Search Results (21)

Background/Objectives: Basal cell carcinoma (BCC) is the most frequent skin cancer in Caucasian populations. While dermoscopy supports diagnosis, accurate subtype classification requires histopathology. Line-field confocal optical coherence tomography (LC-OCT) offers high resolution, adequate penetration, and three-dimensional imaging, bridging the gap between dermoscopy and histopathology. This study assessed the concordance between LC-OCT and histopathology for BCC criteria and subtypes. Methods: We retrospectively analyzed 127 histopathologically confirmed BCCs from the Departments of Dermatology and Pathology, Hôpital Erasme, Brussels. LC-OCT images and corresponding histopathological slides were evaluated. Objective analysis used a predefined checklist of LC-OCT criteria compared with histopathology. Subjective analysis consisted of independent side-by-side assessments of global resemblance by three observers with varying expertise. Concordance rates and κ statistics were calculated. Results: The objective analysis showed the highest concordance (≥80%) for lobules, blood vessels, bright cells, lobule location, and dermal-epidermal junction disruption. Intermediate concordance (50–80%) was found for hemispheric morphology, outer bright rim, stromal stretching, and parakeratosis. Inner dark rim and palisading showed low concordance (<50%). Subjective evaluations demonstrated strong resemblance between LC-OCT and histopathology (overall concordance 81.1%), ranging from 86.6% to 98.4% across observers. Interobserver agreement was slight overall (κ = 0.10, p = 0.02), with one moderate pairwise κ (0.41). Conclusions: LC-OCT demonstrates good concordance with histopathology for key diagnostic and subtype-discriminating BCC features. Despite variability in subtle criteria, the findings support LC-OCT as a clinically relevant tool for non-invasive diagnosis and management of BCC. Full article

Mesenchymal stem cells are widely cultivated in stirred tank bioreactors. Due to their adhesion properties, they are attached to small spherical spheres called microcarriers. To understand the hydromechanical stresses encountered by the cells, it is essential to characterize the flow using the PIV technique. However, the usual solid–liquid system used in cell cultures has poor optical properties. Thus, shifting to one with better optical properties, while respecting the physical characteristics, is mandatory to achieve a relevant representation. PMMA microparticles suspended with 61 wt% ammonium thiocyanate solution NH₄SCN were found to be a robust candidate. The refractive index (RI) of both sides is of the order of 1.491 with a density ratio of ${\rho }_f/{\rho }_p\approx$ 0.96, and particle size averaged around 168 μm. Using the RIM-PIV (refractive index matched particle image velocimetry) technique for a 0.7 L volume stirred tank equipped with an HTPG down-pumping axial impeller and operating at full homogeneous speed $N=150$ rpm, mean and turbulence quantities of the liquid phase were measured as a function of PMMA particle volume fractions ${\alpha }_p$, which ranged from 0.5 to 3 v%. This corresponds to a particle number density of $n=12$ particles/mm³, which is considered original and challenging for the PIV technique. At 3 v%, the addition of particles dampened the turbulent kinetic energy (TKE) of the liquid phase locally by 20% near the impeller. This impact became trivial (<10%) at the local-average level. The structure and direction of the recirculation loop also shifted. Full article

Background: Optical coherence tomography (OCT) is the main diagnostic technology used to detect damage to the retinal ganglion cells (RGCs) in glaucoma. However, it remains unclear which OCT parameter demonstrates the best diagnostic performance for eyes with early, especially preperimetric glaucoma (PPG). We determined the diagnostic performance of ganglion cell–inner plexiform layer (GCIPL) parameters using spectral-domain OCT (SD-OCT) in primary open-angle preperimetric and early perimetric glaucoma and compared them with optic nerve head (ONH) and peripapillary retinal nerve fiber layer (pRNFL) parameters. Methods: We analyzed 101 eyes: 36 normal eyes, 33 with PPG, and 32 with early perimetric glaucoma. All patients underwent Topcon SD–OCT imaging using the Optic Disc and Macular Vertical protocols. The diagnostic abilities of the GCIPL, rim area, vertical cup-to-disc ratio (CDR), and pRNFL were assessed using the area under the receiver operating characteristic curve (AUC). Results: For PPG, the AUCs ranged from 0.60 to 0.63 (GCIPL), 0.82 to 0.86 (ONH), and 0.49 to 0.75 (pRNFL). For early perimetric glaucoma, the AUCs for GCIPL and pRNFL ranged from 0.81 to 0.88 and 0.57 to 0.91, respectively, whereas both ONH parameters demonstrated an AUC of 0.89. The GCIPL parameters were significantly lower than both ONH parameters in detecting preperimetric glaucoma (p < 0.05). For early perimetric glaucoma, comparisons between the AUCs of the best-performing mGCIPL parameters and those of the best-performing pRNFL and ONH parameters revealed no significant differences in their diagnostic abilities (p > 0.05). Conclusions: GCIPL parameters exhibited a diagnostic performance comparable to that of ONH and pRNFL parameters for early perimetric glaucoma. However, their ability to detect preperimetric glaucoma was significantly lower than the ONH parameters. Full article

Background: Ossifying fibromyxoid tumors (OFMTs) are rare mesenchymal neoplasms with behaviors ranging from benign to malignant. Although most occur in the extremities and trunk, 9–13% are found in the head and neck, such as the oral cavity, scalp, and calvarium. Diagnosis is challenging due to their rarity and histological similarity to other neoplasms. This review synthesizes evidence on the clinical presentation, diagnostic features, and treatment outcomes of OFMTs in the head and neck, focusing on surgical management and adjuvant therapies. Methods: A systematic review was conducted according to PRISMA guidelines, with searches in PubMed/MEDLINE, Embase, Scopus, and Web of Science. Studies from 1989 to 2024 reporting OFMTs in the head and neck with clinical, histopathological, and treatment data were included. Extracted data encompassed demographics, tumor features, surgical margins, adjuvant therapy, and outcomes. Results: Forty studies with 99 patients were included. Patient ages ranged from 3 weeks to 88 years (median 47), with a male predominance (63.64%). The most common presentation was a slow-growing, painless mass. Tumors were most often found in the neck, oral cavity, scalp, and calvarium. Histopathology revealed encapsulated tumors with fibromyxoid stroma, spindle-shaped cells, and a peripheral rim of metaplastic bone in 70% of cases. Immunohistochemistry showed positivity for S-100, vimentin, and SOX10. Surgical excision was the main treatment, used in 28.28% of cases, with recurrence in 9.09% and no metastases. Adjuvant therapies, mainly radiotherapy, were employed in 15.15% of cases. Conclusions: OFMTs of the head and neck are rare neoplasms requiring multidisciplinary care. Imaging, histopathology, and immunohistochemistry are key to diagnosis. Surgical excision with clear margins remains the primary treatment, with a low recurrence rate. Adjuvant therapy may be needed for malignant or incompletely excised cases. Further research is needed to optimize follow-up protocols and assess molecular profiling for risk stratification. Full article

Recycled glass has been the focus of attention owing to its role in reducing plastic waste and further increasing the demand for glass containers. Cosmetics glass bottles require strict quality inspections because of the frequent handling, safety concerns, and other factors. During manufacturing, glass bottles sometimes develop chips on the top surface, rim, or screw threads of the bottle mouth. Conventionally, these chips are visually inspected by inspectors; however, this process is time consuming and prone to inaccuracies. To address these issues, automatic inspection using image processing has been explored. Existing methods, such as dynamic luminance value correction and ring-shaped inspection gates, have limitations: the former relies on visible light, which is strongly affected by natural light, and the latter acquires images directly from above, resulting in low accuracy in detecting chips on the lower part of screw threads. To overcome these challenges, this study proposes a method that combines infrared backlighting and image processing to determine the range of screw threads and detect chips accurately. Experiments were conducted in an experimental environment replicating an actual factory production line. The results confirmed that the detection accuracy of chipping was 99.6% for both good and defective bottles. This approach reduces equipment complexity compared to conventional methods while maintaining high inspection accuracy, contributing to the productivity and quality control of glass bottle manufacturing. Full article

Objective: The objective of this study was to prospectively assess the extent to which magnetic resonance imaging (MRI) can differentiate malignant from benign lesions of the testis. Materials and Methods: All included patients underwent multiparametric testicular MRI, including diffusion-weighted imaging (DWI) and subtraction dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI). Subsequently, all patients underwent a histopathological examination via orchiectomy or testicular biopsy/partial resection. The Kolmogorov–Smirnov test, t-test, Mann–Whitney U test, Fisher’s exact test, and logistic regression were applied for statistical analysis. Results: We included 48 male patients (median age 37.5 years [range 18–69]) with testicular tumors. The median tumor size on MRI was 2.0 cm for malignant tumors and 1.1 cm for benign tumors (p < 0.05). A statistically significant difference was observed for the type (type 0-III curve, p < 0.05) and pattern of enhancement (homogeneous, heterogeneous, or rim-like, p < 0.01) between malignant and benign tumors. The minimum apparent diffusion coefficient (ADC) value was 0.9 for benign tumors and 0.7 for malignant tumors (each ×10³ mm²/s, p < 0.05), while the mean ADC was 0.05. The mean ADC value was significantly lower for malignant tumors; the mean ADC value was 1.1 for benign tumors and 0.9 for malignant tumors (each ×10³ mm²/s, p < 0.05). The sensitivity, specificity, positive predictive value, and negative predictive value of multiparametric MRI for differentiating malignant from benign testicular lesions were 94.3%, 76.9%, 91.7%, and 83.3%, respectively. The surgical procedures performed included orchiectomy (n = 33; 71.7%) and partial testicular resection (n = 11; 23.9%). Histopathology (HP) revealed malignancy in 35 patients (72.9%), including 26 with seminomas and 9 with non-seminomatous germ cell tumors (NSGCTs). The HP was benign in 13 (27.1%) patients, including 5 with Leydig cell tumors. Conclusions: Malignant and benign tumors differ in MRI characteristics in terms of the type and pattern of enhancement and the extent of diffusion restriction, indicating that MRI can be an important imaging modality for the accurate diagnosis of testicular lesions. Full article

Background: The European Association of Endoscopic Surgery (EAES) recommends, with strong evidence, the use of indocyanine green (ICG) fluorescence imaging combined with intraoperative ultrasound (IOUS) to improve identification of superficial liver tumors. This study reports the use of ICG for the detection of colorectal liver metastases (CRLMs) during minimally invasive liver resection. Methods: A single-center consecutive series of minimally invasive (laparoscopic and robotic) hepatic resections for CRLMs was prospectively evaluated (April 2019 and October 2023). Results: A total of 25 patients were enrolled—11 undergoing laparoscopic and 14 undergoing robotic procedures. The median age was 65 (range 50–85) years. Fifty CRLMs were detected: twenty superficial, eight exophytic, seven shallow (<8 mm from the hepatic surface), and fifteen deep (>10 mm from the hepatic surface) lesions. The detection rates of CRLMs through preoperative imaging, laparoscopic ultrasound (LUS), ICG fluorescence, and combined modalities (ICG and LUS) were 88%, 90%, 68%, and 100%, respectively. ICG fluorescence staining allowed us to detect five small additional superficial lesions (not identified with other preoperative/intraoperative techniques). However, two lesions were false positive fluorescence accumulations. All rim fluorescence pattern lesions were CRLMs. ICG fluorescence was used as a real-time guide to assess surgical margins during parenchymal-sparing liver resections. All patients with integrity of the fluorescent rim around the CRLM displayed a radical resection during histopathological analysis. Four patients (8%) with a protruding rim or residual rim patterns had positive resection margins. Conclusions: ICG fluorescence imaging can be integrated with other conventional intraoperative imaging techniques to optimize intraoperative staging. Rim fluorescence proved to be a valid indicator of the resection margins: by removing the entire fluorescent area, a tumor-negative resection (R0) is achieved. Full article

Purpose: To characterize the magnetic resonance imaging features of primary intrahepatic lymphoepithelioma-like cholangiocarcinoma (LELCC). Materials and Methods: Thirty-four patients with 38 histologically confirmed LELCCs were enrolled retrospectively from January 2014 to August 2022. We evaluated the clinical features, histologic findings, and imaging manifestations on dynamic enhanced MRI. Results: 74% (25/34) of the cases were associated with EBV infection. Moreover, patients infected with EBV exhibited a lower level of Ki-67 proliferation. The serum CA199 level was elevated in 10 patients. The median tumor diameter was 2.8 cm (range, 1.1–8.7 cm). Most tumors were well-defined with a smooth or lobulated margin and showed peripheral hyperintensity and central hypointensity on T2-weighted imaging (T2WI). T2 hyperintense foci were recognized in 8 patients. In the dynamic enhanced MRI, 21 tumors demonstrated Type A enhancement pattern (rim enhancement), 10 demonstrated Type B (rapid wash-in and wash-out), and seven demonstrated Type C (rapid wash-in without wash-out). Capsular enhancement in PVP or DP was found in 22 tumors. A few patients had satellite lesions, portal vein thrombosis, bile duct dilatation, and distal metastasis. Lymph node metastases were discovered pathologically in 11 patients. Conclusions: MRI findings of LELCC vary and are non-specific. While a majority of LELCCs exhibit typical features of intrahepatic cholangiocarcinoma (iCCA), unique findings like T2 hyperintense foci or capsular enhancement could suggest LELCC. EBV infection and elevated tumor markers can aid in differentiation. However, given the mimics of some cases of liver hypervascular lesions, histological examination remains essential for definitive diagnosis. Full article

Accurately segmenting the optic disk (OD) and optic cup (OC) on retinal fundus images is important for treating glaucoma. With the development of deep learning, some CNN-based methods have been implemented to segment OD and OC, but it is difficult to accurately segment OD and OC boundaries affected by blood vessels and the lesion area. To this end, we propose a novel boundary-enhanced adaptive context network (BEAC-Net) for OD and OC segmentation. Firstly, a newly designed efficient boundary pixel attention (EBPA) module enhances pixel-by-pixel feature capture to collect the boundary contextual information of OD and OC in the horizontal and vertical directions. In addition, background noise makes segmenting boundary pixels difficult. To this end, an adaptive context module (ACM) was designed, which simultaneously learns local-range and long-range information to capture richer context. Finally, BEAC-Net adaptively integrates the feature maps from different levels using the attentional feature fusion (AFF) module. In addition, we provide a high-quality retinal fundus image dataset named the 66 Vision-Tech dataset, which advances the field of diagnostic glaucoma. Our proposed BEAC-Net was used to perform extensive experiments on the RIM-ONE-v3, DRISHTI-GS, and 66 Vision-Tech datasets. In particular, BEAC-Net achieved a Dice coefficient of 0.8267 and an IoU of 0.8138 for OD segmentation and a Dice coefficient of 0.8057 and an IoU value of 0.7858 for OC segmentation on the 66 Vision-Tech dataset, achieving state-of-the-art segmentation results. Full article

The northeastern part of the cyclonic Rim Current, which encircles the entire basin of the Black Sea, is named as the Northeast Caucasian Current. It periodically approaches the coast, triggering the formation of topographic generated eddies, including long-living isolated anticyclonic eddies and short-living multiple anticyclonic eddies, which group and merge into eddy chain structures. Both types of eddies affect coastal dynamics and interact with multiple river plumes formed in the study area. This interaction determines cross- and along-shelf transport of fluvial water, enhancing the processes of self-cleaning of the coastal zone. In this study, we used a 3D low-dissipation model, DieCAST, coupled with a Lagrangian particle tracking model, and supported by analysis of satellite images, to study the generation and evolution of eddy chains and their interaction with river plumes along the Caucasian coast. Using Fourier and wavelet analyses of kinetic energy time series, we revealed that the occurrence of eddy chains ranges from 10 to 20 days, predominantly in spring-summer season in the area between the Pitsunda and Iskuria capes. During the period of eddy merging, the angular velocities of the orbiting eddies reach maximal values of 7 × 10⁻⁶ rad s⁻¹, while after merging, the angular velocities of the resulting eddies decreased to 5 × 10⁻⁶ rad s⁻¹. Numerical experiments with Lagrangian particle tracking showed that eddy chains effectively capture water from river plumes localized along the coast and then eject it to the open sea. This process provides an effective mechanism of cross-shelf transport of fluvial water, albeit less intense than the influence of isolated anticyclonic eddies, which are typical for autumn-winter season. Full article

Unmanned aerial vehicles (UAVs) and light detection and ranging (LiDAR) can be used to analyze the geomorphic features in complex plateau mountains. Accordingly, a UAV–LiDAR system was adopted in this study to acquire images and lidar point-cloud dataset in the annular structure of Lufeng, Yunnan. A three-dimensional (3D) model was constructed based on structure from motion and multi-view stereo (SfM–MVS) in combination with a high-resolution digital elevation model (DEM). Geomorphic identification, measurement, and analysis were conducted using integrated visual interpretation, DEM visualization, and geographic information system (GIS) topographic feature extraction. The results indicated that the 3D geomorphological visualization and mapping were based on DEM, which was employed to identify the dividing lines and ridges that were delineated of the pit rim structure. The high-resolution DEM retained more geomorphic detail information, and the topography and the variation between ridges were analyzed in depth. The catchment and ponding areas were analyzed using accurate morphological parameters through a multi-angle 3D visualization. The slope, aspect, and topographic wetness index (TWI) parameters were analyzed through mathematical statistics to qualitatively and accurately analyze the differences between different ridges. This study highlighted the significance of the UAV–LiDAR high-resolution topographic measurements and the SfM–MVS 3D scene modelling in accurately identifying geomorphological features and conducting refined analysis. An effective framework was established to acquire high-precision topographic datasets and to analyze geomorphological features in complex mountain areas, which was beneficial in deepening the research on numerical simulation analysis of geomorphological features and reveal the process evolution mechanism. Full article

E-region field-aligned irregularities (FAIs) are a hot topic in space research, since electromagnetic signal propagation through ionospheric irregularities can undergo sporadic enhancements and fading known as ionospheric scintillation, which could severely affect communication, navigation, and radar systems. However, the range resolution of very-high-frequency (VHF) radars, which is widely used to observe E-region FAIs, is limited due to its bandwidth. As a technology that is widely used in atmosphere radars to improve the range resolution of pulsed radars by transmitting multiple frequencies, this paper employed the multifrequency radar imaging (RIM) technique in a Wuhan VHF radar. The results showed that the range resolution of E-region FAIs greatly improved when compared with the results in traditional single-frequency mode, and that finer structures of E-region FAIs can be obtained. Specifically, the imaging results in multifrequency mode show that E-region FAIs demonstrate an overall descending trend at night, and it could be related to the tides or gravity waves due to their downward phase velocities or even driven by downwind shear. In addition, typical quasi-periodic (QP) echoes with a time period of around 10 min could be clearly seen using the RIM technique, and the features of the echoes suggest that they could be modulated by gravity waves. Furthermore, the RIM technique can be used to obtain the fine structure of irregularities within a short time period, and the hierarchical structure of E-region FAIs can be easily found. Therefore, the multifrequency imaging RIM technique is suitable for observing E-region FAIs and their evolution, as well as for identifying the different layers of E-region FAIs. Combined with the RIM technique, a VHF radar provides an effective and promising way to observe the structure of E-region FAIs in more detail to study the physical mechanism behind the formation and evolution of ionospheric E-region irregularities. Full article

The Northeast Caucasian Current (NCC) is the northeastern part of the cyclonic Rim Current (RC) in the Black Sea. As it sometimes approaches the narrow shelf very closely, topographically generated cyclonic eddies (TGEs) can be triggered. These eddies contribute to intense, along- and cross-shelf transport of trapped water with enhanced self-cleaning effects of the coastal zone. Despite intense studies of eddy dynamics in the Black Sea, the mechanisms of the generation of such coastal eddies, their unpredictability, and their capacity to capture and transport impurities are still poorly understood. We applied a 3-D low-dissipation model DieCAST/Die2BS coupled with a Lagrangian particle transport model supported by analysis of optical satellite images to study generation and evolution of TGEs and their effect on river plumes unevenly distributed along the northeastern Caucasian coast. Using the Furrier and wavelet analyses of kinetic energy time series, it was revealed that the occurrence of mesoscale TGEs ranges from 10 up to 50 days. We focused on one particular isolated anticyclonic TGE that emerged in late fall as a result of instability of the RC impinging on the abrupt submarine area adjoining the Pitsunda and Iskuria capes. Being shed, the eddy with a 30-km radius traveled along the coast as a coherent structure during ~1.5 months at a velocity of ~3 km/day and vertical vorticity normalized by the Coriolis parameter ~(0.1 ÷ 1.2). This eddy captured water from river plumes localized along the coast and then ejected it to the open sea, providing an intense cross-shelf transport of riverine matter. Full article

Fire severity represents fire-induced environmental changes and is an important variable for modeling fire emissions and planning post-fire rehabilitation. Remotely sensed fire severity is traditionally evaluated using the differenced normalized burn ratio (dNBR) derived from multispectral imagery. This spectral index is based on bi-temporal differenced reflectance changes caused by fires in the near-infrared (NIR) and short-wave infrared (SWIR) spectral regions. Our study aims to evaluate the spectral sensitivity of the dNBR using hyperspectral imagery by identifying the optimal bi-spectral NIR SWIR combination. This assessment made use of a rare opportunity arising from the pre- and post-fire airborne image acquisitions over the 2013 Rim and 2014 King fires in California with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) sensor. The 224 contiguous bands of this sensor allow for 5760 unique combinations of the dNBR at a high spatial resolution of approximately 15 m. The performance of the hyperspectral dNBR was assessed by comparison against field data and the spectral optimality statistic. The field data is composed of 83 in situ measurements of fire severity using the Geometrically structured Composite Burn Index (GeoCBI) protocol. The optimality statistic ranges between zero and one, with one denoting an optimal measurement of the fire-induced spectral change. We also combined the field and optimality assessments into a combined score. The hyperspectral dNBR combinations demonstrated strong relationships with GeoCBI field data. The best performance of the dNBR combination was derived from bands 63, centered at 0.962 µm, and 218, centered at 2.382 µm. This bi-spectral combination yielded a strong relationship with GeoCBI field data of R² = 0.70 based on a saturated growth model and a median spectral index optimality statistic of 0.31. Our hyperspectral sensitivity analysis revealed optimal NIR and SWIR bands for the composition of the dNBR that are outside the ranges of the NIR and SWIR bands of the Landsat 8 and Sentinel-2 sensors. With the launch of the Precursore Iperspettrale Della Missione Applicativa (PRISMA) in 2019 and several planned spaceborne hyperspectral missions, such as the Environmental Mapping and Analysis Program (EnMAP) and Surface Biology and Geology (SBG), our study provides a timely assessment of the potential and sensitivity of hyperspectral data for assessing fire severity. Full article

Carolina Bays are oriented and sandy-rimmed depressions that are ubiquitous throughout the Atlantic Coastal Plain (ACP). Their origin has been a highly debated topic since the 1800s and remains unsolved. Past population estimates of Carolina Bays have varied vastly, ranging between as few as 10,000 to as many as 500,000. With such a large uncertainty around the actual population size, mapping these enigmatic features is a problem that requires an automated detection scheme. Using publicly available LiDAR-derived digital elevation models (DEMs) of the ACP as training images, various types of convolutional neural networks (CNNs) were trained to detect Carolina bays. The detection results were assessed for accuracy and scalability, as well as analyzed for various morphologic, land-use and land cover, and hydrologic characteristics. Overall, the detector found over 23,000 Carolina Bays from southern New Jersey to northern Florida, with highest densities along interfluves. Carolina Bays in Delmarva were found to be smaller and shallower than Bays in the southeastern ACP. At least a third of Carolina Bays have been converted to agricultural lands and almost half of all Carolina Bays are forested. Few Carolina Bays are classified as open water basins, yet almost all of the detected Bays were within 2 km of a water body. In addition, field investigations based upon detection results were performed to describe the sedimentology of Carolina Bays. Sedimentological investigations showed that Bays typically have 1.5 m to 2.5 m thick sand rims that show a gradient in texture, with coarser sand at the bottom and finer sand and silt towards the top. Their basins were found to be 0.5 m to 2 m thick and showed a mix of clayey, silty, and sandy deposits. Last, the results compiled during this study were compared to similar depressional features (i.e., playa-lunette systems) to pinpoint any similarities in origin processes. Altogether, this study shows that CNNs are valuable tools for automated geomorphic feature detection and can lead to new insights when coupled with various forms of remotely sensed and field-based datasets. Full article