Search Results (120)

Background/Objectives: Preservation of critical white matter (WM) pathways is essential for maximizing surgical safety in neuro-oncology and functional neurosurgery. Constrained spherical deconvolution (CSD) offers superior modeling of complex fiber architecture compared to diffusion tensor imaging (DTI). This case series evaluates the clinical utility of CSD in surgical planning and intraoperative navigation. Methods: A retrospective review of 20 patients (15 brain tumors, 5 functional disorders) treated between September 2022, and September 2024 was performed. All patients underwent preoperative MRI with CSD-based reconstruction of eloquent WM tracts. Clinical presentation, tract involvement, surgical strategy, and postoperative outcomes were analyzed. Results: CSD reliably reconstructed CST, AF, IFOF, OT, and DRTT depending on tumor location or DBS target. Compared with standard DTI, CSD provided improved delineation of tract extent and tumor–tract interfaces. Gross total resection (GTR) was achieved in all tumor patients without new neurological deficits. DBS cases showed precise correlation between stimulation thresholds, side effects, and CSD-predicted distances to critical WM tracts. DRTT targeting resulted in marked clinical improvement in Holmes tremor. Conclusions: CSD enhances anatomical accuracy in WM tract visualization, supporting safer resections in eloquent areas and improving DBS targeting. Its integration into routine workflow may optimize neurosurgical outcomes. Full article

Introduction: It is accepted that nano- and micro-plastic (NMP) pollutants threaten ecosystems and human health by their bioaccumulation but, interestingly, their toxicity is shape-dependent. However, a clear definition of irregular NMPs, as the dominant shape in environmental and biological samples, is currently lacking when compared to spherical and fibrous NMPs. Objectives: This study quantifies morphometric descriptors in order to develop a standardized definition for irregular NMPs. Methods: Hyperspectral images of 34 spherical, 50 fibrous, and 45 irregular NMPs were collected from the literature. All shape-related features reported previously were analyzed using a machine learning model. Using five-fold cross-validation, a decision tree-based ensemble classifier with fixed parameters and Gini coefficient was established to screen key morphometric descriptors and their optimal interval ranges. The model was independently validated, enabling the accurate distinction of irregular NMPs from spherical and fibrous NMPs. Results: Three morphometric descriptors, including circularity, roundness, and perimeter-to-area ratio, were identified using five-fold cross-validation as optimal indicators for NMP shape classification. Optimal interval ranges for irregular NMPs were as follows: circularity (0.388 ± 0.004–0.768 ± 0.004), roundness (0.248 ± 0.01–0.752 ± 0.06) and perimeter-to-area ratio (>11.608 ± 1.39). This approach generated a 96.0% macro-averaged accuracy across these NMPs, with 100% precision and 89.0% recall. Conclusions: Irregular NMPs may be characterized using three morphometric descriptors, such as circularity, roundness, and perimeter-to-area ratio. The three-descriptor combination has highly accurate discrimination from spherical and fibrous NMPs. Full article

Background/Objectives: The oral administration of donepezil has been shown to have common side effects due to systemic drug delivery, with fluctuations in blood and brain donepezil concentrations. Therefore, we obtained nanostructured lipid carriers loaded with donepezil (donepezil–NLC) for nose-to-brain targeting. Methods: The obtained NLCs were characterized by measurements of particle size, the polydispersity index, zeta potential, encapsulation efficiency, atomic force microscopy, Differential Scanning Calorimetry, Fourier transform infrared spectroscopy, X-ray diffraction, and in vitro release studies. Plasma and brain pharmacokinetic studies in Wistar rats were carried out to determine brain targeting. Results: Donepezil–NLC showed low polydispersity and nanometric size, high zeta potential, and high drug entrapment efficiency. Microscopy images showed spherical particles with regular surfaces. Thermal analysis, X-ray diffraction, and FTIR-ATR suggested the formation of an amorphous lipid matrix and the incorporation of donepezil molecularly dispersed within the lipid matrix. In vitro drug release studies demonstrated a biphasic drug release pattern with an initial burst followed by sustained release, with results better fitted to the Korsmeyer–Peppas model (n-value > 0.5). Following the nasal administration of donepezil–NLC, brain pharmacokinetic studies in Wistar rats demonstrated a significant improvement in bioavailability. Compared to the intravenous injection of donepezil, the AUC^0–ꝏ value was 10.5-fold higher. Drug targeting efficiency and direct transport percentage showed extremely higher values, suggesting nose-to-brain targeting after donepezil–NLC intranasal administration. Conclusions: Donepezil–NLC has proven to be an efficient drug delivery system for the nose to the brain, which may reduce systemic toxicity and improve Alzheimer’s therapy with low doses of donepezil and fewer adverse effects. Full article

Background/Objectives: Electroanatomic mapping (EAM) provides high-resolution spatial and electrogram information, but the prognostic utility of quantitative EAM features has not been systematically evaluated with contemporary artificial intelligence (AI) methods. We investigated whether an AI analysis of quantitative EAM exports from the CARTO system enhances the prediction of major arrhythmic events (MAEs). Methods: In this retrospective, multicenter cohort study, 248 consecutive patients undergoing left ventricular EAM at four tertiary electrophysiology centers were analyzed. Numerical EAM descriptors (spatial coordinates, unipolar/bipolar voltages, local activation time, impedance) were transformed into derived metrics, including local activation heterogeneity (GR), late-potential extent (LAT), bipolar–unipolar discrepancy (VLT), and low-amplitude scar extent (Scar Areas), and were spatially normalized via spherical projection. Clinical, anamnestic, and imaging variables were integrated. Machine learning and deep learning models were trained with an 80:20 train/test split and evaluated using three-fold cross-validation. Performance metrics included area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, and precision. Results: Models incorporating both clinical and AI-processed EAM features achieved high discriminatory performance (test AUC up to 0.92; accuracy up to 0.896). Specificity was consistently high (≈0.97–0.998), whereas sensitivity remained modest (≈0.39–0.58). Among the EAM-derived features, GR was the most consistently informative predictor across algorithms and analyses; VLT, LAT, and Scar Areas also contributed substantially. Regionally, basal sub-mitral, subaortic, and posterolateral basal-to-mid zones exhibited the strongest associations with MAEs. Conclusions: AI-driven quantitative analysis of left ventricular EAM exports augments risk stratification for MAEs beyond conventional clinical and binary EAM descriptors. Reflecting local conduction heterogeneity, GR emerged as the dominant EAM predictor. Prospective validation in larger, disease-specific cohorts and real-time integration within EAM platforms are warranted. Full article

Accurate estimation of object attitude is essential for understanding motion behavior and achieving dynamic tracking. Existing image-based methods often suffer from low efficiency and limited accuracy, while the potential of deep learning has not been fully exploited in this field. To address these limitations, a lightweight deep learning method for attitude estimation is proposed and validated on spherical particles. A synthetic dataset is generated through VTK-based rendering and automatic annotation, providing large-scale training samples with known Euler angles. An improved MobileNetV1 backbone is developed by integrating Squeeze-and-Excitation blocks, a dual-scale Pyramid Pooling Module, global average pooling, and a regression-oriented multilayer perceptron, which enhances feature extraction and enables direct Euler angle prediction. Experimental results show that the proposed method achieves an average error of 0.308° on synthetic test images. Furthermore, a solid particle was fabricated through 3D printing and physical measurements were conducted, where the network combined with image preprocessing and augmentation achieved an average error of about 0.5° on real images, demonstrating a lightweight and deployment-friendly framework for practical attitude estimation. The results verify the effectiveness of the method and demonstrate its potential for accurate and computationally efficient attitude measurement in applications such as fluid dynamics, industrial inspection, and motion tracking. Full article

Background/Objectives: Accurate determination of active pharmaceutical ingredient (API) particle size within dry powder inhaler (DPI) formulations is essential for ensuring effective pulmonary delivery but remains analytically challenging due to low API content and micronized particle size. Methods: In this study, scanning electron microscopy (SEM) coupled with energy-dispersive X-ray microanalysis (EDX) was used to directly identify and calculate the API particle size within several different commercial DPI products fit for purpose under regulatory constraints. The method exploits unique elemental markers inherent to each API, enabling reliable discrimination from excipients without prior sample modification or API extraction. Results: Large-area SEM–EDX mapping was used to localize API particles, followed by high-magnification imaging and confirmatory spot microanalysis. Particle sizes were manually measured for at least 50 API particles per formulation using image analysis software, and particle size distribution parameters were calculated from equivalent spherical diameters. Conclusions: The methodology was successfully applied to Spiriva^®, Anoro^® Ellipta, and Relvar^® Ellipta inhalation powders, revealing micronized APIs with distinct morphological features and verifying systematic application across products. Cross-validation against laser diffraction measurements of pure APIs demonstrated statistical equivalence, confirming the robustness and analytical utility of the proposed method for particle size assessment in DPI formulations. Full article

Background/Objectives: Novel hotspot displacement radiomic features (normalized hotspot-to-centroid distance [NHOC]/normalized hotspot-to-perimeter distance [NHOP]) are robust against image resampling and spatial resolution variations. However, their reproducibility under respiratory motion remains unvalidated. This study aimed to evaluate the reproducibility, reliability, and survival prognostic value of NHOC/NHOP features in thoracic ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) images with and without respiratory motion correction and to determine whether these features maintain stability and predictive performance for overall survival (OS) compared with respiratory-stable reference features. Methods: We analyzed 138 patients (203 lesions) who underwent ¹⁸F-FDG PET/CT with and without data-driven respiratory gating. Reproducibility and reliability were assessed using the coefficient of variation (CoV) and intraclass correlation coefficient (ICC), respectively. OS prediction was evaluated using Cox regression and concordance index (c-index) analyses. Results: Except for NHOCmax and NHOPpeak, which showed ICC values of 0.782 and 0.93, respectively, the novel morphological features generally exhibited poor reproducibility and moderate reliability (CoV > 20% and ICC < 0.75). In contrast, reference features (entropy-based and sphericity) demonstrated excellent robustness. Motion-corrected NHOCmax showed significant OS prediction for both spatially resampled and non-resampled images. No significant differences in c-indices were observed between motion-corrected and non-corrected features. Conclusions: The marked sensitivity of novel hotspot-displacement features to respiratory motion substantially limits their clinical applicability in thoracic disease. To ensure reproducibility and generalizability in future research, prioritizing inherently robust radiomic parameters, such as entropy-based features, is strongly recommended. Full article

Background/Objectives: Premium intraocular lenses (IOLs) are increasingly being selected for cataract and refractive lens surgery, but their functional performance depends critically on pupil size and corneal spherical aberration (SA). This study evaluates how these factors modulate the optical behavior of the RayOne EMV and Tecnis Synergy using a profilometry-based Through Object modulation transfer function (TO MTF) analysis. Methods: The surface profiles of the RayOne EMV and Tecnis Synergy were measured with a confocal optical profilometer and implemented in pseudophakic eye models via ray tracing. TO MTF at 50 cycles/mm was computed for object vergences from −4.0 D to +2.0 D over entrance pupil diameters from 2.0 to 5.5 mm in three corneal configurations derived from the Liou–Brennan model and ISO recommendations: mean population SA, aberration-free, and a myopic LASIK-like oblate cornea. Simulated optotype images were generated to relate TO MTF values to the expected distant, intermediate, and near visual performances. Results: RayOne EMV delivered high-quality distant image performance in all models. Its depth of focus increased only modestly and showed a strong dependence on pupil size. Intermediate and near vision rarely reached clinically acceptable levels. The Tecnis Synergy produced a broad depth-of-field plateau in distant to near visual performance for mean population spherical aberration at a 3.5 mm pupil. However, image quality at 90 cm remained limited. Optical performance worsened with increasing pupil size and positive spherical aberration, particularly under post-myopic LASIK conditions. Conclusions: The RayOne EMV behaves predominantly as a distance-oriented design with minimal true presbyopic benefit; the Tecnis Synergy provides a wider range of vision but is highly sensitive to corneal spherical aberration and pupil size, so thorough preoperative evaluation of corneal asphericity and functional pupil diameter is essential for IOL selection and power targeting. Full article

Background/Objectives: Subjective refraction is the clinical gold standard but is time-consuming and examiner-dependent. Most artificial intelligence (AI)-based approaches rely on specialized imaging or biometric data not routinely available. This study aimed to predict subjective refraction using only routine, non-cycloplegic autorefraction and keratometric data and to identify factors associated with reduced prediction accuracy. Methods: This retrospective study included 1856 eyes from 1006 patients. A multi-output histogram gradient-boosting model predicted subjective spherical equivalent, cylindrical power, and astigmatic axis. Performance was evaluated on an independent test dataset using R² and mean absolute error, with circular statistics for axis prediction. Prediction failure was assessed using clinically relevant tolerance thresholds (sphere/cylinder ≤ 0.50 D; axis ≤ 10°) and multivariable logistic regression. Results: The model achieved high accuracy for spherical and cylindrical prediction (R² = 0.987 and 0.933; MAE = 0.126 D and 0.137 D). Astigmatic axis prediction demonstrated strong circular agreement (ρ = 0.898), with a mean absolute angular error of 4.65° (median, 0.96°). Axis errors were higher in eyes with low cylinder magnitude (<0.75 D) and oblique astigmatism. In multivariable analysis, steeper keratometry (K2; OR = 7.25, 95% CI 1.62–32.46, p = 0.010) and greater objective cylindrical power (OR = 2.79, 95% CI 1.87–8.94, p = 0.032) were independently associated with poor prediction. Conclusions: A machine-learning model based solely on routine, non-cycloplegic autorefractor and keratometric measurements can accurately estimate subjective refraction, supporting AI as a complementary decision-support tool rather than a replacement for conventional subjective refraction. Full article

This work presents a compact refractometric system based on In-Line Digital Holography (ILDH) for the non-invasive characterization of transparent media, encompassing both liquids and high-refractive-index optical glasses. The core of the system is a cost-effective, lensless setup in which a 532 nm laser source and a microscope objective generate a divergent spherical wavefront that illuminates a 10 μm aluminum particle. The resulting diffraction pattern, modulated by samples in the optical path, is recorded by a CMOS sensor. The refractive index of the sample is determined by numerically locating the axial position of the particle-reconstructed image, which directly corresponds to the optical path difference introduced by the test medium. The optimal reconstruction plane is objectively located using an autofocus algorithm based on the Kurtosis metric, which identifies the sharpest image. The system successfully characterizes media across a broad refractive index range from 1.33 to 1.78, yielding linear calibration curves for both liquid and solid samples. The instrument achieves an axial reconstruction resolution of 30 μm and a refractive index precision of ±0.01 RIU. This ILDH approach offers a highly portable, cost-effective, and non-contact solution for refractive index measurement, demonstrating significant potential for industrial quality control and high-throughput point-of-care applications. Full article

Objective: To develop a stable nanoemulsion loaded with Magnoliae Flos essential oil (MEO-NE) and evaluated its potential as an enhancer for nose-to-brain delivery in both solution and gel formulations. Methods: The MEO-NE was prepared using a low-energy emulsification method, with the formulation optimized via single-factor experiments and Box–Behnken design-response surface methodology. The optimized MEO-NE was characterized for particle size, PDI, morphology, and nasal mucosal irritation. Ex vivo histological imaging in rats was performed using hydrophilic sulfo-cyanine7 carboxylic acid and lipophilic coumarin 6 as fluorescent probes to assess distribution and retention in the trigeminal nerve and brain tissues. Results: The optimized MEO-NE exhibited a small particle size (27.96 ± 0.94 nm), low PDI (0.089 ± 0.013), spherical morphology, a stable O/W structure, and no irritation to the nasal mucosa. Ex vivo imaging revealed that MEO-NE significantly enhanced the distribution and retention of both hydrophilic and lipophilic probes in the trigeminal nerve and brain tissues. Moreover, the gel formulation of MEO-NE demonstrated superior brain-targeting efficiency over the solution within 6 h. Conclusions: MEO-NE served as an effective enhancer for nose-to-brain delivery, improving brain uptake of both hydrophilic and lipophilic drugs, and provided an experimental basis for utilizing herbal essential oils in CNS-targeted delivery systems. Full article

Background: Three-dimensional (3D) culture systems offer a physiologically relevant alternative to monolayers for studying tumor organization, signaling, and drug response. HER2-positive breast cancers (BCa) account for 15–30% of BCa cases and benefit from HER2-targeted therapies, yet predictive in vitro models remain limited. Objective: To generate and compare 3D spheroids from two HER2+ BCa cell lines, SKBR3 and BT474, and investigate how 3D architecture influences HER2 distribution, intracellular signaling, and cellular organization. Methods: Spheroids were reproducibly generated from SKBR3 and BT474 cells and analyzed after 4 days of culture. Cell viability was evaluated using live/dead staining, HER2 distribution was assessed by confocal microscopy and quantified on cryosections, and protein expression/phosphorylation was measured by Western blotting. Epithelial and EMT markers were visualized by immunofluorescence, and ultrastructural features were examined by transmission electron microscopy (TEM). Results: Both cell lines formed viable spheroids with distinct architectures: SKBR3 spheroids were loose and heterogeneous, whereas BT474 spheroids were compact and highly spherical. Confocal and cryosection imaging showed consistent membrane HER2 localization with a progressive signal decrease toward the core of the spheroids, more pronounced in BT474. Western blotting revealed divergent HER2 expression and AKT phosphorylation: SKBR3 spheroids displayed increased HER2 but reduced pAKT, while BT474 spheroids showed reduced HER2 and pAKT levels. EpCAM and E-cadherin staining revealed cell line-specific epithelial organization, and TEM demonstrated differences in intercellular spacing and mitochondrial morphology, reflecting spheroid compactness. Conclusions: 3D architecture profoundly influences HER2 distribution, signaling, and structural organization in HER2+ BCa spheroids. This model provides a robust platform for investigating architecture-dependent molecular processes, with potential applications in drug response, receptor trafficking, and targeted therapy evaluation. Full article

Background/Objectives: The purpose of this study was to evaluate the implementation of ultra-widefield swept-source optical coherence tomography (SS-OCT) in characterizing peripheral retinal degenerations and rhegmatogenous lesions, and to assess its potential implications for clinical management. These lesions are often challenging to visualize with conventional techniques, highlighting the need for advanced imaging modalities to improve detection and characterization. Methods: We conducted a retrospective observational study involving patients diagnosed with peripheral retinal degenerations and/or rhegmatogenous lesions referred to our center. All participants underwent comprehensive ophthalmological evaluation, including slit-lamp biomicroscopy, dilated fundus examination, and peripheral SS-OCT imaging. Key parameters assessed included the presence of vitreoretinal attachment, vitreous traction, full-thickness retinal defects, and subretinal fluid associated with the peripheral lesions under investigation. Results: A total of 107 eyes from 95 patients were included. The mean spherical equivalent was −2.18 ± 2.5 diopters, and mean BCVA was 0.03 ± 0.11. Peripheral SS-OCT imaging successfully captured and characterized 130 retinal lesions, including retinal tears (n = 34), lattice degeneration (n = 25), retinal holes (n = 21), peripheral retinoschisis (n = 17), and schisis/detachment (n = 7). Less commonly observed lesions were snail track degeneration (n = 4), white without pressure (n = 4) microcystic degeneration (n = 2), dialysis (n = 2), condensed vitreous (n = 2), and paving stone degeneration (n = 1). SS-OCT provided high-resolution visualization of the peripheral retina and vitreoretinal interface, revealing findings such as vitreous traction, everted edges in retinal holes, and associated subretinal fluid, some of which were not clinically detectable and, in several cases, directly influenced management decisions. Conclusions: Ultra-widefield SS-OCT significantly enhanced the visualization of peripheral retinal degenerations and rhegmatogenous lesions, providing clinically meaningful details that may influence diagnosis and clinical decision-making. Full article

Background/Objectives: The aim of this study was to establish the relationship between target size and the required diagnostic PET maximum standard uptake value (SUVmax) thresholds needed for successful Biology-guided Radiotherapy (BgRT) delivery on RefleXion X1 PET-linac. The current clinical eligibility recommendation is an SUVmax ≥ 6 at simulation, but the RefleXion system subsequently evaluates Activity Concentration (AC), which must exceed 5 kBq/mL for successful BgRT planning. Methods: A custom 3D-printed phantom containing six spherical targets (8 to 20 mm diameter) was used with varying target-to-background ratios (5:1 to 20:1) of 18F-FDG to systematically achieve a range of SUVmax values for each target size. Images were acquired on Siemens Biograph mCT for SUVmax quantification and RefleXion X1 for AC measurements. Twenty-four BgRT plans were evaluated, and delivery accuracy was validated using ArcCHECK. Additionally, retrospective data from 18 patients across four institutions were analyzed to validate the phantom-derived findings. Results: The PET-linac successfully planned treatments for 13/24 experiments, all achieving an AC > 5 kBq/mL. SUVmax requirements varied by target size: 16–20 mm targets required an SUVmax > 6, consistent with current recommendations, while smaller targets required higher thresholds (e.g., 13 mm: SUVmax > 10, and 11 mm: SUVmax > 15). 8 and 9 mm targets failed to meet AC requirements even at SUVmax 14. Successful deliveries maintained acceptable accuracy, with gamma passing rates of 92.4% ± 5.0% (3%/2 mm) and 97.6% ± 1.9% (3%/3 mm). Analysis revealed that Volume (cc) × SUVmax > 11 consistently predicted successful BgRT planning across all target sizes. This threshold was validated using multi-institutional PET-CT patient data (mean: 11.36, 95% CI: 9.1–12.9), correctly predicting treatment eligibility in 15 of 18 cases. Conclusions: Target size significantly influences BgRT eligibility. We derived a new criterion, Volume(cc) × SUVmax > 11 (95% CI: 9.1–12). Full article

Silver nanoparticles (AgNPs) were synthesized using a modified literature method involving aqueous AgNO₃ (3 mM) and plant extract (LCE) at a constant ratio, under alkaline conditions and controlled temperature. The nanoparticles were characterized by UV-Vis spectroscopy, dynamic light scattering (DLS), zeta potential analysis and scanning transmission electron microscopy (STEM). The UV-Vis spectra displayed a broad absorption band around 450 nm, indicative of polydispersity, while DLS revealed a hydrodynamic diameter of 90.3 nm with a polydispersity index of 0.3366. Zeta potential values suggested reduced electrostatic stability compared with previously reported plant-derived AgNPs, although STEM images confirmed predominantly spherical, well-dispersed nanoparticles with sizes between 15 and 20 nm. Functional assays in zebrafish demonstrated the biological relevance of AgNPs. In scopolamine-induced models of cognitive and behavioral deficits, AgNPs treatment significantly improved memory and locomotor activity, as assessed by the Y-Maze, Novel Tank Diving Test and Novel Object Recognition Test. Full article