Background/Objectives: In recent years, numerous studies have been published on determining the WHO grade of central nervous system (CNS) tumors using machine learning algorithms. These studies are usually based on magnetic resonance imaging (MRI) and sometimes also on positron emission tomography (PET) images. To date, however, there are virtually no corresponding studies based on routinely generated computed tomography (CT) images. The aim of our proof-of-concept study is to investigate whether machine learning-based tumor diagnosis is also possible using CT images. Methods: We investigate the differentiability of histologically confirmed low-grade and high-grade gliomas. Three conventional machine learning algorithms and a neural net are tested. In addition, we analyze which of the common imaging methods (MRI or CT) appears to be best suited for the diagnostic question under investigation when machine learning algorithms are used. For this purpose, we compare our results based on CT images with numerous studies based on MRI scans. Results: Our best-performing model includes six features and is obtained using univariate analysis for feature preselection and a Naive Bayes approach for model construction. Using independent test data, this model yields a mean AUC of 0.903, a mean accuracy of 0.839, a mean sensitivity of 0.807 and a mean specificity of 0.864. Conclusions: Our results demonstrate that low-grade and high-grade gliomas can be differentiated with high accuracy using machine learning algorithms, not only based on the usual MRI scans, but also based on CT images. In the future, such CT-image-based models can help to further accelerate brain tumor diagnostics and to reduce the number of necessary biopsies.

Background: Our aim was to investigate the predictability of postoperative meningioma resection status based on clinical features. Methods: We examined 23 clinical features to assess their effectiveness in distinguishing gross total resections (GTR) from subtotal resections (STR). We analyzed whether GTR/STR cases are better predictable if the classification is based on the Simpson grading or the postoperative operative tumor volume (POTV). Results: Using a study cohort comprising a total of 157 patients, multivariate models for the preoperative prediction of GTR/STR outcome in relation to Simpson grading and POTV were developed and subsequently compared. Including only two clinical features, our models showed a notable discriminatory power in predicting postoperative resection status. Our final model, a straightforward decision tree applicable in daily clinical practice, achieved a mean AUC of 0.885, a mean accuracy of 0.866, a mean sensitivity of 0.889, and a mean specificity of 0.772 based on independent test data. Conclusions: Such models can be a valuable tool both for surgical planning and for early planning of postoperative treatment, e.g., for additional radiotherapy/radiosurgery, potentially required in case of subtotal resections.

Background/Objectives: Perimesencephalic subarachnoid hemorrhage (pmSAH) is generally considered to be a benign variant of spontaneous SAH. However, in rare cases, an underlying aneurysm may be present, altering both clinical management and prognosis. The aim of this study was to evaluate the prognostic impact of aneurysmal pathology in patients presenting with perimesencephalic hemorrhage, focusing on the occurrence of complications and functional outcomes. Methods: This single-center, retrospective study included 77 patients diagnosed with perimesencephalic hemorrhage between 2012 and 2022. Clinical and radiological data were extracted, including demographics, risk factors, complications (hydrocephalus, vasospasm, and delayed cerebral ischemia (DCI)), and outcome scores (Glasgow Outcome Scale (GOS) and modified Rankin scale (mRS) at discharge). Patients were divided into two groups based on the presence or absence of an aneurysm confirmed through digital subtraction angiography (DSA). Results: Of the 77 patients, 7 (9.1%) were found to have an aneurysm. While rates of complications such as hydrocephalus and DCI were higher in the aneurysm group, these differences did not reach statistical significance. However, patients with aneurysms had significantly worse functional outcomes, with higher mRS and lower GOS scores at discharge. Logistic regression confirmed the presence of aneurysms as an independent factor associated with poor outcomes (OR = 21.6; 95% CI: 1.00−467.3; p = 0.050), while other variables such as age, sex, and World Federation of Neurosurgical Societies (WFNS) score were not statistically significant. ROC analysis showed moderate discriminative power of aneurysm presence for poor outcomes (AUC = 0.72). Conclusions: The presence of an aneurysm, although rare in pmSAH, significantly worsens functional outcomes. These findings highlight the necessity of early and sensitive vascular diagnostics—particularly DSA—to reliably exclude aneurysms. Differentiating between aneurysmal and non-aneurysmal perimesencephalic bleeding is essential not only for clinical decision-making but also for optimizing resource allocation in neurocritical care.

Objective: The benign nature of perimesencephalic subarachnoid hemorrhage (pmSAH) can be challenged by the occurrence of complications. Given the limited prognostic value of established clinical parameters for the development of complications in patients with pmSAH, this study evaluates the potential of volumetric hemorrhage quantification for risk assessment and the evaluation of the clinical outcome. Material and Methods: In this retrospective single-center study, we analyzed all consecutive patients diagnosed with pmSAH between 2010 and 2023 at a tertiary care academic medical center in Germany. The volumetric quantification of the hemorrhage in cm³ was performed using non-contrast CT imaging. The occurrence of clinical complications, including hydrocephalus, vasospasm, and delayed cerebral ischemia (DCI), were assessed. Clinical outcomes were determined by the Glasgow Outcome Scale (GOS) at discharge. Multivariable logistic regression models were used to assess the correlation between quantified hemorrhage volumes and the occurrence of complications and clinical outcomes (GOS) controlled for other variables such as age, sex, cardiovascular risk factors, clinical symptoms, and the modified Fisher scale. Results: A total of 82 patients (58.5% male, 54.8 ± 12.1 years) were enrolled. The median World Federation of Neurosurgical Societies (WFNS) score for all patients at admission was 1.0 (IQR 1.0–1.0). During the clinical course, hydrocephalus occurred in 29%, vasospasm in 14.6%, and DCI in 8.5% of all patients. Hemorrhage volume quantification was found to be the strongest independent predictor for hydrocephalus (OR 1.28; 95% CI 1.02–1.61; p = 0.032) and vasospasm (OR 1.25; 95% CI 1.07–1.46; p = 0.007) and showed a high predictive accuracy in ROC analyses (AUC = 0.77 and 0.76, respectively). Conversely, neither clinical parameters nor the modified Fisher scale were associated with these complications. A higher hemorrhage volume was also significantly correlated with a worse functional outcome (GOS; β = –0.07, CI: −0.12–−0.02, p = 0.021). Conclusions: In patients with pmSAH, the volumetric quantification of hemorrhage may be an adequate prognostic parameter regarding the occurrence of hydrocephalus and vasospasm. In addition, the quantitative assessment of hemorrhage volumes was strongly associated with clinical outcomes in these patients. Despite the generally benign nature of pmSAH, this imaging biomarker could improve individualized clinical management strategies and inform about the risk for the occurrence of complications.

Objective: The insertion of venous catheters into supra-aortic vessels is a standard procedure in the treatment of a large number of diseases. Incorrect placement of venous catheters into and accidental perforation of arterial vessels is a rare but serious complication that can lead to severe bleeding, dissections, and strokes. Materials and Methods: We present a case of iatrogenic malposition of a Broviac catheter into the right vertebral artery and its successful treatment through stenting of the perforation site using a Walrus balloon catheter to achieve a secure treatment position and eventually cover the perforation site. Additionally, we conducted a systematic literature review on endovascular rescue procedures in inadvertent injuries of the supra-aortic arteries related to venous catheter placement. Results: A balloon guide catheter was used to achieve a secure treatment position for the deployment of a stent graft covering the perforation site, ensuring no significant arterial hemorrhage occurred during the removal of the incorrectly placed Broviac catheter. The review of the literature on endovascular rescue procedures for supra-aortic arterial vessel damage caused by venous catheter placement revealed that endovascular treatment has been successful in all reported cases of catheter-related supra-aortic arterial injury. Primary stent graft placement without additional actions was the most common treatment approach. Conclusions: In the treatment of iatrogenic injuries to the supra-aortic vessels, endovascular treatment strategies represent a safe, reliable, and generally recognized option and thus are used much more frequently than surgical procedures. Key point: In rare cases of accidental malposition of venous catheters into supra-aortic arterial vessels, endovascular insertion of a stent graft covering the perforation site using a balloon guide catheter can be a safe treatment option.