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Abstract Background Monopolar cautery is the most commonly used surgical cutting and hemostatic tool for head and neck surgery. There are newer technologies that are being utilized with the goal of precise cutting, decreasing blood loss, reducing thermal damage, and allowing faster wound healing. Our study compares thermal damage caused by Harmonic scalpel and CO2 laser to cadaveric tongue. Methods Two fresh human cadaver heads were enrolled for the study. Oral tongue was exposed and incisions were made in the tongue akin to a tongue tumor resection using the harmonic scalpel and flexible C02 laser fiber at various settings recommended for surgery. The margins of resection were sampled, labeled, and sent for pathological analysis to assess depth of thermal damage calculated in millimeters. The pathologist was blinded to the surgical tool used. Control tongue tissue was also sent for comparison as a baseline for comparison. Results Three tongue samples were studied to assess depth of thermal damage by harmonic scalpel. The mean depth of thermal damage was 0.69 (range, 0.51 - 0.82). Five tongue samples were studied to assess depth of thermal damage by CO2 laser. The mean depth of thermal damage was 0.3 (range, 0.22 to 0.43). As expected, control samples showed 0 mm of thermal damage. There was a statistically significant difference between the depth of thermal injury to tongue resection margins by harmonic scalpel as compared to CO2 laser, (p = 0.003). Conclusion In a cadaveric model, flexible CO2 laser fiber causes less depth of thermal damage when compared with harmonic scalpel at settings utilized in our study. However, the relevance of this information in terms of wound healing, hemostasis, safety, cost-effectiveness, and surgical outcomes needs to be further studied in clinical settings.

Three-dimensional endocardial impedance mapping: a new approach for myocardial infarction assessment. Am J Physiol Heart Circ Physiol 280: H179-H188, 2001.--Precise identification of infarcted myocardial tissue is of importance in diagnostic and interventional cardiology. A three-dimensional, catheter-based endocardial electromechanical mapping technique was used to assess the ability of local endocardial impedance in delineating the exact location, size, and border of canine myocardial infarction. Electromechanical mapping of the left ventricle was performed in a control group (n = 10) and 4 wk after left anterior descending coronary artery ligation (n = 10). Impedance, bipolar electrogram amplitude, and endocardial local shortening (LS) were quantified. The infarcted area was compared with the corresponding regions in controls, revealing a significant reduction in impedance values [infarcted vs. controls: 168.8 [+ or -] 11.7 and 240.7 [+ or -] 22.3 [Omega], respectively (means [+ or -] SE), P [is less than] 0.05] bipolar electrogram amplitude (1.8 [+ or -] 0.2 mV, 4.4 [+ or -] 0.7 mV, P [is less than] 0.05), and LS (-2.36 [+ or -] 1.6%, 11.9 [+ or -] 0.9%, P [is less than] 0.05). The accuracy of the impedance maps in delineating the location and extent of the infarcted region was demonstrated by the high correlation with the infarct area (Pearson's correlation coefficient = 0.942) and the accurate identification of the infarct borders in pathology. By accurately defining myocardial infarction and its borders, endocardial impedance mapping may become a clinically useful tool in differentiating healthy from necrotic myocardial tissue. myocardial viability assessment; electromechanical coupling; electrophysiology

Background: The creation of operative reports is a tedious documentation task that increases administrative burden, which is a potential driver of burnout. Additionally, operative reports are inherently subjective and may contain inaccuracies and incomplete information. Recent advances in artificial intelligence (AI) technology have enabled computer-vision systems to accurately detect operative steps on surgical video. We aim to develop a platform for automated creation of video-based AI surgical operative reports in robotic-assisted radical prostatectomy (RARP)., Study Design: An AI computer-vision algorithm was employed to automatically detect surgical steps. Each step detected on video was mapped to pre-specified text, which was then compiled into a narrative AI operative report. Accuracy of the AI operative reports was compared to operative reports written by surgeons, using expert review of raw surgical video footage as the ground-truth., Results: 158 cases from a tertiary referral center were included. In surgeon operative reports, 84(53.2%) cases had at least one discrepancy between the operative report and surgical video. Of these, 43(27.2%) cases had a clinically significant discrepancy based on expert video review. In AI operative reports, 46(29.1%) cases had at least one discrepancy between the operative report and surgical video. Of these, 20(12.7%) cases had a clinically significant discrepancy. Overall accuracy was higher for AI operative reports as compared to surgeon operative reports (87.3% versus 72.8%,p=0.001)., Conclusion: Operative reports created by AI achieved higher accuracy than those written by surgeons. To our knowledge, this is the first report of automated video-based AI surgical documentation. Future studies are warranted to explore the potential for this novel tool to reduce documentation burden, improve operative report accuracy, promote surgical transparency, and decrease subjectivity in surgical documentation., (Copyright © 2025 by the American College of Surgeons. Published by Wolters Kluwer Health, Inc. All rights reserved.)

Introduction: The use of artificial intelligence (AI) in medicine is rising fast. We continually hear about novel AI-based technologies being deployed to aid clinical teams in areas like interpreting medical images, understanding pathology, determining diagnosis, predicting prognosis, and deciding on interventions. The field of surgery, however, has been slower to jump on the AI bandwagon. In this paper, we present Surgical Intelligence, an innovative and fast-developing field involving routine capture and AI-based analysis of endoscopic procedure videos. We discuss the need for documenting surgical video, the potential benefits for training and quality improvement, and the features that allow Surgical Intelligence platforms to provide accessible and effective solutions for medical teams.

Recurrent and residual medullary thyroid carcinoma (MTC) are common in patients following primary surgical resection. Difficulty arises in performing precise localization of the tumor because of anatomical distortion of the neck structures following surgery. To date, no modality has been shown superior to others in the diagnosis of recurrent or residual MTC, and the issue is currently under debate in the literature. We report a case in which secondary recurrence of MTC was detected and localized using a novel combination of preoperative and intraoperative radionuclide imaging, and a method of preventing intraoperative damage to the recurrent laryngeal nerve in the anatomically disrupted neck. To our knowledge, this is the first report of a combination of these three modalities in detection and localization of recurrent MTC, while minimizing the possibility for nerve injury during the operative procedure. Such a therapeutic strategy may prove useful in the management of patients who have previously undergone neck surgery and suffer from anatomical distortion of normal neck structures.