Search Results (85)

Background: Dental ankylosis (DA) in growing patients leads to progressive infraocclusion and alveolar ridge deformities, compromising future implant rehabilitation. Decoronation has been proposed as a biologically driven alternative to extraction for preserving alveolar bone during growth. Objective: We aimed to evaluate the clinical outcomes of decoronation—alveolar ridge preservation, infraocclusion progression, implant site development, and the influence of treatment timing—in growing patients with ankylosed permanent anterior teeth. Methods: This systematic review was conducted in accordance with PRISMA 2020 guidelines. A comprehensive search of MEDLINE (EBSCO), EMBASE, Scopus, and Web of Science was performed (January 2006–May 2026), supplemented by grey literature screening. Eligible studies included clinical investigations reporting outcomes of decoronation in patients ≤18 years. Risk of bias was assessed using the Newcastle–Ottawa Scale (NOS) and Joanna Briggs Institute (JBI) checklist. Certainty of evidence was evaluated using the GRADE framework. Lastly, an inter-rater agreement was quantified using Cohen’s kappa coefficient. Results: Five studies (two retrospective cohorts and three case series) comprising 140 decoronated teeth with follow-up periods ranging from 1 to 30 years were included. A total of 78 records were identified across four databases; five studies met the eligibility criteria after duplicate removal and screening. Inter-rater agreement at the full-text eligibility stage was good (κ = 0.70). The overall risk of bias was low to moderate, and the certainty of evidence was rated as low using the GRADE framework. Vertical alveolar bone preservation or gain was consistently observed, particularly when decoronation was performed during the prepubertal or pubertal growth phases. The largest cohort (n = 103) reported substantial vertical bone gain when intervention occurred at a mean age of 13.0 years in girls and 14.6 years in boys. Infraocclusion stabilisation or improvement was reported across all studies. In contrast, horizontal ridge reduction persisted, with the only quantitative study reporting a mean bucco-palatal loss of 1.67 ± 1.12 mm (p = 0.004). No included study directly assessed implant placement outcomes. Overall, the certainty of evidence was low due to observational study designs, heterogeneity in outcome assessment, and absence of controlled comparators. Conclusions: Decoronation appears to be a promising strategy for preserving vertical alveolar bone and stabilising infraocclusion in growing patients with ankylosed teeth, particularly when performed before or during the pubertal growth phase. Evidence showed considerable bone height preservation, though horizontal ridge reduction persisted across cases. However, the certainty of evidence remains low because available studies are observational, heterogeneous, and lack direct extraction comparators. Therefore, high-quality prospective studies with standardised outcome measures and controlled comparisons are required to establish definitive clinical protocols. Participants underwent decoronation during childhood or adolescence (≤18 years); reported follow-up periods of up to 30 years reflect monitoring that extended into adulthood. Clinical significance: For clinical decision-making, decoronation should be considered once ankylosis with progressive infraocclusion is confirmed during active growth, ideally before the pubertal spurt; the decision should be guided by growth stage rather than chronological age, and clinicians should anticipate likely horizontal ridge reduction by planning for possible augmentation at implant placement and coordinating multidisciplinary follow-up until skeletal maturity. Full article

Fourth-generation immunoassays are widely used for HIV and syphilis screening; however, false-reactive results may increase confirmatory testing and operational burden in high-throughput laboratories. This study evaluated the comparative performance of automated chemiluminescent immunoassays (MAGLUMI^® HIV Ab/Ag Combi (Snibe Diagnostics Co. Ltd., Shenzhen, China), VITROS^® ECiQ HIV Combo (Ortho Clinical Diagnostics, Raritan, NJ, USA), MAGLUMI^® Syphilis (Snibe Diagnostics Co. Ltd., Shenzhen, China), and ARCHITECT^® Syphilis TP (Abbott Diagnostics, Abbott Park, IL, USA) within a routine diagnostic algorithm, incorporating antibody differentiation immunoassays (INNO-LIA^® HIV I/II Score (Fujirebio Europe N.V., Ghent, Belgium) and HIV-1 RNA PCR where applicable. A total of 240 archived serum samples for HIV testing and 180 for syphilis testing were analyzed. Agreement-based performance measures including sensitivity, specificity, overall percent agreement (OPA), and Cohen’s kappa (κ) were calculated as comparator-based estimates reflecting concordance within the routine diagnostic algorithm rather than absolute diagnostic accuracy against a universal reference standard. For comparisons with HIV-1 RNA PCR, positive and negative concordance rates are reported to reflect agreement between assays detecting different biological targets. Among samples with definitive (positive or negative) results, the MAGLUMI^® HIV Ab/Ag Combi assay showed complete agreement with INNO-LIA^® HIV I/II Score (κ = 1.00) and high agreement with PCR within the ARCHITECT^® HIV Ag/Ab Combo-reactive subset (κ = 0.90). The VITROS^® ECiQ HIV Combo assay demonstrated high agreement with INNO-LIA^® HIV I/II Score (κ = 0.916) and substantial agreement with PCR (κ = 0.715), with a lower negative concordance rate with PCR observed in the ARCHITECT-reactive subset. A parallel five-modality analysis of 11 discordant samples applying the CDC 2014 algorithm demonstrated that all three immunoassay platforms successfully detected confirmed HIV-seropositive individuals with controlled viremia despite negative PCR, while MAGLUMI^® HIV Ab/Ag Combi produced fewer false-reactive results than both ARCHITECT^® and VITROS^® in this discordant subset. Additionally, two cases showed INNO-LIA^® indeterminate results with positive PCR, consistent with acute HIV infection during the early seroconversion stage; all three immunoassay platforms produced signals above the non-reactive threshold in both cases. For syphilis testing, both MAGLUMI^® Syphilis and ARCHITECT^® Syphilis TP assays showed complete agreement with INNO-LIA^® Syphilis Score among samples with definitive results (κ = 1.00). In contrast, the RPR assay showed reduced positive predictive value (49.4%) and moderate agreement with INNO-LIA^® Syphilis Score (κ = 0.52). Automated chemiluminescent immunoassay (CLIA) platforms demonstrated high agreement within a structured diagnostic algorithm in a high-throughput screening setting. Differences in assay performance were observed across platforms, particularly with respect to discordant results in the ARCHITECT-reactive PCR-evaluated subset for HIV and non-treponemal concordance for syphilis. These platforms may support more efficient laboratory workflows; however, findings should be interpreted within the context of comparator-based classification rather than absolute diagnostic accuracy. Full article

The present entry focuses on definiteness agreement patterns in Modern Greek by exploring the function of the definite article in structures that involve a head noun and a modifier—typically an adjective, but not only—that is also accompanied by the definite article. Such structures have been variously dubbed polydefinite noun phrases/Determiner Phrases (or, simply, polydefinites), appositions, (pseudo)partitives, and evaluative appositives in the numerous studies that have been put forward to account for them over the past four decades or so. The peculiarity of these structures is the very presence of the second definite article that shows up whenever the modified noun itself is definite; at first sight, this ‘second’ article seems redundant, or expletive. Polydefiniteness has earned a privileged position in the literature, as has been discussed extensively and in depth over the past thirty years or so. The aim of this entry is to provide i. a description of the patterns that involve a noun and a modifier accompanied by its own definite article, and ii. a comprehensive survey of the relevant literature by highlighting commonalities and differences across the basic studies that have been written about polydefiniteness. Full article

DTDL (Digital Twins Definition Language) provides no mechanism for logical reasoning or constraint checking over digital twin models. We integrate DTDL with ASP Chef, a web-based Answer Set Programming (ASP) platform, via a structured DTDL-to-ASP mapping and three dedicated operations: @DTDL/Parse for fact generation, @DTDL/Analysis for structural metrics, and @DTDL/Debug for symbolic validation with LLM-guided repair. The key design decision is that error detection is symbolic and deterministic within the implemented set of constraint classes; a language model is invoked only after the ASP layer has produced a concrete, grounded diagnostic, keeping the correctness boundary with the symbolic layer. Soundness and completeness guarantees are scoped to these constraint classes; a formal proof is left as future work. We illustrate the framework on two agricultural use cases and report a proof-of-concept assessment on 99 diagnostics spanning 21 error classes across four domains. Three binary metrics are used: json_valid and entity_recall are computed mechanically; fix quality (judge_correct) is assessed by an independent LLM judge (Claude Sonnet 4.6). The complete grounded workflow achieves 90% judge_correct and 86% json_valid; a fair ablation baseline—same LLM and system message, but error type and entity name in natural language without structured diagnostics—achieves 77% and 75%, respectively. The gap is consistent across three independent judges and statistically significant (McNemar $p<0.01$), but the inter-judge reliability of judge_correct is limited ($\kappa$ ranging from 0.00 to 0.44), so results should be read as directional evidence rather than precise effect estimates. Excluding the dominant isolated_interface class ($n=28$, ceiling score), the conservative estimate is 87% vs. 79% on the remaining 71 diagnostics. These results constitute a preliminary proof-of-concept limited to a small number of models, a few application domains, and a single LLM configuration; results do not generalize beyond this specific setting. The judge_correct metric is assessed by LLM-as-judge and does not carry a perfect inter-annotator agreement. Full article

This manuscript develops and demonstrates a practical framework for evaluating automated classifiers used in communication research, using harmful language detection as an illustrative case. We combine (a) a structured review of documentation practices for 27 publicly available classifiers and their associated annotation processes with (b) a cross-dataset evaluation that re-tests each model beyond its original training context. Across 27 datasets, we extract and compare reporting on construct definitions, annotator instructions, and inter-annotator agreement, and we quantify generalization by applying each model to multiple out-of-domain test sets. We also benchmark a contemporary large language model (GPT-5) under a consistent prompting protocol to illustrate how LLM-based classification compares to fine-tuned classifiers. Results show that documentation is uneven and often insufficient for theory-driven measurement, inter-annotator agreement varies widely across datasets, and cross-dataset performance frequently drops substantially relative to within-dataset evaluations. Building on these findings and existing validation guidance, we provide a reusable checklist and decision flow to help researchers select, justify, and report classifier-based measures in ways that support transparency and cumulative science. Recommendations for researchers, reviewers, and journal editors stress aligning model selection with standards of validity, reliability, and transparency. Full article

Background/Objectives: To develop and assess the feasibility of a natural language processing (NLP) framework for automated assessment of radiology–pathology concordance in breast biopsy using machine learning-based analysis of unstructured reports. Methods: This retrospective study included 766 paired radiology and pathology reports from ultrasound- or mammography-guided breast biopsies (August 2020–May 2024). Reports underwent translation, normalization, tokenization, lemmatization, and synonym expansion, followed by structured encoding of BI-RADS and pathology categories. Three models were trained: a Decision Tree, a LightGBM classifier, and a fine-tuned BioBERT model. Concordance labels were defined by multidisciplinary consensus. Performance metrics included accuracy, sensitivity, specificity, F1-score, area under the curve (AUC), and Cohen’s kappa. SHapley Additive exPlanations (SHAP) analysis was used to identify influential features. Results: Among 766 cases, 707 (92.3%) were concordant and 59 (7.7%) were initially discordant. After excluding B3 lesions (n = 46), 13 true discordant cases remained (1.7%). Including B3 lesions increased clinically non-concordant or indeterminate cases from 1.7% to 7.7%, indicating that the apparent performance of the models is likely sensitive to case definition and dataset composition. BI-RADS 4a was the most common category (31.3%), and benign pathology (B2) accounted for 64.4% of biopsies. Within this dataset, LightGBM yielded the highest apparent AUC (0.999) (however, given the extremely small number of true discordant cases, this estimate is likely unstable and should be interpreted with caution), while BioBERT showed the strongest agreement with expert consensus (κ = 0.89). SHAP analysis identified clinically meaningful terms such as calcification, hypoechoic, ductal, and carcinoma as key contributors to model predictions. Given the very limited number of true discordant cases, these performance estimates are likely unstable and should be regarded as preliminary, requiring validation in larger, multi-center cohorts. Conclusions: This study presents a proof-of-concept NLP-based framework for radiology–pathology concordance assessment. The models showed promising performance in identifying potentially discordant cases; however, given the limited number of true discordant samples, these findings should be considered preliminary and require further validation in larger, multi-center datasets before clinical implementation. Full article

Introduction: Nerve-sparing (NS) during robot-assisted radical prostatectomy (RARP) plays a critical role in postoperative functional recovery, particularly urinary continence and erectile function. Despite the importance of precise neurovascular bundle (NVB) preservation, intraoperative assessment of NS quality remains largely subjective and lacks standardized evaluation tools. The aim of this study was to develop and preliminarily evaluate a structured intraoperative scoring system designed specifically for assessing NS quality during RARP. Methods: A novel 10-point intraoperative NS scoring system (NSQ Score) based on five domains was developed: dissection plane, bleeding control, bundle manipulation, continuity of dissection, and symmetry. Each parameter was rated on a 0–2 scale. Thirty robot-assisted radical prostatectomy (RARP) procedures performed in 2024 were randomly selected from a prospectively maintained institutional surgical video archive. Cases were not pre-filtered based on tumor stage, surgical difficulty, or intraoperative complexity. High-definition video recordings of the nerve-sparing phase were anonymized and independently evaluated by three experienced observers blinded to patient outcomes and to each other’s assessments. Inter-rater agreement was analyzed using weighted Cohen’s kappa statistics with quadratic weights, complemented by exact and near-agreement proportions. Cluster bootstrap resampling was applied to account for bilateral observations. Results: A total of 48 evaluable observations were analyzed. The overall inter-rater agreement demonstrated a weighted kappa of 0.41 (95% CI 0.36–0.48), indicating fair-to-moderate agreement among reviewers. Exact agreement occurred in 43% of observations, while near-agreement (allowing one ordinal level difference) reached 98%. Among individual parameters, symmetry demonstrated the highest reliability with substantial agreement (κ = 0.70; 95% CI 0.58–0.81). Other domains showed fair agreement, including intraoperative bleeding (κ = 0.36), continuity of dissection (κ = 0.39), bundle manipulation (κ = 0.34), and dissection plane (κ = 0.27). Agreement levels were comparable between left- and right-sided dissections. Conclusions: We propose a novel structured intraoperative scoring system for evaluating nerve-sparing quality during RARP. The scale is simple, procedure-specific, and feasible for structured postoperative or video-based assessment. Preliminary results demonstrate fair-to-moderate inter-rater reliability with very high near-agreement, supporting the feasibility of this tool for clinical use. The proposed scoring system may facilitate standardized training, objective performance assessment, and future studies correlating intraoperative NS quality with functional outcomes. Full article

Background/Objectives: Spontaneous spinal subdural hematoma (SSSDH) is a rare and severe condition that causes rapid neurological decline. Spontaneous spinal epidural hematoma (SSEH) presents similarly but is more common, and surgical management differs because SSSDH requires an intradural approach. Few studies have assessed the reliability of magnetic resonance imaging (MRI) features used to distinguish SSSDH from SSEH in patients requiring surgery. Methods: We retrospectively reviewed 27 patients who underwent surgical evacuation of spinal hematomas at two institutions (2015–2025). Definitive hematoma location was determined intraoperatively. Four MRI features—shape (crescentic vs. biconvex), location (ventral vs. dorsal), craniocaudal length (<5 vs. ≥5 segments), and spinal region—were independently evaluated by two reviewers. Inter- and intra-rater reliability was assessed using agreement rate and Cohen’s kappa (κ) with 95% confidence intervals (95% CIs). Results: Among 27 cases, three (11.1%) were SSSDH and 24 were SSEH. Hematoma location, length, and spinal region demonstrated perfect inter- and intra-rater agreement (κ = 1.00). For hematoma shape, intra-rater agreement was good (96.2%, κ = 0.84; 95% CI 0.52–1.00), whereas inter-rater agreement was poor to fair (84.6%, κ = 0.26; 95% CI −0.25–0.77). Notably, two of the three SSSDHs demonstrated a biconvex configuration, and 83.3% of SSEHs also exhibited a biconvex morphology. Conclusions: MRI features such as hematoma location, extent, and spinal level were highly reproducible, whereas hematoma shape showed limited reliability. Although ventral hematomas most strongly suggest SSSDH, atypical SSEH presentations occur. When dorsal exposure reveals no epidural hematoma, intradural exploration should be promptly considered. Full article

Objectives: Oral leukoplakia (OL) is the most prevalent oral potentially malignant disorder and requires accurate diagnosis, safe excision, and reliable margin evaluation to minimize recurrence and malignant transformation. Diode laser excision is increasingly adopted due to its precision and favorable clinical outcomes; however, laser-induced thermal effects at surgical margins raise concerns regarding tissue integrity and histopathological reliability. This study aimed to evaluate optical coherence tomography (OCT) as a real-time, high-resolution, non-invasive imaging modality for assessing peri-incisional thermal effects during diode laser excision of non-dysplastic OL. The primary objective was to validate OCT for ultrastructural and morphometric tissue analysis while ensuring preservation of diagnostic readability. Methods: A single-center observational case series was conducted at the University of Turin. Thirty patients with clinically and histopathologically confirmed oral leukoplakia without epithelial dysplasia were enrolled and allocated to two groups: 15 lesions excised using a 980 nm diode laser in continuous-wave contact mode (laser group) and 15 lesions removed by conventional scalpel biopsy (control group). Laser excisions were performed with standardized parameters and a circumferential safety margin of 5 mm. Immediately after excision, specimens underwent ex vivo spectral-domain OCT (SD-OCT) imaging to evaluate the epithelial and connective tissue microarchitecture at surgical margins and central lesion areas. OCT acquisition sites were precisely correlated with histological sections. Quantitative OCT measurements of epithelial thickness, lamina propria thickness, and laser-induced thermal alterations were compared with corresponding histological findings. Results: OCT consistently provided high-resolution visualization of oral mucosal microarchitecture in both groups, allowing clear identification of epithelial stratification, basement membrane continuity, and lamina propria organization. In the laser group, OCT detected superficial optical alterations at the surgical margins consistent with laser-induced thermal effects, while deeper tissue layers remained structurally readable. Histological analysis revealed mean epithelial and connective tissue thermal alterations of 288.9 μm and 430.3 μm, respectively. OCT-derived measurements showed high concordance with histology, with an overall agreement of 88.5% and no statistically significant differences between OCT and histological assessments. Importantly, laser-induced thermal effects did not impair definitive histopathological diagnosis in any specimen. Comparison with the control group confirmed preserved tissue architecture in scalpel-excised samples and highlighted OCT sensitivity in detecting laser-related structural remodeling. Conclusions: OCT proved to be a reliable, non-invasive imaging technique for real-time assessment of diode laser-induced thermal effects during OL excision. The technique accurately delineated tissue microstructure and surgical margins without compromising histopathological interpretation. Integration of OCT into the laser-assisted management of oral potentially malignant disorders may enhance surgical precision, optimize margin control, reduce diagnostic uncertainty, and support individualized follow-up strategies. Full article

Background: Accurate diagnosis of periprosthetic joint infection (PJI) remains challenging, particularly in culture-negative and borderline cases where current practices lead to high diagnostic uncertainty. SynTuition™, a machine-learning-based probability score integrating preoperative biomarkers, was developed to support clinical decision-making. This study compared its diagnostic performance and economic impact with standard physician practice. Methods: A total of 12 physicians provided diagnoses of 274 clinical vignettes representing suspected PJI cases. SynTuition probabilities were converted to binary diagnostic classifications using a validated threshold. Diagnostic accuracy, agreement, indecision rates, decision curve analysis, and misdiagnosis-related costs were evaluated. Results: SynTuition achieved an overall percent agreement of 96.0% when compared against the expert adjudicated clinical reference, outperforming the pooled physician group at 90.8%. Physicians showed high indecision (38–48%) in inconclusive 2018 ICM cases, whereas SynTuition generated a definitive diagnosis with an 86.7% agreement against expert adjudication. Decision curve analysis demonstrated a higher net benefit for SynTuition across a broad range of thresholds, reducing projected unnecessary revision by up to 5.8%. Economic modeling showed a reduction in misdiagnosis-related costs from $6.9 million to $2.9 million per 1000 suspected PJI cases, yielding estimated savings of $4000 per suspected case. Conclusions: SynTuition demonstrated high diagnostic accuracy, lower uncertainty, and significant clinical and economic advantages over routine physician practice, supporting its integration into clinical decision-making for suspected PJI, particularly in diagnostically ambiguous cases. Full article

A clinically useful classification system requires precise definitions, reproducibility, and applicability across different levels of clinical experience. Distal radioulnar joint instability remains insufficiently represented in fracture based classifications, contributing to diagnostic uncertainty and variability in treatment strategies. This retrospective observational study assessed the interobserver and intraobserver reliability of a previously proposed classification system for distal radioulnar joint instability. Five orthopedic surgeons, including three board-certified specialists and two final year residents, independently evaluated forty five clinical cases comprising distal radius fractures, Galeazzi fractures, and Essex Lopresti injuries, using predefined clinical and radiological criteria. Interobserver agreement was analyzed using Fleiss Kappa statistics, while intraobserver reliability was evaluated after a two week interval using Cohen Kappa. Overall interobserver agreement was excellent, with a global Fleiss Kappa value of 0.87. Agreement was highest in Galeazzi fractures and lowest in Essex Lopresti injuries, reflecting increased diagnostic complexity in this subgroup. Specialists demonstrated higher agreement than residents. Intraobserver reproducibility was excellent, with identical classifications in 96 percent of reassessed cases. These findings indicate that the proposed classification system shows high reliability and reproducibility, supporting its potential clinical utility for standardized assessment of distal radioulnar joint instability and for guiding future clinical and biomechanical research. Full article

Background: Early and accurate diagnosis remains crucial to improving outcomes in oral cancer. Optical coherence tomography (OCT) offers real-time, high-resolution imaging that may support diagnosis and treatment planning in oral squamous cell carcinoma (OSCC). Methods: In this prospective study, preoperative OCT scans were obtained from 68 histologically confirmed OSCC lesions, with 30 paired adjacent mucosa samples from the same patients as histologically negative comparators (diagnostic dataset: 98 lesions). OCT findings were compared with histopathology for diagnostic performance, OCT biomarker patterns by tumour grade, tumour depth measurement, margin assessment, and subsite-specific performance. Results: OCT demonstrated 98.5% sensitivity, 96.7% specificity, and an AUC of 0.98 for detection of invasive OSCC. OCT biomarkers—including abnormal epithelial architecture with variable epithelial thickness, stratification loss, basement membrane disruption, and increased subepithelial reflectivity—varied systematically with tumour differentiation grade. Tumour depth measurements showed acceptable agreement with histology, while margin definition was correct in 80% of cases. Performance was highest in the tongue and the floor of the mouth, with reduced performance in posterior/keratinised subsites. Image artefacts occurred in 5.1% of scans. Conclusions: OCT provides a reproducible, real-time adjunct for diagnosis, margin planning, and lesion stratification in OSCC, with recognised limitations related to light attenuation and operator-dependent factors. Multicentre validation and integration with digital interpretation platforms are warranted. Full article

As the impacts of climate change intensify, water resource conflicts are escalating globally, particularly in regions with uneven water distribution, such as Central Asia. Long-standing disputes over water allocation persist between Kyrgyzstan and Uzbekistan. This paper aims to examine the conflicts and challenges in water allocation between the two countries and explore the potential of Decision Support Systems (DSSs) as a viable solution. The paper begins by reviewing the historical evolution of water allocation in Central Asia, analyzing upstream–downstream disputes and notable cooperation efforts, with a focus on key water agreements. It then outlines the definitions, development, and classifications of DSSs in the context of water allocation and presents two illustrative case studies—the Tarim River Basin in Xinjiang, China, and the Nile River Basin in Africa. These cases demonstrate the applicability of DSSs in water-scarce regions with similar socio-ecological dynamics and complex multi-country, cross-sectoral water demands. Building on these insights, the paper analyzes the key challenges to implementing DSSs for transboundary water allocation in Central Asia, including limited data availability and sharing, insufficient technical capacity, chronic funding shortages, socio-political complexities, climate change impacts, and the inherent difficulty of modeling complex systems. In response, a set of targeted pragmatic recommendations is proposed. While acknowledging its limitations, the paper argues that establishing a structured, system-based decision-making framework—namely DSSs—can help stakeholders enhance climate-informed strategic planning and foster cooperation, ultimately contributing to more equitable and sustainable water resource allocation in the region. Full article

Background/Objectives: The parapharyngeal space is a complex anatomical region that houses critical neurovascular structures and serves as the origin of rare tumors, which account for 0.5–1% of head and neck neoplasms. Magnetic resonance imaging (MRI) is useful for their preoperative assessment. However, its accuracy in real-world clinical settings remains underexplored. This study aimed to investigate the diagnostic accuracy of MRI for parapharyngeal tumors at two tertiary centers. Methods: This retrospective study included patients who underwent MRI and surgical excision at two tertiary centers in Saudi Arabia between 2018 and 2024. Two reviewers independently extracted their MRI data and compared them with the final pathological data to determine the diagnostic performance of MRI. Results: Of the 31 patients (58.1% female; median age, 37.5 years), 90.3% had benign tumors. Neurogenic (41.9%) and salivary (25.8%) tumors were most common; 61.3% were located within the pre-styloid space. The benign and malignant groups had comparable baseline characteristics. MRI demonstrated moderate overall diagnostic agreement (κ = 0.525) and near-perfect concordance for schwannomas (κ = 0.912) and paragangliomas (κ = 0.839) but poor agreement for hemangiopericytomas (κ = −0.051). It had high accuracy (90.3%), specificity (92.9%), and negative predictive value (96.3%) for detecting malignancy but limited sensitivity (66.7%) or positive predictive value (50.0%). Nonetheless, cautious interpretation is required due to the limited prevalence of malignancy in the cohort (n = 3). Conclusions: MRI demonstrated high specificity for benign parapharyngeal space lesions in routine clinical reporting within this retrospective cohort, reflecting strong radiologic–pathologic agreement. Estimates of sensitivity and positive predictive value for malignancy were influenced by the limited number of malignant cases. Accordingly, the reported diagnostic performance measures should be interpreted as descriptive and exploratory, characterizing real-world MRI performance rather than definitive diagnostic accuracy. Full article

Background: Periprosthetic joint infections (PJI) represent a serious complication following joint arthroplasty and require, in addition to surgical intervention, a targeted antibiotic therapy. The aim of this study was to compare microbiological recommendations for the antibiotic treatment of fictitious PJI patients generated by an artificial intelligence (AI) system with those of an interdisciplinary team (IT) consisting of microbiologists and orthopedic surgeons. The differences between the recommendations suggested by AI and the IT were analyzed with regard to the suggested agents and duration of antibiotic therapy. Methods: Based on meta-analyses, a cohort of 100 fictitious patients with acute early- and acute late-onset PJI was created, reflecting the typical demographic data, comorbidities and pathogen profiles of such a population. This information was input into the AI system ChatGPT (OpenAI, GPT-5 “Thinking mode” accessed via ChatGPT Plus, San Francisco, CA, USA) to generate corresponding recommendations. The objective was to use these profiles to obtain recommendations for definitive antibiotic therapy, including daily dosage, intravenous and oral treatment durations. Simultaneously, the same fictitious patient data were reviewed by the IT to produce their own recommendations. Results: The results revealed both concordances and discrepancies in the selection of antibiotics. Notably, in cases involving multidrug-resistant organisms and more complex clinical scenarios, the AI-generated recommendations were incongruent with those of the IT, with estimated percentage agreement ranging from 0–33%. In straightforward clinical scenarios with monomicrobial infections, AI reached an estimated percentage agreement of up to 57% (95%-CI [0.47–0.67]). Furthermore, AI consistently recommended 12 weeks of therapy duration vs. six weeks usually recommended by the IT. Conclusions: The study provides important insights into the potential and limitations of AI-assisted decision-making models in orthopedic infection treatments. Consultation of AI is universally accessible at all times of day, which may offer a significant advantage in the future for the treatment of PJI. This kind of application will be of particular interest for institutions without in-house microbiology services. However, from our perspective, the current level of incongruence between the AI-generated recommendations and those of an experienced interdisciplinary team remains too high for this approach to be clinically implemented at this time. Furthermore, AI lacks transparency regarding the sources it uses to inform about its decision-making and therapeutic recommendations, currently carries no legal weight and clinical implementation is severely hindered by restrictive privacy laws regarding health care data. Full article