantitative diagnostic performance between C-SPECT and CZT-SPECT was observed in 52 (48%) women with a κ value of 0.09. Normalcy rate was significantly higher using CZT-SPECT compared to C-SPECT (P < .001). Machine learning analysis performed through the implementation of J48 algorithm proved that CZT-SPECT has higher sensitivity, specificity, and accuracy than C-SPECT. ConclusionsIn women with low-intermediate likelihood of CAD, there is a poor concordance of diagnostic performance between C-SPECT and CZT-SPECT, and CZT-SPECT allows better normalcy rate detection compared to C-SPECT.

Self-Collimating SPECT With Multi-Layer Interspaced Mosaic Detectors.

Conventional single photon emission computed tomography (SPECT) relies on mechanical collimation whose resolution and sensitivity are interdependent, the best performance a SPECT system can attain is only a compromise of these two equally desired properties. To simultaneously achieve high resolution and sensitivity, we propose to use sensitive detectors constructed in a multi-layer in ter spaced mosaicdetectors (MATRICES) architecture to accomplish part of the collimation needed. We name this new approach self-collimation. We evaluate three self-collimating SPECT systems and report their imaging performance: 1) A simulated human brain SPECT achieves 3.88% sensitivity, it clearly resolves 0.5-mm and 1.0-mm hot-rod patterns at noise-free and realistic count-levels, respectively; 2) a simulated mouse SPECT achieves 1.25% sensitivity, it clearly resolves 50- [Formula: see text] and 100- [Formula: see text] hot-rod patterns at noise-free and realistic count-levels, respectively; 3) a SPECT prototype achieves 0.14% sensitivity and clearly separates 0.3-mm-diameter point sources of which the center-to-center neighbor distance is also 0.3 mm. Simulated contrast phantom studies show excellent resolution and signal-to-noise performance. The unprecedented system performance demonstrated by these 3 SPECT scanners is a clear manifestation of the superiority of the self-collimating approach over conventional mechanical collimation. It represents a potential paradigm shift in SPECT technology development.