Time Resolution Research Articles

Xylem sap residue in cut-open conduits can affect gas discharge in pneumatic experiments.

Considerable attention has been paid to address methodological concerns related to measurements of embolism in conduits of angiosperm xylem. A fast, easy, and cheap method is based on gas extraction measurements from dehydrating samples to obtain pneumatic vulnerability curves (VCs). Here, we tested the assumption that cutting open conduits leads to gas-filled lumina when these are cut in air at fairly high water potentials, which is required to detect embolism in intact conduits. We performed VCs with the Pneumatron for 12 angiosperm species, and extracted sap from cut-open vessels in branches of nine species under early stages of branch dehydration. The optical method was applied to Citrus plants as an alternative reference method to estimate embolism resistance. We found an increase in gas discharge during early stages of dehydration, which affected the pneumatic VCs for most of the species studied. Xylem sap residue was not absorbed immediately by surrounding tissue in cut-open conduits in six of the nine species, but gradually disappeared over time during progressive dehydration. The amount of gas discharged increased until all residual sap was absorbed, and was not related to embolism. We conclude that residual xylem sap in cut-open conduits affects early stages of pneumatic VCs, and represents a novel artefact that can easily be corrected for. Yet, it remains unclear why exactly the air-water meniscus in cut-open conduits did not fully withdraw to the conduit end wall in most species. By analysing the slope of VCs over time, we could improve estimations of embolism resistance, as evidenced by a strong agreement between the pneumatic and the optical methods. Since residual sap in cut-open conduits of some species could slightly underestimate embolism resistance, we propose to apply a correction for this artefact based on the high time resolution measurements taken with a Pneumatron.

Eye Tracking Based on Event Camera and Spiking Neural Network

An event camera generates an event stream based on changes in brightness, retaining only the characteristics of moving objects, and addresses the high power consumption associated with using high-frame-rate cameras for high-speed eye-tracking tasks. However, the asynchronous incremental nature of event camera output has not been fully utilized, and there are also issues related to missing event datasets. Combining the temporal information encoding and state-preserving properties of a spiking neural network (SNN) with an event camera, a near-range eye-tracking algorithm is proposed as well as a novel event-based dataset for validation and evaluation. According to experimental results, the proposed solution outperforms artificial neural network (ANN) algorithms, while computational time remains only 12.5% of that of traditional SNN algorithms. Furthermore, the proposed algorithm allows for self-adjustment of time resolution, with a maximum achievable resolution of 0.081 ms, enhancing tracking stability while maintaining accuracy.

Efficient, nonparametric removal of noise and recovery of probability distributions from time series using nonlinear-correlation functions: Photon and photon-counting noise.

A preceding paper [M. Dhar, J. A. Dickinson, and M. A. Berg, J. Chem. Phys. 159, 054110 (2023)] shows how to remove additive noise from an experimental time series, allowing both the equilibrium distribution of the system and its Green's function to be recovered. The approach is based on nonlinear-correlation functions and is fully nonparametric: no initial model of the system or of the noise is needed. However, single-molecule spectroscopy often produces time series with either photon or photon-counting noise. Unlike additive noise, photon noise is signal-size correlated and quantized. Photon counting adds the potential for bias. This paper extends noise-corrected-correlation methods to these cases and tests them on synthetic datasets. Neither signal-size correlation nor quantization is a significant complication. Analysis of the sampling error yields guidelines for the data quality needed to recover the properties of a system with a given complexity. We show that bias in photon-counting data can be corrected, even at the high count rates needed to optimize the time resolution. Using all these results, we discuss the factors that limit the time resolution of single-molecule spectroscopy and the conditions that would be needed to push measurements into the submicrosecond region.

Design and characterization of a hybrid PET detector with DOI capability.

Monolithic or semi-monolithic detectors are attractive for positron emission tomography (PET) scanners with depth-of-interaction (DOI) capability. However, they often require complicated calibrations to determine the interaction positions of gamma photons. We introduce a novel hybrid detector design that combines pixelated and semi-monolithic elements to achieve DOI capability while simplifying the calibrations for positioning. A prototype detector with eight hybrid lutetium-yttrium oxyorthosilicate (LYSO)layers having dimensions of 25.8×12.9×15mm3 was constructed. The energy-weighted and energy-squared weighted averages were used for estimating the x- (pixelated direction) and y-positions (non-pixelated direction). Pseudo-pixels were defined as discrete areas on the flood image based on the crystal look-up table (LUT). The intrinsic spatial resolutions in the pixelated and non-pixelated directions were measured. The ratio of the maximum to the sum of the multipixel photon counter (MPPC) signals was used to estimate the DOI positions. The coincidence timing resolution (CTR) was measured using the average and energy-weighted average of the earliest n time stamps. Two energy windows of 250-700 and 400-600keV were applied for the measurements. The pattern of the flood images showed discrete event clusters, demonstrating that simple calibrations for determining the x- and y-positions of events could be achieved. Under 400-600keV energy window, the average intrinsic spatial resolutions were 1.15 and 1.34mm for the pixelated and non-pixelated directions; the average DOI resolution of the second row of pseudo-pixels was 5.1mm in full width at half maximum (FWHM); when using the energy-weighted average of the earliest four-time stamps, the best CTR of 350ps was achieved. Applying a broader energy window of 250-700keV only slightly degrades the DOI resolution while maintaining the intrinsic resolution; the best CTR degrades to 410ps. The proposed hybrid detector concept was verified, and a prototype detector showed high performance for 3D positioning and timing resolution. The novel detector concept shows promise for preclinical and clinical PET scanners with DOI capability.

Insights into the nucleation and growth of BiOCl nanoparticles by in situ X-ray pair distribution function analysis and in situ liquid cell TEM.

The synthesis of bismuth oxyhalides as defined nanostructures is hindered by their fast nucleation and growth in aqueous solutions. Using our recently developed single-source precursor, the formation of bismuth oxychloride in such solutions can be slowed significantly. As reported herein, this advance enables BiOCl formation to be investigated by in situ X-ray total scattering and in situ liquid cell transmission electron microscopy. In situ pair distribution function analysis of X-ray total scattering data reveals the local order of atomic structures throughout the synthesis, while in situ liquid cell transmission electron microscopy allows for tracking the growth of individual nanoparticles. Through this work, the precursor complex is shown to give rise to BiOCl upon heating in solution without the observation of structurally distinct intermediates. The emerging nanoparticles have a widened interlayer spacing, which moderately decreases as the particles grow. Mechanistic insights into the formation of bismuth oxyhalide nanoparticles, including the absence of distinct intermediates within the available time resolution, will help facilitate future design of controlled BiOX nanostructures.

Modeling of a “Hydrogen Valley” to investigate the impact of a regional pipeline for hydrogen supply

Introduction: The transition towards electrolysis-produced hydrogen in refineries and chemical industries is expected to have a potent impact on the local energy system of which these industries are part. In this study, three urban areas with hydrogen-intense industries are studied regarding how the energy system configuration is affected if the expected future hydrogen demand is met in each node individually, as compared to forming a “Hydrogen Valley,” in which a pipeline can be used to trade hydrogen between the nodes.Method: A technoeconomic, mixed-integer, linear optimization model is used to study the investments in and dispatch of the included technologies with an hourly time resolution, while minimizing the total system cost. Four cases are investigated based on the availability of offshore wind power and the possibility to invest in a pipeline.Results: The results show that investments in a pipeline reduces by 4%–7% the total system cost of meeting the demands for electricity, heating, and hydrogen in the cases investigated. Furthermore, investments in a pipeline result in greater utilization of local variable renewable electricity resources, as compared to the cases without the possibility to invest in a pipeline.Discussion: The different characteristics of the local energy systems of the three nodes in local availability of variable renewable electricity, grid capacity and available storage options compared to local demands of electricity, heating and hydrogen, are found to be the driving forces for forming a Hydrogen Valley.

Development and validation of the RP-HPLC method for quantification of tavaborole.

The stability-indicating approach for tavaborole quantification was developed and validated to establish a precise, linear, accurate, and robust HPLC method. The development section includes optimizing the detection wavelength, the mobile phase ratio, and the type of column used to achieve the best possible separation and sensitivity for analysis. The chromatographic conditions were established, considering peak symmetry, resolution, and retention time. The mobile phase composition, comprising a buffer: acetonitrile (75 : 25, %v/v), with an injection volume of 15 μL, showed suitable elution and recovery at 265 nm. A constant column oven temperature of 35 °C and a 1 mL min-1 flow rate were maintained. The pH of the buffer was changed to 3.0 by using orthophosphoric acid. Linearity was observed from 5 to 1000 ppm (r2 = 1.00000). The capacity (retention) factor (k) of 3.43 was observed, indicating significant interaction and good separation. Forced degradation (FD) or stress tests were performed for chemical and physical photolytic stress conditions, and the results observed were within the specified limits. The stability in the analytical solution was observed for up to 35 hours at 5 °C, confirming the stability of the solution. Validation of the developed HPLC method confirmed the system's suitability, precision, linearity, accuracy, FD, robustness, and results. All validation criteria for the technique were within acceptable limits.

Laser-Induced Stress-Driven Nanoplate Jumping Visualized by Ultrafast Electron Microscopy.

Understanding laser-induced jumping has attracted great interest in nanomaterial launching and transfer but requires a high spatiotemporal resolution visualization. Here, we report a jumping dynamics of nanoplate driven by ultrafast laser-induced stress using time-resolved transmission electron microscopy. Single-shot imaging reveals a nondestructive launching of gold nanoplates in several nanoseconds after the pulsed femtosecond laser excitation. The temperature rise and acoustic vibration, derived from ultrafast electron crystallography with a picosecond time resolution, confirm the existence of a laser-induced elastic stress wave. The generation, propagation, and reflection of thermal stress waves are further clarified by atomic simulation. The nonequilibrium ultrafast laser heating produces a compressive stress wave within several picoseconds, constrained by the supporting substrate under nanoplate to provide thrust force. This compressive stress is subsequently reflected into tensile stress by the substrate, promoting the nanoplate to jump off the substrate. Furthermore, the uneven interface adhesion results in the jumping flip of nanoplates, as well as, diminished their jumping speed. This study unveils the jumping regime driven by impulsive laser-excited stress and offers understanding of light-matter interaction.

Investigation of intra-fractionated range guided adaptive proton therapy: I. On-line PET imaging and range measurement

Objective. Develop a prototype on-line positron emission tomography (PET) scanner and evaluate its capability of on-line imaging and intra-fractionated proton-induced radioactivity range measurement. Approach. Each detector consists of 32 × 32 array of 2 × 2 × 30 mm3 Lutetium–Yttrium Oxyorthosilicate scintillators with single-scintillator-end readout through a 20 × 20 array of 3 × 3 mm2 Silicon Photomultipliers. The PET can be configurated with a full-ring of 20 detectors for conventional PET imaging or a partial-ring of 18 detectors for on-line imaging and range measurement. All detector-level readout and processing electronics are attached to the backside of the system gantry and their output signals are transferred to a field-programable-gate-array based system electronics and data acquisition that can be placed 2 m away from the gantry. The PET imaging performance and radioactivity range measurement capability were evaluated by both the offline study that placed a radioactive source with known intensity and distribution within a phantom and the online study that irradiated a phantom with proton beams under different radiation and imaging conditions. Main results. The PET has 32 cm diameter and 6.5 cm axial length field-of-view (FOV), ∼2.3–5.0 mm spatial resolution within FOV, 3% sensitivity at the FOV center, 18%–30% energy resolution, and ∼9 ns coincidence time resolution. The offline study shows the PET can determine the shift of distal falloff edge position of a known radioactivity distribution with the accuracy of 0.3 ± 0.3 mm even without attenuation and scatter corrections, and online study shows the PET can measure the shift of proton-induced positron radioactive range with the accuracy of 0.6 ± 0.3 mm from the data acquired with a short-acquisition (60 s) and low-dose (5 MU) proton radiation to a human head phantom. Significance. This study demonstrated the capability of intra-fractionated PET imaging and radioactivity range measurement and will enable the investigation on the feasibility of intra-fractionated, range-shift compensated adaptive proton therapy.

Using deep learning to integrate paleoclimate and global biogeochemistry over the Phanerozoic Eon

Abstract. Databases of 3D paleoclimate model simulations are increasingly used within global biogeochemical models for the Phanerozoic Eon. This improves the accuracy of the surface processes within the biogeochemical models, but the approach is limited by the availability of large numbers of paleoclimate simulations at different pCO2 levels and for different continental configurations. In this paper we apply the Frame Interpolation for Large Motion (FILM) deep learning method to a set of Phanerozoic paleoclimate model simulations to upscale their time resolution from one model run every ∼25 million years to one model run every 1 million years (Myr). Testing the method on a 5 Myr time-resolution set of continental configurations and paleoclimates confirms the accuracy of our approach when reconstructing intermediate frames from configurations separated by up to 40 Myr. We then apply the method to upscale the paleoclimate data structure in the SCION climate-biogeochemical model. The interpolated surface temperature and runoff are reasonable and present a logical progression between the original key frames. When updated to use the high-time-resolution climate data structure, the SCION model predicts climate shifts that were not present in the original model outputs due to its previous use of widely spaced datasets and simple linear interpolation. We conclude that a time resolution of ∼10 Myr in Phanerozoic paleoclimate simulations is likely sufficient for investigating the long-term carbon cycle and that deep learning methods may be critical in attaining this time resolution at reasonable computational expense, as well as for developing new fully continuous methods in which 3D continental processes are able to translate over a moving continental surface in deep time. However, the efficacy of deep learning methods in interpolating runoff data, compared to that of paleogeography and temperature, is diminished by the heterogeneous distribution of runoff. Consequently, interpolated climates must be confirmed by running a paleoclimate model if scientific conclusions are to be based directly on them.

DiffSim: a user-friendly tool for precise magmatic timescale determination and error propagation via major element diffusion chronometry in magmatic phases

Diffusion chronometry is a technique gaining interest in the scientific community related to volcanology and petrology; however, modelling can be challenging for non-expert users. Here, we present DiffSim, a user-friendly standalone freeware that allows users to calculate magmatic timescales simulating 1D diffusion of major elements in olivine, orthopyroxene, titanomagnetite, and melt (inclusions). The freeware works solving the Fick’s second law equation (for both Cartesian and spherical polar coordinates, depending on the phase) using finite differences through the Crank-Nicolson method. Users must specify the initial composition vs. distance profile, the time resolution, and the intensive conditions (such as temperature, pressure, and oxygen fugacity). For orthorhombic phases, such as olivine and orthopyroxene, users must also specify the plunge and the trend of the (001)-axis and the angle traverse of the 2D section being studied. The best-fitting profile, comparing the natural (measured) and the modelled (calculated) profiles, is obtained using the least-squares fitting method in accordance with the total time specified by the user for performing the diffusion modelling. To determine the uncertainties of the timescale calculation, DiffSim propagates errors based on the uncertainties associated with each intensive condition and the experimental diffusivity measurements. DiffSim is available as executable freeware, allowing researchers and students to use diffusion chronometry to elucidate information about crustal processes with ease and precision.

Holistic evaluation of a machine learning-based timing calibration for PET detectors under varying data sparsity.


Modern PET scanners offer precise TOF information, improving the SNR of the reconstructed images. Timing calibrations are performed to reduce the worsening effects of the system components and provide valuable TOF information. Traditional calibration procedures often provide static or linear corrections, with the drawback that higher-order skews or event-to-event corrections are not addressed. Novel research demonstrated significant improvements in the reachable timing resolutions when combining conventional calibration approaches with machine learning, with the disadvantage of extensive calibration times infeasible for a clinical application. In this work, we made the first steps towards an in-system application and analyzed the effects of varying data sparsity on a machine learning timing calibration, aiming to accelerate the calibration time. Furthermore, we demonstrated the versatility of our calibration concept by applying the procedure for the first time to analog readout technology.
Approach. 
We modified experimentally acquired calibration data used for training regarding their statistical and spatial sparsity, mimicking reduced measurement time and variability of the training data. Trained models were tested on unseen test data, characterized by fine spatial sampling and rich statistics. In total, 80 decision tree models with the same hyperparameter settings, were trained and holistically evaluated regarding data scientific, physics-based, and PET-based quality criteria. 
Main results.
The calibration procedure can be heavily reduced from several days to some minutes without sacrificing quality and still significantly improving the timing resolution from (304 ± 5) ps to (216 ± 1) ps compared to conventionally used analytical calibration methods. 
Significance. 
This work serves as the first step in making the developed machine learning-based calibration suitable for an in-system application to profit from the method's capabilities on the system level. Furthermore, this work demonstrates the functionality of the methodology on detectors using analog readout technology. The proposed holistic evaluation criteria here serve as a guideline for future evaluations of machine learning-based calibration approaches.&#xD.

Diabetic ketoacidosis resolution: From the traditional way to guideline-based management in the MICU at University Medical Center, Lubbock, Texas

Diabetes is a chronic, metabolic disease characterized by hyperglycemia which eventually can cause serious organ damage. The prevalence of diabetes has steadily increased over the past few decades, and approximately 1.4 million Americans are diagnosed with diabetes every year. Diabetes was the seventh leading cause of death in the United States in 2019. Diabetic ketoacidosis (DKA) is a serious complication of diabetes that can be life-threatening. It occurs more frequently in the patients with type 1 diabetes but can also develop in people with type 2 diabetes. It was determined that the average cost per DKA episode was $6,444, and that the annual cost of medical treatment in a diabetic patient with a prior episode of DKA was 2.67 times higher than a diabetic patient with no history of DKA. The criteria for DKA resolution at University Medical Center (UMC) in Lubbock, Texas, are different from current American Diabetes Association (ADA) guidelines. At UMC, a plasma bicarbonate ≥18 mEq/L, a venous pH > 7.3, and anion gap ≤12 mEq/L must be recorded twice (4 hours apart) before bridging to subcutaneous long-acting insulin administration. This time requirement could contribute to a longer time for DKA resolution and longer intensive care unit and hospital stays.Keywords: Diabetic ketoacidosis, DKA resolution

Linking Interfacial Structure and Electrochemical Behaviors of Batteries by High-Resolution Electrocapillarity.

The electrode-electrolyte interface governs the kinetics and reversibility of all electrochemical processes. While theoretical models can calculate and simulate the structure and associated properties of this intriguing component, their validation by direct experimental measurement has been a long-standing challenge. Electrocapillarity is a classical technique that derives the interfacial structure through potential-dependent surface tensions, but its limited resolution has confined its application to ideal systems such as extremely diluted aqueous electrolytes. In this work, we revive this technique with unprecedented time resolution, which allows fast and precise extraction of intrinsic interfacial structure and properties for a wide spectrum of electrolytes, be it ideal or nonideal, aqueous or nonaqueous, dilute or superconcentrated. For the very first time, this new electrocapillarity enables the measurements of a set of interfacial quantities, such as ion concentration distribution and potential drop across Helmholtz planes. Applying it on Zn-battery electrolytes, we discovered that Cl- specific adsorption at the inner-Helmholtz plane results in unexpected Zn2+ aggregation at the outer-Helmholtz plane, and identified such a unique interfacial structure as the fundamental driving force for fast Zn deposition/stripping kinetics and crystallographic texturing. The renaissance of electrocapillarity brings a new tool to the understanding and design of new electrolytes for future battery systems.

Nanoscale terahertz conductivity and ultrafast dynamics of terahertz plasmons in periodic arrays of epitaxial graphene nanoribbons

The dynamics of plasmons in nanoribbons of (hydrogen intercalated) quasi-freestanding single-layer graphene is studied by terahertz spectroscopy both in the steady state and upon photoexcitation by an ultrashort near infrared laser pulse. The use of two-dimensional frequency-domain analysis of the optical pump–terahertz (THz) probe signals allows us to determine the evolution of carrier temperature and plasmon characteristics with ∼100 fs time resolution. Namely, we find that the carrier temperature decreases from more than 5000 K to the lattice temperature within about 7 ps and that during this evolution the carrier mobility remains practically constant. The time-resolved THz conductivity spectra suggest that graphene nanoribbons contain defects which act as low potential barriers causing a weak localization of charges; the potential barriers are overcome upon photoexcitation. Furthermore, the edges of graphene nanoribbons are found to slightly enhance the scattering of carriers. The results are supported by complementary measurements using THz scanning near-field microscopy, which confirm a high uniformity of the THz conductivity across the sample and demonstrate high enough sensitivity to resolve even the impact of nanometric terrace steps on SiC substrate under the graphene monolayer. Published by the American Physical Society 2024

Deformation-induced CPT violation in entangled pairs of neutral kaons

In this paper we consider description of kaon-antikaon interference in the context of a theory with deformed CPT symmetry. In the case of such theoretical models, deviations from the standard CPT invariance is related to the momentum carried by the particles; in particular the rest masses of particles and antiparticles are equal. We find that the decay intensity of kaon-antikaon pair has three contributing terms: the correct-parity, the wrong-parity, and the interference between them, all of which are affected by deformation. Using the fact that the presence of such terms was not observed we estimate, under plausible assumptions, the magnitude of deformation parameter κ≳1017 GeV at the LHC energy. This limit can be possibly improved to values closer to the expected Planck mass scale κ≳1018 GeV using a next-generation collider with energy larger by an order of magnitude. This raises hopes that the effect, if it exists, could be detected in future accelerator experiments. Uncertainties of the energy measurement and time resolution are important for accuracy of these predictions. Published by the American Physical Society 2024

Capturing Catalyst Strain Dynamics during Operando CO Oxidation.

Understanding the strain dynamic behavior of catalysts is crucial for the development of cost-effective, efficient, stable, and long-lasting catalysts. Using time-resolved Bragg coherent diffraction imaging at the fourth generation Extremely Brilliant Source of the European Synchrotron (ESRF-EBS), we achieved subsecond time resolution during operando chemical reactions. Upon investigation of Pt nanoparticles during CO oxidation, the three-dimensional strain profile highlights significant changes in the surface and subsurface regions, where localized strain is probed along the [111] direction. Notably, a rapid increase in tensile strain was observed at the top and bottom Pt {111} facets during CO adsorption. Moreover, we detected oscillatory strain changes (6.4 s period) linked to CO adsorption during oxidation, where a time resolution of 0.25 s was achieved. This approach allows for the study of adsorption dynamics of catalytic nanomaterials at the single-particle level under operando conditions, which provides insight into nanoscale catalytic mechanisms.

Comparison of clinical characteristics and treatment outcomes between initially diagnosed type 1 and type 2 diabetes mellitus patients presenting with diabetic ketoacidosis

ObjectivePatients with type 1 diabetes (T1DM) and type 2 diabetes (T2DM) can present with diabetic ketoacidosis (DKA) as the first manifestation. Differentiating types of newly diagnosed diabetes could provide appropriate long-term management. Therefore, we conducted this study to compare clinical characteristics and outcomes between initially diagnosed type 1 and type 2 diabetes mellitus patients presenting with DKA.Materials and methodsA retrospective study was conducted on adult patients who presented with DKA as the first diagnosis of diabetes in our tertiary hospital between January 2005 and December 2019. Demographic data, precipitating causes, laboratory investigations, treatment, and outcomes were obtained by chart review. The primary outcome was to compare the clinical characteristics of initially diagnosed patients with T1DM and T2DM who presented with DKA.ResultsA total of 100 initially diagnosed diabetic patients who presented with DKA were analyzed (85 T2DM patients and 15 T1DM patients). Patients with T1DM were younger than patients with T2DM (mean age 33 ± 16.2 vs. 51 ± 14.5 years, p value < 0.001). Patients with T2DM had a higher body mass index, family history of diabetes, precipitating factors, plasma glucose, and lower renal function than those with T1DM. There was no difference in resolution time or DKA management between T1DM and T2DM patients. The overall mortality rate of DKA was 4%.ConclusionIn this population, most adult patients who presented with DKA had T2DM. Older age, obesity, a family history of diabetes, and the presence of precipitating factors were strong predictors of T2DM. We can implement the same clinical management for DKA in both T1DM and T2DM patients. However, T2DM patients had longer hospitalization than T1DM patients. After DKA resolution for 12 months, more than half of patients with T2DM could discontinue insulin. Therefore, the accurate classification of the type of diabetes leads to appropriate treatment.

High-quality ghost imaging based on undersampling natural order Hadamard source

Abstract Improving the imaging speed of ghost imaging is one of the main ways to leverage its advantages in sensitivity and imperfect spectral regions for practical applications. Due to the proportional relationship between image resolution and measurement times, when the image pixels are large, the measurement times also increase, making it difficult to achieve real-time imaging. Therefore, a high-quality ghost imaging method based on undersampling natural order Hadamard is proposed. This method utilizes the characteristics of the Hadamard matrix under undersampling conditions where image information can be fully obtained but overlaps, and utilizes deep learning to extract the aliasing information from the overlapping results to obtain the true original image information. We conducted numerical simulations and experimental tests on binary and grayscale objects under undersampling conditions, demonstrating the effectiveness and scalability of this method. This method can significantly reduce the number of measurements required for obtaining high-quality image information and promote application promotion.

Enhanced positronium lifetime imaging through two-component reconstruction in time-of-flight positron emission tomography

Positronium lifetime imaging (PLI) is a newly demonstrated technique possible with time-of-flight (TOF) positron emission tomography (PET), capable of producing an image reflecting the lifetime of the positron, more precisely ortho-positronium (o-Ps), before annihilation, in addition to the traditional uptake image of the PET tracer. Due to the limited time resolution of TOF-PET systems and the added complexities in physics and statistics, lifetime image reconstruction presents a challenge. Recently, we described a maximum-likelihood approach for PLI by considering only o-Ps. In real-world scenarios, other populations of positrons that exhibit different lifetimes also exist. This paper introduces a novel two-component model aimed at enhancing the accuracy of o-Ps lifetime images. Through simulation studies, we compare this new model with the existing single-component model and demonstrate its superior performance in accurately capturing complex lifetime distributions.