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Dynamic PET allows quantification of physiological parameters through tracer kinetic modeling. For dynamic imaging of brain or head and neck cancer on conventional PET scanners with a short axial field of view, the image-derived input function (ID-IF) from intracranial blood vessels such as the carotid artery (CA) suffers from severe partial volume effects. Alternatively, optimization-derived input function (OD-IF) by the simultaneous estimation (SIME) method does not rely on an ID-IF but derives the input function directly from the data. However, the optimization problem is often highly ill-posed. We proposed a new method that combines the ideas of OD-IF and ID-IF together through a kernel framework. While evaluation of such a method is challenging in human subjects, we used the uEXPLORER total-body PET system that covers major blood pools to provide a reference for validation.MethodsThe conventional SIME approach estimates an input function using a joint estimation together with kinetic parameters by fitting time activity curves from multiple regions of interests (ROIs). The input function is commonly parameterized with a highly nonlinear model which is difficult to estimate. The proposed kernel SIME method exploits the CA ID-IF as a priori information via a kernel representation to stabilize the SIME approach. The unknown parameters are linear and thus easier to estimate. The proposed method was evaluated using 18F-fluorodeoxyglucose studies with both computer simulations and 20 human-subject scans acquired on the uEXPLORER scanner. The effect of the number of ROIs on kernel SIME was also explored.ResultsThe estimated OD-IF by kernel SIME showed a good match with the reference input function and provided more accurate estimation of kinetic parameters for both simulation and human-subject data. The kernel SIME led to the highest correlation coefficient (R = 0.97) and the lowest mean absolute error (MAE = 10.5 %) compared to using the CA ID-IF (R = 0.86, MAE = 108.2 %) and conventional SIME (R = 0.57, MAE = 78.7 %) in the human-subject evaluation. Adding more ROIs improved the overall performance of the kernel SIME method.ConclusionThe proposed kernel SIME method shows promise to provide an accurate estimation of the blood input function and kinetic parameters for brain PET parametric imaging.

Dual-layer detectors provide a low-cost solution to improved material decomposition and lesion differentiation in X-ray imaging, while eliminating motion artifacts from multiple exposures. Most designs utilize two indirect detectors with scintillators designed for low-energy and higher-energy detection and separated by a copper filter to harden the beam for high energy detection. To improve the performance of the bottom detector and lower dose requirements, we have previously proposed an alloyed amorphous selenium photodetector to achieve improved resolution and absorption at green wavelengths, better suited to high-performance scintillators such as CsI:Tl. In this work, we demonstrate a baseline prototype for the bottom layer-a continuous, large area 83 μm pixel pitch flat panel indirect detector with well-established amorphous selenium as the photodetector-and verify the architectures performance and detector design. We characterize lag, noise-power spectrum, detective quantum efficiency, and modular transfer function of the detector, and show resolution up to 6 lp/mm when operated at an applied bias of 150 V. This provides a starting point for evaluating the alloyed selenium materials, and shows promise for this detector in the future dual-layer design.

Cadmium zinc telluride (CZT) detectors enable high spatial resolution and high detection efficiency and are utilized for many gamma-ray and X-ray spectroscopy applications. In this article, we describe a stable bonding process and report on the characterization of cross-strip CZT detectors before and after bonding to flexible circuit. The bonding process utilizes gold stud bonding and polymer epoxy technique to bond the flexible circuits to two CZT crystals and form a detector module in an anode-cathode-cathode-anode (ACCA) configuration. The readout electronics is optimized in terms of shaper setting and steering electrode voltage. The average full-width half maximum (FWHM) energy resolution at 662 keV of 110 CZT crystals tested individually was 3.5% ± 0.59% and 4.75% ± 0.48% prebonded and post-bonded, respectively. No depth correction was performed in this study. The average FWHM energy resolution at 662 keV of the scaled-up system with 80 CZT crystals was 4.40% ± 0.53%, indicating the scaled-up readout electronics and stacking of the modules does not deteriorate performance. The proper shielding and grounding of the scaled-up system slightly improved the system-wide performance. The FWHM energy resolution at 511 keV of the scaled-up system was 5.85% ± 0.73%.

Amorphous selenium (a-Se) is a large-area compatible photoconductor that has received significant attention toward the development of UV and X-ray detectors for a wide range of applications in medical imaging, life science, high-energy physics, and nuclear radiation detection. A subset of applications require detection of photons with spectral coverage from UV to infrared wavelengths. In this work, we present a systematic study utilizing density functional theory simulations and experimental studies to investigate optical and electrical properties of a-Se alloyed with tellurium (Te). We report hole and electron mobilities and conversion efficiencies for a-Se1-xTex (x = 0, 0.03, 0.05, 0.08) devices as a function of applied field, along with band gaps and comparisons to previous studies. For the first time, these values are reported at high electric field (>10 V/μm), demonstrating recovery of quantum efficiency in Se-Te alloys. A comparison to the Onsager model for a-Se demonstrates the strong field dependence in the thermalization length and expands on the role of defect states in device performance.

Cadmium zinc telluride (CZT) detectors are suitable for various applications due to the good energy resolution and the simple pixilation to achieve high spatial resolution. Our group is developing a two-panel head and neck dedicated positron emission tomography system based on CZT detectors. Each panel will consist of 150 CZT crystals (4×4×0.5 cm3) covering an area of 20×15 cm2 in an edge-on configuration to achieve high detector efficiency at 511 keV. In this work, we present the design and development of a full data acquisition chain that enables a low noise and compact readout for each panel. The initial results of the readout circuit were quantified using a 1 kHz square wave test pulse. The pulse amplitude was chosen to generate approximately the same amount of charges as a 511 keV photon would provide in CZT. The best-case FWHM electronic noise at 511 keV was measured to be 0.69% ± 0.16% (3.52 ± 0.81 in keV units after conversion). The FWHM electronic noise at 511 keV for a complete DAQ chain was 4.33% ± 0.30% (22.13 ± 1.53 in keV units).

Optical property modulation induced by ionizing radiation is a promising approach for ultra-fast, lower time jitter detection of photon arrival time. If successful, this method can be utilized in time-of-flight positron emission tomography to achieve a coincidence time resolution approaching 10 ps. In this work, the optical property modulation based method is further developed with focus on a detection setup based on two crossed polarizers. Previous work demonstrated that such an optical setup could be utilized in radiation detection, though its detection sensitivity needed improvement. This work investigates the angle between polarizers and electric field distribution within the detection crystal to understand and improve the detection sensitivity of an optical polarization modulation based method. For this work, cadmium telluride (CdTe) was studied as the detector crystal . The magic angle (i.e. optimal working angle) of the two crossed polarizers based optical setup with CdTe were explored theoretically and experimentally. The experimental results show that the detection sensitivity could be improved by around 10% by determining the appropriate magic angle. We then studied the dependence of detection sensitivity on electric field distribution as well as on the bias voltage across the detector crystal using CdTe crystals. The experimental results show that a smaller electrode on the detector crystal, or a more concentrated electric field distribution could improve detection sensitivity. For CdTe, a detector crystal sample with 2.5 mm × 2.5 mm square electrode has twice the detection sensitivity of a detector crystal with 5 mm × 5 mm square electrode. Increasing the bias voltage before saturation for CdTe could further enhance the modulation strength and thus, the sensitivity. Our investigations demonstrated that by determining the proper working angle of polarizers and bias electrical distribution to the detector, we could improve the sensitivity of the proposed optical setup.

While the localization of radiological sources has traditionally been handled with statistical algorithms, such a task can be augmented with advanced machine learning methodologies. The combination of deep and reinforcement learning has provided learning-based navigation to autonomous, single-detector, mobile systems. However, these approaches lacked the capacity to terminate a surveying/search task without outside influence of an operator or perfect knowledge of source location (defeating the purpose of such a system). Two stopping criteria are investigated in this work for a machine learning navigated system: one based upon Bayesian and maximum likelihood estimation (MLE) strategies commonly used in source localization, and a second providing the navigational machine learning network with a stop search action. A convolutional neural network was trained via reinforcement learning in a 10 m × 10 m simulated environment to navigate a randomly placed detector-agent to a randomly placed source of varied strength (stopping with perfect knowledge during training). The network agent could move in one of four directions (up, down, left, right) after taking a 1 s count measurement at the current location. During testing, the stopping criteria for this navigational algorithm was based upon a Bayesian likelihood estimation technique of source presence, updating this likelihood after each step, and terminating once the confidence of the source being in a single location exceeded 0.9. A second network was trained and tested with similar architecture as the previous but which contained a fifth action: for self-stopping. The accuracy and speed of localization with set detector and source initializations were compared over 50 trials of MLE-Bayesian approach and 1000 trials of the CNN with self-stopping. The statistical stopping condition yielded a median localization error of ~1.41 m and median localization speed of 12 steps. The machine learning stopping condition yielded a median localization error of 0 m and median localization speed of 17 steps. This work demonstrated two stopping criteria available to a machine learning guided, source localization system.

Organ-dedicated PET scanners are becoming more prevalent because of their advantages in higher sensitivity, improved image quality, and lower cost. Detectors utilized in these scanners have finer pixel size with depth of interaction (DOI) capability. This work presents a LYSO(Ce) detector module with DOI capability which has the potential to be scaled up to a high-resolution small animal or organ-dedicated PET system. For DOI capability, a submodule with one LYSO block detector utilizing PETsys TOFPET2 application-specific integrated circuit (ASIC) was previously developed in our lab. We scaled up the submodule and optimized the configuration to allow for a compact housing of the dual-readout boards in one side of the blocks by designing a high-speed dual-readout cable to maintain the original pin-to-pin relationship between the Samtec connectors. The module size is 53.8 × 57.8 mm2. Each module has 2 × 2 LYSO blocks, each LYSO block consists of 4 × 4 LYSO units, and each LYSO unit contains a 6 × 6 array of 1 × 1 × 20 mm3 LYSO crystals. The four lateral surfaces of LYSO crystal were mechanically ground to W14, and the two end surfaces were polished. Two ends of the LYSO crystal are optically connected to SiPM for DOI measurement. Eight LYSO blocks performance including energy, timing, and DOI resolution is characterized with a single LYSO slab. The in-panel and orthogonal-panel spatial resolution of the two modules with 107.4 mm distance between each other are measured at 9 positions within the field of view (FOV) with a 22Na source. Results show that the average energy, timing, and DOI resolution of all LYSO blocks are 16.13% ± 1.01% at 511 keV, 658.03 ± 15.18 ps, and 2.62 ± 0.06 mm, respectively. The energy and timing resolution of two modules are 16.35% and 0.86 ns, respectively. The in-panel and orthogonal-panel spatial resolution of the two modules at the FOV center are 1.9 and 4.4 mm respectively.

In this paper, the room-temperature performance of different optical coupling materials post temperature exposure was tested. The tested couplers included OC431A-LVP, OG0010 optical grease, BLUESIL V-788, and SAINT-GOBAIN BC-630. This was done by subjecting the whole detector with newly applied optical coupling materials to a 2-h temperature exposure-ranging from -20 to 50 °C and then by letting it return to room temperature before collecting a spectrum from a Cs-137 source. The energy resolution at 662 keV was computed as the metric for evaluating the performance. Three trials were run at each coupler-temperature combination. Our results reveal that the performance of all coupling agents do indeed change with temperature after the 2-h exposure. Over all the tested temperature trials, the energy resolution ranged from 11.4 to 14.3% for OC431A-LVP; 10.2 to 14.6% for OG0010; 10 to 13.4% for BLUESIL V-788; and 9.8 to 13.3% for SAINT-GOBAIN BC-630. OC431A-LVP had the lowest variance over the full range, while BC-630 was the most constant for temperatures above 20 °C. Ultraviolet-visible (UV-Vis) spectra experiments were also performed on isolated optical coupling materials to measure the light absorption coefficient. The results show that the temperature-induced variance in light absorption coefficient of each optical coupling materials is one of the reasons for the variance in energy resolution performance. Our findings suggest the need for further investigation into this effect and the recommendation that optical coupling materials need to be selected for the task at hand with greater scrutiny.

Positron emission tomography (PET) suffers from limited spatial resolution in current head and neck cancer management. We are building a dual-panel high-resolution PET system to aid the detection of tumor involvement in small lymph nodes ([Formula: see text]10 mm in diameter). The system is based on cadmium zinc telluride (CZT) detectors with cross-strip electrode readout (1 mm anode pitch and 5 mm cathode pitch). One challenge of the dual-panel system is that the limited angular coverage of the imaging volume leads to artifacts in reconstructed images, such as the elongation of lesions. In this work, we leverage a penalized maximum-likelihood (PML) reconstruction for the limited-angle PET system. The dissimilarity between the image to be reconstructed and a prior image from a low-resolution whole-body scanner is penalized. An image-based resolution model is incorporated into the regularization. Computer simulations were used to evaluate the performance of the method. Results demonstrate that the elongation of the 6-mm and 8-mm diameter hot spheres is eliminated with the regularization strength γ being 0.02 or larger. The PML reconstruction yields higher contrast recovery coefficient (CRC) of hot spheres compared to the maximum-likelihood reconstruction, as well as the low-resolution whole-body image, across all hot sphere sizes tested (3, 4, 6, and 8 mm). The method studied in this work provides a way to mitigate the limited-angle artifacts in the reconstruction from limited-angle PET data, making the high-resolution dual-panel dedicated head and neck PET system promising for head and neck cancer management.

The tumor-involved regions of head and neck cancer (HNC) have complex anatomical structures and vital physiological roles. As a consequence, there is a need for high sensitivity and high spatial resolution dedicated HNC PET scanner. The purpose of this study is to evaluate and optimize system design that includes detecting materials and geometries. For the detecting material, two scanners with the same two-panel geometry based on CZT and LYSO were evaluated. For the system geometry, four CZT scanners with two-panel, lengthened two-panel, four-panel, and full-ring geometries were evaluated. A cylinder phantom with sphere lesions and an XCAT phantom in the head and neck region were simulated. The results showed that the sensitivity of the 40-mm thickness CZT system and the 20-mm thickness LYSO system were comparable. However, the multiple interaction photon events recovery accuracy of the CZT system was about 20% higher. The in-panel and orthogonal-panel spatial resolutions of CZT are 0.58 and 0.74 mm, while those of LYSO are 0.70 and 1.40 mm. For system geometry, the four-panel and full-ring scanners have a higher contrast recovery coefficient (CRC) and contrast-to-noise ratio (CNR) than the two-panel and lengthened two-panel scanners. However, a 5-mm lesion in the XCAT phantom was visualized within 6 min in the two-panel system.

In radioactive source surveying protocols, a number of task-inherent features degrade the quality of collected gamma ray spectra, including: limited dwell times, a fluctuating background, a large distance to the source, weak source activity, and the low sensitivity of mobile detectors. Thus, collected gamma ray spectra are expected to be sparse and noise dominated. For extremely sparse spectra, direct background subtraction is infeasible and many background estimation techniques do not apply. In this paper, we present a statistical algorithm for source estimation and anomaly detection under such conditions. We employ a fixed-hyperparameter Gaussian processes regression methodology with a linear innovation sequence scheme in order to quickly update an ongoing source distribution estimate with no prior training required. We have evaluated the effectiveness of this approach for anomaly detection using background spectra collected with a Kromek D3S and simulated source spectrum and hyperparameters defined by detector characteristics and information derived from collected spectra. We attained an area under the ROC curve of 0.902 for identifying sparse source peaks within a sparse gamma ray spectrum and achieved a true positive rate of 93% when selecting the optimum thresholding value derived from the ROC curve.

Currently, injection sites of probes, cannula, and optic fibers in stereotactic neurosurgery are typically located manually. This step involves location estimations based on human experiences and thus introduces errors. In order to reduce localization error and improve repeatability of experiments and treatments, we investigate an automated method to locate injection sites. This paper proposes a localization framework, which integrates a region-based convolutional network and a fully convolutional network, to locate specific anatomical points on skulls of rodents. Experiment results show that the proposed localization framework is capable of identifying and locatin bregma and lambda in rodent skull anatomy images with mean errors less than 300 μm. This method is robust to different lighting conditions and mouse orientations, and has the potential to simplify the procedure of locating injection sites.

Improving 511 keV photon detection sensitivity is a common goal for positron emission tomography system designers. One attractive approach to increase sensitivity is recovering events that are normally rejected. The kinematics of Compton scattering can be used to recover the line of response through direction difference angle (DDA). The uncertainty of DDA is determined by the energy and spatial resolution of a system. In this work, we evaluated the performance of small animal CZT-based positron emission tomography systems with energy resolution of 1%, 4%, and 6% and different spatial resolution based on prior work for guiding new design efforts. Designs with energy resolution limited by counting statistics and by electronic noise were considered. The influence of modifying the conventional energy window and uncertainty of DDA was investigated. For a system with 4% energy resolution and limited by electronic noise, the figure of merit of noise equivalent count increases by 65% as the lower energy bound increases from 471 keV to 493 keV. If the system-wide energy resolution becomes worse than 4% of the full width half maximum at 511 keV, going to a pixel size finer than 1 mm has very limited effect in reducing total angular uncertainty. For a system with 1% energy resolution, as the spatial resolution improves from 1 mm to 0.5 mm, the contrast-to-noise ratio increases by 9%.

Depth-of-interaction (DOI) capability is important for achieving high spatial resolution and sensitivity in dedicated organ and small animal positron emission tomography (PET) scanners. The dual-ended readout is one of the common methods that can achieve good DOI resolution. The aim of this study is to evaluate a dual-ended readout detector based on silicon photomultiplier (SiPM) and TOFPET2 application-specific integrated circuit (ASIC). The detector is based on 4 [Formula: see text] 4 lutetium-yttrium oxyorthosilicate (LYSO) units, each unit contained 6 [Formula: see text] 6 LYSO crystals, and the crystal size was 1 [Formula: see text] 1 [Formula: see text] 20 mm3. The four lateral surfaces of LYSO crystals were mechanically ground to W14 (surface roughness 10-14 [Formula: see text]m), and the two ended surfaces were polished (surface roughness

Anomalous radiation source detection in urban environments is challenging due to the complex nature of background radiation. When a suspicious area is determined, a radiation survey is usually carried out to search for anomalous radiation sources. To locate the source with high accuracy and in a short time, different survey approaches have been studied such as scanning the area with fixed survey paths and data-driven approaches that update the survey path on the fly with newly acquired measurements. In this work, we propose reinforcement learning as a data-driven approach to conduct radiation detection tasks with no human intervention. A simulated radiation environment is constructed, and a convolutional neural network-based double Q-learning algorithm is built and tested for radiation source detection tasks. Simulation results show that the double Q-learning algorithm can reliably navigate the detector and reduce the searching time by at least 44% compared with traditional uniform search methods and gradient search methods.

The kinematics of Compton scatter can be used to estimate the interaction sequence of inter-crystal scatter interactions in 3D position-sensitive cadmium zinc telluride (CZT) detectors. However, in the case of intra-crystal scatter in a cross-strip CZT detector slab, multiple anode and cathode strips may be triggered, creating position ambiguity due to uncertainty in possible combinations of anode-cathode pairings. As a consequence, methods such as energy-weighted centroid are not applicable to position the interactions. In practice, since the event position is uncertain, these intra-crystal scatters events are discarded. In this work, we studied using Compton kinematics and a direction difference angle to provide a method to correctly identify the anode-cathode pair corresponding to the first interaction position in an intra-crystal scatter event. GATE simulation studies of a NEMA NU4 image quality phantom in a small animal positron emission tomography under development composed of 192, [Formula: see text] mm CZT crystals shows that 47% of total numbers of multiple-interaction photon events (MIPEs) are intra-crystal scatter with a 100 keV lower energy threshold per interaction. The sensitivity of the system increases from 0.6 to 4.10 (using 10 keV as system lower energy threshold) by including rather than discarding inter- and intra-crystal scatter. The contrast-to-noise ratio (CNR) also increases from [Formula: see text] to [Formula: see text]. It was shown that a higher energy threshold limits the capability of the system to detect MIPEs and reduces CNR. Results indicate a sensitivity increase (4.1 to 5.88) when raising the lower energy threshold (10 keV to 100 keV) for the case of only two-interaction events. In order to detect MIPEs accurately, a low noise system capable of a low energy threshold (10 keV) per interaction is desired.

Modeling of background radiation for the urban environment plays an important role in homeland security. However, background radiation is difficult to assess due to its spatial-temporal fluctuations caused by the variation in soil composition, building materials, and weather patterns etc. To address the challenge of background radiation modeling, we developed a mobile sensor network to continuously monitor the background radiation; we also proposed a maximum likelihood estimation algorithm to decouple and estimate the backgrounds spatial distribution and temporal fluctuation. Experimental results demonstrated how this background radiation monitoring system accurately recognized high background regions in the experimental area, and successfully captured temporal fluctuation trends of background radiation during rains. Our system provides an efficient solution to model the temporal fluctuation and spatial distribution of background radiation.

The next generation of discoveries in molecular imaging requires positron emission tomography (PET) systems with high spatial resolution and high sensitivity to visualize and quantify low concentrations of molecular probes. The goal of this work is to assemble and explore such a system. We use cadmium zinc telluride (CZT) to achieve high spatial resolution, three-dimensional interaction positioning, and excellent energy resolution. The CZT crystals are arranged in an edge-on configuration with a minimum gap of [Formula: see text] in a four-sided panel geometry to achieve superior photon sensitivity. The developed CZT detectors and readout electronics were scaled up to complete significant portions of the final PET system. The steering electrode bias and the amplitude of the analog signals for time measurement were optimized to improve performance. The energy resolution (at 511 keV) over 468 channels is [Formula: see text] full-width-at-half-maximum (FWHM). The spatial resolution is [Formula: see text] FWHM. The time resolution of six CZT crystals in coincidence with six other CZT crystals is 37 ns. With high energy and spatial resolution and the relatively low random rate for small animal imaging, this system shows promise to be very useful for molecular imaging studies.