RESUMEN
Auditory impairment stands as a pervasive global issue, exerting significant effects on individuals' daily functioning and interpersonal engagements. Cochlear implants (CIs) have risen as a cutting-edge solution for severe to profound hearing loss, directly stimulating the auditory nerve with electrical signals. The success of CI procedures hinges on precise pre-operative planning and post-operative evaluation, highlighting the significance of advanced three-dimensional (3D) inner ear reconstruction software. Accurate pre-operative imaging is vital for identifying anatomical landmarks and assessing cochlear deformities. Tools like 3D Slicer, Amira and OTOPLAN provide detailed depictions of cochlear anatomy, aiding surgeons in simulating implantation scenarios and refining surgical approaches. Post-operative scans play a crucial role in detecting complications and ensuring CI longevity. Despite technological advancements, challenges such as standardization and optimization persist. This review explores the role of 3D inner ear reconstruction software in patient selection, surgical planning, and post-operative assessment, tracing its evolution and emphasizing features like image segmentation and virtual simulation. It addresses software limitations and proposes solutions, advocating for their integration into clinical practice. Ultimately, this review underscores the impact of 3D inner ear reconstruction software on cochlear implantation, connecting innovation with precision medicine.
RESUMEN
Non-Hodgkin's lymphoma (NHL) of the lacrimal sac is a rare, yet clinically significant entity within the spectrum of ocular malignancies. While primary lacrimal sac lymphoma is uncommon, it poses unique diagnostic and therapeutic challenges due to its anatomical location and potential for aggressive behavior. Despite advancements being made in the current understanding and treatment of NHL, research that specifically addresses the involvement of the lacrimal sac is currently lacking. Thus, the present review aimed to provide insight into the epidemiology, clinical presentation, diagnostic modalities, histopathological features, treatment strategies and prognosis of lacrimal sac NHL. Through a methodical analysis of previous literature, the present review highlights the diverse spectrum of NHL subtypes that affect the lacrimal sac, including diffuse large B-cell lymphoma, extranodal marginal zone lymphoma, mantle cell lymphoma and follicular lymphoma. Moreover, the present review discusses the role of advanced imaging techniques in accurate staging and treatment planning, including computed tomography (CT), magnetic resonance imaging and positron emission tomography-CT. The present review also discusses evolving treatment approaches, such as surgical intervention, chemotherapy, radiotherapy, immunotherapy, combinations of the aforementioned treatments and targeted therapy. In addition, the present review highlights the significance of multidisciplinary collaboration in attaining optimal outcomes for individuals with lacrimal sac NHL. The present review aimed to provide a basis for 'further investigations into novel treatment modalities and prognostic markers that may aid in guiding personalized management strategies, ultimately improving outcomes for patients with NHL.
RESUMEN
PURPOSE: A possible correlation between epistaxis occurrence and atmospheric parameters' variation has long been hypothesized. This study aims to determine whether cumulative epistaxis incidence is related to seasonal variation and its relationship to monthly, weekly, and daily recordings of atmospheric measurements in the city of Patras, Greece. METHODS: In this retrospective study, data concerning the patients who presented with active epistaxis at the ED of a tertiary university hospital in Western Greece between January 2020 and December 2021 were collected. Only cases of spontaneous epistaxis were included in the study; patients bleeding secondarily due to a known mechanical cause, i.e., a tumor, trauma, or surgery, were excluded. The measurements of atmospheric parameters were supplied by the Department of Physics, University of Patras. RESULTS: In total, 230 cases of spontaneous, active epistaxis were evaluated in the ED over the course of the study. The median frequency of epistaxis presentations was two cases per week. Most of the patients were male, comprising 62.6% of the cohort, and the median age stood at 70 years, with an interquartile range (IQR) of 54 to 81 years. A minor yet statistically significant negative correlation between the incidence of epistaxis and mean relative humidity was observed both on a daily and weekly basis. Mean relative humidity emerged as a significant predictor for the incidence of epistaxis, both daily and weekly. Significantly lower mean relative humidity values were recorded during weeks with a high incidence of epistaxis cases (57.72% vs. 63.39%, p = 0.02). No discernible seasonality was observed in the frequency of epistaxis presentations to the ED. CONCLUSION: A modest yet statistically significant trend toward fewer epistaxis cases was observed in conditions of higher ambient humidity during the study period in the region of Western Greece.
RESUMEN
Over the last decades, the field of medicine has witnessed significant progress in artificial intelligence (AI), the Internet of Medical Things (IoMT), and deep learning (DL) systems. Otorhinolaryngology, and imaging in its various subspecialties, has not remained untouched by this transformative trend. As the medical landscape evolves, the integration of these technologies becomes imperative in augmenting patient care, fostering innovation, and actively participating in the ever-evolving synergy between computer vision techniques in otorhinolaryngology and AI. To that end, we conducted a thorough search on MEDLINE for papers published until June 2023, utilizing the keywords 'otorhinolaryngology', 'imaging', 'computer vision', 'artificial intelligence', and 'deep learning', and at the same time conducted manual searching in the references section of the articles included in our manuscript. Our search culminated in the retrieval of 121 related articles, which were subsequently subdivided into the following categories: imaging in head and neck, otology, and rhinology. Our objective is to provide a comprehensive introduction to this burgeoning field, tailored for both experienced specialists and aspiring residents in the domain of deep learning algorithms in imaging techniques in otorhinolaryngology.
