Faculty Bibliography

BACKGROUND AND AIMS/UNASSIGNED:In patients with achalasia treated via Heller myotomy (HM) or peroral endoscopic myotomy (POEM), incomplete myotomy can lead to a "blown-out myotomy" (BOM) diverticulum, worsening obstruction, and dysphagia. We present peroral direct diverticulotomy (PODD), a salvage technique, similar to the "ultrashort tunnel" Zenker's peroral endoscopic myotomy technique, targeting the residual sphincter at the diverticular septum. METHODS/UNASSIGNED:We performed PODD in a 49-year-old man with type I achalasia who underwent POEM with minimal relief (Eckardt score 4). At 18 months, the esophagram showed delayed emptying, incomplete myotomy, and BOM diverticulum, and endoscopy revealed a "puckered," tight lower esophageal sphincter (LES) and a BOM diverticulum. PODD achieved a 2-cm myotomy at the diverticular septum, completing the initial myotomy. RESULTS/UNASSIGNED:The 25-minute procedure was uneventful, and the patient was discharged after 23 hours. Four-week follow-up endoscopy showed patulous LES, resolution of the septum, and no reflux esophagitis. Endoluminal functional lumen imaging probe and esophagram were consistent with resolution of obstruction. At 6 months, swallowing was improved (Eckardt score 1) with no gastroesophageal reflux disease symptoms. CONCLUSIONS/UNASSIGNED:As POEM spreads to low-volume centers, BOM diverticula-once mainly seen after failed HM-are increasingly seen after POEM. PODD offers a technically simple, effective salvage technique with potential broad applicability in managing POEM and HM failure due to BOM.

BACKGROUND AND OBJECTIVES/OBJECTIVE:Hand-sewn (HS) microsuturing is limited by tremor and fatigue. Robotic systems may improve performance, but quantitative comparisons remain limited. This study evaluates the precision of robot-assisted vs manual suturing during end-to-side microanastomosis. METHODS:Under simulation, microsurgical robot-assisted and HS sutures for end-to-side microanastomosis were performed by a single surgeon. One thousand four hundred and ninety-four total frames were assessed within 4 videos. Each robotic clip was paired with a corresponding HS clip. Tracker software extracted 2-dimensional positional data. Motion trajectories were smoothed using Savitzky-Golay filtering for an ideal suture trajectory. Deviation from an ideal path was quantified using Euclidean distance. Mean and SD of path deviation were calculated. Group comparisons were made as fold-change reductions and standardized effect sizes (Cohen d) to quantify the magnitude of observed differences. RESULTS:Robotic-assisted sutures demonstrated significantly lower mean path deviation and variability than HS sutures, particularly for the dominant (right) hand, with consistently large effect sizes for the right hand (all = 1.2, r = 0.5) and smaller for the left hand (d = 0.36-0.71, r = 0.18-0.33). CONCLUSION/CONCLUSIONS:Robotic microsuturing with microsurgical assistant significantly improves path fidelity, particularly in dominant-hand tasks. Manual sutures showed larger deviations between the ideal suture and raw data, supporting robotic integration into cerebrovascular neurosurgery and warranting study in live models.

The rise of artificial intelligence (AI)-driven tools like ChatGPT is transforming professional fields, including pathology. This study provides early insights into how pathology trainees and practicing pathologists are integrating AI into their training and clinical practice. To assess adoption, usage patterns, perceptions, and challenges related to AI-driven tools, including large language models and vision-language models, among pathology professionals. The study also explores future directions for AI integration. A cross-sectional, anonymous survey was distributed electronically to pathology residents, fellows, and attending pathologists through the Accreditation Council for Graduate Medical Education program director registry, professional organizations, and social media (X, Reddit, LinkedIn, and The Pathologist email listserv). The survey included multiple-choice, Likert-scale, and open-ended questions on AI familiarity, usage, perceived benefits/risks, and institutional policies. Data were analyzed using descriptive and inferential statistics, with qualitative responses categorized thematically. A total of 268 respondents participated, primarily residents (41%), attendings (39%), and fellows (7%), representing 23 countries (65% from the USA). Most were affiliated with academic medical centers (72%) and aged 25-44. Whereas 73% reported some familiarity with AI, actual use was limited, 31% reported rare use and 29% no use at all, especially among residents and attendings. ChatGPT was the most used tool (84%), applied mainly for document drafting (57%), research (54%), and administrative tasks (34%). Diagnostic use was minimal. Top concerns included accuracy (81%), over-reliance (65%), and data security (63%). Only 10% reported having clear institutional AI guidelines. Familiarity was strongly associated with usage frequency (p < 0.00001). AI is increasingly used in non-diagnostic areas of pathology but adoption remains cautious. Significant gaps in clinical application, trust, and institutional support persist. Clear guidelines, targeted education, and robust validation are essential for safe, effective AI integration into pathology practice and training.

Schwannomas are benign encapsulated nerve sheath tumors that are rarely found in the lower extremity. We report a unique case of a 65-year-old woman presenting with chronic lateral ankle instability and a palpable mass posterior to the lateral malleolus. Magnetic resonance imaging revealed an 11 by 6 by 10 mm lesion contiguous with the sural nerve. The mass was excised via meticulous enucleation with nerve preservation. Histopathology confirmed a cellular schwannoma. The patient underwent concurrent ankle arthroscopy and lateral ligament repair, thereby achieving complete resolution of symptoms and return to function at 6 months. This is the first reported case of a sural nerve schwannoma associated with chronic lateral ankle instability.

BACKGROUND:Impaired multi-ciliated cell (MCC) differentiation, observed in various airway diseases, causes prolonged inflammation and further airway complications due to malfunction of the airway defense mechanism. YAP/TAZ-TEAD signaling mediates multiple mechanisms associated with MCC differentiation. However, YAP reportedly has both negative and positive roles in MCC differentiation, putatively due to its dual functions in the cytoplasm and nucleus. We hypothesize inhibition of nuclear YAP, while preserving cytoplasmic YAP functions, restores MCCs in various airway disorders. Here, we investigated the relationship between YAP nuclear localization and the presence of MCCs across patients. In addition, we identified compounds that promote MCC differentiation based on the inhibitory function of YAP nuclear localization. METHOD/METHODS:Tracheal specimens were collected from patients with different conditions (smoking, irradiation, tracheotomy, dysphagia), and YAP nuclear localization in MCCs was assessed by immunohistochemistry at areas with varying MCC compositions. To identify compounds that efficiently inhibit nuclear localization of YAP, airway epithelial cells were treated with multiple YAP inhibitors and YAP nuclear localization was assessed by immunofluorescence-based image analysis. The effects of the compounds on MCC differentiation were evaluated using air-liquid interface (ALI) culture and rat airway squamous metaplasia models. RESULTS:In the human trachea, YAP nuclear localization in MCCs was negatively correlated with the proportion of MCCs in the epithelium, regardless of patient condition. Among known YAP inhibitors, verteporfin and atorvastatin efficiently inhibited YAP nuclear localization in cultured airway epithelial cells. Additionally, verteporfin promoted MCC differentiation in ALI culture and in vivo squamous metaplasia models. CONCLUSION/CONCLUSIONS:Our findings suggest YAP nuclear localization in human airway MCCs is broadly associated with decreased MCCs regardless of patient condition, and verteporfin improves airway MCC differentiation.

OBJECTIVE/UNASSIGNED:Cardiothoracic surgery requires mastery of a broad knowledge base and advanced skillset to manage critically ill patients. Although competency-based assessment frameworks have been developed in several specialties, there remains a paucity of resources to guide practical progression for early cardiothoracic surgical trainees. METHODS/UNASSIGNED:Members of the Thoracic Surgery Residents Association, Thoracic Surgery Medical Student Association, and attending cardiothoracic surgeons with a strong track record of surgical education were invited to share their insights and experiences. A structured, milestone-driven roadmap was developed on the basis of their contributions. RESULTS/UNASSIGNED:We developed a structured, competency-based framework for early surgical trainees, with an emphasis on progressive development of clinical knowledge, technical skills, and academic proficiency. Key milestones and applicable resources were curated to help guide independent learning and skill acquisition. CONCLUSIONS/UNASSIGNED:This structured roadmap offers early-stage cardiothoracic surgery trainees a competency-guided path toward proficiency. By providing clear guidance and granular action points, this guide may help facilitate independent learning and prepare residents for advanced cardiothoracic surgical training.

BACKGROUND:The Charlson Comorbidity Index (CCI) is widely used in surgical research to summarize patients' baseline comorbidities. However, large surgical databases, such as the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP), lack key CCI components, limiting its applicability. Developing a modified CCI (mCCI) using available ACS-NSQIP variables could improve baseline risk stratification for patients undergoing pancreatoduodenectomy (PD). This study aimed to define such an mCCI and evaluate its performance compared with that of the conventional CCI. METHODS:This was a 2-phase retrospective study that included patients who underwent PD. In the derivation phase, our institutional ACS-NSQIP database (2015-2021) was used to construct the mCCI, with scores reweighted to the observed 14-point maximum. The Spearman rank correlation was used to evaluate the relationship between CCI and mCCI. The nationwide ACS-NSQIP database (2022) was used for external validation. Unadjusted logistic regression models were constructed to predict discharge disposition and postoperative complications. Model discrimination was evaluated using area under the receiver operating characteristic curve (AUC)/receiver operating characteristic curve analysis with AUCs compared with the DeLong test. RESULTS:A total of 333 institutional and 4867 national patients who underwent PD were included. In the derivation cohort, the mCCI was strongly correlated with the CCI (r = 0.85; P <.001). For discharge disposition, both indices yielded an AUC of 0.74. For postoperative complications, AUCs were 0.50 for CCI and 0.55 for mCCI. Similar trends were observed in external validation. No significant differences were found in the discriminatory capacities between the models. CONCLUSION/CONCLUSIONS:mCCI is a reasonable alternative to account for baseline comorbidities in patients undergoing PD using the ACS-NSQIP database. Further studies should refine weighting schemes across diverse populations to optimize mCCI performance.