Updates on eyelid cancers.

In this review, we aim to provide an overview of the five most common malignant eyelid tumors with current treatment recommendations based on international guidelines. Particular attention is paid to the clinicopathological correlation and the update with regard to adequate treatment. Newer systemic therapies enrich the existing treatment options, of which complete tumor excision remains the most important therapeutic measure.

HIF1α and HIF2α immunoreactivity in epithelial tissue of primary and recurrent pterygium by immunohistochemical analysis.

PURPOSE: Hypoxia-inducible factors (HIFs) are considered to play a significant role in the pathogenesis of pterygium. The aim of this study was to investigate the relative expression or immunoreactivity of HIF1α and HIF2α in the epithelium of primary pterygium, recurrences and healthy conjunctiva. METHODS: Immunohistochemical staining was performed with antibodies against HIF1α and HIF2α, respectively, on 55/84 primary pterygium specimens, 6/28 recurrences and 20/20 control tissues (healthy conjunctiva). RESULTS: Immunohistochemical staining revealed lower epithelial immunoreactivity of HIF1α and HIF2α in both primary pterygium (11% and 38%) and recurrences (18% and 21%) when compared to healthy conjunctival tissue (46% and 66%). Differences between immunoreactivity of HIF1α and of HIF2α in primary pterygium and controls were each highly significant (p < .001). Within the group of primary pterygium, epithelial immunoreactivity of HIF2α (38%) was significantly higher than that of HIF1α (11%). In recurrent pterygium and healthy conjunctiva, immunoreactivity levels of HIF2α were higher than those of HIF1α as well; however, differences between both isoforms were not significant. CONCLUSION: Our study shows evidence that the higher expressed epithelial HIF2α, rather than HIF1α, and the balance between both HIF isoforms might be relevant factors associated with pathogenesis of primary pterygium. Modulation of HIF2α levels and activity may thus offer a new therapeutic approach to the treatment of advancing pterygium where the initial stage with its HIF1-peak has already passed.

Intrastromal Keratolimbal Epithelial Cysts: Congenital and Postsurgical. / Intrastromale keratolimbale Epithelzysten: kongenital und postoperativ.

Two very rare cases of intrastromal keratolimbal epithelial cysts are reported. Firstly, an enlarging congenital cyst in a 9-year-old boy, and secondly, a recurrent postsurgical cyst in an 18-year-old female patient. Both cases presented with a limbal cyst, continuing into the corneal stroma as a whitish mass up to the optical axis. The indication for surgery was stabilization of visual acuity in case one and improvement of cosmetic aspects in case two. In the first case, a small part of the cyst was opened at the limbus and the whitish material in the cyst was flushed out. In the second case, anterior lamellar keratectomy over the whole cyst was performed with subsequent application of mitomycin C. Immunohistochemical analysis revealed cytokeratin 19-positive epithelial cells in both cysts. Therefore, an implantation of conjunctival epithelium into the sclera seems to be responsible for the respective keratolimbal cyst. Postsurgically, satisfying cosmetic and functional results were obtained in both cases, with follow-ups of 4 and 9 months. Keratolimbal cysts have rarely been described in the literature. In most cases, a conjunctival epithelial implantation occurs following surgery or trauma and very rarely congenitally. After simple aspiration of the cyst's content, a rapid recurrence is often observed, so that partial or - if possible - complete removal of the anterior cyst wall is recommended, as shown in our cases.

Chronic Granulomatous Inflammation after CyPass® Implantation.

A 65-year-old patient suffering from pseudoexfoliation glaucoma and multiple previous surgeries at the right eye underwent CyPass® explantation 19 months after CyPass® Micro-Stent implantation due to chronic inflammation in the an-terior chamber. Histologically, a foreign body granuloma around and in the CyPass® implant was found. We conclude that patients with previous multiple glaucoma surgeries should not undergo CyPass® Micro-Stent implantation.

[Quality Management at the Eye Centre of Freiburg University Hospital: Does it Help to Use Quality Parameters?] / Qualitätsmanagement an der Klinik für Augenheilkunde des Universitätsklinikums Freiburg: Was nutzt das Erheben von Qualitätsparametern?

BACKGROUND: All hospitals in Germany have a legal obligation to carry out internal quality management (QM). This means enormous costs as well as a burden for the employees through QM-specific tasks. The benefits can be advertising through certification, higher quality and safety for the treated patients and thus greater patient and employee satisfaction. The aim of this work is to compare effort and benefit of a QM system in ophthalmology. MATERIAL AND METHODS: The surgical quality parameters already published in the annual reports, the available data of the QM handbook via the digital QM portal and patient feedbacks from 2004 to 2018/2019 were evaluated. RESULTS: In 2004, a quality management system was established for the first time in the Eye Centre at the Freiburg University Hospital. From 2005 to 2017, the entire hospital was KTQ-certified. In order to analyse the quality of surgery and patient safety, different surgical quality parameters were collected over the years with a constantly increasing number of operations. The majority of the quality parameters have remained stable or even decreased over the years. A peak in the postoperative endophthalmitis rate of 0.14% in 2015 and the decreasing percentage of cataract operations under topical anaesthesia in recent years were striking. The QM handbook was slimmed down. The analysis of clicks shows that the documents are increasingly used by the employees. The statistics of patient feedbacks show that this is a tool that is used quite frequently by patients to provide feedback on their stay and that the feedback is often positive. CONCLUSION: To operate quality management over many years, i.e. in our case to collect data of surgical quality parameters, to maintain the QM manual and to process patient feedbacks, means considerable effort. However, only the analysis of these parameters provides an insight into the current state of our clinic, from which conclusions can be drawn as to where processes or treatments can be optimised, which in turn can increase employee and patient satisfaction. Overall, transparency is increased and creates confidence for future treatments at the Eye Centre at the Freiburg University Hospital.

[Deep Learning in Pathology: Applications and Challenges in Ophthalmic Pathology]. / Deep Learning in der Pathologie: Anwendungsmöglichkeiten und Herausforderungen in der Ophthalmopathologie.

INTRODUCTION: Deep learning has received increasing attention in recent years and is used in many different areas. Since image analysis is a strength of deep learning, it would be obvious to use it for histopathological questions too. Our goal is to identify possible deep learning approaches from general pathology which could be used in ophthalmic pathology. In addition, the data of the past year will be used to estimate the proportion of potentially interesting cases and the necessary technical effort. METHODS: Firstly, a literature search for deep learning models and their possible applications in the field of pathology was carried out. In order to estimate the potential benefit, technical challenges and feasibility, the number of suitable ophthalmopathology cases in our lab in 2019 for the identified models was determined and put in relation to the resulting amount of data and the scanning time. RESULTS: We identified 7 areas of particular interest: determination of regions of interest (ROI), classification of histological images in scoring systems, mapping of tumor fractions, differentiation of different types of inflammation, differentiation of various cutaneous tumors, classification of lymphomas and prediction of patient outcome-based on tumor histology. Within one year, a total of 831 cases (43%) would have been suitable for the above models. The creation of whole slide images (WSI) for all histological cases would have required a storage capacity of 630 GB with a scanning time of 35 h. CONCLUSION: There are several deep learning approaches which are also interesting for ophthalmic pathology. Most of them would have to be specially trained for the ophthalmopathological aspects. To be able to apply deep learning approaches, it is necessary to have a good IT infrastructure with the possibility to create and permanently store WSI, and this seems to be technically feasible. Future studies should focus on the specific practical implementation of current deep learning possibilities for ophthalmic pathology.