Deep denoiser prior driven relaxed iterated Tikhonov method for low-count PET image restoration.

Objective. Low-count positron emission tomography (PET) imaging is an efficient way to promote more widespread use of PET because of its short scan time and low injected activity. However, this often leads to low-quality PET images with clinical image reconstruction, due to high noise and blurring effects. Existing PET image restoration (IR) methods hinder their own restoration performance due to the semi-convergence property and the lack of suitable denoiser prior.Approach. To overcome these limitations, we propose a novel deep plug-and-play IR method called Deep denoiser Prior driven Relaxed Iterated Tikhonov method (DP-RI-Tikhonov). Specifically, we train a deep convolutional neural network denoiser to generate a flexible deep denoiser prior to handle high noise. Then, we plug the deep denoiser prior as a modular part into a novel iterative optimization algorithm to handle blurring effects and propose an adaptive parameter selection strategy for the iterative optimization algorithm.Main results. Simulation results show that the deep denoiser prior plays the role of reducing noise intensity, while the novel iterative optimization algorithm and adaptive parameter selection strategy can effectively eliminate the semi-convergence property. They enable DP-RI-Tikhonov to achieve an average quantitative result (normalized root mean square error, structural similarity) of (0.1364, 0.9574) at the stopping iteration, outperforming a conventional PET IR method with an average quantitative result of (0.1533, 0.9523) and a state-of-the-art deep plug-and-play IR method with an average quantitative result of (0.1404, 0.9554). Moreover, the advantage of DP-RI-Tikhonov becomes more obvious at the last iteration. Experiments on six clinical whole-body PET images further indicate that DP-RI-Tikhonov successfully reduces noise intensity and recovers fine details, recovering sharper and more uniform images than the comparison methods.Significance. DP-RI-Tikhonov's ability to reduce noise intensity and effectively eliminate the semi-convergence property overcomes the limitations of existing methods. This advancement may have substantial implications for other medical IR.

Development and evaluation of a new high-TOF-resolution all-digital brain PET system.

Objective.Time-of-flight (TOF) capability and high sensitivity are essential for brain-dedicated positron emission tomography (PET) imaging, as they improve the contrast and the signal-to-noise ratio (SNR) enabling a precise localization of functional mechanisms in the different brain regions.Approach.We present a new brain PET system with transverse and axial field-of-view (FOV) of 320 mm and 255 mm, respectively. The system head is an array of 6 × 6 detection elements, each consisting of a 3.9 × 3.9 × 20 mm3lutetium-yttrium oxyorthosilicate crystal coupled with a 3.93 × 3.93 mm2SiPM. The SiPMs analog signals are individually digitized using the multi-voltage threshold (MVT) technology, employing a 1:1:1 coupling configuration.Main results.The brain PET system exhibits a TOF resolution of 249 ps at 5.3 kBq ml-1, an average sensitivity of 22.1 cps kBq-1, and a noise equivalent count rate (NECR) peak of 150.9 kcps at 8.36 kBq ml-1. Furthermore, the mini-Derenzo phantom study demonstrated the system's ability to distinguish rods with a diameter of 2.0 mm. Moreover, incorporating the TOF reconstruction algorithm in an image quality phantom study optimizes the background variability, resulting in reductions ranging from 44% (37 mm) to 75% (10 mm) with comparable contrast. In the human brain imaging study, the SNR improved by a factor of 1.7 with the inclusion of TOF, increasing from 27.07 to 46.05. Time-dynamic human brain imaging was performed, showing the distinctive traits of cortex and thalamus uptake, as well as of the arterial and venous flow with 2 s per time frame.Significance.The system exhibited a good TOF capability, which is coupled with the high sensitivity and count rate performance based on the MVT digital sampling technique. The developed TOF-enabled brain PET system opens the possibility of precise kinetic brain PET imaging, towards new quantitative predictive brain diagnostics.

Kinetically Consistent Data Assimilation for Plant PET Sparse Time Activity Curve Signals.

Time activity curve (TAC) signal processing in plant positron emission tomography (PET) is a frontier nuclear science technique to bring out the quantitative fluid dynamic (FD) flow parameters of the plant vascular system and generate knowledge on crops and their sustainable management, facing the accelerating global climate change. The sparse space-time sampling of the TAC signal impairs the extraction of the FD variables, which can be determined only as averaged values with existing techniques. A data-driven approach based on a reliable FD model has never been formulated. A novel sparse data assimilation digital signal processing method is proposed, with the unique capability of a direct computation of the dynamic evolution of noise correlations between estimated and measured variables, by taking into explicit account the numerical diffusion due to the sparse sampling. The sequential time-stepping procedure estimates the spatial profile of the velocity, the diffusion coefficient and the compartmental exchange rates along the plant stem from the TAC signals. To illustrate the performance of the method, we report an example of the measurement of transport mechanisms in zucchini sprouts.

Metabolomics of blood reveals age-dependent pathways in Parkinson's Disease.

BACKGROUND: Parkinson's Disease (PD) is the second most frequent degenerative disorder, the risk of which increases with age. A preclinical PD diagnostic test does not exist. We identify PD blood metabolites and metabolic pathways significantly correlated with age to develop personalized age-dependent PD blood biomarkers. RESULTS: We found 33 metabolites producing a receiver operating characteristic (ROC) area under the curve (AUC) value of 97%. PCA revealed that they belong to three pathways with distinct age-dependent behavior: glycine, threonine and serine metabolism correlates with age only in PD patients; unsaturated fatty acids biosynthesis correlates with age only in a healthy control group; and, finally, tryptophan metabolism characterizes PD but does not correlate with age. CONCLUSIONS: The targeted analysis of the blood metabolome proposed in this paper allowed to find specific age-related metabolites and metabolic pathways. The model offers a promising set of blood biomarkers for a personalized age-dependent approach to the early PD diagnosis.

Correlation of [18F]florbetaben textural features and age of onset of Alzheimer's disease: a principal components analysis approach.

BACKGROUND: When Alzheimer's disease (AD) is occurring at an early onset before 65 years old, its clinical course is generally more aggressive than in the case of a late onset. We aim at identifying [[Formula: see text]F]florbetaben PET biomarkers sensitive to differences between early-onset Alzheimer's disease (EOAD) and late-onset Alzheimer's disease (LOAD). We conducted [[Formula: see text]F]florbetaben PET/CT scans of 43 newly diagnosed AD subjects. We calculated 93 textural parameters for each of the 83 Hammers areas. We identified 41 independent principal components for each brain region, and we studied their Spearman correlation with the age of AD onset, by taking into account multiple comparison corrections. Finally, we calculated the probability that EOAD and LOAD patients have different amyloid-[Formula: see text] ([Formula: see text]) deposition by comparing the mean and the variance of the significant principal components obtained in the two groups with a 2-tailed Student's t-test. RESULTS: We found that four principal components exhibit a significant correlation at a 95% confidence level with the age of onset in the left lateral part of the anterior temporal lobe, the right anterior orbital gyrus of the frontal lobe, the right lateral orbital gyrus of the frontal lobe and the left anterior part of the superior temporal gyrus. The data are consistent with the hypothesis that EOAD patients have a significantly different [[Formula: see text]F]florbetaben uptake than LOAD patients in those four brain regions. CONCLUSIONS: Early-onset AD implies a very irregular pattern of [Formula: see text] deposition. The authors suggest that the identified textural features can be used as quantitative biomarkers for the diagnosis and characterization of EOAD patients.

Effect of Increased IL-1ß on Expression of HK in Alzheimer's Disease.

Alzheimer's disease (AD) is a neurodegenerative disease characterized by decreased glucose metabolism and increased neuroinflammation. Hexokinase (HK) is the key enzyme of glucose metabolism and is associated with mitochondria to exert its function. Recent studies have demonstrated that the dissociation of HK from mitochondria is enough to activate the NOD-like receptor protein 3 (NLRP3) inflammasome and leads to the release of interleukin-1ß (IL-1ß). However, the effect of increased IL-1ß on the expression of HK is still unclear in AD. In this paper, we used positron emission tomography (PET), Western blotting and immunofluorescence to study the glucose metabolism, and the expression and distribution of HK in AD. Furthermore, we used lipopolysaccharide (LPS), nigericin (Nig), CY-09 and lonidamine (LND) to treat N2a and N2a-sw cells to investigate the link between IL-1ß and HK in AD. The results show decreased expression of HK and the dissociation of HK from mitochondria in AD. Furthermore, a reduction of the expression of IL-1ß could increase the expression of HK in AD. These results suggest that inhibiting inflammation may help to restore glucose metabolism in AD.

Design Study of a Novel Positron Emission Tomography System for Plant Imaging.

Positron Emission Tomography is a non-disruptive and high-sensitive digital imaging technique which allows to measure in-vivo and non invasively the changes of metabolic and transport mechanisms in plants. When it comes to the early assessment of stress-induced alterations of plant functions, plant PET has the potential of a major breakthrough. The development of dedicated plant PET systems faces a series of technological and experimental difficulties, which make conventional clinical and preclinical PET systems not fully suitable to agronomy. First, the functional and metabolic mechanisms of plants depend on environmental conditions, which can be controlled during the experiment if the scanner is transported into the growing chamber. Second, plants need to be imaged vertically, thus requiring a proper Field Of View. Third, the transverse Field of View needs to adapt to the different plant shapes, according to the species and the experimental protocols. In this paper, we perform a simulation study, proposing a novel design of dedicated plant PET scanners specifically conceived to address these agronomic issues. We estimate their expected sensitivity, count rate performance and spatial resolution, and we identify these specific features, which need to be investigated when realizing a plant PET scanner. Finally, we propose a novel approach to the measurement and verification of the performance of plant PET systems, including the design of dedicated plant phantoms, in order to provide a standard evaluation procedure for this emerging digital imaging agronomic technology.

Does Chronic Sleep Fragmentation Lead to Alzheimer's Disease in Young Wild-Type Mice?

Chronic sleep insufficiency is becoming a common issue in the young population nowadays, mostly due to life habits and work stress. Studies in animal models of neurological diseases reported that it would accelerate neurodegeneration progression and exacerbate interstitial metabolic waste accumulation in the brain. In this paper, we study whether chronic sleep insufficiency leads to neurodegenerative diseases in young wild-type animals without a genetic pre-disposition. To this aim, we modeled chronic sleep fragmentation (SF) in young wild-type mice. We detected pathological hyperphosphorylated-tau (Ser396/Tau5) and gliosis in the SF hippocampus. 18F-labeled fluorodeoxyglucose positron emission tomography scan (18F-FDG-PET) further revealed a significant increase in brain glucose metabolism, especially in the hypothalamus, hippocampus and amygdala. Hippocampal RNAseq indicated that immunological and inflammatory pathways were significantly altered in 1.5-month SF mice. More interestingly, differential expression gene lists from stress mouse models showed differential expression patterns between 1.5-month SF and control mice, while Alzheimer's disease, normal aging, and APOEε4 mutation mouse models did not exhibit any significant pattern. In summary, 1.5-month sleep fragmentation could generate AD-like pathological changes including tauopathy and gliosis, mainly linked to stress, as the incremented glucose metabolism observed with PET imaging suggested. Further investigation will show whether SF could eventually lead to chronic neurodegeneration if the stress condition is prolonged in time.

Evaluation of image quality with four positron emitters and three preclinical PET/CT systems.

BACKGROUND: We investigated the image quality of 11C, 68Ga, 18F and 89Zr, which have different positron fractions, physical half-lifes and positron ranges. Three small animal positron emission tomography/computed tomography (PET/CT) systems were used in the evaluation, including the Siemens Inveon, RAYCAN X5 and Molecubes ß-cube. The evaluation was performed on a single scanner level using the national electrical manufacturers association (NEMA) image quality phantom and analysis protocol. Acquisitions were performed with the standard NEMA protocol for 18F and using a radionuclide-specific acquisition time for 11C, 68Ga and 89Zr. Images were assessed using percent recovery coefficient (%RC), percentage standard deviation (%STD), image uniformity (%SD), spill-over ratio (SOR) and evaluation of image quantification. RESULTS: 68Ga had the lowest %RC (< 62%) across all systems. 18F had the highest maximum %RC (> 85%) and lowest %STD for the 5 mm rod across all systems. For 11C and 89Zr, the maximum %RC was close (> 76%) to the %RC with 18F. A larger SOR were measured in water with 11C and 68Ga compared to 18F on all systems. SOR in air reflected image reconstruction and data correction performance. Large variation in image quantification was observed, with maximal errors of 22.73% (89Zr, Inveon), 17.54% (89Zr, RAYCAN) and - 14.87% (68Ga, Molecubes). CONCLUSIONS: The systems performed most optimal in terms of NEMA image quality parameters when using 18F, where 11C and 89Zr performed slightly worse than 18F. The performance was least optimal when using 68Ga, due to large positron range. The large quantification differences prompt optimization not only by terms of image quality but also quantification. Further investigation should be performed to find an appropriate calibration and harmonization protocol and the evaluation should be conducted on a multi-scanner and multi-center level.

Past and Future of Plant Stress Detection: An Overview From Remote Sensing to Positron Emission Tomography.

Plant stress detection is considered one of the most critical areas for the improvement of crop yield in the compelling worldwide scenario, dictated by both the climate change and the geopolitical consequences of the Covid-19 epidemics. A complicated interconnection of biotic and abiotic stressors affect plant growth, including water, salt, temperature, light exposure, nutrients availability, agrochemicals, air and soil pollutants, pests and diseases. In facing this extended panorama, the technology choice is manifold. On the one hand, quantitative methods, such as metabolomics, provide very sensitive indicators of most of the stressors, with the drawback of a disruptive approach, which prevents follow up and dynamical studies. On the other hand qualitative methods, such as fluorescence, thermography and VIS/NIR reflectance, provide a non-disruptive view of the action of the stressors in plants, even across large fields, with the drawback of a poor accuracy. When looking at the spatial scale, the effect of stress may imply modifications from DNA level (nanometers) up to cell (micrometers), full plant (millimeters to meters), and entire field (kilometers). While quantitative techniques are sensitive to the smallest scales, only qualitative approaches can be used for the larger ones. Emerging technologies from nuclear and medical physics, such as computed tomography, magnetic resonance imaging and positron emission tomography, are expected to bridge the gap of quantitative non-disruptive morphologic and functional measurements at larger scale. In this review we analyze the landscape of the different technologies nowadays available, showing the benefits of each approach in plant stress detection, with a particular focus on the gaps, which will be filled in the nearby future by the emerging nuclear physics approaches to agriculture.

[18F] FBB cortical uptake is not related to the age of onset of Alzheimer's disease.

AIM: To investigate the relationships between amyloid burden in brain and the age of onset of Alzheimer's disease. MATERIALS AND METHODS: We examined 60 patients with clinical diagnosis of Alzheimer's disease. Of them, 22 were early-onset of Alzheimer's disease and 38 were late-onset of Alzheimer's disease. All of them underwent a brain PET scan 90 minutes after the injection of 4-[(E)-2-[4-[2-[2-(2-fluoranylethoxy)ethoxy]ethoxy]phenyl]ethenyl]-N-methylaniline ([F] FBB); 300 ± 10 MBq). Relationships between amyloid burden in brain and age of onset of Alzheimer's disease were assessed by means of statistical parametric mapping version 12. RESULTS: There were no significant differences [F] FBB uptake between early-onset of Alzheimer's disease and late-onset of Alzheimer's disease patients. CONCLUSION: In our study group, the age of onset is not related to brain amyloid burden in Alzheimer's disease patients.

New Digital Plug and Imaging Sensor for a Proton Therapy Monitoring System Based on Positron Emission Tomography.

One of the most challenging areas of sensor development for nuclear medicine is the design of proton therapy monitoring systems. Sensors are operated in a high detection rate regime in beam-on conditions. We realized a prototype of a monitoring system for proton therapy based on the technique of positron emission tomography. We used the Plug and Imaging (P&I) technology in this application. This sensing system includes LYSO/silicon photomultiplier (SiPM) detection elements, fast digital multi voltage threshold (MVT) readout electronics and dedicated image reconstruction algorithms. In this paper, we show that the P&I sensor system has a uniform response and is controllable in the experimental conditions of the proton therapy room. The prototype of PET monitoring device based on the P&I sensor system has an intrinsic experimental spatial resolution of approximately 3 mm (FWHM), obtained operating the prototype both during the beam irradiation and right after it. The count-rate performance of the P&I sensor approaches 5 Mcps and allows the collection of relevant statistics for the nuclide analysis. The measurement of both the half life and the relative abundance of the positron emitters generated in the target volume through irradiation of 10 10 protons in approximately 15 s is performed with 0.5% and 5 % accuracy, respectively.

Application of CMOS Technology to Silicon Photomultiplier Sensors.

We use the 180 nm GLOBALFOUNDRIES (GF) BCDLite CMOS process for the production of a silicon photomultiplier prototype. We study the main characteristics of the developed sensor in comparison with commercial SiPMs obtained in custom technologies and other SiPMs developed with CMOS-compatible processes. We support our discussion with a transient modeling of the detection process of the silicon photomultiplier as well as with a series of static and dynamic experimental measurements in dark and illuminated environments.