30 research outputs found
Comments on: “Vocal Cord Leukoplakia Classification Using Siamese Network Under Small Samples of White Light Endoscopy Images”
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Artificial Intelligence for Upper Aerodigestive Tract Endoscopy and Laryngoscopy: A Guide for Physicians and State‐of‐the‐Art Review
No full textObjective: The endoscopic and laryngoscopic examination is paramount for laryngeal, oropharyngeal, nasopharyngeal, nasal, and oral cavity benign lesions and cancer evaluation. Nevertheless, upper aerodigestive tract (UADT) endoscopy is intrinsically operator-dependent and lacks objective quality standards. At present, there has been an increased interest in artificial intelligence (AI) applications in this area to support physicians during the examination, thus enhancing diagnostic performances. The relative novelty of this research field poses a challenge both for the reviewers and readers as clinicians often lack a specific technical background. Data sources: Four bibliographic databases were searched: PubMed, EMBASE, Cochrane, and Google Scholar. Review methods: A structured review of the current literature (up to September 2022) was performed. Search terms related to topics of AI, machine learning (ML), and deep learning (DL) in UADT endoscopy and laryngoscopy were identified and queried by 3 independent reviewers. Citations of selected studies were also evaluated to ensure comprehensiveness. Conclusions: Forty-one studies were included in the review. AI and computer vision techniques were used to achieve 3 fundamental tasks in this field: classification, detection, and segmentation. All papers were summarized and reviewed. Implications for practice: This article comprehensively reviews the latest developments in the application of ML and DL in UADT endoscopy and laryngoscopy, as well as their future clinical implications. The technical basis of AI is also explained, providing guidance for nonexpert readers to allow critical appraisal of the evaluation metrics and the most relevant quality requirements
Recurrent respiratory papillomatosis: comparing in-office and operating room treatments
No full textObjective. We report the management of recurrent respiratory papillomatosis (RRP) employing a protocol that includes both office-based (OB) and general anaesthesia (GA) procedures. Quality of life (QoL) outcomes in the OB cohort were compared to those obtained from an historical cohort treated only under GA. Methods. Patients affected by RRP from 2019 until 2023 (“new protocol”) and from 2012 to 2019 (“historical protocol”) were enrolled. In both groups the Derkay site score (DSS) was calculated. In patients adhering to the new protocol, questionnaires measuring QoL were prospectively administered (voice handicap hindex-10 [VHI-10] along with a specific questionnaire to measure the tolerance to the OB procedures). A cost analysis was also performed. Results. In all, 35 patients composed the new protocol cohort and 13 the historical. In the first group, patients underwent a median of 4 treatments. At 2 years, 68% of patients were treated ex clusively in the office. Overall, for the new protocol, median DSS and VHI-10 after one year were both significantly lower than those at baseline [2 vs 4 and 3 vs 14, respectively; p < 0.001]. No differences were found between the new and the historical protocol cohorts considering DSS over time. Conclusions. Treatment of RRP may be conducted successfully in an office-based setting reducing healthcare costs
Office‐Based Treatment of Vocal Fold Polyps and Reinke's Edema: A Rational Comparison With Suspension Laryngoscopy
No full textObjective Benign laryngeal lesions have traditionally been treated through suspension laryngoscopy under general anesthesia (GA). Recently, the development of operative videoendoscopes coupled with photoangiolytic lasers has allowed clinicians to treat these conditions in the outpatient clinic. We report our experience in the office-based (OB) setting for the treatment of patients affected by vocal fold polyps (VFPs) and Reinke's edema (RE), comparing it to patients treated under GA.Methods A retrospective analysis was conducted on patients affected by VFP or RE. A 445 nm diode blue laser was used through the operative channel of a flexible video-endoscope for OB procedures, while GA surgeries were carried out with cold steel instrumentation. The Voice Handicap Index-10 (VHI-10) represented the primary outcome. Endoscopic outcomes, duration, and morbidity of the procedures were investigated as secondary outcomes.Results A total of 153 patients were retrospectively enrolled. 52 were treated in an OB setting, while 91 underwent GA. Regarding patients with RE, both the OB and GA cohorts showed a significant improvement in VHI-10 (from 12.7 to 2.6 and 19.5 to 5.1, respectively; p < 0.001), as did those with VFPs (from 11.8 to 2.3 and 15.9 to 2.9 respectively; p < 0.001). No differences were found when comparing VHI-10 in the OB and GA cohorts. The mean procedural time of OB treatment (4.9 min) was significantly shorter than GA (37.1 min). No adverse events were reported.Conclusion Our data demonstrate the efficacy and safety of the OB setting. For selected patients, OB treatments offer comparable vocal outcomes, favorable morbidity, and reduced operation times, making them an appealing alternative to the traditional approach
Post-COVID-19 airway stenosis treated by tracheal resection and anastomosis: a bicentric experience
No full textOBJECTIVE: The COVID-19 pandemic was an extraordinary challenge for the global healthcare system not only for the number of patients affected by pulmonary disease, but also for the incidence of long-term sequalae. In this regard, laryngo-tracheal stenosis (LTS) represents one of the most common complications of invasive ventilation. METHODS: A case series of patients who underwent tracheal resection and anastomosis (TRA) for post-COVID-19 LTS was collected from June 2020 to September 2021. RESULTS: Among 14 patients included, 50% had diabetes and 64.3% were obese. During intensive care unit stay, mean duration of orotracheal intubation (OTI) was 15.2 days and 10 patients (71.4%) underwent tracheostomy, which was maintained in 7 for an average of 31 days. According to the European Laryngological Society classification, 13 patients (92.9%) had a grade IIIa LTS and one a grade IIIa+. All patients underwent Type A TRA, according to the authors’ classification. No major perioperative complications were reported and at the last follow-up all patients were asymptomatic. CONCLUSIONS: With the appropriate indications, TRA represents an effective treatment in post-COVID-19 LTS patients. Short OTI times and careful tracheostomy are required in order to reduce the incidence of airway injury
Enhancing quality of life in head and neck cancer patients: a comparative analysis of 3D exoscope-assisted surgery vs. traditional approaches
No full textReal-Time Laryngeal Cancer Boundaries Delineation on White Light and Narrow-Band Imaging Laryngoscopy with Deep Learning
No full textObjective: To investigate the potential of deep learning for automatically delineating (segmenting) laryngeal cancer superficial extent on endoscopic images and videos. Methods: A retrospective study was conducted extracting and annotating white light (WL) and Narrow-Band Imaging (NBI) frames to train a segmentation model (SegMENT-Plus). Two external datasets were used for validation. The model's performances were compared with those of two otolaryngology residents. In addition, the model was tested on real intraoperative laryngoscopy videos. Results: A total of 3933 images of laryngeal cancer from 557 patients were used. The model achieved the following median values (interquartile range): Dice Similarity Coefficient (DSC) = 0.83 (0.70-0.90), Intersection over Union (IoU) = 0.83 (0.73-0.90), Accuracy = 0.97 (0.95-0.99), Inference Speed = 25.6 (25.1-26.1) frames per second. The external testing cohorts comprised 156 and 200 images. SegMENT-Plus performed similarly on all three datasets for DSC (p = 0.05) and IoU (p = 0.07). No significant differences were noticed when separately analyzing WL and NBI test images on DSC (p = 0.06) and IoU (p = 0.78) and when analyzing the model versus the two residents on DSC (p = 0.06) and IoU (Senior vs. SegMENT-Plus, p = 0.13; Junior vs. SegMENT-Plus, p = 1.00). The model was then tested on real intraoperative laryngoscopy videos. Conclusion: SegMENT-Plus can accurately delineate laryngeal cancer boundaries in endoscopic images, with performances equal to those of two otolaryngology residents. The results on the two external datasets demonstrate excellent generalization capabilities. The computation speed of the model allowed its application on videolaryngoscopies simulating real-time use. Clinical trials are needed to evaluate the role of this technology in surgical practice and resection margin improvement. Level of evidence: III Laryngoscope, 2024
Improving real-time detection of laryngeal lesions in endoscopic images using a decoupled super-resolution enhanced YOLO
No full textBackground and Objective: Laryngeal Cancer (LC) constitutes approximately one third of head and neck cancers. Detecting early-stage lesions in this anatomical region is crucial for achieving a high survival rate. However, it poses significant diagnostic challenges owing to the varied appearance of lesions and the need for precise characterization for appropriate clinical management. Conventional diagnostic approaches rely heavily on endoscopic examination, which often requires expert interpretation and may be limited by subjective assessment. Deep learning (DL) approaches offer promising opportunities for automating lesion detection, but their efficacy in handling multi-modal imaging data and accurately localizing small lesions remains a subject of investigation. Furthermore, the clinical domain may largely benefit from the deployment of efficient DL methods that can ensure equitable access to advanced technologies, regardless of the availability of resources that can often be limited. In this study, a DL-based approach, named SRE-YOLO, was introduced to provide real-time assistance to less-experienced personnel during laryngeal assessment, by automatically detecting lesions at different scales from endoscopic White Light (WL) and Narrow-Band Imaging (NBI) images. Methods: During the training, the SRE-YOLO integrates a YOLOv8 nano (YOLOv8n) baseline with a Super-Resolution (SR) branch to enhance lesion detection. This last component is decoupled during inference to preserve the low computational demand of the YOLOv8n baseline. The evaluation was conducted on a multi-center dataset, encompassing diverse laryngeal pathologies and acquisition modalities. Results: The SRE-YOLO method improved the Average Precision (AP @IoU=0.5) in lesion detection by 5% with respect to the YOLOv8n baseline, while maintaining the inference speed of 58.8 Frames Per Second (FPS). Comparative analyses against state-of-the-art DL methods highlighted the efficacy of the SRE-YOLO approach in balancing detection accuracy, computational efficiency, and real-time applicability. Conclusions: This research underscores the potential of SRE-YOLO in developing efficient DL-driven decision support systems for real-time detection of laryngeal lesions at different scales from both WL and NBI endoscopic dat
High-resolution US of the facial vessels with new facial vein landmarks for reconstructive surgery and dermal injection
No full textAbstract Background Accurate knowledge of vessel anatomy is essential in facial reconstructive surgery. The technological advances of ultrasound (US) equipment with the introduction of new high-resolution probes improved the evaluation of facial anatomical structures. Our study had these objectives: the primary objective was to identify new surgical landmarks for the facial vein and to verify their precision with US, the secondary objective was to evaluate the potential of high-resolution US examination in the study of both the facial artery and vein. Methods Two radiologists examined a prospective series of adult volunteers with a 22–8 MHz hockey-stick probe. Two predictive lines of the facial artery and vein with respective measurement points were defined. The distance between the facial vein and its predictive line (named mandibular-orbital line) was determined at each measurement point. The distance from the skin and the area of the two vessels were assessed at every established measurement point. Results Forty-one volunteers were examined. The median distance of the facial vein from its predictive line did not exceed 2 mm. The facial vein was visible at every measurement point in all volunteers on the right side, and in 40 volunteers on the left. The facial artery was visible at every measurement point in all volunteers on the right and in 37 volunteers on the left. Conclusions The facial vein demonstrated a constant course concerning the mandibular-orbital line, which seems a promising clinical and imaging-based method for its identification. High-resolution US is valuable in studying the facial artery and vein. Relevance statement High-resolution US is valuable for examining facial vessels and can be a useful tool for pre-operative assessment, especially when combined with the mandibular-orbital line, a new promising imaging and clinical technique to identify the facial vein. Key points • High-resolution US is valuable in studying the facial artery and vein. • The facial vein demonstrated a constant course concerning its predictive mandibular-orbital line. • The clinical application of the mandibular-orbital line could help reduce facial surgical and cosmetic procedure complications. Graphical Abstrac
