Introduction: Third-window syndromes (TWS), including superior semicircular canal dehiscence (SSCD) and enlarged vestibular aqueduct (EVA), cause paradoxical auditory and vestibular symptoms such as apparent conductive loss, bone-conduction hyperacusis, and sound- or pressure-induced vertigo. Numerical modeling provides a unique means to explore the mechanical consequences of lesion size, geometry, and location.Methods: A structured search of PubMed, Scopus, and Google Scholar (July 2025) identified nine studies applying lumped-element, finite-element (FE), or computational fluid dynamics (CFD) models to SSCD or EVA, which were analyzed qualitatively.Results: Lumped-element models reproduced air-bone gaps and bone-conduction hypersensitivity, showing that lesion size and location modulate functional severity. FE and CFD simulations offered anatomically detailed insights, revealing that dehiscence geometry strongly shapes basilar membrane motion, that sound-induced endolymphatic streaming can account for the Tullio phenomenon, and that large vestibular aqueducts transmit intracranial pressure fluctuations. Validation across studies remained limited.Conclusion: Numerical models provide complementary insights into TWS. Lumped-element approaches are rapid and clinically interpretable, while FE and CFD enable detailed exploration of fluid-structure interactions. Patient-specific simulations may eventually support individualized diagnosis and surgical planning but remain speculative.

To evaluate the performance of four artificial intelligence (AI) systems (ChatGPT 4o, Claude 3.7, Gemini 2.0, and Grok 2) in analysing nasal deformities. The artificial intelligence chatbots were compared to experts in terms of their capacity to analyse nasal deformities. A quantitative analysis compared AI-generated MIRA scores with expert MIRA scores using error measures, Bland–Altman analysis, concordance metrics, and intraclass correlation coefficients to evaluate agreement and systematic bias. A qualitative evaluation was conducted using a 5-point Likert scale to characterise the major nasal type (tension nose, saddle nose, deviated nose, etc.). Fifty adult patients seeking rhinoplasty were evaluated by the chatbots and two experts based on standardised photographs. The evaluations by the two surgeons demonstrated very strong concordance (ICC = 0.997) for nasal analysis using the MIRA scale. Only Claude 3.7 and the experts had comparable total MIRA score evaluations (p > 0.05). Detailed analysis of MIRA sub-scores showed a significant difference between chatbots and experts across all models (p < 0.05), including Claude. Grok 2 (p < 0.001) demonstrated the poorest performance. The qualitative description of the nose by ChatGPT 4o achieved the best results, with an accuracy rate reaching 70 www.springer.com/00266 .

We describe a stepwise retroauricular microsurgical workflow for bulky tympanic paragangliomas, combining circumferential canaloplasty with temporary removal and replacement of the tympanomeatal flap and malleus to optimize exposure and bleeding control. This strategy facilitates early identification of critical structures, stepwise devascularization, and safe tumor excision in bulky lesions extending to the hypotympanum or protympanum. The technique emphasizes operative sequencing and surgical ergonomics in challenging cases.

This case report describes a 36-year-old patient with severe hyponatremia.

Artificial intelligence (AI)-powered large language models (LLMs) are increasingly used as adjunctive tools in education, research, and patient care. This systematic review aimed to investigate the current literature on the applications, performance, and ethical considerations regarding the use of artificial intelligence (AI), including large language models (LLM) in plastic and reconstructive surgery. A comprehensive search of PubMed, Scopus, and Cochrane Library was conducted by two independent investigators for studies published in English in peer-reviewed journals reporting findings about applications (education, clinical decision-making, research process), ethical and practical challenges (bias, data privacy, and accountability), and performance of LLMs in facial plastic and reconstructive surgery practice. PRISMA statements and PICOTS frameworks were used for conducting the search and summarizing the literature findings. Twenty-one studies met inclusion criteria, including 11 examining practical uses of ChatGPT and other LLMs, 8 evaluating performance on medical and surgical tasks, and 7 assessing ethical issues and potential limitations. Based on several performance tools, LLMs demonstrated moderate-to-high accuracy, ranging from 54.96

Two brothers, aged 69 and 76 years, were independently referred in the same week for evaluation of a right olfactory cleft tumor that had been progressively developing over several years. Computed tomography demonstrated bilateral masses causing widening of the olfactory clefts, with the right-sided lesion being larger than the left and causing nasal bone thinning in both patients. What is your diagnosis?

ImportanceMost French Olfactory Questionnaires are time consuming, which may affect the patient participation.ObjectiveTo validate a short French version of the Olfactory Disorders Questionnaire (Fr-ODQ).DesignProspective controlled study.SettingMulticenter study.ParticipantsPatients with long-lasting olfactory dysfunction (OD) treated with platelet-rich plasma into the olfactory clefts and asymptomatic subjects.InterventionDevelopment and validation of a short ODQ.Main OutcomesIndividuals completed the full Fr-ODQ. The Threshold, Discrimination, and Identification (TDI) test was performed in OD patients. A combined statistical analysis was performed to determine the most informative items of the Fr-ODQ to develop a shorter version. The internal consistency was determined with Cronbach's alpha. The reliability and external validity were evaluated through a test-retest approach and by correlating with the Fr-ODQ. Both the minimal clinically important difference (MCID) and the threshold of the short ODQ version were determined.ResultsA total of 263 patients (173 [65.8%] females) and 129 controls (92 [71.3%] females) completed the evaluations. The mean age of patients was 51.2 ± 15.3 years. The mean duration of OD was 42.4 ± 54.3 months. The biostatistical models selected 10 essential items composing the Fr-ODQ-10. The baseline Fr-ODQ-10 was significantly correlated with the TDI (rs = 0.228; P = .001) and the Fr-ODQ (rs = 0.875; P = .001), demonstrating high external validity. Fr-ODQ-10 was significantly lower in controls compared to OD patients (P = .001), highlighting high internal validity. The internal consistency was good (α = .796). The external consistency was adequate, with significant correlations between the test-retest Fr-ODQ-10. The Fr-ODQ-10 significantly decreased from baseline to 4 months post-treatment. A Fr-ODQ-10 score >7.5 was considered abnormal (sensitivity: 84.8%, specificity: 84.2%). The MCID of Fr-ODQ-10 was established at >3.Conclusion and RelevanceThe Fr-ODQ-10 is a valid and reliable clinical instrument, demonstrating correlation with the psychophysical olfactory assessment.

To evaluate the performance of two AI systems, ChatGPT 4.0 and Algor, in generating concept maps from validated otolaryngology clinical practice guidelines. Concept maps were generated by ChatGPT 4.0 and Algor from four American Academy of Otolaryngology-Head and Neck Surgery Foundation (AAO-HNSF) clinical practice guidelines. Eight otolaryngology specialists evaluated the generated concept maps using the AI-Map questionnaire, covering concept identification, relationship establishment, hierarchical structure representation, and visual presentation. Chi-square tests and Kendall’s tau coefficient were used for statistical analysis. While no consistent superiority was observed across all guidelines, both AI systems demonstrated unique strengths. ChatGPT excelled in representing cross-connections between concepts and layout optimization, particularly for the Rhinoplasty guidelines (χ²=6.000, p = 0.050 for cross-connections). Algor showed strengths in capturing main themes and distinguishing general/abstract concepts, especially in the BPVV and Tympanostomy Tube guidelines (χ²=8.000, p = 0.046 for main themes in BPVV). Statistically significant differences were found in representing dynamic nature (favouring H NMass-GPT, χ²=7.571, p = 0.023) and overall value and usefulness (favouring H NMass-Algor, χ²=7.905, p = 0.019) for the H N Masses guidelines. AI systems showed potential in automating concept map creation from otolaryngology guidelines, with performance varying across different medical topics and evaluation criteria. Further research is required to optimize AI systems for medical education and knowledge representation, highlighting their promise and current limitations.

OBJECTIVE:To investigate the demographic determinants of patient perception toward the role of artificial intelligence (AI) in otolaryngology-head and neck surgery care. METHODS:Outpatients consulting in otolaryngology-head and neck surgery departments of 18 hospitals were surveyed about the perception of the role of AI in health care. The results were analyzed according to the age, gender, patient use of technology, and the level of education. RESULTS:The survey was completed by 1545 patients from Europe and the United States (participation rate: 98.7%). There were 832 (53.9%) females and 669 (43.3%) males. The level of education significantly influences the perception of AI in otolaryngological care with the lowest trust and agreement in patients with the highest education level. The study demonstrated a higher mean overall agreement score for using AI in medicine among daily users of technologies than among others (7.2 ± 1.9 vs 5.6 ± 2.6; P = .001). Females reported more frequent fears about the use of AI in otolaryngology than males. The agreement scores for using AI in medicine significantly decreased with age (P = .001). CONCLUSION:The perception of AI use in otolaryngology was influenced by age, gender, level of education, and the use of new technologies in daily life. Further studies promoting the use of AI in Western populations can consider demographics for improving the perception of patients toward AI, and an AI literacy component to determine whether lower trust is due to misunderstanding AI capabilities.

To evaluate the performance of artificial intelligence (AI)-powered chatbots in generating treatment plans for facial aesthetic injections, focusing on their accuracy, safety, and clinical applicability. A comparative observational study was conducted in an otolaryngology tertiary care department according to STROBE guidelines. Patients seeking facial injections were recruited from July to October 2024. Forty patients (85 www.springer.com/00266 .

Background/Objectives: Optimizing drug deposition to the olfactory region is key in Nose-to-brain drug delivery strategies. However, findings from computational fluid dynamics (CFD) studies remain inconsistent concerning the parameters influencing olfactory deposition, limiting clinical translation and device optimization. This systematic review aims to identify robust CFD parameters for optimizing drug delivery to the olfactory region. Methods: A systematic review and meta-analysis were conducted following PRISMA guidelines, selecting studies reporting CFD simulations of nasal drug delivery with evaluation of olfactory deposition efficiency. The primary outcome was the correlation between each CFD parameter and olfactory deposition rate. Parameters included particle size, impaction parameter, flow rate, spray cone angle, insertion angle, injection velocity, head position, release position, and breathing pattern. Data were extracted and standardized, and statistical methods were used to assess correlations, heterogeneity, and potential biases in study results. Results: Smaller particle size (pooled r = −0.42) and lower impaction parameter (r = −0.39) were significantly associated with higher olfactory deposition. No consistent correlation was observed with breathing flow rate. Heterogeneity across studies was high (I2 > 90%). Funnel plots asymmetry suggested potential publication bias in particle-related outcomes. Conclusions: Particle characteristics, especially size and inertia, are the most critical determinants of olfactory deposition in CFD simulations. These findings support design optimization of nasal delivery devices targeting the olfactory region and underscore the need for standardized reporting and validation across CFD studies.

BackgroundMicroaggressions are subtle verbal or behavioral insults (intentional or unintentional) that typically convey negative or hostile attitudes towards marginalized groups. We aim to study microaggressions and workplace culture amongst European otolaryngologist -head and neck surgeons (E-OTOHNS). The perception of "differential treatment" based on individual traits was used as a proxy for microaggressions.MethodsEuropean members of Young-Otolaryngologists of International Federation of Otorhinolaryngological Societies (IFOS) and Confederation of European Otorhinolaryngological Societies were surveyed regarding observed and personal experiences of microaggressions in the workplace as related to individual factors that comprise one's identity; These factors included biological sex; disability; gender identity; language proficiency; citizenship; ethnicity; political belief; sexual orientation and socioeconomic status.ResultsA total of 230 E-OTOHNS completed the survey (17%), including 113 Women (49%) and 117 men (51%), respectively. The most common daily-to-monthly observed microaggressions were related to age (n = 177, 50.1%), biological sex (n = 105, 45.7%), and language proficiency (n = 67, 29.1%), respectively. Personal experiences of microaggression were related to professional rank (n = 80; 35.3%), age (n = 75; 32.6%), and biological sex (n = 63; 27.5%). Women self-reported significant higher proportions of personal experiences of microaggression related to ageage (40.7% vs 24.8%; P = 0.003), biological sex (41.6% vs 13.8%; P = 0.001), and professional rank (42.0% vs 28.7%; P = 0.049) compared to men. Similarly, Women self-reported higher rates of personal feeling of exclusion from their colleagues at the institution (P = 0.036) than men and were more likely mistaken for another role in the hospital (P = 0.004).ConclusionsWoman European otolaryngologists, particularly those early in their careers, self-report higher proportions of observed or experienced microaggressions related to age, biological sex, and professional rank compared with male otolaryngologists. More efforts are needed in European academic Otolaryngology to reduce microaggressions, discriminations, and exclusions as more woman surgeons enter the medical workforce.

Background and Objectives: this pilot study aimed to evaluate the diagnostic accuracy of ChatGPT-4o in analyzing oral mucosal lesions from clinical images. Materials and Methods: a total of 110 clinical images, including 100 pathological lesions and 10 healthy mucosal images, were retrieved from Google Images and analyzed by ChatGPT-4o using a standardized prompt. An expert panel of five clinicians established a reference diagnosis, categorizing lesions as benign or malignant. The AI-generated diagnoses were classified as correct or incorrect and further categorized as plausible or not plausible. The accuracy, sensitivity, specificity, and agreement with the expert panel were analyzed. The Artificial Intelligence Performance Instrument (AIPI) was used to assess the quality of AI-generated recommendations. Results: ChatGPT-4o correctly diagnosed 85% of cases. Among the 15 incorrect diagnoses, 10 were deemed plausible by the expert panel. The AI misclassified three malignant lesions as benign but did not categorize any benign lesions as malignant. Sensitivity and specificity were 91.7% and 100%, respectively. The AIPI score averaged 17.6 ± 1.73, indicating strong diagnostic reasoning. The McNemar test showed no significant differences between AI and expert diagnoses (p = 0.084). Conclusions: In this proof-of-concept pilot study, ChatGPT-4o demonstrated high diagnostic accuracy and strong descriptive capabilities in oral mucosal lesion analysis. A residual 8.3% false-negative rate for malignant lesions underscores the need for specialist oversight; however, the model shows promise as an AI-powered triage aid in settings with limited access to specialized care.

BackgroundThe pathophysiology of Meniere's disease (MD) is complex and intertwined with endolymphatic hydrops. Available experimental models have limitations.ObjectiveThis study aimed to analyze the impact of endolymphatic hydrops on cochleovestibular hydrodynamics through numerical simulations.MethodsA comprehensive literature review was conducted following PRISMA guidelines for Scoping Reviews. Articles were sourced in June 2024 from PubMed and Google Scholar using a combination of MESH terms related to hydrodynamics, numerical simulation, and MD. Studies involving numerical simulations of hydrops in the vestibule, cochlea, or both were included.ResultsEight studies on hydrodynamics in hydrops using numerical simulations were included. In cochlear models, hydrops affect basilar membrane mechanics, causing low-frequency hearing loss, auditory distortions, and frequency shifts. Vestibular models revealed increased static pressure in the horizontal semicircular canal, explaining abnormal vHIT findings in hydrops patients. Models also suggested chaotic fluid dynamics in dilated labyrinthine structures during caloric tests. The reviewed studies underscore the utility of numerical models in understanding the mechanics of MD; however, significant limitations were identified.ConclusionsNumerical modeling offers valuable insights into the hydrodynamic changes caused by endolymphatic hydrops in MD, but future work should address the current limitations by incorporating more accurate anatomical features and chronic progression in simulations.

Background: The anatomical variability of the nasal cavity affects intranasal drug delivery, especially to the olfactory region for nose-to-brain treatments. While previous studies used average models or 2D measurements to account for inter-individual variability, 3D shape variation of the region crossed by drug particles that target the olfactory area, namely the region of interest (ROI), remains unexplored to our knowledge. Methods: A geometric morphometric analysis was performed on the ROI of 151 unilateral nasal cavities from the CT scans of 78 patients. Ten fixed landmarks and 200 sliding semi-landmarks were digitized, using Viewbox 4.0, and standardized via Generalized Procrustes Analysis. Shape variability was analyzed through Principal Component Analysis. Morphological clusters were identified using Hierarchical Clustering on Principal Components, and characterized with MANOVA, ANOVA, and Tukey tests. Results: Validation tests confirmed the method's reliability. Three morphological clusters were identified. Variations were significant in the X and Y axes, and minimal in Z. Cluster 1 had a broader anterior cavity with shallower turbinate onset, likely improving olfactory accessibility. Cluster 3 was narrower with deeper turbinates, potentially limiting olfactory accessibility. Cluster 2 was intermediate. Notably, 31.5% of patients had at least one cavity in cluster 1. Conclusions: Three distinct morphotypes of the region of the nasal cavity that potentially influence accessibility were identified. These findings will guide future computational fluid dynamics studies for optimizing nasal drug targeting and represent a practical step toward tailoring nose-to-brain drug delivery strategies in alignment with the principles of personalized medicine.

Background/Objectives: Proper nasal irrigation techniques are essential for treating nasal and sinus conditions, influencing drug delivery efficiency and patient comfort. This study evaluates how different head positions—upright, right-tilted, and left-tilted—affect the distribution of saline solution in the nasal cavity and maxillary sinus using computational fluid dynamics (CFD). Methods: CFD simulations were conducted on a CT-based model of a healthy adult. A 4 mL saline solution was administered into the right nostril over three seconds. Fluid distribution and percentage of nasal mucosa coverage was analyzed in the inferior, middle, and superior thirds of the nasal cavity and the right maxillary sinus. Results: In the upright position, fluid primarily accumulated in the inferior (0.075 mL) and middle (0.015 mL) nasal regions, with minimal sinus penetration (0.002 mL). Right-tilting improved maxillary sinus coverage (0.028 mL) and increased irrigation of the inferior region (0.086 mL), while left-tilting enhanced central nasal coverage with only slight sinus penetration improvement. Irrigation patterns exhibited a rapid initial wetting phase followed by a slower, steady increase. Conclusions: Head position significantly influences the distribution achieved by nasal irrigation. These findings can guide clinical recommendations for specific conditions or postoperative care.

We present a reproducible, stepwise middle fossa approach for facial nerve decompression focused on the labyrinthine segment, geniculate ganglion, and meatal foramen, with consistent anatomical landmarks to preserve hearing. The article and video detail patient setup, safe corridor creation, and retrograde drilling with practical tips to avoid cochlear or semicircular canal injury, aiming to lower the learning curve for facial nerve decompression.