Postoperative hemorrhage (POH) is a rare but serious complication of cranial neurosurgery, often resulting in neurological deterioration and necessitating urgent surgical intervention. Despite its clinical relevance, POH remains underreported and insufficiently understood. This study aimed to identify potential risk factors including perioperative variables and tumor-related characteristics associated with POH requiring surgical evacuation. A total of 1862 cranial tumor procedures were performed in our department over a 10-year period. Data on perioperative parameters and tumor characteristics were retrospectively collected and analyzed. Statistical analyses were conducted to assess associations of them to POH. Statistical analysis revealed several peri- and postoperative variables significantly associated with POH in univariate analyses. These included intraoperative blood loss (p = 0.012) and length of postoperative hospital stay (p = 0.016). Furthermore, the outcomes measured using the Glasgow Outcome Scale (p < 0.001) and the Karnofsky Performance Scale (p < 0.001) showed also statistical relevance as a result of postoperative bleeding in these patients. The findings suggest that specific perioperative factors particularly intraoperative blood loss are associated with an increased risk of POH after intracranial tumor surgery. Additionally, prolonged hospitalization and worsened functional outcomes were linked to the occurrence of postoperative hemorrhage. In contrast, tumor-specific characteristics and routine laboratory values showed no significant association with hemorrhagic complications in this cohort.

Background/Objectives: Postoperative pneumonia is a common complication in surgical patients. Despite its clinical significance, there is limited evidence regarding its occurrence following intracranial tumor resection, the most common procedure in neurosurgery. The objective of this study is to determine the incidence of postoperative pneumonia, to examine its association with length of hospital stay, and to identify potential risk factors. Methods: A retrospective cohort study was conducted on 1481 patients who underwent intracranial tumor resection in our department over a ten-year period, excluding the influence of anticoagulant or antiplatelet medications. Results: Of the 1481 patients included in this study, postoperative pneumonia occurred in 1.48% of cases. Smoking status (p = 0.014) and prolonged hospital stay (p = 0.011) emerged as significant risk factors in the univariate analysis for postoperative pneumonia in patients undergoing brain tumor resection. In contrast, demographic factors (age, sex, body mass index), pre-existing comorbidities (hypertension, diabetes, cardiovascular disease, chronic inflammatory conditions), and laboratory parameters did not show significant associations with the development of postoperative pulmonary infection. Conclusions: This study identified pre- and postoperative risk factors associated with pneumonia following craniotomy for intracranial tumors. These findings may provide a valuable framework for pre- und postoperative risk assessment and guide strategies to mitigate the occurrence of postoperative pneumonia.

Background/Objectives: Glioblastoma is the most common and aggressive primary malignant brain tumor in adults, characterized by infiltrative growth and poor prognosis. Achieving maximal resection without inducing neurological deficits remains a challenge in glioblastoma surgery. While 5-aminolevulinic acid-based fluorescence-guided surgery supports intraoperative tumor visualization, its reliability is limited by patient variability and weak fluorescence signals. This study proposes a machine learning framework to enhance fluorescence-guided surgery sensitivity by analyzing surgical microscope images at the pixel level. Methods: Fluorescence-mode neurosurgical microscope images of synthetic samples with known Protoporphyrin IX (PPIX) concentrations were used to train three classifiers (Support Vector Machine, Naïve Bayes, Neural Network) for pixel-wise fluorescence detection. In parallel, three contrastive-learning-based Variational Autoencoders (VAE, $\beta$ = 1, 2, 3) were evaluated for detecting weak fluorescence beyond visual perception. Additionally, a regression model was trained to relate pixel features to PPIX concentration. The best-performing VAE ($\beta$ = 1) was subsequently trained on real intraoperative data, and its detection sensitivity was compared to annotations from four experienced surgeons. Results: The proposed model achieved the highest detection rates on synthetic test data when calibrated for 99% specificity. Applied to real intraoperative images, the model revealed fluorescent areas substantially larger than those marked by experienced surgeons. In non-5-ALA control cases, minimal false positives were observed, indicating a specificity exceeding 99.9%. The regression model reliably quantified PPIX concentration in synthetic samples ($R^2=0.92$). Conclusions: By enabling more sensitive and objective fluorescence detection, this approach offers a valuable tool for improving surgical decision-making and facilitating safer, more extensive tumor resections.

Knee arthroplasty follow-up involves only a limited number of X-ray-based implant condition assessments at extended intervals. Polyethylene (PE) wear of knee endoprosthesis often progresses unnoticed until symptomatic adverse effects become apparent or implant failure occurs. A PE wear measuring concept, consisting of an implanted passive sensor and an extracorporeal readout unit, was previously presented by our group. This system is intended to enable patients to regularly check their knee implants’ condition at home. In this context, an appropriate product design for the readout unit is essential to enable the user to record correct measurements. An experimental investigation of the optimized positioning of the system's readout unit was conducted and the measurement data were analyzed. The findings were then implemented in a prototype for readout unit attachment. A sleeve with Velcro and a sewn-in readout unit has been fabricated. A cutout for the patella ensures intuitive correct alignment of the measurement system according to the experimental results. A hardware housing incorporates the electronics.

Background/Objectives: Postoperative intracerebral hematomas (POHs) are a common complication following brain tumor surgery and are typically associated with unfavorable outcomes. While extensive hemorrhages have been studied extensively, smaller, Non-Space-Occupying hemorrhages are frequently detected, yet their clinical relevance and associated risk factors remain insufficiently understood. This study aimed to identify predictive factors for the occurrence of Non-Space-Occupying postoperative cerebral hemorrhages in patients undergoing brain tumor resection. Methods: A total of 1481 patients without a history of anticoagulant or antiplatelet therapy underwent brain tumor surgery at our neurosurgical institute over a ten-year period. Non-Space-Occupying postoperative hemorrhages were diagnosed in 84 patients using cranial computed tomography (cCT) or magnetic resonance imaging (cMRI) performed after the tumor resection. Demographic data, pre-existing comorbidities, and tumor characteristics were collected and analyzed. Results: Non-Space-Occupying POHs occurred in 5.6% of patients. The most frequent tumor type associated with POHs was glioblastoma multiforme (N = 33; 39.3%), followed by metastatic lesions (N = 9; 10.7%) and benign primary intracranial neoplasms (N = 31; 38%). None of the affected patients exhibited new neurological deficits or signs of increased intracranial pressure. A multivariate analysis identified the tumor size as an independent risk factor for Non-Space-Occupying POHs (p = 0.002), with patient age emerging as the strongest predictor (p = 0.001). Conclusions: Non-Space-Occupying POHs after a brain tumor resection are significantly associated with the tumor size, an advanced patient age, and the presence of pre-existing liver disease. The recognition of these risk factors may facilitate targeted perioperative monitoring and guide postoperative management strategies.

Background: Postoperative hemorrhage (POH) is a rare yet serious complication of cranial surgery, potentially resulting in extended hospitalization, neurological impairment, or death. Existing predictive models often encompass diverse cranial pathologies, despite differing mechanisms of POH depending on the underlying condition. There is a lack of large-scale investigations focusing exclusively on POH following surgery for intracranial tumors. This study aimed to assess demographic variables—age, sex, and blood type—and pre-existing medical conditions as potential risk factors for POH in this specific context. Methods: A retrospective review was conducted on medical records of 1862 adult patients who underwent primary surgical resection of intracranial tumors. Univariate and multivariate analyses were applied to identify associations between POH and demographic or clinical characteristics. Results: POH, defined as postoperative hematoma necessitating surgical evacuation, was observed in 31 patients (1.7%). Univariate analysis revealed no statistically significant correlation between POH and demographic factors (age, sex) or pre-existing conditions such as hypertension, diabetes mellitus, cardiac disease, or liver dysfunction. Conclusions: The study found no evidence that demographic variables or pre-existing medical conditions independently contribute to the risk of POH following intracranial tumor resection in adults.