Diagnostics最新文献

Background: Swept-source optical coherence tomography angiography (SS-OCTA) enables rapid assessment of retinal microvasculature. However, cross-platform comparability remains limited by device-specific acquisition and image quality characteristics. This study prospectively compared two novel SS-OCTA systems, DREAM (200 kHz) and BMizar (400 kHz). Methods: Fifty eyes from 25 healthy participants underwent 3 mm × 3 mm macular OCTA imaging with both devices in a single session. Images were analysed using OCTAVA to extract foveal avascular zone (FAZ) area, vessel area density (VAD), total vessel length (TVL), node counts, fractal dimension (FD), median vessel length (MVL) in SCP, and mean vessel diameter (MVD) in DCP. Image quality was assessed using FAZ-noise rate, contrast-to-noise ratio (CNR), and FAZ noise-floor standard deviation. Paired comparisons were performed using Wilcoxon signed-rank tests and Cliff's delta. Results: BMizar acquisition time was shorter than DREAM for the evaluated 3 × 3 mm protocol (median 5.36 s vs. 9.93 s), reflecting differences in A-scan rate and protocol implementation; acquisition time is therefore reported descriptively. In the SCP, DREAM yielded lower VAD (41.9% vs. 48.8%) and fewer nodes (1547 vs. 1879) but exhibited markedly less background noise (noise-floor SD 4.1 vs. 57.9) and substantially higher CNR (16.7 vs. 0.82). DREAM also showed longer MVL (45 vs. 39 µm) and higher FD (1.98 vs. 1.97; δ = 0.90). In the DCP, DREAM demonstrated smaller FAZ areas (0.27 vs. 0.42 mm²), thinner MVD (14 vs. 25 µm), higher node counts (3144 vs. 2301), longer TVL (223.6 vs. 206.2 mm), and higher FD (1.98 vs. 1.97), whereas VAD was higher on BMizar (32.96% for DREAM vs. 49.93% for BMizar). FAZ-noise rates were consistently higher for BMizar in both plexuses. Conclusions: Both devices provide reliable SS-OCTA imaging, but with distinct strengths. DREAM delivers higher vascular continuity and more reliable FAZ and DCP quantification, whereas BMizar achieves faster acquisition at the cost of noise, inflating SCP density and distorting FAZ-based metrics. Awareness of these characteristics is essential to ensure the valid use of OCTA biomarkers in clinical and research applications.

Background: Existing evidence suggests an association between temporomandibular disorders (TMDs) and alterations in body posture and balance; however, the mechanism underlying this relationship remains unknown. The present study aimed to investigate the associations between specific TMD subtypes, indices of bioelectrical activity of the masticatory muscles, and parameters of body posture and balance. Methods: The study followed a case-control study design. A total of 81 participants were enrolled, including 33 controls and 48 individuals with TMD, classified into myofascial (n = 14), articular (n = 17), and mixed (n = 17) subtypes. Diagnosis of temporomandibular disorders was carried out by prosthodontic specialists using the Polish adaptation of the Diagnostic Criteria for Temporomandibular Disorders. Masticatory muscle bioelectrical activity was assessed by surface electromyography. For statistical analysis, the Asymmetry Index and Functional Clenching Activity Indices were used. Static balance was evaluated with a pedobarographic platform. The sway area, velocity, and length of the Center of Pressure, as well as the foot contact area, were recorded and automatically calculated by the system. Measurements were performed under different mandibular conditions, with both eyes open and eyes closed. Correlation analyses were performed using Spearman Rank Order Correlation. Pearson's Chi-squared test was used for the analysis of categorical variables. Results: Weak to moderate negative correlations were primarily observed, indicating that higher indices of masticatory muscle bioelectrical activity were associated with better postural balance, with distinct correlation patterns identified across different TMD subtypes. Conclusions: This exploratory study identified multiple correlations between masticatory muscle activity and postural or balance parameters, suggesting possible subtype-specific patterns in TMDs. However, the evidence remains preliminary and should be interpreted with caution, warranting further confirmatory and longitudinal research.

Portal vein thrombosis (PVT) refers specifically to the presence of a thrombus within the main portal vein trunk or its intrahepatic branches. In contrast, portal vein occlusion encompasses a broader spectrum of conditions, including tumor invasion, external compression and disorders that predispose to thrombosis, such as thrombophilia or inflammatory states. Advanced liver disease, particularly cirrhosis, is the most common cause of PVT, primarily due to portal hypertension, altered hemostasis and hemodynamic changes, followed by malignancies and inherited or acquired thrombophilic conditions. In contrast to these common etiologies, our clinical experience has highlighted rare causes of portal vein obstruction associated with typical presentations, which pose diagnostic challenges. Examples include acute PVT during transjugular intrahepatic portosystemic shunt (TIPS) placement and non-thrombotic porto-mesenteric obstruction related to portal venous gas. While these events may appear unexpected, they represent a recognizable group of uncommon causes rather than isolated incidents. PVT can present as an acute or chronic condition: acute thrombosis is characterized by recent thrombus formation and potential intestinal ischemia, whereas chronic thrombosis is associated with long-standing obstruction, cavernous transformation and portal hypertension. This narrative review integrates a comprehensive literature search with clinical experience, with particular emphasis on uncommon etiologies of portal vein obstruction.

Background: Non-alcoholic fatty liver disease (NAFLD) represents the most widespread chronic liver disorder globally, impacting roughly 30% of the general population. Numerous factors have been linked to NAFLD, including obesity, type 2 diabetes, diet, physical inactivity, age, sex, genetic factors, and metabolic syndrome. Previous research predominantly treated NAFLD as a categorical outcome, providing less granular data compared to the continuous fatty liver index (FLI). This investigation enrolled healthy young Taiwanese men and applied multivariate adaptive regression spline (MARS) modeling to develop a predictive equation. Our aims were twofold: 1. To assess the predictive accuracy of traditional multiple linear regression (MLR) versus MARS. 2. To construct a MARS-derived equation for estimating FLI in this demographic. Methods: Data originated from the Taiwan MJ Cohort, comprising 5496 men aged 20-50 years not using medications for metabolic syndrome. MARS was used to formulate the FLI estimation equation. Model performance was compared using symmetric mean absolute percentage error (SMAPE), relative absolute error (RAE), root relative squared error (RRSE), and root mean squared error (RMSE). Results: Evaluation indicated that MARS yielded lower estimation errors than MLR, demonstrating its superior performance. The derived equation is: FLI = 65.224 - 0.436 × B1 - 0.490 × B2 + 0.252 × B3 - 2.962 × B4 + 2.231 × B5 - 0.292 × B6 + 0.189 × B7 - 0.361 × B8 - 0.699 × B9 + 0.160 × B10 - 2.715 × B11 + 0.799 × B12 - 0.153 × B13 + 0.084 × B14 - 35.274 × B15 - 4.424 × B16. Conclusions: Using MLR as a benchmark, our analysis revealed that MARS delivered better predictive performance. The presented equation explains 62.7% of the variance in FLI (r² = 0.627). Based on standardized variable importance scores (nsubsets metric), CRP emerged as the most influential predictor, followed by WBC, UA, HDL-C, AST, age, ALT, FPG, SBP, and LDL in this cohort of healthy young Taiwanese men.

Background/Objective: Di-2-ethylhexyl phthalate and its bioactive metabolite mono-2-ethylhexyl phthalate (MEHP) are ubiquitous endocrine-disrupting chemicals implicated in carcinogenesis. However, the molecular mechanisms linking MEHP exposure, host genetic susceptibility, and prostate cancer progression remain incompletely defined. Methods: We integrated transcriptomic profiling of MEHP-exposed human prostate epithelial cells with a genetic association study of 630 patients with prostate cancer receiving androgen deprivation therapy. MEHP-responsive genes were identified from public microarray datasets and subjected to pathway enrichment analyses. Germline single-nucleotide polymorphisms (SNPs) in MEHP-regulated genes were evaluated for their association with progression-free survival, overall survival, and cancer-specific survival. The clinical and functional relevance of the key genes was further assessed using large-scale public prostate cancer expression datasets. Results: MEHP exposure induced widespread transcriptional reprogramming, prominently suppressing focal adhesion and cell-matrix interaction pathways. Genetic analyses identified multiple prognostically relevant SNPs within MEHP-responsive genes, with anoctamin 4 (ANO4) variants showing consistent associations across all clinical endpoints. The minor allele of rs17485225 in ANO4 was significantly associated with reduced all-cause and prostate cancer-specific mortality. Pooled analyses revealed reduced ANO4 expression levels in prostate cancer tissues and improved survival in patients with high ANO4 expression levels. Pathway analyses linked low ANO4 expression levels with enhanced cell cycle activity and compromised cell adhesion. Conclusions: Our findings suggest that ANO4 may act as a mediator of MEHP-associated prostate cancer progression and support a gene-environment interaction model in which environmental toxicant exposure and germline variation converge on focal adhesion dysregulation to potentially contribute to aggressive disease.

Background/Objectives: The presence of untreated second mesio-buccal canals (MB2) in maxillary first molars is usually associated with endodontic treatment failure. Previous CBCT-based investigations have evaluated the quality of root canal fillings and the prevalence of apical lesions in endodontically treated teeth. However, evidence specifically addressing untreated MB2 canals and their association with apical periodontitis remains limited. Therefore, the aim of this cross-sectional study was to evaluate the prevalence of unfilled MB2 canals in endodontically treated maxillary first molars and their association with apical periodontitis. Methods: CBCT scans of 75 patients from an endodontic practice were retrospectively analyzed. Maxillary first molars (teeth 16 and 26) were evaluated for the presence and filling status of root canals (MB1, MB2, palatal, distal) and the presence of periapical radiolucency using the CBCT periapical index. Two calibrated examiners independently assessed all images. The association between unfilled MB2 canals and apical periodontitis was analyzed using chi-square tests, and odds ratios with 95% confidence intervals were calculated. Results: The mean patient age was 53.4 ± 15.5 years (range: 14-80). An MB2 canal was present in 84% (63/75) of eligible teeth. Among teeth with an MB2 canal, only 20.6% (13/63) were endodontically filled, while 79.4% remained untreated. Apical periodontitis was observed in 65.3% (49/75) of all teeth. A significant association was found between unfilled MB2 canals and apical periodontitis (p < 0.001), with an odds ratio of 0.095 (95% CI: 0.022-0.402), indicating that filled MB2 canals significantly reduced the possible risk of periapical pathology. Conclusions: A high prevalence of unfilled MB2 canals was observed in this German population (79.4%). Furthermore, unfilled MB2 canals were strongly associated with apical periodontitis. Therefore, clinicians should utilize all available diagnostic tools, including CBCT and dental microscopes, to maximize MB2 canal identification and improve endodontic treatment outcomes.

In relation to the most commonly described ampullary ectopic pregnancies in contemporary gynecological practice, rare localizations of ectopic pregnancies represent a diagnostic and therapeutic challenge whose clinical significance far exceeds their frequency. In contrast to tubal ectopic pregnancy, these implantation localizations are characterized by specific anatomical relationships and early trophoblastic invasion into highly vascularized tissues, which is why classical diagnostic algorithms and therapeutic patterns are often not applicable in clinical practice. Clinical uncertainty is further increased by the fact that a large proportion of these pregnancies in early gestation cannot be precisely mapped and initially present as pregnancies of unknown location. This narrative review integrates contemporary evidence and guidelines of relevant professional societies with the aim of highlighting patterns of diagnostic errors, systemic weaknesses of existing approaches, and key points for safe clinical decision-making. Special emphasis is placed on the role of disciplined transvaginal ultrasound evaluation, terminological precision, and timely recognition of high-risk and nonspecific implantations. Analysis of the available literature indicates that therapeutic decisions must be individualized and guided by the implantation site and assessment of hemorrhagic risk, rather than gestational age or absolute β-hCG values. Understanding these principles represents the basis for reducing serious complications and for the development of future diagnostic and therapeutic algorithms, thereby improving treatment outcomes.

Isolated pelvic nodal metastasis from carcinoma of unknown primary origin (CUP) is rare. Evaluation should prioritize gynecological and anorectal sites based on pelvic lymphatic drainage. Although spontaneous regression of these primary lesions is exceptional, regressed lesions can present as CUP, necessitating diagnostic caution. Here, we report the case of a 40-year-old woman with a solitary, intensely fluorodeoxyglucose F-18 avid left obturator lymph node and a subtle endocervical abnormality on pelvic magnetic resonance imaging. Loop electrosurgical excision revealed a Nabothian cyst only. Excisional nodal biopsy by polymerase chain reaction revealed metastatic squamous cell carcinoma with diffuse block-type p16 and human papillomavirus (HPV) 16. Considering the potential for a primary cervical tumor along the obturator drainage pathway, the patient underwent hysterectomy with pelvic lymph node dissection. No residual invasive carcinoma was found; however, HPV16 was detected in the cervix with a low-grade squamous intraepithelial lesion, supporting a regressed cervical focus. She received adjuvant cisplatin-based chemoradiotherapy and has remained disease-free for 56 months. This case highlights the diagnostic value of integrating lymphatic anatomy with the molecular profile of HPV. Cervical squamous cell carcinoma rarely regresses and presents solely as an isolated nodal disease.

Background: The clinical use of machine learning (ML) in survival analysis is often limited by the "black box" nature of complex algorithms, which makes their results difficult to interpret in practice. In this study, we propose a unified and clinically grounded framework that integrates ML-based feature selection with traditional survival analysis. This approach aims to bridge the gap between strong predictive performance and clear, clinically meaningful interpretation. Methods: High-impact prognostic clinical features were identified using ML models GBM-Cox, RSF, and LASSO-Cox with 5-fold stratified cross-validation and subsequently validated using Cox Proportional Hazards and Kaplan-Meier analysis. The framework was evaluated across two distinct disease domains, Heart Failure and the METABRIC breast cancer cohort, to assess robustness and generalizability. Results: In the Heart Failure dataset, age group, serum creatinine, and blood pressure stratified patients into distinct risk groups. The high-risk group had significantly higher mortality (HR: 2.61; 95% CI: 1.42-4.78; p = 0.0013). In the METABRIC cohort, age at diagnosis, HER2 status, and Nottingham Prognostic Index (NPI) showed strong survival separation (p < 0.001). The high-risk group had an HR of 2.73 (95% CI: 2.34-3.19) and the faced a significantly shorter median survival (104.7 vs. 252.3 months), representing a 12.3-year reduction in life expectancy compared to low-risk group. This prognostic separation emphasizes the predictive power of selected baseline variables. Performance remained stable across cohorts, with C-index values (0.665-0.794) consistent with standard clinical benchmarks. Conclusions: Integrating cross-validated machine learning feature selection with Cox-based survival analysis enables stable and clinically interpretable risk stratification across diseases. By translating ML selected predictors into hazard ratios and absolute survival differences, this framework provides a reproducible and clinically grounded approach for survival risk assessment.

Objective: Accurate odor classification from EEG signals requires informative and interpretable features. Although Local Binary Pattern (LBP) and variants such as the center-symmetric binary pattern are widely used, they lack sufficient explainability and tensor-level implementations. Additionally, neuroscientific understanding of odor processing remains limited. Methods: We propose Tensor Center-Symmetric Binary Pattern (TensorCSBP), a novel tensor-based feature extractor designed for EEG odor analysis. TensorCSBP is integrated into an explainable feature engineering (XFE) pipeline with four steps: (1) TensorCSBP for feature generation, (2) CWNCA for feature selection, (3) tkNN classifier for decision making, and (4) DLob method for symbolic interpretability. Results: TensorCSBP XFE was evaluated on a newly collected 32-channel EEG dataset for odor detection. It achieved 96.68% accuracy under 10-fold cross-validation. Conclusions: The information entropy of the DLob symbol sequence was 3.5675, demonstrating the richness of the interpretability output. Significance: This study presents a high-accuracy, explainable, and computationally efficient model for EEG-based odor classification. TensorCSBP bridges low-level signal patterns with symbolic neuroscience insights, offering real-time potential for BCI and clinical applications.