International Pediatric ORL Group (IPOG) laryngomalacia consensus recommendations

Objective To provide recommendations for the comprehensive management of young infants who present with signs or symptoms concerning for laryngomalacia. Methods Expert opinion by the members of the International Pediatric Otolaryngology Group (IPOG). Results Consensus recommendations include initial care and triage recommendations for health care providers who commonly evaluate young infants with noisy breathing. The consensus statement also provides comprehensive care recommendations for otolaryngologists who manage young infants with laryngomalacia including: evaluation and treatment considerations for commonly debated issues in laryngomalacia, initial work-up of infants presenting with inspiratory stridor, treatment recommendations based on disease severity, management of the infant with feeding difficulties, post-surgical treatment management recommendations, and suggestions for acid suppression therapy. Conclusion Laryngomalacia care consensus recommendations are aimed at improving patient-centered care in infants with laryngomalacia

Endoscopic Access to the Infratemporal Fossa and Skull Base: A Cadaveric Study

OBJECTIVES: To demonstrate that the regions of the infratemporal fossa and skull base at the level of the foramen ovale can be visualized endoscopically and that structures can be manipulated within these regions using endoscopic instruments. METHODS: Cadaveric dissection of 3 human cadavers using an endoscopic optical dissector. In all, 6 endoscopic infratemporal fossa and skull base approaches were performed. SETTING: Human temporal bone laboratory. RESULTS: A Gillies incision was coupled with a lateral brow incision, and then subperiosteal planes were developed. Endoscopic visualization and instrumentation was then performed. The infratemporal fossa was readily identified. The skull base at the level of the foramen ovale and the branches of the third division of the trigeminal nerve were seen distinctly. A probe was placed with ease within the foramen ovale itself. CONCLUSIONS: Endoscopic access to the infratemporal fossa is readily accomplished, with excellent visualization and instrumentation ability. This novel technique provides access to this remote region for evaluation, possible biopsy, and potential treatment of infratemporal fossa lesions

Generation of synthetic tympanic membrane images: Development, human validation, and clinical implications of synthetic data

Synthetic clinical images could augment real medical image datasets, a novel approach in otolaryngology–head and neck surgery (OHNS). Our objective was to develop a generative adversarial network (GAN) for tympanic membrane images and to validate the quality of synthetic images with human reviewers. Our model was developed using a state-of-the-art GAN architecture, StyleGAN2-ADA. The network was trained on intraoperative high-definition (HD) endoscopic images of tympanic membranes collected from pediatric patients undergoing myringotomy with possible tympanostomy tube placement. A human validation survey was administered to a cohort of OHNS and pediatrics trainees at our institution. The primary measure of model quality was the Frechet Inception Distance (FID), a metric comparing the distribution of generated images with the distribution of real images. The measures used for human reviewer validation were the sensitivity, specificity, and area under the curve (AUC) for humans’ ability to discern synthetic from real images. Our dataset comprised 202 images. The best GAN was trained at 512x512 image resolution with a FID of 47.0. The progression of images through training showed stepwise “learning” of the anatomic features of a tympanic membrane. The validation survey was taken by 65 persons who reviewed 925 images. Human reviewers demonstrated a sensitivity of 66%, specificity of 73%, and AUC of 0.69 for the detection of synthetic images. In summary, we successfully developed a GAN to produce synthetic tympanic membrane images and validated this with human reviewers. These images could be used to bolster real datasets with various pathologies and develop more robust deep learning models such as those used for diagnostic predictions from otoscopic images. However, caution should be exercised with the use of synthetic data given issues regarding data diversity and performance validation. Any model trained using synthetic data will require robust external validation to ensure validity and generalizability. Author summary Synthetic clinical images could augment real medical image datasets with diverse and rare pathologies. Such synthetic data would have applications in medical education and in bolstering datasets to improve the performance of machine learning models such as diagnostic classifiers. Our study represents one of the first generative models for synthetic image data within our field of Otolaryngology–Head and Neck Surgery. We use a state-of-the-art generative adversarial network (GAN) architecture on a limited dataset to develop a model that produces photo-realistic synthetic images of the tympanic membrane. We developed this model using a small training set of just 202 images. The successful production of photo-realistic synthetic images using a small training set demonstrates the potential for synthetic data approaches with limited datasets, as is often the case in clinical medicine. We validate our images with human reviewers to determine how well humans can distinguish real from synthetic images. This human Turing Test validation approach is rare in synthetic data studies and provides unique insights into the quality of generated images. Future studies could use synthetic tympanic membrane images to train improved diagnostic classifiers based on otoscopic images. However, caution must be exercised with the use of synthetic data, and robust external validation of models trained using synthetic data will be necessary