Artificial intelligence based diagnosis of sulcus: assesment of videostroboscopy via deep learning.

PURPOSE: To develop a convolutional neural network (CNN)-based model for classifying videostroboscopic images of patients with sulcus, benign vocal fold (VF) lesions, and healthy VFs to improve clinicians' accuracy in diagnosis during videostroboscopies when evaluating sulcus. MATERIALS AND METHODS: Videostroboscopies of 433 individuals who were diagnosed with sulcus (91), who were diagnosed with benign VF diseases (i.e., polyp, nodule, papilloma, cyst, or pseudocyst [311]), or who were healthy (33) were analyzed. After extracting 91,159 frames from videostroboscopies, a CNN-based model was created and tested. The healthy and sulcus groups underwent binary classification. In the second phase of the study, benign VF lesions were added to the training set, and multiclassification was executed across all groups. The proposed CNN-based model results were compared with five laryngology experts' assessments. RESULTS: In the binary classification phase, the CNN-based model achieved 98% accuracy, 98% recall, 97% precision, and a 97% F1 score for classifying sulcus and healthy VFs. During the multiclassification phase, when evaluated on a subset of frames encompassing all included groups, the CNN-based model demonstrated greater accuracy when compared with that of the five laryngologists (%76 versus 72%, 68%, 72%, 63%, and 72%). CONCLUSION: The utilization of a CNN-based model serves as a significant aid in the diagnosis of sulcus, a VF disease that presents notable challenges in the diagnostic process. Further research could be undertaken to assess the practicality of implementing this approach in real-time application in clinical practice.

Demographic and clinical characteristics of our patients diagnosed with laryngeal dystonia.

PURPOSE: Laryngeal dystonia (LD) is a focal dystonia affecting laryngeal musculature with no known etiology or cure. The present study evaluated the sociodemographic and clinical features of patients diagnosed with LD. MATERIALS AND METHODS: All patients diagnosed with LD at our University Hospital's Ear, Nose, and Throat Department between January 2017 and July 2023 were retrospectively analyzed. The study included 43 patients. RESULTS: Out of the 43 patients, 19 (44%) were male. At the time of diagnosis, the mean age of the patients was 35.1 years (ranging from 17 to 65 years). The mean elapsed time between the first symptom onset and the first diagnosis was 49.2 months (min. 4 months, max. 240 months). Of the participants, 94% had adductor-type LD. None of the patients had a family history of LD. Of the patients, 9 (20%) experienced a life-altering event or trauma just before the onset of symptoms. All patients who consumed alcohol reported symptom relief with alcohol intake. A total of 67.6% of patients stated that their symptoms were triggered by stress. All of our patients received at least one Botulinum toxin injection, with an average of 2.75 dosages per patient. CONCLUSION: The gender distribution was approximately equitable between males and females. There was a tendency for men to receive a diagnosis earlier than women following the manifestation of symptoms. A significant number of patients associate the emergence of their symptoms with a stressful event or traumatic experience. This study represents the initial investigation into the sociodemographic characteristics of patients within the Turkish population.