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Here, we report high-fidelity correspondence imaging (CI) in complex media. By introducing varying thresholds to binarize single-pixel light intensities recorded in complex media, dynamic scaling factors can be eliminated. Then, the binarized light intensities and illumination patterns can be fed into a modified 1-bit compressive sensing algorithm to realize high-fidelity object reconstruction. The proposed method can implement object reconstruction with high fidelity in complex media without extra temporal carriers. It is experimentally verified that the method can effectively eliminate dynamic scaling factors and realize high-fidelity object reconstruction in complex media where conventional CI methods could fail. Experimental results demonstrate that the proposed method broadens a potential application of CI in complex media, e.g., turbid water, biological tissues, and dynamic smoke. [ABSTRACT FROM AUTHOR]

Temporal expectation refers to the capacity to allocate resources at a particular point in time, enabling us to enhance our behavior performance. Empirical evidence indicates that, among younger adults, temporal expectation can be driven by rhythm (i.e., regular sequences of stimuli). However, whether there are age-related changes in rhythm-based temporal expectation has not been clearly established. Furthermore, whether tempo can influence the relationship between rhythm-based temporal expectation and aging remains unexplored. To address these questions, both younger and older participants took part in a rhythm-based temporal expectation task, engaging three distinct tempos: 600 ms (fast), 1800 ms (moderate), or 3000 ms (slow). The results demonstrated that temporal expectation effects (i.e., participants exhibited significantly faster responses during the regular trials compared to the irregular trials) were observed in both the younger and older participants under the moderate tempo condition. However, in the fast and slow tempo conditions, the temporal expectation effects were solely observed in the younger participants. These findings revealed that rhythm-based temporal expectations can be preserved during aging but within a specific tempo range. When the tempo falls within the range of either being too fast or too slow, it can manifest age-related declines in temporal expectations driven by rhythms. [ABSTRACT FROM AUTHOR]

Dandelion pappus is a special geometry of radial porous disc and exhibits the separated vortex ring wake structure in low Reynolds numbers. In the current study, dynamic wake behind dandelion pappus models were experimentally studied in a high Reynolds number of 8000 by PIV and smoke-wire system. The effects of porosity and pappus angle were explored. The results revealed that the unsteady vortex shedding occurred in the wake flow field. Due to increased filaments and corresponding reduction in the interspaces for fluids to pass through, the shear layers were developed more fully and expanded, and the entrainment was stronger with the porosity decreased. Therefore, the recirculation zone was decentralized in width and enlarged, shifted further downstream as well. The turbulence intensity was also increased with lower porosity. By proper orthogonal decomposition (POD) and phase-averaged swirling strength λci, the wake had two different shedding patterns when taking 83% as an approximate porosity threshold. The pappus angle played a role in concentrating wake, elongating the recirculation zones and reducing kinetic turbulence. In the smoke-wire visualization, multiple Karman vortex streets are observed, which is induced by the filaments. Combined these two regions, we interpreted the flow properties of pappus and revealed the mechanism of dynamic wake. [ABSTRACT FROM AUTHOR]

The purpose is to establish and validate a machine-learning-derived radiomics approach to determine the existence of atrial fibrillation (AF) by analyzing epicardial adipose tissue (EAT) in CT images. Patients with AF based on electrocardiographic tracing who underwent contrast-enhanced (n = 200) or non-enhanced (n = 300) chest CT scans were analyzed retrospectively. After EAT segmentation and radiomics feature extraction, the segmented EAT yielded 1691 radiomics features. The most contributive features to AF were selected by the Boruta algorithm and machine-learning-based random forest algorithm, and combined to construct a radiomics signature (EAT-score). Multivariate logistic regression was used to build clinical factor and nested models. In the test cohort of contrast-enhanced scanning (n = 60/200), the AUC of EAT-score for identifying patients with AF was 0.92 (95%CI: 0.84–1.00), higher than 0.71 (0.58–0.85) of the clinical factor model (total cholesterol and body mass index) (DeLong's p = 0.01), and higher than 0.73 (0.61–0.86) of the EAT volume model (p = 0.01). In the test cohort of non-enhanced scanning (n = 100/300), the AUC of EAT-score was 0.85 (0.77–0.92), higher than that of the CT attenuation model (p < 0.001). The two nested models (EAT-score+volume and EAT-score+volume+clinical factors) for contrast-enhanced scan and one (EAT-score+CT attenuation) for non-enhanced scan showed similar AUCs with that of EAT-score (all p > 0.05). EAT-score generated by machine-learning-based radiomics achieved high performance in identifying patients with AF. A radiomics analysis based on machine learning allows for the identification of AF on the EAT in contrast-enhanced and non-enhanced chest CT. [ABSTRACT FROM AUTHOR]

We experimentally investigated the attenuation of the von Kármán vortex street behind a circular cylinder by the use of active suction through a structured porous surface in wind tunnel tests. The Reynolds number Re, based on the outer diameter of the cylinder D, is set to be 1.0 × 10 4 . The structured porous surface of the test model is made of resin by the three-dimensional printing technique to obtain well-organized porous structures. The active suction control effectiveness is quantified by a non-dimensional suction coefficient CQ, which is determined by the suction flow rate Q, the porous structure of the cylinder's surface, and the free stream velocity U ∞ . A high-speed particle image velocimetry measurement system is utilized to acquire global and detailed wake flows behind the baseline and controlled cylinders. In addition to directly perceived time-averaged characteristics, flow analysis methods including proper orthogonal decomposition, spectral analysis, and linear stability analysis are employed to study the underlying nature of cylinder wakes with and without distributed suction control. Experimental results show that multi-scale coherent structures in the cylinder wake are homogenized and the near wake is regularized under the control of suction. With a proper CQ, the alternating vortex street behind the circular cylinder is found to be greatly attenuated and the vortex shedding mode completely switched. [ABSTRACT FROM AUTHOR]

Temporal expectation is the ability to select the precise point in time for doing something to produce an optimal effect. Two sources of information that humans use to generate temporal expectations are rhythmic and symbolic cues. Both types of cues have been proven effective in directing attention to a future point in time resulting in improved performance. However, the temporal precision of the two forms of temporal expectation have rarely been compared. In the current study, 17 participants performed two temporal expectation tasks in which either a rhythmic cue or a symbolic cue indicated that a future target would appear after a 500-ms (short) or 1,500-ms (long) interval; the target appeared at the expected time in 54% of trials and at an unexpected earlier or later interval in 36% of trials. In both tasks, we observed that the reaction time (RT) curves were U-shaped, with a slower RT for the earlier and later unexpected intervals and a faster RT for intervals approaching the expected point in time. Furthermore, we found a significant interaction between task and the quadratic term of temporal expectation, which indicates that the U-shaped RT curves for the rhythmic cue task are steeper than those for the symbolic cue task. Thus, the current results revealed that compared with symbolic cues, temporal expectation driven by rhythmic cues provides a more precise attentional focus in time. [ABSTRACT FROM AUTHOR]

Age-related audio-visual integration (AVI) has been investigated extensively; however, AVI ability is either enhanced or reduced with ageing, and this matter is still controversial because of the lack of systematic investigations. To remove possible variates, 26 older adults and 26 younger adults were recruited to conduct meaningless and semantic audio-visual discrimination tasks to assess the ageing effect of AVI systematically. The results for the mean response times showed a significantly faster response to the audio-visual (AV) target than that to the auditory (A) or visual (V) target and a significantly faster response to all targets by the younger adults than that by the older adults (A, V, and AV) in all conditions. In addition, a further comparison of the differences between the probability of audio-visual cumulative distributive functions (CDFs) and race model CDFs showed delayed AVI effects and a longer time window for AVI in older adults than that in younger adults in all conditions. The AVI effect was lower in older adults than that in younger adults during simple meaningless image discrimination (63.0 ms vs. 108.8 ms), but the findings were inverse during semantic image discrimination (310.3 ms vs. 127.2 ms). In addition, there was no significant difference between older and younger adults during semantic character discrimination (98.1 ms vs. 117.2 ms). These results suggested that AVI ability was impaired in older adults, but a compensatory mechanism was established for processing sematic audio-visual stimuli. [ABSTRACT FROM AUTHOR]

Age-related audio-visual integration (AVI) has been investigated extensively; however, AVI ability is either enhanced or reduced with ageing, and this matter is still controversial because of the lack of systematic investigations. To remove possible variates, 26 older adults and 26 younger adults were recruited to conduct meaningless and semantic audio-visual discrimination tasks to assess the ageing effect of AVI systematically. The results for the mean response times showed a significantly faster response to the audio-visual (AV) target than that to the auditory (A) or visual (V) target and a significantly faster response to all targets by the younger adults than that by the older adults (A, V, and AV) in all conditions. In addition, a further comparison of the differences between the probability of audio-visual cumulative distributive functions (CDFs) and race model CDFs showed delayed AVI effects and a longer time window for AVI in older adults than that in younger adults in all conditions. The AVI effect was lower in older adults than that in younger adults during simple meaningless image discrimination (63.0 ms vs. 108.8 ms), but the findings were inverse during semantic image discrimination (310.3 ms vs. 127.2 ms). In addition, there was no significant difference between older and younger adults during semantic character discrimination (98.1 ms vs. 117.2 ms). These results suggested that AVI ability was impaired in older adults, but a compensatory mechanism was established for processing sematic audio-visual stimuli. [ABSTRACT FROM AUTHOR]

Age-related audio-visual integration (AVI) has been investigated extensively; however, AVI ability is either enhanced or reduced with ageing, and this matter is still controversial because of the lack of systematic investigations. To remove possible variates, 26 older adults and 26 younger adults were recruited to conduct meaningless and semantic audio-visual discrimination tasks to assess the ageing effect of AVI systematically. The results for the mean response times showed a significantly faster response to the audio-visual (AV) target than that to the auditory (A) or visual (V) target and a significantly faster response to all targets by the younger adults than that by the older adults (A, V, and AV) in all conditions. In addition, a further comparison of the differences between the probability of audio-visual cumulative distributive functions (CDFs) and race model CDFs showed delayed AVI effects and a longer time window for AVI in older adults than that in younger adults in all conditions. The AVI effect was lower in older adults than that in younger adults during simple meaningless image discrimination (63.0 ms vs. 108.8 ms), but the findings were inverse during semantic image discrimination (310.3 ms vs. 127.2 ms). In addition, there was no significant difference between older and younger adults during semantic character discrimination (98.1 ms vs. 117.2 ms). These results suggested that AVI ability was impaired in older adults, but a compensatory mechanism was established for processing sematic audio-visual stimuli. [ABSTRACT FROM AUTHOR]

An active control method was used to attenuate the unsteady vortex shedding in the wake of a square cylinder. Distributed jets were applied to the rear porous surface at a Reynolds number of 1.07 × 104. The strength of the jets was measured using the dimensionless jet momentum coefficient C Q. The dynamic mode decomposition, instantaneous vorticity evolution, and time-averaged characteristics, e.g., turbulent kinetic energy, streamlines, velocity profiles and Reynolds stress distributions of the wake flow field were used to analyze the control effects. The results suggest that with increasing C Q , two jet vortices gradually form near the rear cylinder wall and compete with the vortex shedding. Consequently, the vortex shedding pattern became nearly symmetrical, whereas the jet vortices remained asymmetrical. The vortex shedding process was pushed downstream. The fluctuations in the wake, particularly near cylindrical walls, were significantly suppressed. Thus, this scheme was successful, indicating potential for drag reduction and energy efficiency. Better control effects were associated with higher C Q in the present study. • A square cylinder wake is controlled via distributed jets over the coated rear porous surface. • The formed jets vortices manipulate the wake vortex shedding process. • The turbulent kinetic energy and the Reynolds stress distributions are restrained and the wake flow stabilized. [ABSTRACT FROM AUTHOR]

Temporal expectation relies on different predictive information, such as regular rhythms and symbolic cues, to direct attention to a future moment in time to optimize behaviour. However, whether differences exist between temporal expectations driven by regular rhythms and symbolic cues has not been clearly established. In this study, 20 participants performed two temporal expectation tasks in which a rhythmic cue or a symbolic cue indicated (70% expected) that the target would appear after an interval of 500 ms (short), 1,500 ms (medium), or 2,500 ms (long). We found larger cueing effects for the rhythmic cued task than for the symbolic cued task during the short interval, indicating that rhythmic cues were more effective in improving performance. Furthermore, no significant difference was found during the longer interval, reflect that the behavioural differences between the two forms of temporal expectations were likely to diminish as the time interval increased. Thus, we speculate that the temporal expectation driven by rhythmic cues differs from that driven by symbolic cues only in the limited time range; however, the mechanisms underlying the two forms of temporal expectations trend to become more similar over increasing temporal scales. [ABSTRACT FROM AUTHOR]

In several HTS applications, the superconducting tapes experience the simultaneous presence of DC and AC excitations. For example in high-current DC cables, where the transport current is not perfectly constant, but it exhibits some ripples at different frequencies introduced by the rectification process (AC–DC conversion). These ripples give rise to dissipation, whose magnitude and possible influence on the device’s cooling requirements need to be evaluated. Here we report a study of the AC losses in a HTS coated conductor subjected to DC currents and AC ripples simultaneously. The modeling approach is based on an integral equation method for thin superconductors: the superconducting tape is modeled as a 1-D object with a non-linear resistivity, which includes the dependence of the critical current density J c on the magnetic field. The model, implemented in a commercial finite-element program, runs very fast (the simulation of one AC cycle typically takes a few seconds on standard desktop workstation): this allows simulating a large number of cycles and estimating when the AC ripple losses stabilize to a constant value. The model is used to study the influence of the flux creep power index n on the stabilization speed and on the AC loss values, as well as the effect of using a field-dependent J c instead of a constant one. The simulations confirm that the dissipation level should not be a practical concern in HTS DC cables. At the same time, however, they reveal a strong dependence of the results upon the power index n and the form of J c , which spurs the question whether the power-law is the most suitable description of the superconductor’s electrical behavior for this kind of analysis. [ABSTRACT FROM AUTHOR]

In the current study, a new passive flow control strategy characterized by 3D printing structured porous surface was introduced and experimentally investigated to manipulate the dynamic wake evolution and flow characteristics around a circular cylinder at a Reynolds number of 2.02 × 10 4. With the 3D printing structured porous surface, parts of the incoming flow could go through the cylinder and communicate with the wake flow spontaneously. As a result, the vortex shedding was suppressed and the drag was reduced. From POD analysis results, we observed shifted modes and decreased vorticity distribution, indicating that the periodic vortex shedding process was weakened. This was also verified by the analysis of dynamic wake evolution and by the power spectrum analysis. In addition, experimental results showed that the time-averaged turbulent kinetic energy (TKE) and the Reynolds shear stress (RSS) distributions were restrained in the wake of the porous cylinder. Moreover, the mean estimated drag coefficients witnessed a significant decrease up to 49.47%. • The flow around a cylinder is modified via structured porous surface. • The porous cylinder stabilizes the dynamic wake and alleviate the unsteady vortex shedding from the cylinder. • The mean estimated drag coefficient is estimated to be decreased up to 49.47%. [ABSTRACT FROM AUTHOR]

Simulation studies were conducted on the magnetization of (RE)BCO (RE-Ba-Cu-O, where RE represents a rare earth element) bulk superconductors using various split-coil arrangements by solving the critical state equation using the commercial software FlexPDE. A pair of coaxial coils of identical size is identified as an optimum arrangement for practical magnetization at 77 K by the 'zero-field cooling' technique. In general, the magnetization process is likely to be most effective when the outer radius of the coils lies between 100% and 50% of the sample radius. A relatively large coil pair is necessary for samples with either a smaller aspect ratio or larger values of Jc0. Two different regimes of flux penetration are found to be involved in the magnetization process. For a sufficiently small sample, the penetration field is determined by flux propagation from beneath the coil to the centre of the sample; for a sufficiently large sample, the definitive propagation route is from beneath the coil to the periphery of the sample. Effective split-coil magnetization occurs only in the former regime, and both penetration regimes are completely different from that involved in the solenoidal-coil magnetization process. [ABSTRACT FROM AUTHOR]

The fault location in underground cables is characterized as the technical difficulties due to complexities in cables. Based on the direct circuit analysis, a fault location algorithm for underground cables with no laterals is presented in this paper. The single-end phasor measurements, including the voltages and currents sampled in the substation side, are utilized to locate the single phase faults in the typical single-conductor cross-linked polyethylene (XLPE) cables rated at the medium voltage (MV) levels. The distinctive cable characteristics are considered, such as relatively large capacitance, effects of sheaths and sheath bonding methods. The different fault scenarios are taken into account as well. The effect of changes of cable parameters and application of static response load model are also investigated. The simulation studies demonstrate the proposed algorithm can achieve the high accuracy under various system and fault conditions. [ABSTRACT FROM AUTHOR]

Simple Summary: Multiple genetic mutations are associated with the outcomes of patients with non-small cell lung cancer (NSCLC) after using tyrosine kinase inhibitor, but the cost for detecting multiple genetic mutations is high. Few studies have investigated whether multiple genetic mutations can be simultaneously detected based on image features in patients with NSCLC. We developed a machine learning-derived radiomics approach that can simultaneously discriminate the presence of EGFR, KRAS, ERBB2, and TP53 mutations on CT images in patients with NSCLC. These findings suggest that machine learning-derived radiomics may become a noninvasive and low-cost method to screen for multiple genetic mutations in patients with NSCLC before using next-generation sequencing tests, which can help to improve individualized targeted therapies. Purpose: To develop a machine learning-derived radiomics approach to simultaneously discriminate epidermal growth factor receptor (EGFR), Kirsten rat sarcoma viral oncogene (KRAS), Erb-B2 receptor tyrosine kinase 2 (ERBB2), and tumor protein 53 (TP53) genetic mutations in patients with non-small cell lung cancer (NSCLC). Methods: This study included consecutive patients from April 2018 to June 2020 who had histologically confirmed NSCLC, and underwent pre-surgical contrast-enhanced CT and post-surgical next-generation sequencing (NGS) tests to determine the presence of EGFR, KRAS, ERBB2, and TP53 mutations. A dedicated radiomics analysis package extracted 1672 radiomic features in three dimensions. Discriminative models were established using the least absolute shrinkage and selection operator to determine the presence of EGFR, KRAS, ERBB2, and TP53 mutations, based on radiomic features and relevant clinical factors. Results: In 134 patients (63.6 ± 8.9 years), the 20 most relevant radiomic features (13 for KRAS) to mutations were selected to construct models. The areas under the curve (AUCs) of the combined model (radiomic features and relevant clinical factors) for discriminating EGFR, KRAS, ERBB2, and TP53 mutations were 0.78 (95% CI: 0.70–0.86), 0.81 (0.69–0.93), 0.87 (0.78–0.95), and 0.84 (0.78–0.91), respectively. In particular, the specificity to exclude EGFR mutations was 0.96 (0.87–0.99). The sensitivity to determine KRAS, ERBB2, and TP53 mutations ranged from 0.82 (0.69–90) to 0.92 (0.62–0.99). Conclusions: Machine learning-derived 3D radiomics can simultaneously discriminate the presence of EGFR, KRAS, ERBB2, and TP53 mutations in patients with NSCLC. This noninvasive and low-cost approach may be helpful in screening patients before invasive sampling and NGS testing. [ABSTRACT FROM AUTHOR]

Porous coating and blowing jets are both effective flow control methods for a bluff body. In the present study, we conducted wind tunnel experiments to investigate the combined control effects on a circular cylinder. The flow control was achieved by active steady blowing flows through the structured porous surface on the leeward side of the cylinder. The Reynolds number Re in the experiments, based on the cylinder outer diameter, was 1.0 × 10 4 . The control effects were evaluated by a non-dimensional blowing momentum coefficient C μ , which was determined by various blowing mass flow rates, incoming wind speed, and the geometry of the porous surface. Reduced-order models, including proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD), were employed to analyze the wake stabilization effects of the secondary jet flows. We found that, under the control of secondary flows ejected from the porous region of the cylinder, POD modal characteristics in the global flow wake were changed; temporal and spatial properties of DMD transformed; frequency and mode of the vortex shedding process shifted; statistical turbulent flow characteristics ameliorated; and the estimated drag coefficients restrained. Experimental results in the present study demonstrated that the secondary flow ejected from the structured porous surface and the resultant small-scale vortices could stabilize the cylinder wake with proper C μ values. [ABSTRACT FROM AUTHOR]

In order to explore the tensile properties of VCM deep drawing steel plate and its relationship with constituent materials, ABAQUS finite element method was used to conduct numerical simulation of VCM deep drawing steel plate and its constituent materials, and the relevant mechanical parameters (tensile strength, upper yield strength, fracture strain and elongation after fracture) were compared and analyzed. The influence coefficient of steel plate substrate and VCM film on the mechanical properties of VCM deep drawing steel plate was introduced. The results showed that the strength and plasticity of VCM deep drawing steel plate were improved compared with that of steel plate substrate after the VCM film was bonded on the substrate surface. The steel plate substrate had a great influence on the tensile strength and upper yield strength of VCM deep drawing steel plate, and the VCM film had a great influence on the fracture strain and elongation after fracture of VCM deep drawing steel plate, that was, the steel plate substrate had a great influence on the strength of VCM deep drawing steel plate, and the VCM film had a great influence on the plasticity and ductility of VCM deep drawing steel plate. [ABSTRACT FROM AUTHOR]

Introduction: Previous studies have confirmed increased functional connectivity in elderly adults during processing of simple audio–visual stimuli; however, it is unclear whether elderly adults maximize their performance by strengthening their functional brain connectivity when processing dynamic audio–visual hand‐held tool stimuli. The present study aimed to explore this question using global functional connectivity. Methods: Twenty‐one healthy elderly adults and 21 healthy younger adults were recruited to conduct a dynamic hand‐held tool recognition task with high/low‐intensity stimuli. Results: Elderly adults exhibited higher areas under the curve for both the high‐intensity (3.5 versus. 2.7) and low‐intensity (3.0 versus. 1.2) stimuli, indicating a higher audio–visual integration ability, but a delayed and widened audio–visual integration window for elderly adults for both the high‐intensity (390 – 690 ms versus. 360 – 560 ms) and low‐intensity (460 – 690 ms versus. 430 – 500 ms) stimuli. Additionally, elderly adults exhibited higher theta‐band (all p <.01) but lower alpha‐, beta‐, and gamma‐band functional connectivity (all p <.05) than younger adults under both the high‐ and low‐intensity‐stimulus conditions when processing audio–visual stimuli, except for gamma‐band functional connectivity under the high‐intensity‐stimulus condition. Furthermore, higher theta‐ and alpha‐band functional connectivity were observed for the audio–visual stimuli than for the auditory and visual stimuli and under the high‐intensity‐stimulus condition than under the low‐intensity‐stimulus condition. Conclusion: The higher theta‐band functional connectivity in elderly adults was mainly due to higher attention allocation. The results further suggested that in the case of sensory processing, theta, alpha, beta, and gamma activity might participate in different stages of perception. [ABSTRACT FROM AUTHOR]

Locating a fault in a series-capacitor-compensated transmission line (SCCTL) is a challenging task due to the action of a metal-oxide varistor a nonlinear element present as a part of the protection system of the series capacitor. In this paper, an accurate fault-location algorithm that uses synchronized measurements from both ends of the SCCTL is presented which provides fault-location results without using the model of MOV or natural fault loop for single-phase-to-ground, and double-phase-to-ground faults. Another salient feature of the proposed technique is that the subroutines for locating faults in different sections transmission line yield almost identical fault-location results regardless of which section the transmission line is faulted. The proposed technique could also be extended to the double-circuit transmission lines. First, the proposed technique is introduced and its features are elaborated through detailed mathematical analysis. Thereafter, a 500-\textkV system with an SCCTL is designed in PSCAD, while the fault-location algorithm is modeled in MATLAB. The proposed algorithm is tested through simulations covering various fault scenarios in an SCCTL. For performance evaluation, the comparative analysis of the proposed technique with a well-known existing technique is performed in this paper. [ABSTRACT FROM PUBLISHER]

Background: A non-invasive tool for tumor regression grade (TRG) evaluation is urgently needed for gastric cancer (GC) treated with neoadjuvant chemotherapy (NAC). Purpose: To develop and validate a radiomics signature (RS) to evaluate TRG for locally advanced GC after NAC and assess its prognostic value. Material and Methods: A total of 103 patients with GC treated with NAC were retrospectively recruited from April 2018 to December 2019 and were randomly allocated into a training cohort (n = 69) and a validation cohort (n = 34). Delineation was performed on both mixed and iodine-uptake images based on dual-energy computed tomography (DECT). A total of 4094 radiomics features were extracted from the pre-NAC, post-NAC, and delta feature sets. Spearman correlation and the least absolute shrinkage and selection operator were used for dimensionality reduction. Multivariable logistic regression was used for TRG evaluation and generated the optimal RS. Kaplan–Meier survival analysis with the log-rank test was implemented in an independent cohort of 40 patients to validate the prognostic value of the optimal RS. Results: Three, five, and six radiomics features were finally selected for the pre-NAC, post-NAC, and delta feature sets. The delta model demonstrated the best performance in assessing TRG in both the training and the validation cohorts (AUCs=0.91 and 0.76, respectively; P >0.1). The optimal RS from the delta model showed a significant capability to predict survival in the independent cohort (P <0.05). Conclusion: Delta radiomics based on DECT images serves as a potential biomarker for TRG evaluation and shows prognostic value for patients with GC treated with NAC. [ABSTRACT FROM AUTHOR]

A hybrid structure of GaN/Ga2O3 microrods was fabricated on carbon cloth (CC) using a hydrothermal process combined with a high-temperature nitridation followed by an air annealing process. By elevating the post-annealing temperature to 500 °C, both electron density (ND) and specific capacitance (Ca) of the composite electrode were significantly enhanced. Symmetric SCs assembled with GaN/CC-500 showed great potential in both 1 M H2SO4 aqueous solution and a PVA–H2SO4 gel-like electrolyte. The aqueous symmetric GaN/CC-500 SC exhibited an excellent capacitance (1301.20 mF cm−2, 0.5 mA cm−2), high rate capability (75.23% of capacitance retention at 10 mA cm−2), outstanding cycling stability (77.27% of capacitance retention after 20 000 cycles, 10 mA cm−2), and large energy storage capability (27.53 μW h cm−2 of energy density, 0.10 mW cm−2 of power density). All-solid-state symmetric GaN/CC-500 SC also manifested a high capacitance (1183.35 mF cm−2, 0.5 mA cm−2) and good rate capability (53.98% capacitance retention, 10 mA cm−2). The high electrochemical performance of the GaN/CC-500 electrode is attributed to the GaN/Ga2O3 hybrid structure, with α-Ga2O3 providing absorption/redox active sites on the surface, and the heavily oxygen-doped GaN enabling fast electron transport. The microrods with the GaN/Ga2O3 hybrid structure as the active material for solid SCs can deliver an energy density of 0.58 W h kg−1 (3.54 mW h cm−3) with a power density of 154 W kg−1 (0.94 W cm−3). The mechanism identified in this work would be helpful in designing GaN-based energy storage devices with better performances in the future. [ABSTRACT FROM AUTHOR]

Neuronal studies have shown that selectively attending to a common object in one sensory modality results in facilitated processing of that object's representations in the ignored sensory modality. Thus, the audiovisual (AV) integration of common objects can be observed under modality-specific selective attention. However, little is known about whether this AV integration can also occur under increased attentional load conditions. Additionally, whether semantic associations between multisensory features of common objects modulate the influence of increased attentional loads on this cross-modal integration remains unknown. In the present study, participants completed an AV integration task (ignored auditory stimuli) under various attentional load conditions: no load, low load, and high load. The semantic associations between AV stimuli were composed of animal pictures presented concurrently with semantically congruent, semantically incongruent, or semantically unrelated auditory stimuli. Our results demonstrated that attentional loads did not disrupt the integration of semantically congruent AV stimuli but suppressed the potential alertness effects induced by incongruent or unrelated auditory stimuli under the condition of modality-specific selective attention. These findings highlight the critical role of semantic association between AV stimuli in modulating the effect of attentional loads on the AV integration of modality-specific selective attention. [ABSTRACT FROM AUTHOR]

Objectives: To investigate the perivascular fat attenuation index (FAI) in association with epicardial adipose tissue (EAT) parameters and its distribution over the entire coronary vasculature in patients with known or suspected coronary artery disease (CAD). Methods: Patients with known or suspected CAD who underwent coronary computed tomography angiography from January 1, 2019, to June 1, 2019, were retrospectively included. The perivascular FAI was quantified on four main epicardial coronary arteries and seven coronary segments. Moreover, EAT density and volume were measured. Results: We included 192 consecutive patients (55 without coronary plaque [mean age 46.4 ± 13.2 years, 69.1% male] and 137 with coronary plaque [mean age 57.9 ± 13.0 years, 84.7% male]). EAT density was lower than perivascular FAI in both groups, but they exhibited substantial correlation (− 83.33 ± 4.54 vs. − 78.22 ± 6.52 HU, p < 0.001; r = 0.667 in plaque− patients and − 83.11 ± 4.48 vs. − 77.81 ± 5.63 HU, p < 0.001; r = 0.778 in plaque+ patients). The left main coronary artery had the highest perivascular FAI, followed by the left circumflex artery. The perivascular FAI in proximal segments was significantly higher compared to that in distal segments (all p < 0.05). Furthermore, the presence of plaque did not alter perivascular FAI on the patient or segmental level. Conclusion: The perivascular FAI was significantly higher than EAT density and correlated substantially with EAT density. The perivascular FAI distribution over the entire coronary tree varied and prompted for vessel-specific or segment-specific thresholds to determine abnormal perivascular FAI in practice. Key Points: • The perivascular FAI correlated well with EAT density and had higher values than EAT density. • The distributions of perivascular FAI differ between coronary vessels or segments; considering segment and vessel confounding factors while conducting a perivascular FAI study is necessary. • No significant difference of perivascular FAI was observed between patients without and with coronary plaque, nor between coronary segments without plaque and those with plaque. [ABSTRACT FROM AUTHOR]

Objectives: This study examines the effectiveness of dual-energy CT (DECT) delayed-phase extracellular volume (ECV) fraction in predicting tumor regression grade (TRG) in far-advanced gastric cancer (FAGC) patients receiving preoperative immuno-chemotherapy.A retrospective analysis was performed on far-advanced gastric adenocarcinoma patients treated with preoperative immuno-chemotherapy at our institution from August 2019 to March 2023. Patients were categorized based on their TRG into pathological complete response (pCR) and non-pCR groups. ECV was determined using the delayed-phase iodine maps. In addition, tumor iodine densities and standardized iodine ratios were meticulously analyzed using the triple-phase enhanced iodine maps. Univariate analysis with five-fold cross-validation and Spearman correlation determined DECT parameters and clinical indicators association with pCR. The predictive accuracy of these parameters for pCR was evaluated using a weighted logistic regression model with five-fold cross-validation.Of the 88 patients enrolled (mean age 60.8 ± 11.1 years, 63 males), 21 (23.9%) achieved pCR. Univariate analysis indicated ECV’s significant role in differentiating between pCR and non-pCR groups (average p value = 0.021). In the logistic regression model, ECV independently predicted pCR with an average odds ratio of 0.911 (95% confidence interval, 0.798–0.994). The model, incorporating ECV, tumor area, and IDAV (the relative change rate of iodine density from venous phase to arterial phase), showed an average area under curves (AUCs) of 0.780 (0.770–0.791) and 0.766 (0.731–0.800) for the training and validation sets, respectively, in predicting pCR.DECT-derived ECV fraction is a valuable predictor of TRG in FAGC patients undergoing preoperative immuno-chemotherapy.This study demonstrates that DECT-derived extracellular volume fraction is a reliable predictor for pathological complete response in far-advanced gastric cancer patients receiving preoperative immuno-chemotherapy, offering a noninvasive tool for identifying potential treatment beneficiaries.Materials and methods: This study examines the effectiveness of dual-energy CT (DECT) delayed-phase extracellular volume (ECV) fraction in predicting tumor regression grade (TRG) in far-advanced gastric cancer (FAGC) patients receiving preoperative immuno-chemotherapy.A retrospective analysis was performed on far-advanced gastric adenocarcinoma patients treated with preoperative immuno-chemotherapy at our institution from August 2019 to March 2023. Patients were categorized based on their TRG into pathological complete response (pCR) and non-pCR groups. ECV was determined using the delayed-phase iodine maps. In addition, tumor iodine densities and standardized iodine ratios were meticulously analyzed using the triple-phase enhanced iodine maps. Univariate analysis with five-fold cross-validation and Spearman correlation determined DECT parameters and clinical indicators association with pCR. The predictive accuracy of these parameters for pCR was evaluated using a weighted logistic regression model with five-fold cross-validation.Of the 88 patients enrolled (mean age 60.8 ± 11.1 years, 63 males), 21 (23.9%) achieved pCR. Univariate analysis indicated ECV’s significant role in differentiating between pCR and non-pCR groups (average p value = 0.021). In the logistic regression model, ECV independently predicted pCR with an average odds ratio of 0.911 (95% confidence interval, 0.798–0.994). The model, incorporating ECV, tumor area, and IDAV (the relative change rate of iodine density from venous phase to arterial phase), showed an average area under curves (AUCs) of 0.780 (0.770–0.791) and 0.766 (0.731–0.800) for the training and validation sets, respectively, in predicting pCR.DECT-derived ECV fraction is a valuable predictor of TRG in FAGC patients undergoing preoperative immuno-chemotherapy.This study demonstrates that DECT-derived extracellular volume fraction is a reliable predictor for pathological complete response in far-advanced gastric cancer patients receiving preoperative immuno-chemotherapy, offering a noninvasive tool for identifying potential treatment beneficiaries.Results: This study examines the effectiveness of dual-energy CT (DECT) delayed-phase extracellular volume (ECV) fraction in predicting tumor regression grade (TRG) in far-advanced gastric cancer (FAGC) patients receiving preoperative immuno-chemotherapy.A retrospective analysis was performed on far-advanced gastric adenocarcinoma patients treated with preoperative immuno-chemotherapy at our institution from August 2019 to March 2023. Patients were categorized based on their TRG into pathological complete response (pCR) and non-pCR groups. ECV was determined using the delayed-phase iodine maps. In addition, tumor iodine densities and standardized iodine ratios were meticulously analyzed using the triple-phase enhanced iodine maps. Univariate analysis with five-fold cross-validation and Spearman correlation determined DECT parameters and clinical indicators association with pCR. The predictive accuracy of these parameters for pCR was evaluated using a weighted logistic regression model with five-fold cross-validation.Of the 88 patients enrolled (mean age 60.8 ± 11.1 years, 63 males), 21 (23.9%) achieved pCR. Univariate analysis indicated ECV’s significant role in differentiating between pCR and non-pCR groups (average p value = 0.021). In the logistic regression model, ECV independently predicted pCR with an average odds ratio of 0.911 (95% confidence interval, 0.798–0.994). The model, incorporating ECV, tumor area, and IDAV (the relative change rate of iodine density from venous phase to arterial phase), showed an average area under curves (AUCs) of 0.780 (0.770–0.791) and 0.766 (0.731–0.800) for the training and validation sets, respectively, in predicting pCR.DECT-derived ECV fraction is a valuable predictor of TRG in FAGC patients undergoing preoperative immuno-chemotherapy.This study demonstrates that DECT-derived extracellular volume fraction is a reliable predictor for pathological complete response in far-advanced gastric cancer patients receiving preoperative immuno-chemotherapy, offering a noninvasive tool for identifying potential treatment beneficiaries.Conclusion: This study examines the effectiveness of dual-energy CT (DECT) delayed-phase extracellular volume (ECV) fraction in predicting tumor regression grade (TRG) in far-advanced gastric cancer (FAGC) patients receiving preoperative immuno-chemotherapy.A retrospective analysis was performed on far-advanced gastric adenocarcinoma patients treated with preoperative immuno-chemotherapy at our institution from August 2019 to March 2023. Patients were categorized based on their TRG into pathological complete response (pCR) and non-pCR groups. ECV was determined using the delayed-phase iodine maps. In addition, tumor iodine densities and standardized iodine ratios were meticulously analyzed using the triple-phase enhanced iodine maps. Univariate analysis with five-fold cross-validation and Spearman correlation determined DECT parameters and clinical indicators association with pCR. The predictive accuracy of these parameters for pCR was evaluated using a weighted logistic regression model with five-fold cross-validation.Of the 88 patients enrolled (mean age 60.8 ± 11.1 years, 63 males), 21 (23.9%) achieved pCR. Univariate analysis indicated ECV’s significant role in differentiating between pCR and non-pCR groups (average p value = 0.021). In the logistic regression model, ECV independently predicted pCR with an average odds ratio of 0.911 (95% confidence interval, 0.798–0.994). The model, incorporating ECV, tumor area, and IDAV (the relative change rate of iodine density from venous phase to arterial phase), showed an average area under curves (AUCs) of 0.780 (0.770–0.791) and 0.766 (0.731–0.800) for the training and validation sets, respectively, in predicting pCR.DECT-derived ECV fraction is a valuable predictor of TRG in FAGC patients undergoing preoperative immuno-chemotherapy.This study demonstrates that DECT-derived extracellular volume fraction is a reliable predictor for pathological complete response in far-advanced gastric cancer patients receiving preoperative immuno-chemotherapy, offering a noninvasive tool for identifying potential treatment beneficiaries.Clinical relevance statement: This study examines the effectiveness of dual-energy CT (DECT) delayed-phase extracellular volume (ECV) fraction in predicting tumor regression grade (TRG) in far-advanced gastric cancer (FAGC) patients receiving preoperative immuno-chemotherapy.A retrospective analysis was performed on far-advanced gastric adenocarcinoma patients treated with preoperative immuno-chemotherapy at our institution from August 2019 to March 2023. Patients were categorized based on their TRG into pathological complete response (pCR) and non-pCR groups. ECV was determined using the delayed-phase iodine maps. In addition, tumor iodine densities and standardized iodine ratios were meticulously analyzed using the triple-phase enhanced iodine maps. Univariate analysis with five-fold cross-validation and Spearman correlation determined DECT parameters and clinical indicators association with pCR. The predictive accuracy of these parameters for pCR was evaluated using a weighted logistic regression model with five-fold cross-validation.Of the 88 patients enrolled (mean age 60.8 ± 11.1 years, 63 males), 21 (23.9%) achieved pCR. Univariate analysis indicated ECV’s significant role in differentiating between pCR and non-pCR groups (average p value = 0.021). In the logistic regression model, ECV independently predicted pCR with an average odds ratio of 0.911 (95% confidence interval, 0.798–0.994). The model, incorporating ECV, tumor area, and IDAV (the relative change rate of iodine density from venous phase to arterial phase), showed an average area under curves (AUCs) of 0.780 (0.770–0.791) and 0.766 (0.731–0.800) for the training and validation sets, respectively, in predicting pCR.DECT-derived ECV fraction is a valuable predictor of TRG in FAGC patients undergoing preoperative immuno-chemotherapy.This study demonstrates that DECT-derived extracellular volume fraction is a reliable predictor for pathological complete response in far-advanced gastric cancer patients receiving preoperative immuno-chemotherapy, offering a noninvasive tool for identifying potential treatment beneficiaries. [ABSTRACT FROM AUTHOR]

• The study explored whether the improvement in clinical symptoms in OCD patients after CBT is associated with changes in functional connectivity of amygdala subregions and whether these changes can serve as potential predictors of long-term treatment efficacy. • We used receiver operating characteristic (ROC) curves were used to assess the sensitivity and specificity of differences in baseline-period FC in distinguishing effective from ineffective groups and remission from nonremission groups. In the presence of differences in YBOCS at baseline, to determine whether baseline YBOCS had an effect on treatment outcome, we performed dichotomous logistic regression analyses with whether CBT was effective as the dependent variable as well as regression analyses with CBT after treatment as the dependent variable. • We found that the functional connectivity between the left basolateral amygdala and the left superior temporal gyrus can predict the long-term efficacy of CBT. Cognitive behavioral therapy (CBT) is considered as the first-line treatment for obsessive-compulsive disorder (OCD). However, the underlying neural mechanisms through which CBT exerts its effects in OCD remain unclear. This study aims to investigate whether the improvement of clinical symptoms in OCD patients after CBT treatment is associated with changes in resting-state functional connectivity (FC) of the amygdala subregion, and whether these changes can be served as potential predictors of four-months treatment efficacy. We collected resting-state functional magnetic resonance imaging (rs-fMRI) data from 57 OCD patients and 50 healthy subjects at baseline. In the patient group, rs-fMRI was also obtained after completion of an 8-week CBT treatment and 4 months post-treatment. A whole-brain rsFC analysis was conducted using the amygdala subregion as the seed point. We analyzed the FC patterns in relation to 4 months clinical outcomes to elucidate the long-term efficacy of CBT in OCD patients. Treatment responseat at pre-treatment was found to be associated with reduced rsFC between the left basolateral amygdala(BLA)and left superior temporal gyrus(STG) at baseline. Lower pre-treatment FC were negatively correlated with the severity of OCD symptoms as measured by the Yale-Brown Obsessive Compulsive Severity Scale (Y-BOCS). Moreover, the area under the receiver operating characteristic (ROC) curve for the FC between the left BLA and STG at the end of treatment was 73.0% and 70.4% for the effective-ineffective and remitted or unremitted groups, respectively. At the 4-month follow-up, the area under the ROC curve for the effective-ineffective and remitted or unremitted groups was 83.9% and 76.5%, respectively. These findings suggest that brain functional activity in patients with OCD can predict treatment response to CBT, and longitudinal changes in relevant brain functional activity following CBT treatment are associated with treatment response in OCD. [ABSTRACT FROM AUTHOR]

Highlights: [•] A new method for nanomolar NAC determination with LOD of 50nM was reported. [•] The combined mechanism for NAC quenching with static dominating was suggested. [•] DNA-Ag NC structure changed with addition of NAC, proved by spectroscopic studies. [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to compare the image quality and diagnostic performance of standard-resolution (SR) and ultra-high-resolution (UHR) coronary CT angiography (CCTA) based on photon-counting detector CT (PCD-CT) of coronary stents and explore the best reconstruction kernel for stent imaging.From July 2023 to September 2023, patients were enrolled to undergo CCTA using a dual-source PCD-CT system after coronary angioplasty with stent placement. SR images with a slice thickness/increment of 0.6/0.4 mm were reconstructed using a vascular kernel (Bv48), while UHR images with a slice thickness/increment of 0.2/0.2 mm were reconstructed using vascular kernels of six sharpness levels (Bv48, Bv56, Bv60, Bv64, Bv72, and Bv76). The in-stent lumen diameters were evaluated. Subjective image quality was also evaluated by a 5-point Likert scale. Invasive coronary angiography was conducted in 12 patients (25 stents).Sixty-nine patients (68.0 [61.0, 73.0] years, 46 males) with 131 stents were included. All UHR images had significantly larger in-stent lumen diameter than SR images (p < 0.001). Specifically, UHR-Bv72 and UHR-Bv76 for in-stent lumen diameter (2.17 [1.93, 2.63] mm versus 2.20 [1.93, 2.59] mm) ranked the two best kernels. The subjective analysis demonstrated that UHR-Bv72 images had the most pronounced effect on reducing blooming artifacts, showcasing in-stent lumen and stent demonstration, and diagnostic confidence (p < 0.001). Furthermore, SR and UHR-Bv72 images showed a diagnostic accuracy of 78.3% (95% confidence interval [CI]: 56.3%–92.5%) and 88.0% (95%CI: 68.8%–97.5%), respectively.UHR CCTA by PCD-CT leads to significantly improved visualization and diagnostic performance of coronary stents, and Bv72 is the optimal reconstruction kernel showing the stent struts and in-stent lumen.The significantly improved visualization of coronary stents using ultra-high resolution CCTA could increase the diagnostic accuracy for in-stent restenosis and avoid unnecessary invasive quantitative coronary angiography, thus changing the clinical management for patients after percutaneous coronary intervention.Coronary stent imaging is challenging with energy-integrating detector CT due to “blooming artifacts.”UHR images using a PCD-CTenhanced coronary stent visualization.UHR coronary stent imaging demonstrated improved diagnostic accuracy in clinical settings.Coronary stent imaging is challenging with energy-integrating detector CT due to “blooming artifacts.”UHR images using a PCD-CTenhanced coronary stent visualization.UHR coronary stent imaging demonstrated improved diagnostic accuracy in clinical settings.Methods: This study aimed to compare the image quality and diagnostic performance of standard-resolution (SR) and ultra-high-resolution (UHR) coronary CT angiography (CCTA) based on photon-counting detector CT (PCD-CT) of coronary stents and explore the best reconstruction kernel for stent imaging.From July 2023 to September 2023, patients were enrolled to undergo CCTA using a dual-source PCD-CT system after coronary angioplasty with stent placement. SR images with a slice thickness/increment of 0.6/0.4 mm were reconstructed using a vascular kernel (Bv48), while UHR images with a slice thickness/increment of 0.2/0.2 mm were reconstructed using vascular kernels of six sharpness levels (Bv48, Bv56, Bv60, Bv64, Bv72, and Bv76). The in-stent lumen diameters were evaluated. Subjective image quality was also evaluated by a 5-point Likert scale. Invasive coronary angiography was conducted in 12 patients (25 stents).Sixty-nine patients (68.0 [61.0, 73.0] years, 46 males) with 131 stents were included. All UHR images had significantly larger in-stent lumen diameter than SR images (p < 0.001). Specifically, UHR-Bv72 and UHR-Bv76 for in-stent lumen diameter (2.17 [1.93, 2.63] mm versus 2.20 [1.93, 2.59] mm) ranked the two best kernels. The subjective analysis demonstrated that UHR-Bv72 images had the most pronounced effect on reducing blooming artifacts, showcasing in-stent lumen and stent demonstration, and diagnostic confidence (p < 0.001). Furthermore, SR and UHR-Bv72 images showed a diagnostic accuracy of 78.3% (95% confidence interval [CI]: 56.3%–92.5%) and 88.0% (95%CI: 68.8%–97.5%), respectively.UHR CCTA by PCD-CT leads to significantly improved visualization and diagnostic performance of coronary stents, and Bv72 is the optimal reconstruction kernel showing the stent struts and in-stent lumen.The significantly improved visualization of coronary stents using ultra-high resolution CCTA could increase the diagnostic accuracy for in-stent restenosis and avoid unnecessary invasive quantitative coronary angiography, thus changing the clinical management for patients after percutaneous coronary intervention.Coronary stent imaging is challenging with energy-integrating detector CT due to “blooming artifacts.”UHR images using a PCD-CTenhanced coronary stent visualization.UHR coronary stent imaging demonstrated improved diagnostic accuracy in clinical settings.Coronary stent imaging is challenging with energy-integrating detector CT due to “blooming artifacts.”UHR images using a PCD-CTenhanced coronary stent visualization.UHR coronary stent imaging demonstrated improved diagnostic accuracy in clinical settings.Results: This study aimed to compare the image quality and diagnostic performance of standard-resolution (SR) and ultra-high-resolution (UHR) coronary CT angiography (CCTA) based on photon-counting detector CT (PCD-CT) of coronary stents and explore the best reconstruction kernel for stent imaging.From July 2023 to September 2023, patients were enrolled to undergo CCTA using a dual-source PCD-CT system after coronary angioplasty with stent placement. SR images with a slice thickness/increment of 0.6/0.4 mm were reconstructed using a vascular kernel (Bv48), while UHR images with a slice thickness/increment of 0.2/0.2 mm were reconstructed using vascular kernels of six sharpness levels (Bv48, Bv56, Bv60, Bv64, Bv72, and Bv76). The in-stent lumen diameters were evaluated. Subjective image quality was also evaluated by a 5-point Likert scale. Invasive coronary angiography was conducted in 12 patients (25 stents).Sixty-nine patients (68.0 [61.0, 73.0] years, 46 males) with 131 stents were included. All UHR images had significantly larger in-stent lumen diameter than SR images (p < 0.001). Specifically, UHR-Bv72 and UHR-Bv76 for in-stent lumen diameter (2.17 [1.93, 2.63] mm versus 2.20 [1.93, 2.59] mm) ranked the two best kernels. The subjective analysis demonstrated that UHR-Bv72 images had the most pronounced effect on reducing blooming artifacts, showcasing in-stent lumen and stent demonstration, and diagnostic confidence (p < 0.001). Furthermore, SR and UHR-Bv72 images showed a diagnostic accuracy of 78.3% (95% confidence interval [CI]: 56.3%–92.5%) and 88.0% (95%CI: 68.8%–97.5%), respectively.UHR CCTA by PCD-CT leads to significantly improved visualization and diagnostic performance of coronary stents, and Bv72 is the optimal reconstruction kernel showing the stent struts and in-stent lumen.The significantly improved visualization of coronary stents using ultra-high resolution CCTA could increase the diagnostic accuracy for in-stent restenosis and avoid unnecessary invasive quantitative coronary angiography, thus changing the clinical management for patients after percutaneous coronary intervention.Coronary stent imaging is challenging with energy-integrating detector CT due to “blooming artifacts.”UHR images using a PCD-CTenhanced coronary stent visualization.UHR coronary stent imaging demonstrated improved diagnostic accuracy in clinical settings.Coronary stent imaging is challenging with energy-integrating detector CT due to “blooming artifacts.”UHR images using a PCD-CTenhanced coronary stent visualization.UHR coronary stent imaging demonstrated improved diagnostic accuracy in clinical settings.Conclusion: This study aimed to compare the image quality and diagnostic performance of standard-resolution (SR) and ultra-high-resolution (UHR) coronary CT angiography (CCTA) based on photon-counting detector CT (PCD-CT) of coronary stents and explore the best reconstruction kernel for stent imaging.From July 2023 to September 2023, patients were enrolled to undergo CCTA using a dual-source PCD-CT system after coronary angioplasty with stent placement. SR images with a slice thickness/increment of 0.6/0.4 mm were reconstructed using a vascular kernel (Bv48), while UHR images with a slice thickness/increment of 0.2/0.2 mm were reconstructed using vascular kernels of six sharpness levels (Bv48, Bv56, Bv60, Bv64, Bv72, and Bv76). The in-stent lumen diameters were evaluated. Subjective image quality was also evaluated by a 5-point Likert scale. Invasive coronary angiography was conducted in 12 patients (25 stents).Sixty-nine patients (68.0 [61.0, 73.0] years, 46 males) with 131 stents were included. All UHR images had significantly larger in-stent lumen diameter than SR images (p < 0.001). Specifically, UHR-Bv72 and UHR-Bv76 for in-stent lumen diameter (2.17 [1.93, 2.63] mm versus 2.20 [1.93, 2.59] mm) ranked the two best kernels. The subjective analysis demonstrated that UHR-Bv72 images had the most pronounced effect on reducing blooming artifacts, showcasing in-stent lumen and stent demonstration, and diagnostic confidence (p < 0.001). Furthermore, SR and UHR-Bv72 images showed a diagnostic accuracy of 78.3% (95% confidence interval [CI]: 56.3%–92.5%) and 88.0% (95%CI: 68.8%–97.5%), respectively.UHR CCTA by PCD-CT leads to significantly improved visualization and diagnostic performance of coronary stents, and Bv72 is the optimal reconstruction kernel showing the stent struts and in-stent lumen.The significantly improved visualization of coronary stents using ultra-high resolution CCTA could increase the diagnostic accuracy for in-stent restenosis and avoid unnecessary invasive quantitative coronary angiography, thus changing the clinical management for patients after percutaneous coronary intervention.Coronary stent imaging is challenging with energy-integrating detector CT due to “blooming artifacts.”UHR images using a PCD-CTenhanced coronary stent visualization.UHR coronary stent imaging demonstrated improved diagnostic accuracy in clinical settings.Coronary stent imaging is challenging with energy-integrating detector CT due to “blooming artifacts.”UHR images using a PCD-CTenhanced coronary stent visualization.UHR coronary stent imaging demonstrated improved diagnostic accuracy in clinical settings.Clinical relevance statement: This study aimed to compare the image quality and diagnostic performance of standard-resolution (SR) and ultra-high-resolution (UHR) coronary CT angiography (CCTA) based on photon-counting detector CT (PCD-CT) of coronary stents and explore the best reconstruction kernel for stent imaging.From July 2023 to September 2023, patients were enrolled to undergo CCTA using a dual-source PCD-CT system after coronary angioplasty with stent placement. SR images with a slice thickness/increment of 0.6/0.4 mm were reconstructed using a vascular kernel (Bv48), while UHR images with a slice thickness/increment of 0.2/0.2 mm were reconstructed using vascular kernels of six sharpness levels (Bv48, Bv56, Bv60, Bv64, Bv72, and Bv76). The in-stent lumen diameters were evaluated. Subjective image quality was also evaluated by a 5-point Likert scale. Invasive coronary angiography was conducted in 12 patients (25 stents).Sixty-nine patients (68.0 [61.0, 73.0] years, 46 males) with 131 stents were included. All UHR images had significantly larger in-stent lumen diameter than SR images (p < 0.001). Specifically, UHR-Bv72 and UHR-Bv76 for in-stent lumen diameter (2.17 [1.93, 2.63] mm versus 2.20 [1.93, 2.59] mm) ranked the two best kernels. The subjective analysis demonstrated that UHR-Bv72 images had the most pronounced effect on reducing blooming artifacts, showcasing in-stent lumen and stent demonstration, and diagnostic confidence (p < 0.001). Furthermore, SR and UHR-Bv72 images showed a diagnostic accuracy of 78.3% (95% confidence interval [CI]: 56.3%–92.5%) and 88.0% (95%CI: 68.8%–97.5%), respectively.UHR CCTA by PCD-CT leads to significantly improved visualization and diagnostic performance of coronary stents, and Bv72 is the optimal reconstruction kernel showing the stent struts and in-stent lumen.The significantly improved visualization of coronary stents using ultra-high resolution CCTA could increase the diagnostic accuracy for in-stent restenosis and avoid unnecessary invasive quantitative coronary angiography, thus changing the clinical management for patients after percutaneous coronary intervention.Coronary stent imaging is challenging with energy-integrating detector CT due to “blooming artifacts.”UHR images using a PCD-CTenhanced coronary stent visualization.UHR coronary stent imaging demonstrated improved diagnostic accuracy in clinical settings.Coronary stent imaging is challenging with energy-integrating detector CT due to “blooming artifacts.”UHR images using a PCD-CTenhanced coronary stent visualization.UHR coronary stent imaging demonstrated improved diagnostic accuracy in clinical settings.Key Points: This study aimed to compare the image quality and diagnostic performance of standard-resolution (SR) and ultra-high-resolution (UHR) coronary CT angiography (CCTA) based on photon-counting detector CT (PCD-CT) of coronary stents and explore the best reconstruction kernel for stent imaging.From July 2023 to September 2023, patients were enrolled to undergo CCTA using a dual-source PCD-CT system after coronary angioplasty with stent placement. SR images with a slice thickness/increment of 0.6/0.4 mm were reconstructed using a vascular kernel (Bv48), while UHR images with a slice thickness/increment of 0.2/0.2 mm were reconstructed using vascular kernels of six sharpness levels (Bv48, Bv56, Bv60, Bv64, Bv72, and Bv76). The in-stent lumen diameters were evaluated. Subjective image quality was also evaluated by a 5-point Likert scale. Invasive coronary angiography was conducted in 12 patients (25 stents).Sixty-nine patients (68.0 [61.0, 73.0] years, 46 males) with 131 stents were included. All UHR images had significantly larger in-stent lumen diameter than SR images (p < 0.001). Specifically, UHR-Bv72 and UHR-Bv76 for in-stent lumen diameter (2.17 [1.93, 2.63] mm versus 2.20 [1.93, 2.59] mm) ranked the two best kernels. The subjective analysis demonstrated that UHR-Bv72 images had the most pronounced effect on reducing blooming artifacts, showcasing in-stent lumen and stent demonstration, and diagnostic confidence (p < 0.001). Furthermore, SR and UHR-Bv72 images showed a diagnostic accuracy of 78.3% (95% confidence interval [CI]: 56.3%–92.5%) and 88.0% (95%CI: 68.8%–97.5%), respectively.UHR CCTA by PCD-CT leads to significantly improved visualization and diagnostic performance of coronary stents, and Bv72 is the optimal reconstruction kernel showing the stent struts and in-stent lumen.The significantly improved visualization of coronary stents using ultra-high resolution CCTA could increase the diagnostic accuracy for in-stent restenosis and avoid unnecessary invasive quantitative coronary angiography, thus changing the clinical management for patients after percutaneous coronary intervention.Coronary stent imaging is challenging with energy-integrating detector CT due to “blooming artifacts.”UHR images using a PCD-CTenhanced coronary stent visualization.UHR coronary stent imaging demonstrated improved diagnostic accuracy in clinical settings.Coronary stent imaging is challenging with energy-integrating detector CT due to “blooming artifacts.”UHR images using a PCD-CTenhanced coronary stent visualization.UHR coronary stent imaging demonstrated improved diagnostic accuracy in clinical settings. [ABSTRACT FROM AUTHOR]

Objectives: To compare the diagnostic performance of machine learning (ML)–based computed tomography–derived fractional flow reserve (CT-FFR) and cardiac magnetic resonance (MR) perfusion mapping for functional assessment of coronary stenosis.Between October 2020 and March 2022, consecutive participants with stable coronary artery disease (CAD) were prospectively enrolled and underwent coronary CTA, cardiac MR, and invasive fractional flow reserve (FFR) within 2 weeks. Cardiac MR perfusion analysis was quantified by stress myocardial blood flow (MBF) and myocardial perfusion reserve (MPR). Hemodynamically significant stenosis was defined as FFR ≤ 0.8 or > 90% stenosis on invasive coronary angiography (ICA). The diagnostic performance of CT-FFR, MBF, and MPR was compared, using invasive FFR as a reference.The study protocol was completed in 110 participants (mean age, 62 years ± 8; 73 men), and hemodynamically significant stenosis was detected in 36 (33%). Among the quantitative perfusion indices, MPR had the largest area under receiver operating characteristic curve (AUC) (0.90) for identifying hemodynamically significant stenosis, which is in comparison with ML-based CT-FFR on the vessel level (AUC 0.89, p = 0.71), with comparable sensitivity (89% vs 79%, p = 0.20), specificity (87% vs 84%, p = 0.48), and accuracy (88% vs 83%, p = 0.24). However, MPR outperformed ML-based CT-FFR on the patient level (AUC 0.96 vs 0.86, p = 0.03), with improved specificity (95% vs 82%, p = 0.01) and accuracy (95% vs 81%, p < 0.01).ML-based CT-FFR and quantitative cardiac MR showed comparable diagnostic performance in detecting vessel-specific hemodynamically significant stenosis, whereas quantitative perfusion mapping had a favorable performance in per-patient analysis.ML-based CT-FFR and MPR derived from cardiac MR performed well in diagnosing vessel-specific hemodynamically significant stenosis, both of which showed no statistical discrepancy with each other.• Both machine learning (ML)–based computed tomography–derived fractional flow reserve (CT-FFR) and quantitative perfusion cardiac MR performed well in the detection of hemodynamically significant stenosis.• Compared with stress myocardial blood flow (MBF) from quantitative perfusion cardiac MR, myocardial perfusion reserve (MPR) provided higher diagnostic performance for detecting hemodynamically significant coronary artery stenosis.• ML-based CT-FFR and MPR from quantitative cardiac MR perfusion yielded similar diagnostic performance in assessing vessel-specific hemodynamically significant stenosis, whereas MPR had a favorable performance in per-patient analysis.Methods: To compare the diagnostic performance of machine learning (ML)–based computed tomography–derived fractional flow reserve (CT-FFR) and cardiac magnetic resonance (MR) perfusion mapping for functional assessment of coronary stenosis.Between October 2020 and March 2022, consecutive participants with stable coronary artery disease (CAD) were prospectively enrolled and underwent coronary CTA, cardiac MR, and invasive fractional flow reserve (FFR) within 2 weeks. Cardiac MR perfusion analysis was quantified by stress myocardial blood flow (MBF) and myocardial perfusion reserve (MPR). Hemodynamically significant stenosis was defined as FFR ≤ 0.8 or > 90% stenosis on invasive coronary angiography (ICA). The diagnostic performance of CT-FFR, MBF, and MPR was compared, using invasive FFR as a reference.The study protocol was completed in 110 participants (mean age, 62 years ± 8; 73 men), and hemodynamically significant stenosis was detected in 36 (33%). Among the quantitative perfusion indices, MPR had the largest area under receiver operating characteristic curve (AUC) (0.90) for identifying hemodynamically significant stenosis, which is in comparison with ML-based CT-FFR on the vessel level (AUC 0.89, p = 0.71), with comparable sensitivity (89% vs 79%, p = 0.20), specificity (87% vs 84%, p = 0.48), and accuracy (88% vs 83%, p = 0.24). However, MPR outperformed ML-based CT-FFR on the patient level (AUC 0.96 vs 0.86, p = 0.03), with improved specificity (95% vs 82%, p = 0.01) and accuracy (95% vs 81%, p < 0.01).ML-based CT-FFR and quantitative cardiac MR showed comparable diagnostic performance in detecting vessel-specific hemodynamically significant stenosis, whereas quantitative perfusion mapping had a favorable performance in per-patient analysis.ML-based CT-FFR and MPR derived from cardiac MR performed well in diagnosing vessel-specific hemodynamically significant stenosis, both of which showed no statistical discrepancy with each other.• Both machine learning (ML)–based computed tomography–derived fractional flow reserve (CT-FFR) and quantitative perfusion cardiac MR performed well in the detection of hemodynamically significant stenosis.• Compared with stress myocardial blood flow (MBF) from quantitative perfusion cardiac MR, myocardial perfusion reserve (MPR) provided higher diagnostic performance for detecting hemodynamically significant coronary artery stenosis.• ML-based CT-FFR and MPR from quantitative cardiac MR perfusion yielded similar diagnostic performance in assessing vessel-specific hemodynamically significant stenosis, whereas MPR had a favorable performance in per-patient analysis.Results: To compare the diagnostic performance of machine learning (ML)–based computed tomography–derived fractional flow reserve (CT-FFR) and cardiac magnetic resonance (MR) perfusion mapping for functional assessment of coronary stenosis.Between October 2020 and March 2022, consecutive participants with stable coronary artery disease (CAD) were prospectively enrolled and underwent coronary CTA, cardiac MR, and invasive fractional flow reserve (FFR) within 2 weeks. Cardiac MR perfusion analysis was quantified by stress myocardial blood flow (MBF) and myocardial perfusion reserve (MPR). Hemodynamically significant stenosis was defined as FFR ≤ 0.8 or > 90% stenosis on invasive coronary angiography (ICA). The diagnostic performance of CT-FFR, MBF, and MPR was compared, using invasive FFR as a reference.The study protocol was completed in 110 participants (mean age, 62 years ± 8; 73 men), and hemodynamically significant stenosis was detected in 36 (33%). Among the quantitative perfusion indices, MPR had the largest area under receiver operating characteristic curve (AUC) (0.90) for identifying hemodynamically significant stenosis, which is in comparison with ML-based CT-FFR on the vessel level (AUC 0.89, p = 0.71), with comparable sensitivity (89% vs 79%, p = 0.20), specificity (87% vs 84%, p = 0.48), and accuracy (88% vs 83%, p = 0.24). However, MPR outperformed ML-based CT-FFR on the patient level (AUC 0.96 vs 0.86, p = 0.03), with improved specificity (95% vs 82%, p = 0.01) and accuracy (95% vs 81%, p < 0.01).ML-based CT-FFR and quantitative cardiac MR showed comparable diagnostic performance in detecting vessel-specific hemodynamically significant stenosis, whereas quantitative perfusion mapping had a favorable performance in per-patient analysis.ML-based CT-FFR and MPR derived from cardiac MR performed well in diagnosing vessel-specific hemodynamically significant stenosis, both of which showed no statistical discrepancy with each other.• Both machine learning (ML)–based computed tomography–derived fractional flow reserve (CT-FFR) and quantitative perfusion cardiac MR performed well in the detection of hemodynamically significant stenosis.• Compared with stress myocardial blood flow (MBF) from quantitative perfusion cardiac MR, myocardial perfusion reserve (MPR) provided higher diagnostic performance for detecting hemodynamically significant coronary artery stenosis.• ML-based CT-FFR and MPR from quantitative cardiac MR perfusion yielded similar diagnostic performance in assessing vessel-specific hemodynamically significant stenosis, whereas MPR had a favorable performance in per-patient analysis.Conclusion: To compare the diagnostic performance of machine learning (ML)–based computed tomography–derived fractional flow reserve (CT-FFR) and cardiac magnetic resonance (MR) perfusion mapping for functional assessment of coronary stenosis.Between October 2020 and March 2022, consecutive participants with stable coronary artery disease (CAD) were prospectively enrolled and underwent coronary CTA, cardiac MR, and invasive fractional flow reserve (FFR) within 2 weeks. Cardiac MR perfusion analysis was quantified by stress myocardial blood flow (MBF) and myocardial perfusion reserve (MPR). Hemodynamically significant stenosis was defined as FFR ≤ 0.8 or > 90% stenosis on invasive coronary angiography (ICA). The diagnostic performance of CT-FFR, MBF, and MPR was compared, using invasive FFR as a reference.The study protocol was completed in 110 participants (mean age, 62 years ± 8; 73 men), and hemodynamically significant stenosis was detected in 36 (33%). Among the quantitative perfusion indices, MPR had the largest area under receiver operating characteristic curve (AUC) (0.90) for identifying hemodynamically significant stenosis, which is in comparison with ML-based CT-FFR on the vessel level (AUC 0.89, p = 0.71), with comparable sensitivity (89% vs 79%, p = 0.20), specificity (87% vs 84%, p = 0.48), and accuracy (88% vs 83%, p = 0.24). However, MPR outperformed ML-based CT-FFR on the patient level (AUC 0.96 vs 0.86, p = 0.03), with improved specificity (95% vs 82%, p = 0.01) and accuracy (95% vs 81%, p < 0.01).ML-based CT-FFR and quantitative cardiac MR showed comparable diagnostic performance in detecting vessel-specific hemodynamically significant stenosis, whereas quantitative perfusion mapping had a favorable performance in per-patient analysis.ML-based CT-FFR and MPR derived from cardiac MR performed well in diagnosing vessel-specific hemodynamically significant stenosis, both of which showed no statistical discrepancy with each other.• Both machine learning (ML)–based computed tomography–derived fractional flow reserve (CT-FFR) and quantitative perfusion cardiac MR performed well in the detection of hemodynamically significant stenosis.• Compared with stress myocardial blood flow (MBF) from quantitative perfusion cardiac MR, myocardial perfusion reserve (MPR) provided higher diagnostic performance for detecting hemodynamically significant coronary artery stenosis.• ML-based CT-FFR and MPR from quantitative cardiac MR perfusion yielded similar diagnostic performance in assessing vessel-specific hemodynamically significant stenosis, whereas MPR had a favorable performance in per-patient analysis.Clinical relevance statement: To compare the diagnostic performance of machine learning (ML)–based computed tomography–derived fractional flow reserve (CT-FFR) and cardiac magnetic resonance (MR) perfusion mapping for functional assessment of coronary stenosis.Between October 2020 and March 2022, consecutive participants with stable coronary artery disease (CAD) were prospectively enrolled and underwent coronary CTA, cardiac MR, and invasive fractional flow reserve (FFR) within 2 weeks. Cardiac MR perfusion analysis was quantified by stress myocardial blood flow (MBF) and myocardial perfusion reserve (MPR). Hemodynamically significant stenosis was defined as FFR ≤ 0.8 or > 90% stenosis on invasive coronary angiography (ICA). The diagnostic performance of CT-FFR, MBF, and MPR was compared, using invasive FFR as a reference.The study protocol was completed in 110 participants (mean age, 62 years ± 8; 73 men), and hemodynamically significant stenosis was detected in 36 (33%). Among the quantitative perfusion indices, MPR had the largest area under receiver operating characteristic curve (AUC) (0.90) for identifying hemodynamically significant stenosis, which is in comparison with ML-based CT-FFR on the vessel level (AUC 0.89, p = 0.71), with comparable sensitivity (89% vs 79%, p = 0.20), specificity (87% vs 84%, p = 0.48), and accuracy (88% vs 83%, p = 0.24). However, MPR outperformed ML-based CT-FFR on the patient level (AUC 0.96 vs 0.86, p = 0.03), with improved specificity (95% vs 82%, p = 0.01) and accuracy (95% vs 81%, p < 0.01).ML-based CT-FFR and quantitative cardiac MR showed comparable diagnostic performance in detecting vessel-specific hemodynamically significant stenosis, whereas quantitative perfusion mapping had a favorable performance in per-patient analysis.ML-based CT-FFR and MPR derived from cardiac MR performed well in diagnosing vessel-specific hemodynamically significant stenosis, both of which showed no statistical discrepancy with each other.• Both machine learning (ML)–based computed tomography–derived fractional flow reserve (CT-FFR) and quantitative perfusion cardiac MR performed well in the detection of hemodynamically significant stenosis.• Compared with stress myocardial blood flow (MBF) from quantitative perfusion cardiac MR, myocardial perfusion reserve (MPR) provided higher diagnostic performance for detecting hemodynamically significant coronary artery stenosis.• ML-based CT-FFR and MPR from quantitative cardiac MR perfusion yielded similar diagnostic performance in assessing vessel-specific hemodynamically significant stenosis, whereas MPR had a favorable performance in per-patient analysis.Key Points: To compare the diagnostic performance of machine learning (ML)–based computed tomography–derived fractional flow reserve (CT-FFR) and cardiac magnetic resonance (MR) perfusion mapping for functional assessment of coronary stenosis.Between October 2020 and March 2022, consecutive participants with stable coronary artery disease (CAD) were prospectively enrolled and underwent coronary CTA, cardiac MR, and invasive fractional flow reserve (FFR) within 2 weeks. Cardiac MR perfusion analysis was quantified by stress myocardial blood flow (MBF) and myocardial perfusion reserve (MPR). Hemodynamically significant stenosis was defined as FFR ≤ 0.8 or > 90% stenosis on invasive coronary angiography (ICA). The diagnostic performance of CT-FFR, MBF, and MPR was compared, using invasive FFR as a reference.The study protocol was completed in 110 participants (mean age, 62 years ± 8; 73 men), and hemodynamically significant stenosis was detected in 36 (33%). Among the quantitative perfusion indices, MPR had the largest area under receiver operating characteristic curve (AUC) (0.90) for identifying hemodynamically significant stenosis, which is in comparison with ML-based CT-FFR on the vessel level (AUC 0.89, p = 0.71), with comparable sensitivity (89% vs 79%, p = 0.20), specificity (87% vs 84%, p = 0.48), and accuracy (88% vs 83%, p = 0.24). However, MPR outperformed ML-based CT-FFR on the patient level (AUC 0.96 vs 0.86, p = 0.03), with improved specificity (95% vs 82%, p = 0.01) and accuracy (95% vs 81%, p < 0.01).ML-based CT-FFR and quantitative cardiac MR showed comparable diagnostic performance in detecting vessel-specific hemodynamically significant stenosis, whereas quantitative perfusion mapping had a favorable performance in per-patient analysis.ML-based CT-FFR and MPR derived from cardiac MR performed well in diagnosing vessel-specific hemodynamically significant stenosis, both of which showed no statistical discrepancy with each other.• Both machine learning (ML)–based computed tomography–derived fractional flow reserve (CT-FFR) and quantitative perfusion cardiac MR performed well in the detection of hemodynamically significant stenosis.• Compared with stress myocardial blood flow (MBF) from quantitative perfusion cardiac MR, myocardial perfusion reserve (MPR) provided higher diagnostic performance for detecting hemodynamically significant coronary artery stenosis.• ML-based CT-FFR and MPR from quantitative cardiac MR perfusion yielded similar diagnostic performance in assessing vessel-specific hemodynamically significant stenosis, whereas MPR had a favorable performance in per-patient analysis.Graphical Abstract: To compare the diagnostic performance of machine learning (ML)–based computed tomography–derived fractional flow reserve (CT-FFR) and cardiac magnetic resonance (MR) perfusion mapping for functional assessment of coronary stenosis.Between October 2020 and March 2022, consecutive participants with stable coronary artery disease (CAD) were prospectively enrolled and underwent coronary CTA, cardiac MR, and invasive fractional flow reserve (FFR) within 2 weeks. Cardiac MR perfusion analysis was quantified by stress myocardial blood flow (MBF) and myocardial perfusion reserve (MPR). Hemodynamically significant stenosis was defined as FFR ≤ 0.8 or > 90% stenosis on invasive coronary angiography (ICA). The diagnostic performance of CT-FFR, MBF, and MPR was compared, using invasive FFR as a reference.The study protocol was completed in 110 participants (mean age, 62 years ± 8; 73 men), and hemodynamically significant stenosis was detected in 36 (33%). Among the quantitative perfusion indices, MPR had the largest area under receiver operating characteristic curve (AUC) (0.90) for identifying hemodynamically significant stenosis, which is in comparison with ML-based CT-FFR on the vessel level (AUC 0.89, p = 0.71), with comparable sensitivity (89% vs 79%, p = 0.20), specificity (87% vs 84%, p = 0.48), and accuracy (88% vs 83%, p = 0.24). However, MPR outperformed ML-based CT-FFR on the patient level (AUC 0.96 vs 0.86, p = 0.03), with improved specificity (95% vs 82%, p = 0.01) and accuracy (95% vs 81%, p < 0.01).ML-based CT-FFR and quantitative cardiac MR showed comparable diagnostic performance in detecting vessel-specific hemodynamically significant stenosis, whereas quantitative perfusion mapping had a favorable performance in per-patient analysis.ML-based CT-FFR and MPR derived from cardiac MR performed well in diagnosing vessel-specific hemodynamically significant stenosis, both of which showed no statistical discrepancy with each other.• Both machine learning (ML)–based computed tomography–derived fractional flow reserve (CT-FFR) and quantitative perfusion cardiac MR performed well in the detection of hemodynamically significant stenosis.• Compared with stress myocardial blood flow (MBF) from quantitative perfusion cardiac MR, myocardial perfusion reserve (MPR) provided higher diagnostic performance for detecting hemodynamically significant coronary artery stenosis.• ML-based CT-FFR and MPR from quantitative cardiac MR perfusion yielded similar diagnostic performance in assessing vessel-specific hemodynamically significant stenosis, whereas MPR had a favorable performance in per-patient analysis. [ABSTRACT FROM AUTHOR]

Late gadolinium enhancement (LGE) derived from cardiac magnetic resonance (CMR) represents myocardial fibrosis (MF) and is associated with prognosis in hypertrophic cardiomyopathy (HCM). However, it cannot be evaluated when CMR is unavailable. Hence, we aimed to investigate the ability of radiomic features derived from coronary computed tomography angiography (CCTA) to detect the presence and extent of MF in HCM, with LGE as references. 161 patients with HCM who underwent CCTA and CMR were retrospectively enrolled and randomly divided into training (107 patients, 1712 segments) and testing cohorts (54 patients, 864 segments). Segments were obtained according to AHA 17-segment method. Radiomic features were extracted from per-segment and entire myocardium regions, and multiple machine-learning algorithms were used for radiomic signatures (Rad-sig) generation and model building. Four models were established by multivariable logistic regression using Rad-sig (R-model), clinical characteristic (C-model), echocardiography parameters (E-model), and all features integrated (Integ-model) to identify LGE/left ventricular mass ≥ 15%. The model achieved good diagnostic accuracy in both training (area under the curve [AUC]:0.81, 95% confidence interval [CI]: 0.78–0.83) and testing cohort (AUC: 0.78, 95%CI: 0.75–0.81) on a per-segment basis for the presence of MF. The Integ-model owned the highest discriminative ability for patients with LGE/left ventricular mass ≥ 15% in both training and testing cohorts with AUC of 0.94 (95%CI: 0.89–0.98) and 0.92 (95%CI: 0.85–0.99), respectively. Our radiomic models were considered as useful and complementary biomarkers for the evaluation of the presence and extent of MF on CCTA, facilitating clinical decision-making and risk stratification in HCM patients. • Radiomic features derived from CCTA are related to the presence of MF on the segment level. • Radiomic features of CCTA can strongly predict the extent of MF with LGE/left ventricular mass ≥ 15%. • Radiomic features of CCTA can potentially be a new biomarker for risk stratification of HCM. [ABSTRACT FROM AUTHOR]

Correction for 'A hybrid GaN/Ga2O3 structure anchored on carbon cloth as a high-performance electrode of supercapacitors' by Yan-Ling Hu, et al., Dalton Trans., 2022, https://doi.org/10.1039/d2dt02904a. [ABSTRACT FROM AUTHOR]

Rheumatoid arthritis (RA) is an autoimmune disease, which is characterized by inflammatory synovitis, and the subsequent destruction of articular cartilage and bone. Sinomenine is a traditional Chinese medicine, which has been employed as a clinical treatment for RA for several years in China. The present study investigated the anti-arthritic effects of sinomenine on Sprague-Dawley rats with collagen-induced arthritis (CIA). The differentially expressed proteins in serum were measured by proteomic analysis in order to generate a differentially expressed protein network. A total of 320 differentially expressed proteins were detected in the drug-treated group compared with in the control group. In the sinomenine-treated group, 79 differentially expressed proteins were detected compared with in the model group, and among these, 46 proteins were upregulated. Gene ontology analysis revealed that five functions were affected by sinomenine treatment of CIA rats compared with in the model group. In addition, Ingenuity® Pathway Analysis was used to measure enriched signaling pathways, which revealed nuclear factor-κB, histones, heat shock proteins and protein kinase B as core proteins, generating ~60 pair associations in the network. To the best of our knowledge, the present study is the first to perform proteomic analysis in sinomenine-treated CIA rats, and the results revealed that numerous targets were involved in the process. In addition, the present study provided a novel approach and evidence for exploring the biological effects of sinomenine. Therefore, the findings of the present study may provide a novel insight into the anti-RA mechanisms of sinomenine, and may justify further exploration into its function in other relevant diseases. [ABSTRACT FROM AUTHOR]

This article aims at using Artificial Neural Networks (ANNs) and linear prediction to predict the physicochemical properties of woody biomass, including gross calorific value, carbon content, and oxygen content. By analyzing 43 data groups, it was found that Multilayer Feedforward Neural Network (MLFN) with 11 nodes is the best model for predicting the gross calorific value, with a root mean square (RMS) error of 0.85; General Regression Neural Network (GRNN) is the best model for predicting the carbon content, with an RMS error of 1.66; and linear prediction is the best model for predicting the oxygen content, with an RMS error of 2.11. [ABSTRACT FROM PUBLISHER]

Advanced aging is accompanied by a decline in visuospatial attention. Previous neuroimaging and electrophysiological studies have demonstrated dysfunction in specific brain areas related to visuospatial attention. However, it is still unclear how the functional connectivity between brain regions causes the decline of visuospatial attention. Here, we combined task and rest functional magnetic resonance imaging (fMRI) to investigate the age-dependent alterations of resting-state functional connectivity within the task-related network. Twenty-three young subjects and nineteen elderly subjects participated in this study, and a modified Posner paradigm was used to define the region of interest (ROI). Our results showed that a marked reduction in the number of connections occurred with age, but this effect was not uniform throughout the brain: while there was a significant loss of communication in the anterior portion of the brain and between the anterior and posterior cerebral cortices, communication in the posterior portion of the brain was preserved. Moreover, the older adults exhibited weakened resting-state functional connectivity between the supplementary motor area and left anterior insular cortex. These findings suggest that, the disrupted functional connectivity of the brain network for visuospatial attention that occurs during normal aging may underlie the decline in cognitive performance. [ABSTRACT FROM AUTHOR]

Objective: The objective was to evaluate the normal value of left ventricular myocardial strain using the computed tomography feature-tracking technique and to explore the correlation between myocardial strains and cardiac function parameters. Methods: Participants suspected of coronary heart disease were selected from 17 August 2020 to 5 November 2020 to undergo coronary computed tomography angiography using a third-generation dual-source CT scanner. Data were imported into a commercial software (Medis) after multiphase reconstruction. The cardiac function parameters, radial (Err), circumferential (Ecc), and longitudinal strain (Ell) of the left ventricle were recorded. Results: A total of 87 normal subjects were enrolled, including 41 males and 46 females. For healthy subjects, the global radial strain (GRS), circumferential strain (GCS), and longitudinal strain (GLS) of the left ventricle were 74.5 ± 15.2%, −22.7 ± 3.0%, and −26.6 ± 3.2%, respectively. The Err and Ecc absolute values (|Ecc|) were the largest at the apex, and the |Ell| gradually increased from the base to the apex. The Err and |Ecc| were the largest in the lateral and inferior wall, respectively. |Ell| showed a clockwise decrease from the lateral wall in the short axis. Meanwhile, the GRS and |GLS| in females were higher than that in males. Multiple linear regression analysis showed that both SV and LVEF were the independent determinants of GRS, GCS, and GLS. BMI and CO were the independent determined factors of GCS. Conclusions: At a reasonable radiation dose, CT feature-tracking is a feasible and reproducible method to analyze left ventricular myocardial strain. Left ventricular myocardial strain in normal subjects varies in gender, segments, levels, and regions. [ABSTRACT FROM AUTHOR]