OBJECTIVE:Modern neurosurgical training is increasingly challenged by declining surgical caseloads and reduced hands-on opportunities. While haptic simulators offer safe and repetitive practice, their adoption remains limited due to high costs, suboptimal realism, and lack of standardization. This study introduces a highly realistic, low-cost, and fully replicable microsurgical simulator for repetitive training in complex cranial procedures, including sylvian fissure and white matter dissections, aneurysm clipping, and resection of anterior skull base, frontal, and temporal lobe tumors. METHODS:The simulator was developed using high-resolution anatomical reconstructions, additive manufacturing, and carefully selected materials to replicate the visual and tactile properties of living brain tissue. The entire process relied solely on freely available software, and a detailed blueprint is provided to allow easy replication. Three groups of participants (n = 22) with varying levels of surgical experience tested and evaluated the simulator. Pathology- and procedure-specific objective assessment tools were used to evaluate participants' technical skills and assess the simulator's educational efficacy and transferability. RESULTS:The simulator was produced without specialized infrastructure and at minimal cost. Across all levels of experience, participants highly rated its realism, usability, and educational value (mean Likert score 4.9/5). Objective assessments demonstrated strong construct validity and significant improvements in technical performance, particularly among novice users, after short training intervals. Notably, the simulator allows direct comparison of different surgical approaches to the same pathology. CONCLUSIONS:This study demonstrates the feasibility of creating an anatomically accurate, affordable simulator for advanced neurosurgical training using only freeware and accessible materials. The simulator enables realistic, hands-on practice across a wide range of procedures, including patient-specific simulations and comparison of surgical strategies. This simulator marks a significant step toward integrating physical simulation-based training into standardized neurosurgical curricula, offering a practical and scalable solution to current training limitations.

BackgroundBrain metastases (BrMs) represent the most common intracranial tumors, which occur at a significantly higher incidence than primary brain neoplasms. Although some studies addressed the modulation of endothelial cells (ECs) and macrophages in lung and breast BrMs, it is still unclear how these cells are modulated in other BrM types.MethodsTumor cells (TCs) were isolated from human melanoma, lung and gastrointestinal (GI) BrM tissues, using individual patient isolates (n=2 per tissue origin) as the primary unit of inference. The paracrine effects of BrM-TCs on ECs and macrophages were examined in ex vivo models using BrM-TC-derived supernatants, HUVEC ECs, and peripheral blood monocytes isolated from healthy donors. The functional implications of the macrophages stimulated with BrM-TCs were investigated on autologous T-cells, focusing on T-cell proliferation.ResultsNone of the BrM-TCs had a direct effect on the ECs regarding MMP release, migration, proliferation and tubulogenesis. Interestingly, lung and GI but not melanoma BrM-TCs polarized macrophages into an M2-like phenotype, characterized by enhanced MMP9 release, increased Arg1 and CD206 expression, as well as elevated IL-6, IL-8, IL-10, and VEGF levels. Moreover, macrophages polarized by lung and GI but not melanoma BrM-TCs inhibited the proliferation of CD8 and CD4 T-cells.ConclusionThese findings indicate that lung and GI but not melanoma BrM-TCs polarize macrophages towards a tumor-promoting, M2-like phenotype. Although the direct effects of BrM-TCs on ECs remain to be further elucidated, our results highlight the need for further comparative studies on BrMs, with particular focus on their histological origins.

To evaluate 2-year longitudinal patient-reported outcomes from a multisite, prospective observational study involving a real-world German cohort with mechanical chronic low back pain (CLBP) implanted with restorative neurostimulation. Patients with refractory, predominantly nociceptive, mechanical CLBP associated with lumbar multifidus dysfunction (N=87) consented to undergo restorative neurostimulation therapy implantation through five German clinics. Outcomes measures for pain (Numeric Pain Rating Scale), disability (Oswestry Disability Index-ODI), and quality of life (Euroqol’s EQ-5D) were collected at 90 and 180 days, one year, and two years from therapy activation. The painDETECT scale assessed the likelihood of mixed pain presentation. Sub-cohorts of painDETECT scores ≥19 (High) and <19 (Low) were compared on outcomes to assess mixed pain response. Among patients with complete (n=74) and imputed data, all outcomes improved significantly at two years. Over 75

Background/Objectives: Delayed cerebral ischemia (DCI) is a major cause of poor outcome after aneurysmal subarachnoid hemorrhage (aSAH). Beyond large-vessel vasospasm, DCI reflects a systemic, multifactorial process involving inflammation, hematologic dysregulation, and organ dysfunction. Stroke-associated pneumonia (SAP), a frequent aSAH complication linked to stroke-induced immunodepression, may aggravate secondary ischemic injury. Unlike prior studies focusing on classical predictors alone, we included pneumonia and longitudinal respiratory parameters alongside inflammatory, hematologic, and renal markers. Using machine learning, this study aimed to identify predictors of DCI and functional outcome from routinely collected intensive care data. Methods: In this retrospective single-center study, 182 aSAH patients treated in a neurosurgical intensive care unit were included. Clinical data, SAP status, and longitudinal inflammatory, hematologic, renal, and respiratory parameters were extracted. DCI and functional outcome were assessed. Continuous variables were summarized as minimum, maximum, and mean values. Supervised machine learning models combining 12 feature selection methods and 12 classifiers were trained using five-fold cross-validation and evaluated by accuracy, F1-score, and AUC. Results: DCI occurred in 22% of patients, and SAP in 27%. The machine learning models achieved a mean accuracy of 59.7% (F1-score 58.8%, AUC 59.7%) for DCI prediction. No single dominant feature emerged; predictive patterns included leukocyte counts, CRP, erythrocyte indices, platelet variability, renal function, and oxygenation metrics. Functional outcome prediction performed moderately better (mean AUC 65.7%) and shared overlapping predictors. Conclusions: DCI reflects systemic instability in aSAH, with longitudinal inflammatory and respiratory variability outperforming static thresholds. Dynamic risk stratification may enable earlier detection of deterioration, supporting future time-series modeling and external validation.

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: Holocord astrocytomas are exceptionally rare intramedullary tumors, especially in adults, and often present with extensive longitudinal growth. Because only a small number of cases have been described, management strategies remain insufficiently defined. This report presents an adult patient treated with a staged surgical approach and provides an updated review of the literature. Methods: A 31-year-old male presented with progressive paraparesis, sensory deficits, and sphincter dysfunction. MRI demonstrated an intramedullary tumor extending from T3 to the conus medullaris. The patient underwent a planned two-stage resection with intraoperative neurophysiological monitoring. Histopathological and DNA-methylation analyses were performed. Additionally, a systematic review of previously reported holocord astrocytoma cases was conducted. Results: The two-stage surgical strategy enabled extensive debulking across multiple spinal segments while preserving neurological function. The patient demonstrated marked postoperative improvement, including restoration of sphincter control, improved motor function, and better mobility. Histopathological analyses confirmed a high-grade astrocytoma with piloid features. The literature review identified 28 previously reported cases, including only 5 in adults. Reported neurological outcomes across adult cases are variable, reflecting the heterogeneity and rarity of this tumor entity. Conclusions: Holocord astrocytomas in adults are extremely rare and pose particular diagnostic and therapeutic challenges. This case demonstrates that a carefully planned, staged surgical approach can achieve meaningful neurological recovery, even in patients presenting with severe preoperative deficits. The report expands the limited body of evidence available for adult holocord astrocytomas and may support future management strategies.

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/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, β = 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 (β = 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 (R2=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.

Background/Objectives: Aneurysmal subarachnoid hemorrhage (aSAH) carries high morbidity and mortality, with delayed cerebral ischemia (DCI) as a major secondary complication. Although infection has increasingly been implicated in DCI pathogenesis, the role of central nervous system (CNS) infection remains unclear. We evaluated CNS infection-related parameters for predicting DCI and functional outcome after aSAH using machine learning. Methods: This retrospective single-center study included 191 patients with confirmed aSAH treated in the intensive care unit between 2019 and 2024. Demographic, clinical, radiographic, treatment-related, microbiological, cerebrospinal fluid (CSF), and longitudinal laboratory data were extracted from electronic records. DCI was analyzed as a binary outcome, and discharge functional outcome was dichotomized using the modified Rankin Scale (0-2 vs. 3-6). Twelve feature selection methods and twelve classifiers were evaluated using five-fold cross-validation. Results: For DCI prediction, the models achieved a mean accuracy of 0.96, F1-score of 0.96, and AUC of 0.98. Key predictors included antibiotic therapy, aneurysm treatment modality, history of thrombosis, and EVD revision, along with mean albumin, red cell distribution width, INR, minimum aspartate aminotransferase, and CSF glucose, lactate, nucleated cell count, and cellular debris. For functional outcome prediction, accuracy was 0.948, F1-score 0.95, and AUC was 0.97. Predictors comprised cerebral vasospasm, number of spasmolysis procedures, pre-admission anticoagulation, CSF pathogen detection and type, aPTT, fibrinogen, aspartate aminotransferase, lactate dehydrogenase, and CSF mononuclear cell proportion, leukocyte count, and glucose concentration. Conclusions: Machine learning models integrating clinical, systemic, and CSF-derived parameters demonstrated excellent performance in predicting both DCI and functional outcome after aSAH. The identified predictors highlight the importance of the neurocritical care course, including infection-related and thromboinflammatory processes, and extend beyond traditional vasospasm-centered paradigms. These findings may inform risk stratification, although the temporal relationship between several predictors and outcome onset means the models should be regarded as hypothesis-generating rather than tools for early clinical prediction.

Background:Brain metastases from colorectal cancer (CRC) are associated with poor survival and limited treatment options. As immunomodulatory therapies gain relevance, a deeper understanding of the tumor microenvironment (TME) in this setting is needed. Tumor-associated macrophages (TAMs) are pivotal regulators of tumor immunity, yet their spatial organization, polarization, and relationship to PD-L1-mediated immune checkpoint regulation in CRC brain metastases remain poorly defined. We therefore characterized the compartment-specific architecture and functional orientation of TAMs in brain metastases and matched primary CRCs. Methods:Immunohistochemical analyses of CD68 (pan-macrophages), CD86 (M1-associated), CD163 (M2-associated), and PD-L1 were performed on tissue microarrays from tumor specimens of 50 patients with CRC brain metastases, including 31 matched primary tumor-brain metastasis pairs. Compartment-specific TAM densities and PD-L1 expression were quantified to assess intra- and intertumoral heterogeneity and correlated with clinicopathological parameters and clinical outcomes. Results:Both primary CRCs and brain metastases exhibited macrophage-rich TMEs characterized by stromal predominance and an M2-skewed polarization. Compared with matched primary tumors, brain metastases showed a significant stromal enrichment of CD163+ TAMs. Dexamethasone treatment was associated with reduced densities of CD86+ TAMs in brain metastases. PD-L1 expression was predominantly confined to immune cells and displayed marked intra- and intertumoral heterogeneity, with frequent discordance between matched primary tumors and brain metastases, including recurrent lesions. In primary CRCs, high densities of CD68+ TAMs at the invasive front were associated with shortened brain metastasis-free survival, whereas neither TAM infiltration nor PD-L1 expression correlated with overall survival. Conclusion:CRC brain metastases exhibit a distinct, stroma-dominated and M2-polarized TME, consistent with site-specific enrichment of protumoral TAM phenotypes within the cerebral niche. This may reflect advanced disease biology, immunological adaptation to the brain microenvironment, or therapy- and selection-driven immune remodeling during metastatic progression. The association between dexamethasone treatment and reduced M1-associated TAM infiltration suggests therapy-related modulation of antitumoral immune activity, with potential implications for perioperative management. The heterogeneity and frequent discordance of PD-L1 expression highlight its dynamic regulation and support individualized assessment of metastatic lesions prior to immunotherapy. Collectively, these findings support site-specific immune profiling and identify TAMs as promising therapeutic targets within the TME of CRC brain metastases.

Preclinical studies and data from other cancers suggest that inhibition of the Hedgehog (Hh) pathway also has antiproliferative effects on glioma cells. A key component of this pathway is the Smoothened (SMO) protein, which is expressed in high-grade gliomas. Itraconazole (ITRA), a widely used antifungal agent, inhibits SMO, the PI3K/AKT/mTOR pathway, and the VEGF/VEGFR-2 axis—both of which are critical for GBM progression and angiogenesis. This protocol describes a prospective, single-center, dose-escalation phase I study with the classical 3 + 3 design in order to determine the MTD of ITRA. The study enrolls patients with a newly histologically confirmed diagnosis of GBM, without previous treatment except surgery. They will be treated with standard RT schedule (60 Gy in 30 fractions) with concurrent TMZ 75 mg/m2 and ITRA 2 × 100 mg, 200 mg, or 300 mg daily. The primary endpoint is to determine the MTD of ITRA given concurrently with RT + TMZ. Secondary endpoints include safety and tolerability of ITRA, overall survival (OS), progression-free survival (PFS), overall objective response rate, use of corticosteroids, treatment compliance, and health-related quality of life (EORTC QLQ-C30 and BN20). Participants will be monitored for one week post-treatment. All relevant statistics will be primarily descriptive.

High-fidelity simulation models are crucial for advancing neurosurgical training, particularly for complex skull base pathologies such as sphenoid wing meningiomas. This study introduces and validates a novel, cost-effective 3D-printed simulator specifically designed for sphenoid wing meningioma resection. A key innovation of this model is the integration of shear wave elastography (SWE) to enable objective biomechanical validation of tumor-mimicking materials. A patient-specific skull model was created using fused deposition modeling (FDM) 3D printing and paired with custom-molded tumor replicas. In a material validation substudy, 14 tumors made from seven candidate materials were assessed through SWE-based elasticity measurements and blinded evaluations by experienced neurosurgeons, focusing on tactile feedback, anatomical resemblance, and microsurgical handling. The most suitable material was used for subsequent training simulations involving final-year medical students, neurosurgical residents, and an expert surgeon. Surgical performance was objectively measured using the OSAMS scoring system, complemented by subjective participant surveys across three simulation rounds. SWE identified significant differences in elasticity among materials, enabling classification into soft, medium, and firm consistencies. A 10% cake glaze formulation demonstrated the highest surgical realism and mechanical similarity to real tumor tissue. Participants-especially novices-showed significant improvement in OSAMS scores across simulations, alongside a strong inverse correlation between OSAMS score and simulation time. Subjective evaluations confirmed the simulator's high realism, educational value, and motivational impact. This study presents a validated, anatomically precise, and elastographically characterized simulator for sphenoid wing meningioma surgery. By combining affordable 3D printing with SWE-guided material selection, the model offers a reproducible platform for neurosurgical training with high educational and biomechanical fidelity. Its modular design and low cost make it well-suited for widespread academic implementation.

Small intracranial aneurysms (SIAs) (<5 mm) are increasingly detected due to advanced imaging, but predicting rupture risk remains challenging. Rupture, though rare, can cause devastating subarachnoid hemorrhage. This study analyzed 141 SIAs (101 unruptured, 40 ruptured) using semi-automatic morphological analysis and high-resolution, image-based blood flow simulations from 3D rotational angiography. Advanced morphological and hemodynamic parameters were extracted, with clustering applied to address multicollinearity. Univariate logistic regression identified cluster representatives, and forward selection highlighted the maximum height, Neck inflow rate, and Non-sphericity index as rupture predictors, though only the latter two were significant. Clinical variables like age, sex, and comorbidities were also assessed but failed to predict rupture risk. The full model showed overfitting, with a pseudo-R-2 of 0.142 on the training set but only 0.032 on the test set. A simplified model using just Neck inflow rate and Non-sphericity index performed similarly poorly (pseudo-R-2 of 0.034). Multiple machine learning classifiers were evaluated, with similar performance across models, supporting the model-independence of the results. Overall, neither morphological, hemodynamic, nor clinical variables reliably predicted rupture risk, highlighting the limitations of current methods and underscoring the need for prospective studies and multimodal approaches that integrate imaging biomarkers and compare small and large aneurysms for better risk stratification.

BACKGROUND AND OBJECTIVES:The training of cerebrovascular neurosurgeons faces significant challenges, particularly due to the decreasing volume of aneurysm clipping procedures. Traditional training methods rely heavily on clinical case availability, which limits skill development. This study aimed to implement and validate a Microsurgical Aneurysm Training Simulator (MATS) that offers a comprehensive, realistic, and cost-effective solution for neurosurgical training. METHODS:MATS was designed using semiautomated algorithms and additive manufacturing to replicate a bifurcation aneurysm of the middle cerebral artery. The simulator includes a pulsatile perfusion system and is compatible with indocyanine-green angiography. The simulation was evaluated by medical students, residents, and experienced neurosurgeons through face, content, and construct validity assessments. Performance was measured using a modified Objective Structured Assessment of Aneurysm Clipping Skills. RESULTS:MATS demonstrated high face and content validity, particularly in replicating the visual and procedural aspects of aneurysm clipping. Participants across all experience levels showed significant improvements in modified Objective Structured Assessment of Aneurysm Clipping Skills scores, with medical students displaying the most pronounced learning curve. The simulators compatibility with indocyanine green angiography was confirmed, though limitations were noted in replicating physiological perfusion pressures and the visual impact of subarachnoid hemorrhage during aneurysm rupture simulations. CONCLUSION:MATS is a validated, cost-effective, and reproducible tool that significantly enhances neurosurgical training by improving technical skills, especially in inexperienced participants. While the simulator effectively mimics key aspects of aneurysm surgery, further research is needed to assess its predictive validity and its potential impact on actual surgical outcomes.

OBJECTIVE: To investigate age-related morphological changes of the Sylvian fissure (SF) and their implications for neurosurgical procedures. METHODS: A cohort of 150 individuals across groups 10-20, 40-50, and 80-90 years was analyzed Brainlab software for 3-dimensional visualization volumetric analysis of the SF and various brain regions. compared SF volumes between age groups and gated dynamic changes in SF configuration over Correlation analyses were performed to identify rophy in specific brain regions affects the SF volume configuration. RESULTS: Atrophy was evident in all measured of the brain. The frontoparietal lobe underwent the gest atrophy, while the occipital lobe showed the Each age group exhibited a consistent distribution volumes, although a marginal decrease in frontoparietal lobe proportion was observed in the groups of higher The annual atrophy rate in the frontoparietal and lobes was steady. Additionally, ventricular expansion, which may influence white matter atrophy correlated with age. A consistent increase in SF volume relation to the intracranial volume was observed across age groups, with a notable increase in SF volume patients. This expansion, especially at the superior point, might be influenced by gravity, elasticity, and lobe torque. CONCLUSIONS: Our investigation highlights the cance of age-dependent changes in SF volume configuration due to brain atrophy throughout life. changes, influenced by physical factors, underscore need for tailored surgical approaches. Additionally, pathologies affecting volume could significantly configuration.

Background and Objectives: Realistic surgical simulation models are essential for neurosurgical training, particularly in glioma resection. We developed a patient-specific simulation model designed for fluorescence-guided glioma resection, providing an anatomically accurate and reusable platform for surgical education. While insular gliomas were used as an example, the model can be adapted to simulate gliomas in other brain regions, making it a versatile training tool. Methods: Using open-source 3D software, we created a digitally reconstructed skull, brain, and cerebral vessels, including a fluorescent insular glioma. The model was produced through additive manufacturing and designed with input from neurosurgeons to ensure a realistic and reusable representation of the Sylvian fissure and bone structures. The simulator’s educational effectiveness and usability were evaluated by two senior physicians, four assistant physicians, and six medical students using actual microsurgical instruments. Assessments were based on subjective and objective criteria. Results: Subjective evaluations, using a 5-point Likert scale, showed high face and content validity. Objective measures demonstrated strong construct validity, accurately reflecting the participant’s skills. Medical students and resident neurosurgeons showed marked improvement in their learning curve over three attempts, with progressive improvement in performance. Conclusions: This simulation model addresses advanced neurosurgical training needs by providing a highly realistic, cost- effective, and adaptable platform for fluorescence-guided glioma resection. Its effectiveness in enhancing surgical skills suggests significant potential for broader integration into neurosurgical training programs. Further studies are warranted to explore its applications in different glioma localizations and training settings.

Background MRI diffusion measures have been shown to be valuable imaging tools for assessing neuronal degeneration in vivo. In idiopathic Parkinson's disease, diffusion measures of mesencephalic nuclei appeared to correlate with disease manifestations. However, large selective cohorts are lacking to define the clinical relevance of such potential MRI biomarkers. Method This study investigates the relevance of 3 Tesla diffusion MRI of the subthalamic nucleus (STN) as a potential imaging biomarker. Experts in deep brain stimulation manually segmented the STN on T2-weighted 3 T MRI scans to create templates for measuring mean diffusivity and fractional anisotropy on aligned diffusion-weighted MRI scans. Results Demographic data, including age, sex, handedness, and specifications of neurological symptoms such as motor deficit severity, were collected using the Unified Parkinson’s Disease Rating Scale in 130 patients at disease onset and progression. Despite a homogeneous study cohort no statistically significant correlations were found between local diffusion measures of the STN and contralateral clinical parameters. Conclusion Unlike previous studies that suggested potential correlations between mesencephalic diffusion measures and disease manifestations, this study did not confirm such associations for the subthalamic nucleus at 3 T MRI in a large and homogeneous patient cohort. In the future research might focus on patients in earlier stages of the disease and employ higher field strength MRIs with increased spatial resolution to investigate the clinical relevance of MRI diffusion measures of the STN region in Parkinson's disease.

Background and Objectives: The anterior communicating artery is a common location for intracranial aneurysms. Anterior communicating artery aneurysms (AcomA) pose a significant risk of rupture. Treatment options include microsurgical clipping and endovascular techniques, but the optimal approach remains controversial. This study aims to compare the outcomes of these two treatment modalities in a single-center patient cohort using a comprehensive matching process based on clinical and morphological parameters. Materials and Methods: A retrospective analysis was conducted on 1026 patients with 1496 intracranial aneurysms treated between 2000 and 2018. After excluding cases lacking 3D angiography or aneurysms in other locations or without treatment, 140 AcomA were selected. The study matched 24 surgically treated AcomA cases with 116 endovascularly treated cases based on 21 morphological and clinical criteria, including age, sex, Hunt and Hess score, and Fisher grade. Results: The microsurgical clipping group demonstrated a significantly higher rate of complete aneurysm occlusion compared to the endovascular group (p = 0.007). However, this was associated with a higher incidence of postoperative ischemic complications in the surgical group (13 out of 24 cases) compared to the endovascular group (2 out of 116 cases). Despite these complications, no significant differences were found in clinical outcomes at discharge or follow-up, as measured by the modified Rankin Scale (p > 0.999). Both groups had comparable rates of hydrocephalus, vasospasm, and delayed cerebral ischemia. Conclusions: Microsurgical clipping resulted in higher aneurysm occlusion rates but carried an increased risk of ischemic complications compared to endovascular treatment. Clinical outcomes were comparable between the two modalities, suggesting that treatment decisions should be individualized based on aneurysm characteristics and patient factors. Further prospective studies are warranted to optimize treatment strategies for AcomA.