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Adenoid cystic carcinoma (AdCC) is a salivary gland neoplasm that infrequently appears in the sinonasal region. The aim of this study was to evaluate the outcome and clinicopathological parameters of sinonasal AdCC. A retrospective analysis was conducted on all cases of AdCC affecting the nasal cavity or paranasal sinuses between 2000 and 2018 at the University Hospital Zurich. Tumor material was examined for morphological features and analyzed for molecular alterations. A total of 14 patients were included. Mean age at presentation was 57.7 years. Sequencing revealed MYB::NFIB gene fusion in 11/12 analyzable cases. Poor prognostic factors were solid variant (p < 0.001), histopathological high-grade transformation (p < 0.001), and tumor involvement of the sphenoid sinus (p = 0.02). The median recurrence-free survival (RFS) and OS were 5.2 years and 11.3 years. The RFS rates at 1-, 5-, and 10-year were 100%, 53.8%, and 23.1%. The OS rates at 1-, 5-, and 10- years were 100%, 91.7%, and 62.9%, respectively. In Conclusion, the solid variant (solid portion > 30%), high-grade transformation, and sphenoid sinus involvement are negative prognostic factors for sinonasal AdCC. A high prevalence of MYB::NFIB gene fusion may help to correctly classify diagnostically challenging (e.g. metatypical) cases., (© 2024. The Author(s).)

Our goal with this survey is to provide an overview of the state of the art deep learning methods for face generation and editing using StyleGAN. The survey covers the evolution of StyleGAN, from PGGAN to StyleGAN3, and explores relevant topics such as suitable metrics for training, different latent representations, GAN inversion to latent spaces of StyleGAN, face image editing, cross-domain face stylization, face restoration, and even Deepfake applications. We aim to provide an entry point into the field for readers that have basic knowledge about the field of deep learning and are looking for an accessible introduction and overview.