Pinheiro‐Neto, Carlos

Background: Evaluation of otolaryngology resident technical performance has historically relied on subjective perioperative feedback. Despite various assessment tools attempting to provide consistent surgical skill evaluations, current methods remain inherently subjective. Aim: This proof-of-concept pilot study aimed to assess if a 3-dimensional surgical navigation system could capture objective surgical data during endoscopic sinus surgery (ESS). A secondary aim was to analyze if there were any differences between novice and practiced trainees. Methods: Otolaryngology residents performed supervised ESS on patients while their instrument (microdebrider, suction) motion was recorded using a TruDi ® Navigation System. Prior to the surgery, surgical landmarks were defined with sensory beacons in the navigation system using the patient’s preoperative computed tomography (CT) scan. Metrics included time to reach beacons, number of alerts at each beacon, and instrument speed. Results: Fifteen otolaryngology residents performed 87 ESS. The navigation system successfully obtained “time to reach sinus X” data for 64% of sinuses/ case, velocity data in 93% of cases, and number of beacon “alerts” per minute in 93% of cases. We found a significant difference between PGY 3 residents and PGY 4/PGY5 residents in the number of sphenoid sinus alerts per minute ( P = .01) and the percentage of cases in which the resident accessed the maxillary sinus via the natural os ( P < .001). Impact: This study demonstrates the feasibility of collecting objective, navigation-based intraoperative metrics during live surgery and is a first step toward building a comprehensive objective assessment tool in ESS. We hope this report encourages further research into this technology’s application in objective resident skill assessment and correlation with concurrent faculty assessments.

ABSTRACT Objective Sacrifice of pterygopalatine fossa (PPF) neurovascular structures during endoscopic endonasal transpterygoid approach (EETPA) may impact a patient's comorbidity. We present anatomical and surgical techniques for maximizing PPF transposition while preserving its neurovascular structures through orbito‐pterygo‐sphenoidal (OPS) ligament release and descending palatine canal (DPC) decompression. Methods The EETPA was performed on six specimens. Two measurements were obtained to assess PPF transposition: (1) Inferior transposition (distance between the superior margins of the base of the pterygoid process and PPF); (2) lateral transposition (distance from Eustachian tube lateral margin to PPF medial margin). Results After incising the OPS ligament, a mean gain of PPF inferior transposition of 7 mm (4–11 mm, p = 0.03) was observed, with a total inferior transposition of 12 mm (6–15 mm). Subsequently, the posterior half of the inferior turbinate was removed and the DPC was decompressed, with a mean gain of PPF lateral transposition of 12 mm (range 8–15 mm, p = 0.01). Conclusion The OPS ligament release offers a significant advantage for the PPF inferior transposition, allowing access to the inferolateral recess of the sphenoid sinus, cavernous sinus, and paramedian middle cranial fossa, while the DPC decompression provides a significant advantage for the PPF lateral transposition, granting access to the Eustachian tube and ITF. Level of Evidence N/A.

OBJECTIVE Patients with growth hormone (GH)–secreting pituitary adenomas (PAs) experience various symptoms and comorbidities, which can ultimately lead to increased mortality. This study aimed to develop and validate a machine learning (ML) model for predicting long-term outcomes in patients with GH-secreting PAs following endonasal transsphenoidal surgery (ETS). METHODS The authors conducted a retrospective three-institution cohort study that included patients with GH-secreting PAs treated with ETS between 2013 and 2023. Clinical, radiological, and biochemical data were collected. The main outcome of interest was the intervention-free rate (IFR) after primary ETS. Supervised ML algorithms, including decision trees and random forests, were developed to predict the IFR. Model performance was evaluated using area under the receiver operating characteristic curve (AUROC) and Shapley Additive Explanations (SHAP) values. RESULTS The median follow-up for 100 patients with GH-secreting PAs (53% female) was 64 months (range 1–130 months). Additional intervention for persistent or recurrent acromegaly was required in 32% of patients. Following primary ETS alone, the 3-year IFR was 70% and the 5-year IFR was 67%. Multiple ML models were developed and evaluated using AUROCs. The decision tree analysis achieved an accuracy of 81% and emphasized the importance of both gross-total resection (GTR) and patient age in determining the long-term IFR. To better understand the factors that contributed to model performance, SHAP analysis was applied to the best-performing model. The SHAP dependence plots showed that key factors associated with a longer IFR included tumor size < 9 mm, GTR, patient age > 65 years, and Knosp grade 0. CONCLUSIONS This ML model offers a more nuanced and potentially more accurate approach to identify patients more likely to develop recurrent or persistent acromegaly following primary ETS and require additional treatment. Following external validation, this ML model could improve personalized treatment planning and follow-up strategies and enhance patient care and resource allocation in clinical practice.

ABSTRACT Objective There is limited consensus on endoscopic skull base surgery (ESBS) reconstruction principles. This study aims to generate comprehensive themes regarding ESBS reconstruction by pooling the experiences of ESBS experts, with comparison to a literature review of current published evidence. Methods Structured qualitative interviews of ESBS experts regarding postoperative management and reconstruction of various defect locations were conducted. Results A total of 68 experts comprising 40 academic teams across 13 countries with an average of 18 years of ESBS experience were included. We propose 10 stepwise algorithms for common skull base reconstruction scenarios based on these expert interviews. When available, the nasoseptal flap is used for all high_flow cerebrospinal leak defects. Multilayered reconstruction is favored at all anatomical subsites with increasing number of layers for increasing defect size and complexity. Heterogeneity exists in terms of inlay technique and materials, free grafting versus various pedicled flap options for low‐flow defects or in the absence of a nasal septum, nasal packing, tissue sealant, lumbar drain use, and postoperative management. Commonalities and discrepancies between experts were summarized. Conclusion Skull base reconstruction and post‐ESBS management is highly complex with a wide variety of practice patterns and expert strategies. Further research of higher quality evidence is warranted to identify optimal management patterns, though the current work aims to inform surgeons on these controversial areas by drawing from numerous experiences.

Background Olfactory dysfunction (OD) is a common symptom in patients with coronavirus disease 2019 (COVID-19) with limited treatment options. Objective This pilot study aimed to investigate an acupuncture protocol in patients with COVID-19 related OD. Methods Thirty patients were randomized into 2 groups. The standard group was treated with budesonide nasal irrigation and olfactory training. The acupuncture group received ten sessions of acupuncture therapy in addition to the standard group treatment. Olfaction was assessed using the University of Pennsylvania Smell Identification Test, 10-point visual analog scale, and Sino-Nasal Outcome Test at baseline and after 3 months of treatment. Differences between study arms were compared using Fisher’s exact and Wilcoxon rank sum tests. Results Eighteen of the 30 (60%) enrolled patients completed the study, including 11 (73%) in the standard and 7 (47%) in the acupuncture group. Reasons for participant drop-out included cost of travel and time constraints. There were no acupuncture complications. Conclusions Acupuncture as an adjunct therapy for COVID-19 related OD is well tolerated. Subsequent studies with larger sample sizes are needed to assess the effect of acupuncture on OD.

OBJECTIVE In this study, the authors aimed to establish a supervised machine learning (ML) model based on multiple tree-based algorithms to predict long-term biochemical outcomes and intervention-free survival (IFS) after endonasal transsphenoidal surgery (ETS) in patients with Cushing’s disease (CD). METHODS The medical records of patients who underwent ETS for CD between 2013 and 2023 were reviewed. Data were collected on the patient’s baseline characteristics, intervention details, histopathology, surgical outcomes, and postoperative endocrine functions. The study’s primary outcome was IFS, and the therapeutic outcomes were labeled as "under control" or "treatment failure," depending on whether additional therapeutic interventions after primary ETS were required. The decision tree and random forest classifiers were trained and tested to predict long-term IFS based on unseen data, using an 80/20 cohort split. RESULTS Data from 150 patients, with a median follow-up period of 56 months, were extracted. In the cohort, 42 (28%) patients required additional intervention for persistent or recurrent CD. Consequently, the IFS rates following ETS alone were 83% at 3 years and 78% at 5 years. Multivariable Cox proportional hazards analysis demonstrated that a smaller tumor diameter that could be detected by MRI (hazard ratio 0.95, 95% CI 0.90–0.99; p = 0.047) was significantly associated with greater IFS. However, the lack of tumor detection on MRI was a poor predictor. The ML-based model using a decision tree model displayed 91% accuracy (95% CI 0.70–0.94, sensitivity 87.0%, specificity 89.0%) in predicting IFS in the unseen test dataset. Random forest analysis revealed that tumor size (mean minimal depth 1.67), Knosp grade (1.75), patient age (1.80), and BMI (1.99) were the four most significant predictors of long-term IFS. CONCLUSIONS The ML algorithm could predict long-term postoperative endocrinological remission in CD with high accuracy, indicating that prognosis may vary not only with previously reported factors such as tumor size, Knosp grade, gross-total resection, and patient age but also with BMI. The decision tree flowchart could potentially stratify patients with CD before ETS, allowing for the selection of personalized treatment options and thereby assisting in determining treatment plans for these patients. This ML model may lead to a deeper understanding of the complex mechanisms of CD by uncovering patterns embedded within the data.