Bilateral Acute Macular Neuroretinopathy (AMN) after COVID-19 and its Clinical Course. / Bilaterale akute makuläre Neuroretinopathie (AMN) nach COVID-19 und Verlauf.

Acute macular neuroretinopathy (AMN) is a rare disease entity. It is mainly observed in young women with a history of influenza-like infection or who have been taking oral contraceptives for several years. Patients typically describe subjective visual deterioration and mono- or bilateral paracentral relative scotomas. In some cases, funduscopic ophthalmic examination may reveal subtle sharply demarcated flat lesions of reddish-brown or orange colour in the macular region. Diagnosis is usually made by near-infrared fundus imaging which shows hyporeflective areas, and SD-OCT imaging which manifests changes in the outer retinal layers. In the following, three patient cases with bilateral AMN are described which occurred in direct temporal relationship to a recent SARS-CoV-2 infection.

Post-COVID-19 Syndrome: Retinal Microcirculation as a Potential Marker for Chronic Fatigue.

Post-COVID-19 syndrome (PCS) is characterized by persisting sequelae after infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). PCS can affect patients with all COVID-19 disease severities. As previous studies have revealed impaired blood flow as a provoking factor triggering PCS, it was the aim of the present study to investigate the potential association between self-reported chronic fatigue and retinal microcirculation in patients with PCS, potentially indicating an objective biomarker. A prospective study was performed, including 201 subjects: 173 patients with PCS and 28 controls. Retinal microcirculation was visualized by OCT angiography (OCT-A) and quantified using the Erlangen-Angio-Tool as macula and peripapillary vessel density (VD). Chronic fatigue (CF) was assessed according to the variables of Bell's score, age and gender. VDs in the superficial vascular plexus (SVP), intermediate capillary plexus (ICP) and deep capillary plexus (DCP) were analyzed, considering the repetitions (12 times). Seropositivity for autoantibodies targeting G protein-coupled receptors (GPCR-AAbs) was determined by an established cardiomyocyte bioassay. Taking account of the repetitions, a mixed model was performed to detect possible differences in the least square means between the different groups included in the analysis. An age effect in relation to VD was observed between patients and controls (p < 0.0001). Gender analysis showed that women with PCS showed lower VD levels in the SVP compared to male patients (p = 0.0015). The PCS patients showed significantly lower VDs in the ICP as compared to the controls (p = 0.0001 (CI: 0.32; 1)). Moreover, considering PCS patients, the mixed model revealed a significant difference between those with chronic fatigue (CF) and those without CF with respect to VDs in the SVP (p = 0.0033 (CI: −4.5; −0.92)). The model included variables of age, gender and Bell's score, representing a subjective marker for CF. Consequently, retinal microcirculation might serve as an objective biomarker in subjectively reported chronic fatigue in patients with PCS.

Applying machine learning to optical coherence tomography images for automated tissue classification in brain metastases.

PURPOSE: A precise resection of the entire tumor tissue during surgery for brain metastases is essential to reduce local recurrence. Conventional intraoperative imaging techniques all have limitations in detecting tumor remnants. Therefore, there is a need for innovative new imaging methods such as optical coherence tomography (OCT). The purpose of this study is to discriminate brain metastases from healthy brain tissue in an ex vivo setting by applying texture analysis and machine learning algorithms for tissue classification to OCT images. METHODS: Tumor and healthy tissue samples were collected during resection of brain metastases. Samples were imaged using OCT. Texture features were extracted from B-scans. Then, a machine learning algorithm using principal component analysis (PCA) and support vector machines (SVM) was applied to the OCT scans for classification. As a gold standard, an experienced pathologist examined the tissue samples histologically and determined the percentage of vital tumor, necrosis and healthy tissue of each sample. A total of 14.336 B-scans from 14 tissue samples were included in the classification analysis. RESULTS: We were able to discriminate vital tumor from healthy brain tissue with an accuracy of 95.75%. By comparing necrotic tissue and healthy tissue, a classification accuracy of 99.10% was obtained. A generalized classification between brain metastases (vital tumor and necrosis) and healthy tissue was achieved with an accuracy of 96.83%. CONCLUSIONS: An automated classification of brain metastases and healthy brain tissue is feasible using OCT imaging, extracted texture features and machine learning with PCA and SVM. The established approach can prospectively provide the surgeon with additional information about the tissue, thus optimizing the extent of tumor resection and minimizing the risk of local recurrences.

Correlation between degenerative spine disease and bone marrow density: a retrospective investigation.

BACKGROUND: Spondylosis leads to an overestimation of bone mineral density (BMD) with dual-energy x-ray absorptiometry (DXA) but not with quantitative computed tomography (QCT). The correlation between degenerative changes of the spine and QCT-BMD was therefore investigated for the first time. METHODS: One hundred thirty-four patients (66 female and 68 male) with a mean age of 49.0 ± 14.6 years (range: 19-88 years) who received a CT scan and QCT-BMD measurements of spine and hip were evaluated retrospectively. The occurrence and severity of spondylosis, osteochondrosis, and spondylarthrosis and the height of the vertebral bodies were assessed. RESULTS: A negative correlation was found between spinal BMD and number of spondylophytes (ρ = -0.35; p < 0.01), disc heights (r = -0.33; p < 0.01), number of discal air inclusions (ρ = -0.34; p < 0.01), the number of Schmorl nodules (ρ = -0.25; p < 0.01), the number (ρ = -0.219; p < 0.05) and the degree (ρ = -0.220; p < 0.05) of spondylarthrosis. Spinal and hip BMD correlated moderately, but the latter did not correlate with degenerative changes of the spine. In linear regression models age, osteochondrosis and spondylarthrosis were factors influencing spinal BMD. CONCLUSION: Degenerative spinal changes may be associated with reduced regional spinal mineralization. This knowledge could lead to a modification of treatment of degenerative spine disease with early treatment of osteopenia to prevent secondary fractures.

Decoupling of component diffusion in a glass-forming Zr(46.75)Ti(8.25)Cu(7.5)Ni(10)Be(27.5) melt far above the liquidus temperature.

We report (95)Zr and (57)Co radiotracer diffusivities and viscosity data in the equilibrium liquid state of a bulk metallic glass forming Zr(46.75)Ti(8.25)Cu(7.5)Ni(10)Be(27.5) melt (Vitreloy 4) far above the liquidus temperature T(l) that are not affected by convection, as evidenced via quasielastic neutron scattering. Zr diffusion is strongly decoupled from diffusion of the smaller components by more than a factor of 4 at T(l), although it obeys the Stokes-Einstein equation. The results suggest that, in the present Zr-based metallic glass forming systems, diffusion and viscous flow start to develop solidlike, i.e., energy-landscape-controlled, features already in the stable liquid state more than 300 K above the mode coupling temperature T(c).

Dynamic arrest in multicomponent glass-forming alloys.

We report radiotracer diffusivities in a Pd43Cu27Ni10P20 melt, presenting for the first time a complete set of data for all components over the whole relevant temperature range. While a vast decoupling of more than 4 orders of magnitude is observed between the diffusivity of Pd and of the smaller components, at the glass transition temperature Tg, the diffusivities of all components merge close to the critical temperature Tc of mode coupling theory. For Pd, the Stokes-Einstein relation holds in the whole range investigated encompassing more than 14 orders of magnitude suggesting the formation of a slow subsystem as a key to glass formation in systems with dynamic asymmetry.