RESUMO
Introduction: In clinical research on pituitary disorders, pituitary gland (PG) segmentation plays a pivotal role, which impacts the diagnosis and treatment of conditions such as endocrine dysfunctions and visual impairments. Manual segmentation, which is the traditional method, is tedious and susceptible to inter-observer differences. Thus, this study introduces an automated solution, utilizing deep learning, for PG segmentation from magnetic resonance imaging (MRI). Methods: A total of 153 university students were enrolled, and their MRI images were used to build a training dataset and ground truth data through manual segmentation of the PGs. A model was trained employing data augmentation and a three-dimensional U-Net architecture with a five-fold cross-validation. A predefined field of view was applied to highlight the PG region to optimize memory usage. The model's performance was tested on an independent dataset. The model's performance was tested on an independent dataset for evaluating accuracy, precision, recall, and an F1 score. Results and discussion: The model achieved a training accuracy, precision, recall, and an F1 score of 92.7%, 0.87, 0.91, and 0.89, respectively. Moreover, the study explored the relationship between PG morphology and age using the model. The results indicated a significant association between PG volume and midsagittal area with age. These findings suggest that a precise volumetric PG analysis through an automated segmentation can greatly enhance diagnostic accuracy and surveillance of pituitary disorders.
Assuntos
Aprendizado Profundo , Humanos , Processamento de Imagem Assistida por Computador/métodos , Imageamento por Ressonância Magnética/métodos , Projetos de Pesquisa , Hipófise/diagnóstico por imagemRESUMO
Oxidative stress (OS) affects men's health and impairs spermatogenesis. Micronutrient antioxidants are available for male infertility as complemental support; however, their efficacy remains debatable. This study aimed to investigate whether antioxidants can help to reduce sperm OS and improve semen analysis and quality. We included 171 male partners of couples planning to undergo assisted reproductive technology (ART). Male partners, aged 29-41 years, of couples intending to conceive were self-selected to take daily antioxidants (n = 84) containing folic acid and zinc, or not to take antioxidants (n = 52) for 6 months. We analyzed the alterations in serum oxidant levels, sperm parameters, OS, and deoxyribonucleic acid fragmentation after 3 and 6 months. Additionally, implantation, clinical pregnancy, and miscarriage rates after vitrified-warmed embryo transfer were compared between those taking antioxidants and those not taking them after 6 months. In men with high static oxidation-reduction potential (sORP), we observed a significant improvement in sperm concentration and sORP. The high-quality blastocyst rate tended to increase, and implantation and clinical pregnancy rates also significantly increased after 6 months of intervention. The micronutrient antioxidants could improve sperm function by reducing OS and improving ART outcomes. Therefore, micronutrient antioxidants may be a viable treatment option for male infertility.