Link between b.c.c.-f.c.c. orientation relationship and austenite morphology in CF8M stainless steel.

Slow-cooled CF8M duplex stainless steel is used for critical parts of the primary coolant pipes of nuclear reactors. This steel can endure severe service conditions, but it tends to become more brittle upon very long-term aging (tens of years). Therefore, it is essential to understand its specific microstructure and temporal evolution. As revealed by electron backscatter diffraction (EBSD) analyses, the microstructure consists of millimetre-scale ferritic grains within which austenite lath packets have grown with preferred crystallographic orientations concerning the parent ferritic phase far from the ferrite grain boundaries. In these lath packets where the austenite phase is nucleated, the lath morphology and crystal orientation accommodate the two ferrite orientations. Globally, the Pitsch orientation relationship appears to display the best agreement with the experimental data compared with other classical relationships. The austenite lath packets are parallel plate-shaped laths, characterized by their normal n. A novel methodology is introduced to elucidate the expected relationship between n and the crystallographic orientation given the coarse interfaces, even though n is only partly known from the observation surface, in contrast to the 3D crystal orientations measured by EBSD. The distribution of retrieved normals n is shown to be concentrated over a set of discrete orientations. Assuming that the ferrite and austenite obey the Pitsch orientation relationship, the determined lath normals are close to an invariant direction of the parent phase given by the same orientation relationship.

Influences of Variability in Attenuation Compensation on the Estimation of Backscatter Coefficient of Median Nerves in Vivo.

OBJECTIVE: Peripheral nerves remain a challenging target for medical imaging, given their size, anatomical complexity, and structural heterogeneity. Quantitative ultrasound (QUS) applies a set of techniques to estimate tissue acoustic parameters independent of the imaging platform. Many useful medical and laboratory applications for QUS have been reported, but challenges remain for deployment in vivo, especially for heterogeneous tissues. Several phenomena introduce variability in attenuation estimates, which may influence the estimation of other QUS parameters. For example, estimating the backscatter coefficient (BSC) requires compensation for the attenuation of overlying tissues between the transducer and the underlying tissue of interest. The purpose of this study is to extend prior studies by investigating the efficacy of several analytical methods of estimating attenuation compensation on QUS outcomes in the human median nerve. METHODS: Median nerves were imaged at the volar wrist in vivo and beam-formed radiofrequency (RF) data were acquired. Six analytical approaches for attenuation compensation were compared: 1-2) attenuation estimated by applying spectral difference method (SDM) and spectral log difference method (SLDM) independently to regions of interest (ROIs) overlying the nerve and to the nerve ROI itself; 3-4) attenuation estimation by applying SDM and SLDM to ROIs overlying the nerve, and transferring these properties to the nerve ROI; and 5-6) methods that apply previously published values of tissue attenuation to the measured thickness of each overlying tissue. Mean between-subject estimates of BSC-related outcomes as well as within-subject variability of these outcomes were compared among the 6 methods. RESULTS: Compensating for attenuation using SLDM and values from the literature reduced variability in BSC-based outcomes, compared to SDM. Variability in attenuation coefficients contributes substantially to variability in backscatter measurements. CONCLUSION: This work has implications for the application of QUS to in vivo diagnostic assessments in peripheral nerves and possibly other heterogeneous tissues.

Differences in vascular tissue response after stent implantation between biolimus-eluting and everolimus-eluting stents: a sub-study of the NEXT study.

NEXT [NOBORI biolimus-eluting stent (BES) versus XIENCE/PROMUS everolimus-eluting stent (EES) trial] was a multicenter, randomized, prospective trial that included 3235 patients with 8-12 months of follow-up imaging at 18 centers. IB-IVUS images were analyzed at an interval of 0.5 mm using a motorized pull-back system in each plaque that required stent implantation. We analyzed seven cross-sections at the site of minimal lumen area and ten cross-sections in proximal and distal peripheral sites prior to the procedure, after stent implantation and after 8 months. We averaged the relative blue volume, relative green volume, relative yellow volume, and relative red volume across seven cross-sections using the manufacturer's default setting. Fifty-four lesions in 50 patients were analyzed. There were 28 lesions in 25 patients in the EES group and 26 lesions in 25 patients in the BES group. The patient characteristics did not differ significantly between the two groups except high-density lipoprotein cholesterol. There were no significant differences before and after stent implantation after 8 months in relative red volume, relative yellow volume, relative green volume or relative blue volume. Although the present study was likely underpowered for statistical analyses and larger populations are needed to confirm the conclusions, the vascular response regarding tissue characterization was similar between EES and BES, even though the thickness and releasing materials differed between the stents.

Imaging and Segmenting Grains and Subgrains Using Backscattered Electron Techniques.

We present two new methods of processing data from backscattered electron signals in a scanning electron microscope to image grains and subgrains. The first combines data from multiple backscattered electron images acquired at different specimen geometries to (1) better reveal grain boundaries in recrystallized microstructures and (2) distinguish between recrystallized and unrecrystallized regions in partially recrystallized microstructures. The second utilizes spherical harmonic transform indexing of electron backscatter diffraction patterns to produce high angular resolution orientation data that enable the characterization of subgrains. Subgrains are produced during high-temperature plastic deformation and have boundary misorientation angles ranging from a few degrees down to a few hundredths of a degree. We also present an algorithm to automatically segment grains from combined backscattered electron image data or grains and subgrains from high angular resolution electron backscatter diffraction data. Together, these new techniques enable rapid measurements of individual grains and subgrains from large populations.

Urethral tissue characterization using multiparametric ultrasound imaging.

A decrease in urethral closure pressure is one of the primary causes of stress urinary incontinence in women. Atrophy of the urethral muscles is a primary factor in the 15 % age-related decline in urethral closure pressure per decade. Incontinence not only affects the well-being of women but is also a leading cause of nursing home admission. The objective of this research was to develop a noninvasive test to assess urethral tissue microenvironmental changes using multiparametric ultrasound (mpUS) imaging technique. Transperineal B-scan ultrasound (US) data were captured using clinical scanners equipped with curvilinear or linear transducers. Imaging was performed on volunteers from our institution medical center (n = 15, 22 to 76 y.o.) during Valsalva maneuvers. After expert delineation of the region of interest in each frame, the central axis of the urethra was automatically defined to determine the angle between the urethra and the US beam for further analysis. By integrating angle-dependent backscatter with radiomic texture feature analysis, a mpUS technique was developed to identify biomarkers that reflect subtle microstructural changes expected within the urethral tissue. The process was repeated when the urethra and US beam were at a fixed angle. Texture selection was conducted for both angle-dependent and angle-independent results to remove redundancies. Ultimately, a distinct biomarker was derived using a random forest regression model to compute the urethra score based on features selected from both processes. Angle-dependent backscatter analysis shows that the calculated slope of US mean image intensity decreased by 0.89 (±0.31) % annually, consistent with the expected atrophic disorganization of urethral tissue structure and the associated reduction in urethral closure pressure with age. Additionally, textural analysis performed at a specific angle (i.e., 40 degrees) revealed changes in gray level nonuniformity, skewness, and correlation by 0.08 (±0.04) %, -2.16 (±1.14) %, and -0.32 (±0.35) % per year, respectively. The urethra score was ultimately determined by combining data selected from both angle-dependent and angle-independent analysis strategies using a random forest regression model with age, yielding an R2 value of 0.96 and a p-value less than 0.001. The proposed mpUS tissue characterization technique not only holds promise for guiding future urethral tissue characterization studies without the need for tissue biopsies or invasive functional testing but also aims to minimize observer-induced variability. By leveraging mpUS imaging strategies that account for angle dependence, it provides more accurate assessments. Notably, the urethra score, calculated from US images that reflect tissue microstructural changes, serves as a potential biomarker providing clinicians with deeper insight into urethral tissue function and may aid in diagnosing and managing related conditions while helping to determine the causes of incontinence.

Corneal densitometry: A new evaluation indicator for corneal diseases.

Corneal densitometry (CD) uses the biological properties of the cornea to visualize the morphology of the cornea and determine the degree of corneal transparency. At present, it is an emerging metric that has shown promise in various clinical diagnosis and evaluation of eye diseases and surgeries. We introduce the different methodologies used to measure CD. Furthermore, we systematically categorize the diagnostic value of CD into high, medium, and low levels based on its clinical significance. By analyzing a wide range of conditions, including keratoconus, postrefractive surgery changes, and other corneal pathologies, we assess the utility of CD in each context. We also discuss the potential implications of these classifications for disease monitoring and prognosis evaluation. Our review underscores the importance of integrating CD assessments into routine clinical practice to enhance the accuracy and effectiveness of diagnostic processes for corneal disorders.

Validation of an Optical Technology for the Determination of pH in Milk during Yogurt Manufacture.

Current systems that allow inline pH control in the fermented dairy industry have drawbacks, such as protein adhesion on the non-glass pH probes, measurement distortion, frequent recalibration needs, and sensitivity to extreme pH conditions encountered during clean-in-place operations. Therefore, the objective of this study was to validate the feasibility of estimating the pH of milk during the yogurt making process by using a NIR light backscatter sensor measuring under different fermentation temperatures and milk protein concentrations using a mathematical model that correlates the light scatter signal with pH. Three replications of the experiment with two protein concentrations (3.5 and 4.0%) and two fermentation temperatures (43 and 46 °C) were used to validate this inline pH prediction model. Continuous and discontinuous measurements of pH were collected as a reference during fermentation, simultaneously with the light backscatter data acquisition. Also, the effect of adjusting the initial voltage gain of the light scatter device on the accuracy of the pH prediction model was evaluated. Temperature and initial voltage were the main factors affecting the fitting accuracy of the model. The adjustment of the initial voltage gain improved the pH prediction model fit. The model has been successfully validated for both continuous and discontinuous measurements of pH, with SEP values < 0.09 pH units and CV < 1.78%. The proposed optical inline and non-destructive method was feasible for inline pH monitoring of milk fermentation, avoiding traditional manual pH measurement.

Skeletal microstructures of cheilostome bryozoans (phylum Bryozoa, class Gymnolaemata): crystallography and secretion patterns.

Gymnolaemata bryozoans produce CaCO3 skeletons of either calcite, aragonite, or both. Despite extensive research, their crystallography and biomineralization patterns remain unclear. We present a detailed study of the microstructures, mineralogy, and crystallography of eight extant cheilostome species using scanning electron microscopy, electron backscatter diffraction, atomic force microscopy, and micro-computed tomography. We distinguished five basic microstructures, three calcitic (tabular, irregularly platy, and granular), and two aragonitic (granular-platy and fibrous). The calcitic microstructures consist of crystal aggregates that transition from tabular or irregularly platy to granular assemblies. Fibrous aragonite consists of fibers arranged into spherulites. In all cases, the crystallographic textures are axial, and stronger in aragonite than in calcite, with the c-axis as the fiber axis. We reconstruct the biomineralization sequence in the different species by considering the distribution and morphology of the growth fronts of crystals and the location of the secretory epithelium. In bimineralic species, calcite formation always predates aragonite formation. In interior compound walls, growth proceeds from the cuticle toward the zooecium interior. We conclude that, with the exception of tabular calcite, biomineralization is remote and occurs within a relatively wide extrapallial space, which is consistent with the inorganic-like appearance of the microstructures. This biomineralization mode is rare among invertebrates. Supplementary Information: The online version contains supplementary material available at 10.1007/s42995-024-00233-1.

Spatial distribution of sandeel (Hyperoplus lanceolatus) and implications for monitoring marine protected sites.

Increased human demand on the marine environment and associated biodiversity threatens sustainable delivery of ecosystem goods and services, particularly for shallow shelf-sea habitats. As a result, more attention is being paid to quantifying the geographical range and distribution of seabed habitats and keystone species vulnerable to human pressures. In this study, we develop a workflow based on unsupervised K-Means classification units and Generalized Linear Models built from multi-frequency backscatter analyses (95, 300 kHz), bathymetry and bathymetry derivatives (slope) to predict different levels of sandeel densities in Hempton's Turbot Bank Special Area of Conservation (SAC). For Hyperoplus lanceolatus densities, the performance of single frequency verses multi-frequency models is compared. Relatively high agreement between K-Means clustering outputs (from 95 kHz and multi-frequency models) and ground-truthed sandeel densities is noted. Moreover, Root Mean Squared Error (RMSE) values in this instance demonstrate that single-frequency models are favoured over the multi-frequency model in terms of predictive ability. This is mostly linked to the species strong affinity for sedimentary environments whose variability is better captured by the lower frequency system. Generally, these results provide important information about species-habitat relationships and pinpoint bedform features where sandeels are likely to be found and whose variability is potentially linked to the bathymetry domain. The workflow developed in this study also provides a proof of concept to support the design of a robust species-specific monitoring plan in marine protected areas. Most importantly, we highlight how decisions made during sampling, data handling, analysis could impact the final outputs and interpretation of Species Distribution Models and benthic habitat mapping.

Ultrasound normalized cumulative residual entropy imaging: Theory, methodology, and application.

BACKGROUND AND OBJECTIVE: Ultrasound information entropy imaging is an emerging quantitative ultrasound technique for characterizing local tissue scatterer concentrations and arrangements. However, the commonly used ultrasound Shannon entropy imaging based on histogram-derived discrete probability estimation suffers from the drawbacks of histogram settings dependence and unknown estimator performance. In this paper, we introduced the information-theoretic cumulative residual entropy (CRE) defined in a continuous distribution of cumulative distribution functions as a new entropy measure of ultrasound backscatter envelope uncertainty or complexity, and proposed ultrasound CRE imaging for tissue characterization. METHODS: We theoretically analyzed the CRE for Rayleigh and Nakagami distributions and proposed a normalized CRE for characterizing scatterer distribution patterns. We proposed a method based on an empirical cumulative distribution function estimator and a trapezoidal numerical integration for estimating the normalized CRE from ultrasound backscatter envelope signals. We presented an ultrasound normalized CRE imaging scheme based on the normalized CRE estimator and the parallel computation technique. We also conducted theoretical analysis of the differential entropy which is an extension of the Shannon entropy to a continuous distribution, and introduced a method for ultrasound differential entropy estimation and imaging. Monte-Carlo simulation experiments were performed to evaluate the estimation accuracy of the normalized CRE and differential entropy estimators. Phantom simulation and clinical experiments were conducted to evaluate the performance of the proposed normalized CRE imaging in characterizing scatterer concentrations and hepatic steatosis (n = 204), respectively. RESULTS: The theoretical normalized CRE for the Rayleigh distribution was π/4, corresponding to the case where there were ≥10 randomly distributed scatterers within the resolution cell of an ultrasound transducer. The theoretical normalized CRE for the Nakagami distribution decreased as the Nakagami parameter m increased, corresponding to that the ultrasound backscattered statistics varied from pre-Rayleigh to Rayleigh and to post-Rayleigh distributions. Monte-Carlo simulation experiments showed that the proposed normalized CRE and differential entropy estimators can produce a satisfying estimation accuracy even when the size of the test samples is small. Phantom simulation experiments showed that the proposed normalized CRE and differential entropy imaging can characterize scatterer concentrations. Clinical experiments showed that the proposed ultrasound normalized CRE imaging is capable to quantitatively characterize hepatic steatosis, outperforming ultrasound differential entropy imaging and being comparable to ultrasound Shannon entropy and Nakagami imaging. CONCLUSION: This study sheds light on the theory and methodology of ultrasound normalized CRE. The proposed ultrasound normalized CRE can serve as a new, flexible quantitative ultrasound envelope statistics parameter. The proposed ultrasound normalized CRE imaging may find applications in quantified characterization of biological tissues. Our code will be made available publicly at https://github.com/zhouzhuhuang.

Mussel culture monitoring with semi-supervised machine learning on multibeam echosounder data using label spreading.

High diversity seabed habitats, such as shellfish aggregations, play a significant role in marine ecosystem sustainability but are susceptible to bottom disturbance induced by anthropogenic activities. Regular monitoring of these habitats with effective mapping methods is therefore essential. Multibeam echosounder (MBES) has been widely used in recent decades for seabed characterization due to its non-destructive manner and extensive spatial coverage compared to traditional methods like bottom sampling. Nevertheless, bottom sampling remains essential to link ground truth with acoustic seabed classification. Using seabed samples and MBES measurements, machine learning techniques are commonly employed to model their relationships and generate classification maps of an extended seabed. However, limited ground truth data, resulting from constraints in regulations, budget, or time, may impede the development of robust machine learning models. To address this challenge, we applied a semi-supervised machine learning method to classify seabed sediments of a blue mussel (Mytilus edulis) cultivation area in the Oosterschelde, the Netherlands. We utilized nine boxcore samples to generate pseudo-labels on MBES data. These pseudo-labels enlarged the training data size, facilitated the training of three comprehensive machine learning algorithms (Gradient Boosting, Random Forest, and Support Vector Machine), and helped to classify the study site into mussel and non-mussel areas. We found the geomorphological and backscatter-related features to be complementary for mussel culture detection. Our classification results were demonstrated effective through expert knowledge of this cultivation area and brought insights for future research on natural mussel habitats.

Tissue characteristics of residual lesion in patients with acute coronary syndrome caused by plaque rupture versus plaque erosion: a single-center, retrospective, observational study.

Patients with acute coronary syndrome (ACS), frequently caused by plaque rupture (PR), often have vulnerable plaques in residual lesions as well as in culprit lesions. However, whether this occurs in patients with plaque erosion (PE) as well is unknown. We retrospectively analyzed the data of 88 patients with ACS who underwent both optimal coherence tomography (OCT) and intravascular ultrasound (IVUS). Based on plaque morphology of the culprit lesions identified using OCT, patients were classified into PE (n=23) and PR (n=35) groups. The tissue characteristics of residual lesions evaluated using integrated backscatter IVUS were compared between both groups after percutaneous coronary intervention. The PE group had a significantly lower percent lipid volume and a higher percent fibrous volume than the PR group (35.0±17.8% vs 49.2±13.4%, p<0.001; 63.2±17.1% vs 50.3±13.1%, p=0.002, respectively). Receiver operating characteristic curve analysis revealed that percent lipid volume in the residual lesions was a significant discriminant factor in estimating the plaque morphology of the culprit lesion (optimal cut-off value, <43.5%; sensitivity and specificity values were 73.9% and 68.6%, respectively). In conclusion, patients with PE had a significantly lower percent lipid volume and a significantly higher percent fibrous volume in the residual lesions than those with PR, suggesting that the nature of coronary plaques in patients with PE is different from that of those with PR.

Simulation of ultrasound backscatter coefficient measurement using the finite element method.

Ultrasound backscatter coefficient (BSC) measurement is a method for assessing tissue morphology that can inform on pathologies such as cancer. The BSC measurement is, however, limited by the accuracy with which the investigator can normalise their results to account for frequency dependent effects of diffraction and attenuation whilst performing such measurements. We propose a simulation-based approach to investigate the potential sources of error in assessing the BSC. Presented is a tool for the 2D Finite Element (FE) simulation mimicking a BSC measurement using the planar reflector substitution method in reduced dimensionality. The results of this are verified against new derivations of BSC equations also in reduced dimensionality. These new derivations allow computation of BSC estimates based on the scattering from a 2D scattering area, a line reference reflector and a theoretical value for the BSC of a 2D distribution of scatterers. This 2D model was designed to generate lightweight simulations that allow rapid investigation of the factors associated with BSC measurement, allowing the investigator to generate large data sets in relatively short time scales. Under the conditions for an incoherent scattering medium, the simulations produced BSC estimates within 6% of the theoretical value calculated from the simulation domain, a result reproduced across a range of source f-numbers. This value of error compares well to both estimated errors from other simulation based approaches and to physical experiments. The mathematical and simulation models described here provide a theoretical and experimental framework for continued investigation into factors affecting the accuracy of BSC measurements.

Dispersion analysis of the 2017 Persian Gulf oil spill based on remote sensing data and numerical modelling.

Oil spills, detected by SAR sensors as dark areas, are highly effective marine pollutants that affect the ocean surface. These spills change the water surface tension, attenuating capillary gravitational waves and causing specular reflections. We conducted a case study in the Persian Gulf (Arabian Sea to the Strait of Hormuz), where approximately 163,900 gal of crude oil spilled in March 2017. Our study examined the relationship between oil weathering processes and extracted backscatter values using zonal slices projected over SAR-detected oil spills. Internal backscatter values ranged from -22.5 to -23.5, indicating an oil chemical binding and minimal interaction with seawater. MEDSLIK-II simulations indicated increased oil solubilization and radar attenuation rates with wind, facilitating coastal dispersion. Higher backscatter at the spill edges compared to the core reflected different stages of oil weathering. These results highlight the complex dynamics of oil spills and their environmental impact on marine ecosystems.

Habitat suitability modelling to predict the distribution of deep coral ecosystems: The case of Linosa Island (southern Mediterranean Sea, Italy).

In areas with limited field data, predictive habitat mapping is a valuable method for elucidating species-environment relationships and enhancing our knowledge of the spatial distribution and complexity of benthic habitats. Species distribution models (SDMs) can be an important tool to support in science-based ecosystem management. The availability of direct observations of mesophotic species, including gorgonians and black corals, during costly surveys is generally limited. Therefore, predicting the distribution of mesophotic species in relation to key physical parameters of the seafloor would help improving conservation strategies in existing and new Marine Protected Areas (MPAs). This study aims to assess the distribution of gorgonians and black corals off Linosa Island, in the Strait of Sicily, a biogeographic boundary area between the western and eastern Mediterranean. The volcanic island of Linosa represents a small, naturally preserved area, with very limited human pressure, hosting rich marine benthic biodiversity on its wide submarine portions. Distribution of the most common coral species off Linosa Island was modelled under an SDM framework, relying on direct observations collected during two research cruises in 2016 and 2017 and a series of terrain parameters acquired through geophysical techniques. We used the so-called "ensemble of small models" approach to calibrate SDMs, which achieved fair-to-excellent results (AUC >0.7). In addition to identifying depth as the primary factor influencing coral distribution, our study also highlighted ruggedness as a significant terrain variable. Specifically, the depth range of 110-230 m emerged as the critical parameter determining habitat suitability for all modelled species, also highlighting peculiar and specie-specific habitat requirements.

Synergistic Thermal and Electron Wind Force-Assisted Annealing for Extremely High-Density Defect Mitigation.

This study investigates the effectiveness of combined thermal and athermal stimuli in mitigating the extremely high-density nature of dislocation networks in the form of low-angle grain boundaries in FeCrAl alloy. Electron wind force, generated from very low duty cycle and high current density pulses, was used as the athermal stimulus. The electron wind force stimulus alone was unable to remove the residual stress (80% low-angle grain boundaries) due to cold rolling to 25% thickness reduction. When the duty cycle was increased to allow average temperature of 100 °C, the specimen could be effectively annealed in 1 min at a current density of 3300 A/mm2. In comparison, conventional thermal annealing requires at least 750 °C and 1.5 h. For specimens with 50% thickness reduction (85% low-angle grain boundaries), the electron wind force was again unable to anneal the defects even at 3300 A/mm2 current density and average temperature of 100 °C. Intriguingly, allowing average concurrent temperature of 200 °C eliminated almost all the low-angle grain boundaries at a current density of 700 A/mm2, even lower than that required for the 25% thickness reduced specimens. Comprehensive electron and X-ray diffraction evidence show that alloys with extremely high defect density can be effectively annealed in less than a minute at approximately 200 °C, offering a substantial improvement over conventional high-temperature annealing.

Evaluation of Scatterer Parameters From Ultrasound Scattering Models Taking Into Account Scattering From Nuclei and Cells of Cell-Pellet Biophantoms and Ex Vivo Tumors.

The Quantitative Ultrasound backscatter coefficient provides the capability to evaluate tissue microstructure parameters. Tissue-based scatterer parameters are extracted using ultrasound scattering models. It is challenging to correlate ultrasound scatterer parameters of tissue structures from optical-measured histology, possibly because of inappropriate scattering models or the presence of multiple scatterers. The objective of this study is to pursue the quantification of pertinent scatterer parameters with scattering models that consider ultrasound scattering from nuclei and cells. The concentric sphere model (CSM) and the structure factor model adapted for two types of scatterers (SFM2) are evaluated for cell-pellet biophantoms and ex vivo tumors of four cell lines: 4T1, JC, LMTK, and MAT. The structure factor model (SFM) was used for comparison. CSM and SFM2 provided scatterer parameters closer to histology (lower relative errors) for nucleus and cell radii and volume fractions than SFM but were not always accompanied by lower dispersion of the scatterer distribution (lower coefficient of variation). CSM and SFM2 quantified cell and nucleus radius and volume fraction parameters with lower relative error compared to SFM. For tumors, CSM provided better results than SFM2.

Ultrasound backscatter coefficient for fat quantification is affected by the measurement depth.

PURPOSE: It has been reported that the estimate of ultrasound attenuation coefficient (AC) is affected by depth of measurement, with linear decrease of values with depth. It is unknown whether backscatter coefficient (BSC) has similar behavior. METHODS: This retrospective study was performed with Sequoia US system equipped with ultrasound derived fat fraction (UDFF) algorithm (Siemens Healthineers, Issaquah, WA, USA) that combines BSC with AC. UDFF was obtained positioning upper edge of the region of interest at 1.5,2,3,4,5 cm below liver capsule. BSC data were extracted from UDFF offline. A fractional polynomial regression, which selects the best model considering the polynomial development of the variables of interest, was used. Covariates included were age, sex, skin-to-liver-capsule distance, stiffness. Distance was included as linear factor or with a power ranging from - 2 to 3, and the best fitting model was chosen according to partial F test. Body mass index (BMI) was not included because of collinearity with skin-to-liver capsule distance. RESULTS: 104 individuals (56 females; age: 57.9 ± 13.0 years; BMI: 29.0 ± 6.5 kg/m2; skin-to-liver-capsule distance: 2.3 ± 0.7 cm; liver stiffness: 7.5 ± 5.5 kiloPascal) were studied. Best fitting model for BSC included a combination of depth as linear factor and square root. BSC showed a decrease of - 13.98 dB/cm-steradian for each logarithmic increase of 1 cm depth (coefficient: - 13.98; 95% CI: - 21.016; - 5.379; p = .001). Skin-to-liver-capsule distance and stiffness also were independent predictors of BSC. CONCLUSIONS: The estimation of the BSC in the liver exhibits a depth dependence that significantly affects results. A standardized acquisition protocol is needed to compare results and reliably assess changes over time.

Diagnostic accuracy of ultrasound-derived fat fraction for the detection and quantification of hepatic steatosis in patients with liver biopsy.

PURPOSE: This retrospective study was conducted to investigate the diagnostic accuracy of ultrasound-derived fat fraction (UDFF) for grading hepatic steatosis using liver histology as the reference standard. METHODS: Seventy-three patients with liver disease were assessed using UDFF and liver biopsy. Pearson's test and the Bland-Altman plot were used to assess the correlation between UDFF and histological fat content in liver sections. The UDFF cutoff values for histologically proven steatosis grades were determined using the area under the receiver operating characteristic curve (AUROC). RESULTS: The median age of the patients was 66 (interquartile range 54-74) years, and 33 (45%) were females. The UDFF values showed a stepwise increase with increasing steatosis grade (p < .001) and were strongly correlated with the histological fat content (r = .7736, p < .001). The Bland-Altman plot revealed a mean bias of 2.384% (95% limit of agreement, - 6.582 to 11.351%) between them. Univariate regression analysis revealed no significant predictors of divergence. The AUROCs for distinguishing steatosis grades of ≥ 1, ≥2, and 3 were 0.956 (95% confidence interval [CI], 0.910-1.00), 0.926 (95% CI, 0.860-0.993), and 0.971 (95% CI, 0.929-1.000), respectively. The UDFF cutoff value of > 6% had a sensitivity and specificity of 94.8% and 82.3%, respectively, for diagnosing steatosis grade ≥ 1. There was no association between UDFF and the fibrosis stage. CONCLUSION: UDFF shows strong agreement with the histological fat content and excellent diagnostic accuracy for grading steatosis. UDFF is a promising tool for detecting and quantifying hepatic steatosis in clinical practice.

Miniaturized Active-Frequency Selective Surfaces for Low-Power Internet of Things Devices.

With the proliferation of smart devices, the Internet of Things (IoT) is rapidly expanding. This study proposes a miniaturized controllable metamaterial with low control voltage for achieving low-power and compact designs in IoT node devices. Operating at a target frequency of 2.4 GHz, the proposed metamaterial requires only a 3.3 V control voltage and occupies approximately one-third of the wavelength in size. Experimental validation demonstrates its excellent reflective control performance, positioning it as an ideal choice for low-power IoT systems, particularly in the context of miniaturized and low-power IoT node applications.