Deep learning-based PET image denoising and reconstruction: a review.

This review focuses on positron emission tomography (PET) imaging algorithms and traces the evolution of PET image reconstruction methods. First, we provide an overview of conventional PET image reconstruction methods from filtered backprojection through to recent iterative PET image reconstruction algorithms, and then review deep learning methods for PET data up to the latest innovations within three main categories. The first category involves post-processing methods for PET image denoising. The second category comprises direct image reconstruction methods that learn mappings from sinograms to the reconstructed images in an end-to-end manner. The third category comprises iterative reconstruction methods that combine conventional iterative image reconstruction with neural-network enhancement. We discuss future perspectives on PET imaging and deep learning technology.

Potential for in vivo visualization of intracellular pH gradient in the brain using PET imaging.

Intracellular pH is a valuable index for predicting neuronal damage and injury. However, no PET probe is currently available for monitoring intracellular pH in vivo. In this study, we developed a new approach for visualizing the hydrolysis rate of monoacylglycerol lipase, which is widely distributed in neurons and astrocytes throughout the brain. This approach uses PET with the new radioprobe [11C]QST-0837 (1,1,1,3,3,3-hexafluoropropan-2-yl-3-(1-phenyl-1H-pyrazol-3-yl)azetidine-1-[11C]carboxylate), a covalent inhibitor containing an azetidine carbamate skeleton for monoacylglycerol lipase. The uptake and residence of this new radioprobe depends on the intracellular pH gradient, and we evaluated this with in silico, in vitro and in vivo assessments. Molecular dynamics simulations predicted that because the azetidine carbamate moiety is close to that of water molecules, the compound containing azetidine carbamate would be more easily hydrolyzed following binding to monoacylglycerol lipase than would its analogue containing a piperidine carbamate skeleton. Interestingly, it was difficult for monoacylglycerol lipase to hydrolyze the azetidine carbamate compound under weakly acidic (pH 6) conditions because of a change in the interactions with water molecules on the carbamate moiety of their complex. Subsequently, an in vitro assessment using rat brain homogenate to confirm the molecular dynamics simulation-predicted behaviour of the azetidine carbamate compound showed that [11C]QST-0837 reacted with monoacylglycerol lipase to yield an [11C]complex, which was hydrolyzed to liberate 11CO2 as a final product. Additionally, the 11CO2 liberation rate was slower at lower pH. Finally, to indicate the feasibility of estimating how the hydrolysis rate depends on intracellular pH in vivo, we performed a PET study with [11C]QST-0837 using ischaemic rats. In our proposed in vivo compartment model, the clearance rate of radioactivity from the brain reflected the rate of [11C]QST-0837 hydrolysis (clearance through the production of 11CO2) in the brain, which was lower in a remarkably hypoxic area than in the contralateral region. In conclusion, we indicated the potential for visualization of the intracellular pH gradient in the brain using PET imaging, although some limitations remain. This approach should permit further elucidation of the pathological mechanisms involved under acidic conditions in multiple CNS disorders.

First experimental demonstration of real-time neutron capture discrimination in helium and carbon ion therapy.

This work provides the first experimental proof of an increased neutron capture photon signal following the introduction of boron to a PMMA phantom during helium and carbon ion therapies in Neutron Capture Enhanced Particle Therapy (NCEPT). NCEPT leverages [Formula: see text]B neutron capture, leading to the emission of detectable 478 keV photons. Experiments were performed at the Heavy Ion Medical Accelerator in Chiba, Japan, with two Poly(methyl methacrylate) (PMMA) targets, one bearing a boron insert. The BeNEdiCTE gamma-ray detector measured an increase in the 478 keV signal of 45 ± 7% and 26 ± 2% for carbon and helium ion irradiation, respectively. Our Geant4 Monte Carlo simulation model, developed to investigate photon origins, found less than 30% of detected photons originated from the insert, while boron in the detector's circuit boards contributed over 65%. Further, the model investigated detector sensitivity, establishing its capability to record a 10% increase in 478 keV photon detection at a target [Formula: see text]B concentration of 500 ppm using spectral windowing alone, and 25% when combined with temporal windowing. The linear response extended to concentrations up to 20,000 ppm. The increase in the signal in all evaluated cases confirm the potential of the proposed detector design for neutron capture quantification in NCEPT.

A quantitative assessment of Geant4 for predicting the yield and distribution of positron-emitting fragments in ion beam therapy.

Objective.To compare the accuracy with which different hadronic inelastic physics models across ten Geant4 Monte Carlo simulation toolkit versions can predict positron-emitting fragments produced along the beam path during carbon and oxygen ion therapy.Approach.Phantoms of polyethylene, gelatin, or poly(methyl methacrylate) were irradiated with monoenergetic carbon and oxygen ion beams. Post-irradiation, 4D PET images were acquired and parent11C,10C and15O radionuclides contributions in each voxel were determined from the extracted time activity curves. Next, the experimental configurations were simulated in Geant4 Monte Carlo versions 10.0 to 11.1, with three different fragmentation models-binary ion cascade (BIC), quantum molecular dynamics (QMD) and the Liege intranuclear cascade (INCL++) - 30 model-version combinations. Total positron annihilation and parent isotope production yields predicted by each simulation were compared between simulations and experiments using normalised mean squared error and Pearson cross-correlation coefficient. Finally, we compared the depth of the maximum positron annihilation yield and the distal point at which the positron yield decreases to 50% of peak between each model and the experimental results.Main results.Performance varied considerably across versions and models, with no one version/model combination providing the best prediction of all positron-emitting fragments in all evaluated target materials and irradiation conditions. BIC in Geant4 10.2 provided the best overall agreement with experimental results in the largest number of test cases. QMD consistently provided the best estimates of both the depth of peak positron yield (10.4 and 10.6) and the distal 50%-of-peak point (10.2), while BIC also performed well and INCL generally performed the worst across most Geant4 versions.Significance.The best predictions of the spatial distribution of positron annihilations and positron-emitting fragment production along the beam path during carbon and oxygen ion therapy was obtained using Geant4 10.2.p03 with BIC or QMD. These version/model combinations are recommended for future heavy ion therapy research.

Optimum selection for multi-interaction events in Compton-PET hybrid reconstruction: a Monte Carlo study.

In Compton PET, that has a scatterer inserted inside a PET ring, there are multi-interaction events that can be treated as both PET and Compton events. A PET event from multi-interaction events that include a Compton event and a photoelectric absorption event or two Compton events can be extracted by applying a PET recovery method. In this study, we aimed to establish a method to maximize image quality by utilizing such redundant events. We conducted brain-scale Monte Carlo simulations of a C-shaped Compton-PET geometry and a whole gamma imaging (WGI) geometry. Images were reconstructed by a hybrid image reconstruction method combining both PET and Compton events. The result showed that the spatial resolution was improved when treated as PET events while keeping the noise level. The effect of improvement was more significant in WGI than in C-shaped Compton PET because the number of events recovered as PET events having more accurate spatial information was much larger in WGI. When the PET-recovered multi-interaction events were also included as Compton events in the hybrid reconstruction, we did not observe any improvement in image quality, while the number of used events was largest. The results suggested that treating events as PET events exclusively was better for image quality.

Pre-acquired CT-based attenuation correction with automated headrest removal for a brain-dedicated PET system.

Attenuation correction (AC) is essential for quantitative positron emission tomography (PET) images. Attenuation coefficient maps (µ-maps) are usually generated from computed tomography (CT) images when PET-CT combined systems are used. If CT has been performed prior to PET imaging, pre-acquired CT can be used for brain PET AC, because the human head is almost rigid. This pre-acquired CT-based AC approach is suitable for stand-alone brain-dedicated PET, such as VRAIN (ATOX Co. Ltd., Tokyo, Japan). However, the headrest of PET is different from the headrest in pre-acquired CT images, which may degrade the PET image quality. In this study, we prepared three different types of µ-maps: (1) based on the pre-acquired CT, where namely the headrest is different from the PET system (µ-map-diffHr); (2) manually removing the headrest from the pre-acquired CT (µ-map-noHr); and (3) artificially replacing the headrest region with the headrest of the PET system (µ-map-sameHr). Phantom images by VRAIN using each µ-map were investigated for uniformity, noise, and quantitative accuracy. Consequently, only the uniformity of the images using µ-map-diffHr was out of the acceptance criteria. We then proposed an automated method for removing the headrest from pre-acquired CT images. In comparisons of standardized uptake values in nine major brain regions from the 18F-fluoro-2-deoxy-D-glucose-PET of 10 healthy volunteers, no significant differences were found between the µ-map-noHr and the µ-map-sameHr. In conclusion, pre-acquired CT-based AC with automated headrest removal is useful for brain-dedicated PET such as VRAIN.

Fully 3D implementation of the end-to-end deep image prior-based PET image reconstruction using block iterative algorithm.

Objective. Deep image prior (DIP) has recently attracted attention owing to its unsupervised positron emission tomography (PET) image reconstruction method, which does not require any prior training dataset. In this paper, we present the first attempt to implement an end-to-end DIP-based fully 3D PET image reconstruction method that incorporates a forward-projection model into a loss function.Approach. A practical implementation of a fully 3D PET image reconstruction could not be performed at present because of a graphics processing unit memory limitation. Consequently, we modify the DIP optimization to a block iteration and sequential learning of an ordered sequence of block sinograms. Furthermore, the relative difference penalty (RDP) term is added to the loss function to enhance the quantitative accuracy of the PET image.Main results. We evaluated our proposed method using Monte Carlo simulation with [18F]FDG PET data of a human brain and a preclinical study on monkey-brain [18F]FDG PET data. The proposed method was compared with the maximum-likelihood expectation maximization (EM), maximuma posterioriEM with RDP, and hybrid DIP-based PET reconstruction methods. The simulation results showed that, compared with other algorithms, the proposed method improved the PET image quality by reducing statistical noise and better preserved the contrast of brain structures and inserted tumors. In the preclinical experiment, finer structures and better contrast recovery were obtained with the proposed method.Significance.The results indicated that the proposed method could produce high-quality images without a prior training dataset. Thus, the proposed method could be a key enabling technology for the straightforward and practical implementation of end-to-end DIP-based fully 3D PET image reconstruction.

Submillimeter-Resolution PET for High-Sensitivity Mouse Brain Imaging.

PET is a powerful molecular imaging technique that can provide functional information on living objects. However, the spatial resolution of PET imaging has been limited to around 1 mm, which makes it difficult to visualize mouse brain function in detail. Here, we report an ultrahigh-resolution small-animal PET scanner we developed that can provide a resolution approaching 0.6 mm to visualize mouse brain function with unprecedented detail. Methods: The ultrahigh-resolution small-animal PET scanner has an inner diameter of 52.5 mm and axial coverage of 51.5 mm. The scanner consists of 4 rings, each of which has 16 depth-of-interaction detectors. Each depth-of-interaction detector consists of a 3-layer staggered lutetium yttrium orthosilicate crystal array with a pitch of 1 mm and a 4 × 4 silicon photomultiplier array. The physical performance was evaluated in accordance with the National Electrical Manufacturers Association NU4 protocol. Spatial resolution was evaluated with phantoms of various resolutions. In vivo glucose metabolism imaging of the mouse brain was performed. Results: Peak absolute sensitivity was 2.84% with an energy window of 400-600 keV. The 0.55-mm rod structure of a resolution phantom was resolved using an iterative algorithm. In vivo mouse brain imaging with 18F-FDG clearly identified the cortex, thalamus, and hypothalamus, which were barely distinguishable in a commercial preclinical PET scanner that we used for comparison. Conclusion: The ultrahigh-resolution small-animal PET scanner is a promising molecular imaging tool for neuroscience research using rodent models.

Compton imaging for medical applications.

Compton imaging exploits inelastic scattering, known as Compton scattering, using a Compton camera consisting of a scatterer detector in the front layer and an absorber detector in the back layer. This method was developed for astronomy, and in recent years, research and development for environmental and medical applications has been actively conducted. Compton imaging can discriminate gamma rays over a wide energy range from several hundred keV to several MeV. Therefore, it is expected to be applied to the simultaneous imaging of multiple nuclides in nuclear medicine and prompt gamma ray imaging for range verification in particle therapy. In addition, multiple gamma coincidence imaging is expected to be realized, which allows the source position to be determined from a single coincidence event using nuclides that emit multiple gamma rays simultaneously, such as nuclides that emit a single gamma ray simultaneously with positron decay. This review introduces various efforts toward the practical application of Compton imaging in the medical field, including in vivo studies, and discusses its prospects.

Using inverse Laplace transform in positronium lifetime imaging.

Positronium (Ps) lifetime imaging is gaining attention to bring out additional biomedical information from positron emission tomography (PET). The lifetime of Psin vivocan change depending on the physical and chemical environments related to some diseases. Due to the limited sensitivity, Ps lifetime imaging may require merging some voxels for statistical accuracy. This paper presents a method for separating the lifetime components in the voxel to avoid information loss due to averaging. The mathematics for this separation is the inverse Laplace transform (ILT), and the authors examined an iterative numerical ILT algorithm using Tikhonov regularization, namely CONTIN, to discriminate a small lifetime difference due to oxygen saturation. The separability makes it possible to merge voxels without missing critical information on whether they contain abnormally long or short lifetime components. The authors conclude that ILT can compensate for the weaknesses of Ps lifetime imaging and extract the maximum amount of information.

Marker-less and calibration-less motion correction method for brain PET.

Marker-less head motion correction methods have been well-studied; however, no reports discussing potential issues in positional calibration between a PET system and an external sensor remain limited. In this study, we develop a method for positional calibration between the PET system and an external range sensor to achieve practical head motion correction. The basic concept of the developed method involves using the subject's face model as a marker not only for head motion detection but also for the system positional calibration. The face model of the subject, which can be obtained easily using the range sensor, can also be calculated from a computed tomography (CT) image of the same subject. The CT image, which is acquired separately for attenuation correction in PET, has the same coordinates as the PET image because of the appropriate matching algorithm between CT and PET images. The proposed method was implemented in the helmet-type PET and the motion correction accuracy was assessed quantitatively using a mannequin head. The phantom experiments demonstrated the performance of the developed motion correction method; high-resolution images with no trace of the applied motion were obtained as if no motion was provided. Statistical analysis supported the visual assessment results in terms of the spatial resolution, contrast recovery; uniformity, and the results implied that motion with correction slightly improved image quality compared with the motionless case. The tolerance of the developed method against potential tracking errors had a minimum 10% difference in the amplitude of the rotation angle.

Brain PET motion correction using 3D face-shape model: the first clinical study.

OBJECTIVE: Head motions during brain PET scan cause degradation of brain images, but head fixation or external-maker attachment become burdensome on patients. Therefore, we have developed a motion correction method that uses a 3D face-shape model generated by a range-sensing camera (Kinect) and by CT images. We have successfully corrected the PET images of a moving mannequin-head phantom containing radioactivity. Here, we conducted a volunteer study to verify the effectiveness of our method for clinical data. METHODS: Eight healthy men volunteers aged 22-45 years underwent a 10-min head-fixed PET scan as a standard of truth in this study, which was started 45 min after 18F-fluorodeoxyglucose (285 ± 23 MBq) injection, and followed by a 15-min head-moving PET scan with the developed Kinect based motion-tracking system. First, selecting a motion-less period of the head-moving PET scan provided a reference PET image. Second, CT images separately obtained on the same day were registered to the reference PET image, and create a 3D face-shape model, then, to which Kinect-based 3D face-shape model matched. This matching parameter was used for spatial calibration between the Kinect and the PET system. This calibration parameter and the motion-tracking of the 3D face shape by Kinect comprised our motion correction method. The head-moving PET with motion correction was compared with the head-fixed PET images visually and by standard uptake value ratios (SUVRs) in the seven volume-of-interest regions. To confirm the spatial calibration accuracy, a test-retest experiment was performed by repeating the head-moving PET with motion correction twice where the volunteer's pose and the sensor's position were different. RESULTS: No difference was identified visually and statistically in SUVRs between the head-moving PET images with motion correction and the head-fixed PET images. One of the small nuclei, the inferior colliculus, was identified in the head-fixed PET images and in the head-moving PET images with motion correction, but not in those without motion correction. In the test-retest experiment, the SUVRs were well correlated (determinant coefficient, r2 = 0.995). CONCLUSION: Our motion correction method provided good accuracy for the volunteer data which suggested it is useable in clinical settings.

Small nuclei identification with a hemispherical brain PET.

BACKGROUND: To confirm the performance of the first hemispherical positron emission tomography (PET) for the brain (Vrain) that we developed to visualise the small nuclei in the deep brain area, we compared 18F-fluorodeoxyglucose (FDG) brain images with whole-body PET images. METHODS: Ten healthy male volunteers (aged 22-45 years) underwent a representative clinical whole-body PET, followed by Vrain each for 10 min. These two scans were initiated 30 min and 45 min after FDG injection (4.1 ± 0.5 MBq/kg), respectively. First, we visually identified the small nuclei and then compared their standardised uptake values (SUVs) with the participants' age. Next, the SUVs of each brain region, which were determined by applying a volume-of-interest template for anatomically normalised PET images, were compared between the brain images with the Vrain and those with the whole-body PET images. RESULTS: Small nuclei, such as the inferior colliculus, red nucleus, and substantia nigra, were more clearly visualised in Vrain than in whole-body PET. The anterior nucleus and dorsomedial nucleus in the thalamus and raphe nucleus in the brainstem were identified in Vrain but not in whole-body PET. The SUVs of the inferior colliculus and dentate gyrus in the cerebellum positively correlated with age (Spearman's correlation coefficient r = 0.811, p = 0.004; r = 0.738, p = 0.015, respectively). The SUVs of Vrain were slightly higher in the mesial temporal and medial parietal lobes than those in whole-body PET. CONCLUSIONS: This was the first time that the raphe nuclei, anterior nuclei, and dorsomedial nuclei were successfully visualised using the first hemispherical brain PET. TRIAL REGISTRATION  : Japan Registry of Clinical Trials, jRCTs032210086, Registered 13 May 2021, https://jrct.niph.go.jp/latest-detail/jRCTs032210086 .

Feasibility of triple gamma ray imaging of10C for range verification in ion therapy.

Objective.In carbon ion therapy, the visualization of the range of incident particles in a patient body is important for treatment verification. In-beam positron emission tomography (PET) imaging is one of the methods to verify the treatment in ion therapy due to the high quality of PET images. We have shown the feasibility of in-beam PET imaging of radioactive15O and11C ion beams for range verification using our OpenPET system. Recently, we developed a whole gamma imager (WGI) that can simultaneously work as PET, single gamma ray and triple gamma ray imaging. The WGI has high potential to detect the location of10C, which emits positrons with a simultaneous gamma ray of 718 keV, within the patient's body during ion therapy.Approach.In this work, we focus on investigating the performance of WGI for10C imaging and its feasibility for range verification in carbon ion therapy. First, the performance of the WGI was studied to image a10C point source using the Geant4 toolkit. Then, the feasibility of WGI was investigated for an irradiated polymethyl methacrylate (PMMA) phantom with a10C ion beam at the carbon therapy facility of the Heavy Ion Medical Accelerator in Chiba.Main results.The average spatial resolution and sensitivity for the simulated10C point source at the centre of the field of view were 5.5 mm FWHM and 0.010%, respectively. The depth dose of the10C ion beam was measured, and the triple gamma image of10C nuclides for an irradiated PMMA phantom was obtained by applying a simple back projection to the detected triple gammas.Significance.The shift between Bragg peak position and position of the peak of the triple gamma image in an irradiated PMMA phantom was 2.8 ± 0.8 mm, which demonstrates the capability of triple gamma imaging using WGI for range verification of10C ion beams.

Performance evaluation of VRAIN: a brain-dedicated PET with a hemispherical detector arrangement.

Objective.For PET imaging systems, a smaller detector ring enables less intrinsic spatial resolution loss due to the photon non-collinearity effect as well as better balance between production cost and sensitivity, and a hemispherical detector arrangement is more appropriate for brain imaging than a conventional cylindrical arrangement. Therefore, we have developed a brain-dedicated PET system with a hemispherical detector arrangement, which has been commercialized in Japan under the product name of VRAINTM. In this study, we evaluated imaging performance of VRAIN.Approach.The VRAIN used 54 detectors to form the main hemispherical unit and an additional half-ring behind the neck. Each detector was composed of a 12 × 12 array of lutetium fine silicate crystals (4.1 × 4.1 × 10 mm3) and a 12 × 12 array of silicon photomultipliers (4 × 4 mm2active area) with the one-to-one coupling. We evaluated the physical performance of VRAIN according to the NEMA NU 2-2018 standards. Some measurements were modified so as to fit the hemispherical geometry. In addition, we performed18F-FDG imaging in a healthy volunteer.Main results.In the phantom study, the VRAIN showed high resolution for separating 2.2 mm rods, 229 ps TOF resolution and 19% scatter fraction. With the TOF gain for a 20 cm diameter object (an assumed head diameter), the peak noise-equivalent count rate was 144 kcps at 9.8 kBq ml-1and the sensitivity was 25 kcps MBq-1. Overall, the VRAIN provided excellent image quality in phantom and human studies. In the human FDG images, small brain nuclei and gray matter structures were clearly visualized with high contrast and low noise.Significance.We demonstrated the excellent imaging performance of VRAIN, which supported the advantages of the hemispherical detector arrangement.

An inception network for positron emission tomography based dose estimation in carbon ion therapy.

Objective. We aim to evaluate a method for estimating 1D physical dose deposition profiles in carbon ion therapy via analysis of dynamic PET images using a deep residual learning convolutional neural network (CNN). The method is validated using Monte Carlo simulations of12C ion spread-out Bragg peak (SOBP) profiles, and demonstrated with an experimental PET image.Approach. A set of dose deposition and positron annihilation profiles for monoenergetic12C ion pencil beams in PMMA are first generated using Monte Carlo simulations. From these, a set of random polyenergetic dose and positron annihilation profiles are synthesised and used to train the CNN. Performance is evaluated by generating a second set of simulated12C ion SOBP profiles (one 116 mm SOBP profile and ten 60 mm SOBP profiles), and using the trained neural network to estimate the dose profile deposited by each beam and the position of the distal edge of the SOBP. Next, the same methods are used to evaluate the network using an experimental PET image, obtained after irradiating a PMMA phantom with a12C ion beam at QST's Heavy Ion Medical Accelerator in Chiba facility in Chiba, Japan. The performance of the CNN is compared to that of a recently published iterative technique using the same simulated and experimental12C SOBP profiles.Main results. The CNN estimated the simulated dose profiles with a mean relative error (MRE) of 0.7% ± 1.0% and the distal edge position with an accuracy of 0.1 mm ± 0.2 mm, and estimate the dose delivered by the experimental12C ion beam with a MRE of 3.7%, and the distal edge with an accuracy of 1.7 mm.Significance. The CNN was able to produce estimates of the dose distribution with comparable or improved accuracy and computational efficiency compared to the iterative method and other similar PET-based direct dose quantification techniques.

Rice immediately adapts the dynamics of photosynthates translocation to roots in response to changes in soil water environment.

Rice is susceptible to abiotic stresses such as drought stress. To enhance drought resistance, elucidating the mechanisms by which rice plants adapt to intermittent drought stress that may occur in the field is an important requirement. Roots are directly exposed to changes in the soil water condition, and their responses to these environmental changes are driven by photosynthates. To visualize the distribution of photosynthates in the root system of rice plants under drought stress and recovery from drought stress, we combined X-ray computed tomography (CT) with open type positron emission tomography (OpenPET) and positron-emitting tracer imaging system (PETIS) with 11C tracer. The short half-life of 11C (20.39 min) allowed us to perform multiple experiments using the same plant, and thus photosynthate translocation was visualized as the same plant was subjected to drought stress and then re-irrigation for recovery. The results revealed that when soil is drier, 11C-photosynthates mainly translocated to the seminal roots, likely to promote elongation of the root with the aim of accessing water stored in the lower soil layers. The photosynthates translocation to seminal roots immediately stopped after rewatering then increased significantly in crown roots. We suggest that when rice plant experiencing drought is re-irrigated from the bottom of pot, the destination of 11C-photosynthates translocation immediately switches from seminal root to crown roots. We reveal that rice roots are responsive to changes in soil water conditions and that rice plants differentially adapts the dynamics of photosynthates translocation to crown roots and seminal roots depending on soil conditions.

Initial results of a mouse brain PET insert with a staggered 3-layer DOI detector.

Objective.Small animal positron emission tomography (PET) requires a submillimeter resolution for better quantification of radiopharmaceuticals. On the other hand, depth-of-interaction (DOI) information is essential to preserve the spatial resolution while maintaining the sensitivity. Recently, we developed a staggered 3-layer DOI detector with 1 mm crystal pitch and 15 mm total crystal thickness, but we did not demonstrate the imaging performance of the DOI detector with full ring geometry. In this study we present initial imaging results obtained for a mouse brain PET prototype developed with the staggered 3-layer DOI detector.Approach.The prototype had 53 mm inner diameter and 11 mm axial field-of-view. The PET scanner consisted of 16 DOI detectors each of which had a staggered 3-layer LYSO crystal array (4/4/7 mm) coupled to a 4 × 4 silicon photomultiplier array. The physical performance was evaluated in terms of the NEMA NU 4 2008 protocol.Main Results.The measured spatial resolutions at the center and 15 mm radial offset were 0.67 mm and 1.56 mm for filtered-back-projection, respectively. The peak absolute sensitivity of 0.74% was obtained with an energy window of 400-600 keV. The resolution phantom imaging results show the clear identification of a submillimetric rod pattern with the ordered-subset expectation maximization algorithm. The inter-crystal scatter rejection using a narrow energy window could enhance the resolvability of a 0.75 mm rod significantly.Significance.In an animal imaging experiment, the detailed mouse brain structures such as cortex and thalamus were clearly identified with high contrast. In conclusion, we successfully developed the mouse brain PET insert prototype with a staggered 3-layer DOI detector.

First imaging demonstration of a crosshair light-sharing PET detector.

The crosshair light-sharing (CLS) PET detector is our original depth-of-interaction (DOI) detector, which is based on a single-ended readout scheme with quadrisected crystals comparable in size to a photo-sensor. In this work, we developed 32 CLS PET detectors, each of which consisted of a multi-pixel photon counter (MPPC) array and gadolinium fine aluminum garnet (GFAG) crystals, and we developed a benchtop prototype of a small animal size PET. Each GFAG crystal was 1.45 × 1.45 × 15 mm3. The MPPC had a surface area of 3.0 × 3.0 mm2. The benchtop prototype had two detector rings of 16 detector blocks. The ring diameter and axial field-of-view were 14.2 cm and 4.9 cm, respectively. The data acquisition system used was the PETsys silicon photomultiplier readout system. The continuous DOI information was binned into three DOI layers by applying a look-up-table to a 2D position histogram. Also, energy and timing information was corrected using DOI information. After the calibration procedure, the energy resolution and the coincidence time resolution were 14.6% and 531 ps, respectively. Imaging test results of a small rod phantom obtained by an iterative reconstruction method showed clear separation of 1.6 mm rods with the help of DOI information.

Design consideration of compact cardiac TOF-PET systems: a simulation study.

Myocardial perfusion imaging (MPI) with PET plays a vital role in the management of coronary artery disease. High sensitivity systems can contribute to maximizing the potential value of PET MPI; therefore, we have proposed two novel detector arrangements, an elliptical geometry and a D-shape geometry, that are more sensitive and more compact than a conventional large-bore cylindrical geometry. Here we investigate two items: the benefits of the proposed geometries for cardiac imaging; and the effects of scatter components on cardiac PET image quality. Using the Geant4 toolkit, we modeled four time-of-flight (TOF) PET systems: an 80 cm diameter cylinder, a 40 cm diameter cylinder, a compact ellipse, and a compact D-shape. Spatial resolution and sensitivity were measured using point sources. Noise equivalent count rate and image quality were examined using an anthropomorphic digital chest phantom. The proposed geometries showed higher sensitivity and better count rate characteristics with a fewer number of detectors than the conventional large-bore cylindrical geometry. In addition, we found that the increased intensity of the scatter components was a big factor affecting the contrast in defect regions for such a compact geometry. It is important to address the issue of the increased intensity of the scatter components to develop a high-performance compact cardiac TOF PET system.