High-resolution Imaging Research Articles

Oversampling for Enhanced Spatial Resolution of Zebrafish by Top-Hat IR-MALDESI-MSI.

Mass spectrometry imaging (MSI) has become a significant tool for measuring chemical species in biological tissues, where much of the impact of these platforms lies in their capability to report the spatial distribution of analytes for correlation to sample morphology. As a result, enhancement of spatial resolution has become a frontier of innovation in the field, and necessary developments are dependent on the ionization source. More particularly, laser-based imaging sources may require modifications to the optical train or alternative sampling techniques. These challenges are heightened for systems with infrared (IR) lasers, as their operating wavelength generates spot sizes that are inherently larger than their ultraviolet counterparts. Recently, the infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) source has shown the utility of a diffractive optical element (DOE) to produce square ablation patterns, termed top-hat IR-MALDESI. If the DOE optic is combined with oversampling methods, smaller ablation volumes can be sampled to render higher spatial resolution imaging experiments. Further, this approach enables reproducible spot sizes and ablation volumes for better comparison between scans. Herein, we investigate the utility of oversampling with top-hat IR-MALDESI to enhance the spatial resolution of measured lipids localized within the head of sectioned zebrafish tissue. Four different spatial resolutions were evaluated for data quality (e.g., mass measurement accuracy, spectral accuracy) and quantity of annotations. Other experimental parameters to consider for high spatial resolution imaging are also discussed. Ultimately, 20 μm spatial resolution was achieved in this work and supports feasibility for use in future IR-MALDESI studies.

Multimodal Image Fusion Workflow Incorporating MALDI Imaging Mass Spectrometry and Microscopy for the Study of Small Pharmaceutical Compounds.

Multimodal imaging analyses of dosed tissue samples can provide more comprehensive insights into the effects of a therapeutically active compound on a target tissue compared to single-modal imaging. For example, simultaneous spatial mapping of pharmaceutical compounds and endogenous macromolecule receptors is difficult to achieve in a single imaging experiment. Herein, we present a multimodal workflow combining imaging mass spectrometry with immunohistochemistry (IHC) fluorescence imaging and brightfield microscopy imaging. Imaging mass spectrometry enables direct mapping of pharmaceutical compounds and metabolites, IHC fluorescence imaging can visualize large proteins, and brightfield microscopy imaging provides tissue morphology information. Single-cell resolution images are generally difficult to acquire using imaging mass spectrometry but are readily acquired with IHC fluorescence and brightfield microscopy imaging. Spatial sharpening of mass spectrometry images would thus allow for higher fidelity coregistration with other higher-resolution microscopy images. Imaging mass spectrometry spatial resolution can be predicted to a finer value via a computational image fusion workflow, which models the relationship between the intensity values in the mass spectrometry image and the features of a high-spatial resolution microscopy image. As a proof of concept, our multimodal workflow was applied to brain tissue extracted from a Sprague-Dawley rat dosed with a kratom alkaloid, corynantheidine. Four candidate mathematical models, including linear regression, partial least-squares regression, random forest regression, and two-dimensional convolutional neural network (2-D CNN), were tested. The random forest and 2-D CNN models most accurately predicted the intensity values at each pixel as well as the overall patterns of the mass spectrometry images, while also providing the best spatial resolution enhancements. Herein, image fusion enabled predicted mass spectrometry images of corynantheidine, GABA, and glutamine to approximately 2.5 μm spatial resolutions, a significant improvement compared to the original images acquired at 25 μm spatial resolution. The predicted mass spectrometry images were then coregistered with an H&E image and IHC fluorescence image of the μ-opioid receptor to assess colocalization of corynantheidine with brain cells. Our study also provides insights into the different evaluation parameters to consider when utilizing image fusion for biological applications.

Pseudopus pannonicus (Squamata), the largest known anguid lizard-Redescription of the type material and new specimens from the Neogene and Quaternary of Hungary and Poland.

Herein, we revise the material of the extinct taxon Pseudopus pannonicus from Central Europe, the largest known anguid lizard and iconic member of herpetofaunas from the Upper Cenozoic of Europe. The geographical position of Polgárdi 2, the type locality of P. pannonicus, as well as several other closely located important localities make Central Europe a valuable area of high interest for studies regarding European Cenozoic palaeoherpetological assemblages. We clarified the nature of the type material of Pseudopus pannonicus, showing that it consisted not only of the five specimens originally figured. Instead, the syntype series also includes a considerable number of specimens from Polgárdi 2 that were only described or figured 12 years after the original description of P. pannonicus. Detailed osteological descriptions are provided for specimens from the type series and Polish specimens, with the aid of high-resolution imaging (SEM and μCT scanning), and intraspecific variability is discussed. The articular surface with the lappet of the parietal overlapping the frontal is discussed as a character potentially relevant for the diagnosis of P. pannonicus. We updated the identification of several specimens of P. pannonicus and discussed the biogeographic implications of such revisions. In Poland, P. pannonicus is an abundant component of Neogene and early Quaternary herpetofaunas, known with certainty from the Middle Miocene of Przeworno (the oldest known occurrence of the species globally), the Early-Late Pliocene of Węże I, the Late Pliocene of Rębielice Królewskie I, the Late Pliocene of Węże II, and the Early Pleistocene of Kadzielnia (one of the youngest occurrences documented globally). An indeterminate anguine with Anguis affinities is newly reported from Rębielice Królewskie II. The taxonomic status of other large anguids from the Neogene of Europe is discussed and we conclude that most are junior synonyms of P. pannonicus. We also show that another purported synonym, that is, Ophisaurus intermedius from the Early Pleistocene of Romania, is instead a nomen nudum. We conducted phylogenetic analyses (18 taxa, 65 characters) to understand the relationship of P. pannonicus relative to other anguid representatives and anguid-related group (i.e., glyptosaurids). A single most parsimonious tree (length: 134 steps) was recovered. The clade Pseudopus is stable, comprising the two distinct sister subclades [Pseudopus laurillardi + Pseudopus ahnikoviensis] and [Pseudopus pannonicus + Pseudopus apodus]. These phylogenetic results are in accordance with previously published works.

Extending the emission peak tail of indole cyanine for deep-near-infrared bioimaging

We propose a novel strategy for tailoring the structure of fluorescent molecules to achieve emission at the tail end of the NIR-II window. The favorable spectroscopic properties and low cytotoxicity of YNs make them powerful tools for bioimaging. Notably, YN-4 exhibits a brightness 2.5 times greater than YN-3, 6 times that of IR-783, and 5 times that of ICG. This enhanced brightness enabled high-resolution imaging of mouse thoracic and abdominal cavities, tumor vasculature, and real-time monitoring of gastrointestinal motility using YN-4. Furthermore, covalent grafting of glucose onto the YN-Glu scaffold significantly improved tumor-targeting capability and facilitated tracking of glucose metabolism. This work aims to extend the application of fluorescent molecule imaging beyond the NIR-IIa window.

High-Fidelity and Efficient Pluralistic Image Completion with Transformers.

Image completion has made tremendous progress with convolutional neural networks (CNNs), because of their powerful texture modeling capacity. However, due to some inherent properties (e.g., local inductive prior, spatial-invariant kernels), CNNs do not perform well in understanding global structures or naturally support pluralistic completion. Recently, transformers demonstrate their power in modeling the long-term relationship and generating diverse results, but their computation complexity is quadratic to input length, thus hampering the application in processing high-resolution images. This paper brings the best of both worlds to pluralistic image completion: appearance prior reconstruction with transformer and texture replenishment with CNN. The former transformer recovers pluralistic coherent structures together with some coarse textures, while the latter CNN enhances the local texture details of coarse priors guided by the high-resolution masked images. To decode diversified outputs from transformers, auto-regressive sampling is the most common method, but with extremely low efficiency. We further overcome this issue by proposing a new decoding strategy, temperature annealing probabilistic sampling (TAPS), which firstly achieves more than 70× speedup of inference at most, meanwhile maintaining the high quality and diversity of the sampled global structures. Moreover, we find the full CNN architecture will lead to suboptimal solutions for guided upsampling. To render more realistic and coherent contents, we design a novel module, named texture-aware guided attention, to concurrently consider the procedures of texture copy and generation, meanwhile raising several important modifications to solve the boundary artifacts. Through dense experiments, we found the proposed method vastly outperforms state-of-the-art methods in terms of four aspects: 1) large performance boost on image fidelity even compared to deterministic completion methods; 2) better diversity and higher fidelity for pluralistic completion; 3) exceptional generalization ability on large masks and generic dataset, like ImageNet. 4) Much higher decoding efficiency over previous auto-regressive based methods.

Detection of proteins with ascorbic acid-capped gold nanoparticles: a simple and highly sensitive colorimetric assay.

We report a simple and highly sensitive colorimetric method for the detection and quantification of proteins, based on the aggregation of ascorbic acid (AA) capped gold nanoparticles (AuNPs) by proteins. The interactions between our AuNPs and nine different proteins of various sizes and shapes (cytochrome C (12 kDa), lysozyme (14.3 kDa), myoglobin (17 kDa), human serum albumin (66 kDa), bovine serum albumin (66.4 kDa), human transferrin (80 kDa), aldolase (160 kDa), catalase (240 kDa), and human H-ferritin (500 kDa)) generated similar AuNPs-protein absorption spectra in a concentration-dependent manner in the range of 1-15 nM. Upon the addition of a protein, the UV-visible spectra of AuNPs-protein conjugates shifted from 524 nm for the AuNps alone to longer wavelength (600-750 nm) due to the presence of one of these proteins. This bathochromic shift is accompanied by a color change from a cherry red, to dark purple, and then light grey or colorless if excess protein has been added, indicating the formation of AuNPs-protein conjugates followed by protein-induced aggregation of the AuNPs. High-resolution transmission electron microscopy images revealed uniformly distributed spherical nanoparticles with an average size of 27.5 ± 15.2 nm, increasing in size to 39.6 ± 12.9 nm upon the addition of a protein, indicating the formation of AuNPs-protein conjugates in solution. A general mechanism for the protein-induced aggregation of our AuNPs is proposed. The consistent behavior observed with the nine proteins tested in our study suggests that our assay can be universally applied for the quantification of pure proteins in a solution, regardless of size, shape, or molecular weight.

Simultaneous Multifocal Plane Fourier Ptychographic Microscopy Utilizing a Standard RGB Camera

Fourier ptychographic microscopy (FPM) is a computational imaging technology that can acquire high-resolution large-area images for applications ranging from biology to microelectronics. In this study, we utilize multifocal plane imaging to enhance the existing FPM technology. Using an RGB light emitting diode (LED) array to illuminate the sample, raw images are captured using a color camera. Then, exploiting the basic optical principle of wavelength-dependent focal length variation, three focal plane images are extracted from the raw image through simple R, G, and B channel separation. Herein, a single aspherical lens with a numerical aperture (NA) of 0.15 was used as the objective lens, and the illumination NA used for FPM image reconstruction was 0.08. Therefore, simultaneous multifocal plane FPM with a synthetic NA of 0.23 was achieved. The multifocal imaging performance of the enhanced FPM system was then evaluated by inspecting a transparent organic light-emitting diode (OLED) sample. The FPM system was able to simultaneously inspect the individual OLED pixels as well as the surface of the encapsulating glass substrate by separating R, G, and B channel images from the raw image, which was taken in one shot.

Vision transformer and CNN-based skin lesion analysis: classification of monkeypox

AbstractMonkeypox is an important health problem. Rapid diagnosis of monkeypox skin lesions and emergency isolation when necessary is essential. Also, some skin lesions, such as melanoma, can be fatal and must be rapidly distinguished. However, in some cases, it is difficult to distinguish the lesions visually. Methods such as dermoscopy, high-resolution ultrasound imaging, etc. can be used for better observation. But these methods are often based on qualitative analysis, subjective and time-consuming. Therefore, in this study, a quantitative and objective classification tool has been developed to assist dermatologists and scientists. The proposed system classifies seven skin lesions, including monkeypox. A popular approach Vision Transformer and some popular deep learning convolutional networks have been trained with the transfer learning approach and all results have been compared. Then, the models that show the best accuracy score have been combined to make the final prediction using bagging-ensemble learning. The proposed ensemble-based system produced 81.91% Accuracy, 65.94% Jaccard, 87.16% Precision, 74.12% Recall, and 78.16% Fscore values. In terms of different criteria metrics, the system produced competitive or even better results than the literature.

Using High-Resolution Vessel Wall Magnetic Resonance Images in a Patient of Intracranial Artery Dissection Related Acute Infarction

Acute ischemic stroke in young adults typically carries significant implications for morbidity, mortality, and long-term disability. In this study, we describe the case of a 34-year-old male with no prior medical history who presented with symptoms of right-sided weakness and slurred speech, suggesting an acute ischemic stroke. Initial CT angiography revealed an occlusion in the left M2 segment middle cerebral artery (MCA). The occlusion was successfully recanalized through emergent endovascular thrombectomy, which also identified a dissection as the cause of the stroke. Follow-up assessments at 3 days and three months, which included advanced vessel wall MRI, highlighted the critical role of intracranial artery dissection in strokes among young adults and provided essential images for ongoing evaluation.

Vision transformer and CNN-based skin lesion analysis: classification of monkeypox

AbstractMonkeypox is an important health problem. Rapid diagnosis of monkeypox skin lesions and emergency isolation when necessary is essential. Also, some skin lesions, such as melanoma, can be fatal and must be rapidly distinguished. However, in some cases, it is difficult to distinguish the lesions visually. Methods such as dermoscopy, high-resolution ultrasound imaging, etc. can be used for better observation. But these methods are often based on qualitative analysis, subjective and time-consuming. Therefore, in this study, a quantitative and objective classification tool has been developed to assist dermatologists and scientists. The proposed system classifies seven skin lesions, including monkeypox. A popular approach Vision Transformer and some popular deep learning convolutional networks have been trained with the transfer learning approach and all results have been compared. Then, the models that show the best accuracy score have been combined to make the final prediction using bagging-ensemble learning. The proposed ensemble-based system produced 81.91% Accuracy, 65.94% Jaccard, 87.16% Precision, 74.12% Recall, and 78.16% Fscore values. In terms of different criteria metrics, the system produced competitive or even better results than the literature.

Neuroprotective Effects of Inhaled Xenon Gas on Brain Structural Gray Matter Changes After Out-of-Hospital Cardiac Arrest Evaluated by Morphometric Analysis: A Substudy of the Randomized Xe-Hypotheca Trial.

We have earlier reported that inhaled xenon combined with hypothermia attenuates brain white matter injury in comatose survivors of out-of-hospital cardiac arrest (OHCA). A predefined secondary objective was to assess the effect of inhaled xenon on the structural changes in gray matter in comatose survivors after OHCA. Patients were randomly assigned to receive either inhaled xenon combined with target temperature management (33°C) for 24h (n = 55, xenon group) or target temperature management alone (n = 55, control group). A change of brain gray matter volume was assessed with a voxel-based morphometry evaluation of high-resolution structural brain magnetic resonance imaging (MRI) data with Statistical Parametric Mapping. Patients were scheduled to undergo the first MRI between 36 and 52h and a second MRI 10days after OHCA. Of the 110 randomly assigned patients in the Xe-Hypotheca trial, 66 patients completed both MRI scans. After all imaging-based exclusions, 21 patients in the control group and 24 patients in the xenon group had both scan 1 and scan 2 available for analyses with scans that fulfilled the quality criteria. Compared with the xenon group, the control group had a significant decrease in brain gray matter volume in several clusters in the second scan compared with the first. In a between-group analysis, significant reductions were found in the right amygdala/entorhinal cortex (p = 0.025), left amygdala (p = 0.043), left middle temporal gyrus (p = 0.042), left inferior temporal gyrus (p = 0.008), left parahippocampal gyrus (p = 0.042), left temporal pole (p = 0.042), and left cerebellar cortex (p = 0.005). In the remaining gray matter areas, there were no significant changes between the groups. In comatose survivors of OHCA, inhaled xenon combined with targeted temperature management preserved gray matter better than hypothermia alone. ClinicalTrials.gov: NCT00879892.

Intra-cochlear electrode position impacts the preservation of residual hearing in an animal model of cochlear implant surgery.

Preservation of residual hearing after cochlear implantation remains challenging. There are several approaches to preserve residual hearing, but the configuration of the implant electrode array seems to play a major role. Lateral wall electrode arrays are seemingly more favorable in this context. To date, there are no experimental data available which correlate the spatial electrode position in the scala tympani with the extent of hearing preservation. Based on µCT imaging data, this study analyses the exact position of a pure- silicone electrode array inserted into the cochlea of four guinea pigs. Array position data were correlated with the extent of hearing loss after implantation, measured using auditory brainstem measurements in the frequency range of the area occupied by the electrode array area as well as apical to the array. The use of pure-silicone arrays without electrodes resulted in artifact-free, high-resolution µCT images that allowed precise determination of the arrays' positions within the scala tympani. The electrode arrays' locations ranged from peri-modiolar to an anti-modiolar. These revealed a correlation of a lower postoperative hearing loss with a higher spatial proximity to the lateral wall. This correlation was found in the low-frequency range only. A significant correlation between the interindividual differences in the diameter of the scala tympani and the postoperative hearing loss could not be observed. This study demonstrates the importance of the intra-cochlear electrode array's position for the preservation of residual hearing. The advantage of such an electrode array's position approximated to the lateral wall suggests, at least for this type of electrode array applied in the guinea pig, would be advantageous in the preservation of residual hearing for the apical part of the cochlea, beyond the area occupied by the electrode array.

Live cell imaging of cellular dynamics in poplar wood using computational cannula microscopy

This study presents significant advancements in computational cannula microscopy for live imaging of cellular dynamics in poplar wood tissues. Leveraging machine-learning models such as pix2pix for image reconstruction, we achieved high-resolution imaging with a field of view of 55µm using a 50µm-core diameter probe. Our method allows for real-time image reconstruction at 0.29 s per frame with a mean absolute error of 0.07. We successfully captured cellular-level dynamics in vivo, demonstrating morphological changes at resolutions as small as 3µm. We implemented two types of probabilistic neural network models to quantify confidence levels in the reconstructed images. This approach facilitates context-aware, human-in-the-loop analysis, which is crucial for in vivo imaging where ground-truth data is unavailable. Using this approach we demonstrated deep in vivo computational imaging of living plant tissue with high confidence (disagreement score ⪅0.2). This work addresses the challenges of imaging live plant tissues, offering a practical and minimally invasive tool for plant biologists.

Visual State Space Model for Image Deraining with Symmetrical Scanning

Image deraining aims to mitigate the adverse effects of rain streaks on image quality. Recently, the advent of convolutional neural networks (CNNs) and Vision Transformers (ViTs) has catalyzed substantial advancements in this field. However, these methods fail to effectively balance model efficiency and image deraining performance. In this paper, we propose an effective, locally enhanced visual state space model for image deraining, called DerainMamba. Specifically, we introduce a global-aware state space model to better capture long-range dependencies with linear complexity. In contrast to existing methods that utilize fixed unidirectional scan mechanisms, we propose a direction-aware symmetrical scanning module to enhance the feature capture of rain streak direction. Furthermore, we integrate a local-aware mixture of experts into our framework to mitigate local pixel forgetting, thereby enhancing the overall quality of high-resolution image reconstruction. Experimental results validate that the proposed method surpasses state-of-the-art approaches on six benchmark datasets.

Continuous damage of concrete structures due to reinforcement corrosion: A micromechanical and multi-physics based analysis

Deterioration of concrete and composite structures due to the corrosion of embedded steel components (rebar, structural steel components, and steel fiber, etc.) is a self-accelerating process involving multiple chemophysical processes that occur concurrently in the heterogeneous structure of concrete. The multiple-inclusion matrix of concrete and the multi-chemophysics nature of steel corrosion synergistically challenge an accurate analysis and evaluation of the deterioration process using homogeneity-based continuum mechanics. This study presents a three-dimensional micromechanical model developed for quantifying the continuous deterioration of concrete by steel corrosion. Continuous damage theory of solid-state materials was applied to a steel-concrete sample that consists of mortar, aggregate, and steel phases as were reconstructed from high-resolution X-ray CT images. With due consideration of the variations in environmental temperature and moisture, the complex chemophysical processes involved in corrosion-induced deterioration of concrete were solved concurrently using finite element analysis. Results of the study indicate that capillary suction in a variably saturated concrete plays an important role in steel corrosion and that removal of chloride by an externally applied electrical field can effectively mitigate steel corrosion and the incurred concrete deterioration.

Compact ultrafast neutron sources via bulk acceleration of deuteron ions in an optical trap

A scheme for a quasi-monoenergetic high-flux neutron source with femtosecond duration and highly anisotropic angular distribution is proposed. This scheme is based on bulk acceleration of deuteron ions in an optical trap or density grating formed by two counter-propagating laser pulses at an intensity of ∼1016W/cm2 in a near-critical-density plasma. The deuterons are first pre-accelerated to an energy of tens of keV in the ambipolar fields formed in the optical trap. Their energy is boosted to the MeV level by another one or two laser pulses at an intensity of ∼1020W/cm2, enabling fusion reactions to be triggered with high efficiency. In contrast to previously proposed pitcher–catcher configurations, our scheme can provide spatially periodic acceleration structures and effective collisions between deuterons inside the whole target volume. Subsequently, neutrons are generated directly inside the optical trap. Our simulations show that neutron pulses with energy 2–8 MeV, yield 1018–1019n/s, and total number 106–107 in a duration ∼400 fs can be obtained with a 25 μm target. Moreover, the neutron pulses exhibit unique angularly dependent energy spectra and flux distributions, predominantly along the axis of the energy-boosting lasers. Such microsize femtosecond neutron pulses may find many applications, such as high-resolution fast neutron imaging and nuclear physics research.

Acoustic camera-based super-resolution reconstruction approach for underwater perception in low-visibility marine environments

In low-visibility environments, the underwater perception range of optical cameras is severely restricted, and perception operations in ocean engineering often rely on sonar. Acoustic cameras are a type of forward-looking sonar that have attracted considerable attention because of their ability to produce images similar to those of optical cameras. However, owing to the unique imaging mechanism employed by acoustic cameras, the resulting images suffer from insufficient resolution and a loss of feature details. This issue considerably diminishes the precision of downstream visual tasks, limiting the application of acoustic cameras. In this study, we propose a deep-learning-based super-resolution reconstruction approach for acoustic cameras, where the reconstruction process relies only on images, without prior assumptions regarding the detection scenes. We verified the effectiveness of the proposed method for two practical applications: marine debris detection and marine structure inspection. The experimental results show that our proposed method can robustly reconstruct high-resolution sonar images, and the obtained images have superior feature details, which improved the precision of downstream vision tasks. In this study, we aim to provide better solutions for underwater perception in low-visibility marine environments, while exploring the application of acoustic cameras in marine debris detection and structure inspection.

Non-muscle myosin 2 can incorporate into established filaments in cells without an assembly competence domain.

Myosin 2 dynamically assembles into filaments that exert force on the actin cytoskeleton. To form filaments, myosin 2 monomers transition between folded and unfolded states. Monomer unfolding exposes an extended coiled-coil that interacts with other monomers in parallel and antiparallel fashions, enabling bipolar filament formation. A C-terminal domain of the coiled-coil, termed assembly competence domain (ACD), has been repeatedly identified as necessary for filament assembly. Here, we revisit ACD contribution when full-length filaments are present. Non-muscle myosin 2A lacking the ACD (ΔACD) initially appears diffuse, but triton extraction of cytosolic fraction reveals cytoskeletal association. Disruption of the folded monomer enhances the cytoskeletal fraction, while inhibition of endogenous filament assembly appears to reduce it. Finally, high resolution imaging of endogenous and exogenous bipolar filamentous structures reveals highly coincident signal, suggesting ΔACD constructs co-assemble with endogenous myosin 2A filaments. Our data demonstrate that while the ACD is required for de novo filament assembly, it is not required for monomers to recognize and associate with established filaments in cells. More broadly, this highlights the existence of distinct mechanisms governing myosin 2 monomer assembly into nascent filaments, and monomer recognition and association with established filaments to maintain steady-state contractile networks.

High-spatiotemporal resolution microwave-induced thermoacoustic tomography for imaging biological dynamics in deep tissue

Biological systems undergo constant dynamic changes across various spatial and temporal scales. To investigate the intricate biological dynamics in living organisms, there is a strong need for high-speed and high-resolution imaging capabilities with significant imaging depth. In this work, we present high-spatiotemporal resolution microwave-induced thermoacoustic tomography (HR-MTAT) as a method for imaging biological dynamics in deep tissues. HR-MTAT utilizes nanosecond pulsed microwave excitation and ultrasound detection, with appropriate spatial configurations, to achieve high coupling of the sample to the microwaves, to produce images in soft tissue with dielectric contrast and sub-millimeter spatial resolution (230 μm), to a depth of a few centimeters. Notably, by employing a 128-channel parallel signal acquisition and digitization strategy, the field programmable gate array module manages data synthesis, and GPU-based parallel pixel reconstruction facilitates HR-MTAT to accomplish single-frame image reconstruction in an impressive 50 μs. The practical feasibility of HR-MTAT was evaluated in live mice. The results show that HR-MTAT can noninvasively image whole-body small animals (up to 60 mm in depth) with clear resolution of internal organ structures at a frame rate of 100 Hz, without the need for labeling. At this high spatiotemporal resolution, HR-MTAT can capture respiration, heartbeat, and arterial pulse propagation without motion artifacts and track bio-nanoprobes in livers and tumors. These findings demonstrate HR-MTAT's ability to perform dynamic imaging with high contrast and resolution in deep tissues.

In vitro Accuracy of Ultra-Low Dose Cone-Beam Computed Tomography for Detection of Proximal Caries.

This study aimed to assess the accuracy of ultra-low dose (ULD) cone-beam computed tomography (CBCT) for detection of proximal caries. This in vitro study evaluated 104 molar and premolar teeth. The teeth were mounted in dry skulls and underwent CBCT with four protocols of high-resolution (HR), normal (NORM), ULD-HR, and ULD-NORM; 78 CBCT images were scored by three observers for presence and penetration depth of caries twice with a 2-week interval using a 5-point Likert scale. The teeth were then sectioned and observed under a stereomicroscope (gold standard). The four protocols were compared with each other and with the gold standard. The receiver operating characteristic (ROC) curve was drawn, and the area under the curve (AUC) was calculated and compared by the Chi-square test (alpha = 0.05). The interobserver agreement ranged from 0.5233 to 0.6034 for ULD-NORM, 0.5380 to 0.6279 for NORM, 0.5856 to 0.6300 for ULD-HR, and 0.6614 to 0.7707 for HR images. The intra-observer agreement ranged from 0.6027 to 0.8812 for ULD-HR, 0.7083 to 0.7556 for HR, 0.6076 to 0.9452 for ULD-NORM, and 0.7012 to 0.9221 for NORM images. Comparison of AUC revealed no significant difference between NORM and ULD-NORM (P > 0.05), or HR and ULD-HR (P > 0.05). The highest AUC belonged to HR (0.8529) and the lowest to NORM (0.7774). Considering the significant reduction in radiation dose in ULD CBCT and its acceptable diagnostic accuracy for detection of proximal caries, this protocol may be used for detection of proximal carious lesions and assessment of their depth.