Metabolic and inflammatory parameters in relation to baseline characterization and treatment outcome in patients with prolactinoma: insights from a retrospective cohort study at a single tertiary center.

Background: Prolactinomas (PRLs) are prevalent pituitary adenomas associated with metabolic changes and increased cardiovascular morbidity. This study examined clinical, endocrine, metabolic, and inflammatory profiles in PRL patients, aiming to identify potential prognostic markers. Methods: The study comprised data from 59 PRL patients gathered in a registry at the University Hospital of Zurich. Diagnostic criteria included MRI findings and elevated serum prolactin levels. We assessed baseline and follow-up clinical demographics, metabolic markers, serum inflammation-based scores, and endocrine parameters. Treatment outcomes were evaluated based on prolactin normalization, tumor shrinkage, and cabergoline dosage. Results: The PRL cohort exhibited a higher prevalence of overweight/obesity, prediabetes/diabetes mellitus, and dyslipidemia compared to the general population. Significant correlations were found between PRL characteristics and BMI, HbA1c, and fT4 levels. Follow-up data indicated decreases in tumor size, tumor volume, prolactin levels, and LDL-cholesterol, alongside increases in fT4 and sex hormones levels. No significant associations were observed between baseline parameters and tumor shrinkage at follow-up. A positive association was noted between PRL size/volume and the time to achieve prolactin normalization, and a negative association with baseline fT4 levels. Conclusion: This study underscores the metabolic significance of PRL, with notable correlations between PRL parameters and metabolic indices. However, inflammatory markers were not significantly correlated with patient stratification or outcome prediction. These findings highlight the necessity for standardized follow-up protocols and further research into the metabolic pathogenesis in PRL patients.

Treatment outcomes and the role of the DES scheme in the appropriate treatment selection for high-grade dural arteriovenous fistulas.

OBJECTIVE: Endovascular and microsurgical treatment are viable options for the majority of Borden type III dural arteriovenous fistulas (dAVFs). The aim of this study was to examine treatment outcomes in a comparative analysis of endovascular and surgical treatment modalities for Borden type III fistulas and explore clinical implications of the DES scheme in selecting ideal candidates for surgical therapy. METHODS: Patients diagnosed with dAVFs with leptomeningeal venous drainage admitted to the Departments of Neurosurgery or Neuroradiology of the University Hospital Zurich between January 2014 and October 2021 were included in this study. Comprehensive patient data including demographics, clinical presentation, and dAVF characteristics, including established classifications, were collected. Treatment outcomes were assessed based on postinterventional angiography findings. In addition, treatment-related complications were assessed based on the Clavien-Dindo classification. RESULTS: Among all Borden type III dAVFs, 15 were initially treated endovascularly (60% complete occlusion rate) and 10 with microsurgical disconnection (90% complete occlusion rate) (p = 0.18). Subgroup analysis of dAVFs meeting the criteria for directness and exclusivity based on the DES scheme showed a 100% complete occlusion rate after microsurgical disconnection, whereas embolization achieved a complete occlusion rate of 60% (p = 0.06). There was no significant difference in the rate or severity of treatment-related complications between treatment modalities. CONCLUSIONS: This study suggests that microsurgical disconnection is a viable primary treatment modality for Borden type III dAVFs, particularly for dAVFs that meet the criteria of directness and exclusivity according to the DES scheme. The DES scheme demonstrates its relevance in selecting the most appropriate treatment strategy for affected patients.

Increased Risk of Recurrent Stroke in Symptomatic Large Vessel Disease With Impaired BOLD Cerebrovascular Reactivity.

BACKGROUND: Impaired cerebrovascular reactivity (CVR) has been correlated with recurrent ischemic stroke. However, for clinical purposes, most CVR techniques are rather complex, time-consuming, and lack validation for quantitative measurements. The recent adaptation of a standardized hypercapnic stimulus in combination with a blood-oxygenation-level-dependent (BOLD) magnetic resonance imaging signal as a surrogate for cerebral blood flow offers a potential universally comparable CVR assessment. We investigated the association between impaired BOLD-CVR and risk for recurrent ischemic events. METHODS: We conducted a retrospective analysis of patients with symptomatic cerebrovascular large vessel disease who had undergone a prospective hypercapnic-challenged BOLD-CVR protocol at a single tertiary stroke referral center between June 2014 and April 2020. These patients were followed up for recurrent acute ischemic events for up to 3 years. BOLD-CVR (%BOLD signal change per mm Hg CO2) was calculated on a voxel-by-voxel basis. Impaired BOLD-CVR of the affected (ipsilateral to the vascular pathology) hemisphere was defined as an average BOLD-CVR, falling 2 SD below the mean BOLD-CVR of the right hemisphere in a healthy age-matched reference cohort (n=20). Using a multivariate Cox proportional hazards model, the association between impaired BOLD-CVR and ischemic stroke recurrence was assessed and Kaplan-Meier survival curves to visualize the acute ischemic stroke event rate. RESULTS: Of 130 eligible patients, 28 experienced recurrent strokes (median, 85 days, interquartile range, 5-166 days). Risk factors associated with an increased recurrent stroke rate included impaired BOLD-CVR, a history of atrial fibrillation, and heart insufficiency. After adjusting for sex, age group, and atrial fibrillation, impaired BOLD-CVR exhibited a hazard ratio of 10.73 (95% CI, 4.14-27.81; P<0.001) for recurrent ischemic stroke. CONCLUSIONS: Among patients with symptomatic cerebrovascular large vessel disease, those exhibiting impaired BOLD-CVR in the affected hemisphere had a 10.7-fold higher risk of recurrent ischemic stroke events compared with individuals with nonimpaired BOLD-CVR.

Prognostic Role of Ventricular Size and Its Dynamics in Patients With Leptomeningeal Metastasis From Solid Tumors.

BACKGROUND AND OBJECTIVES: Hydrocephalus is a common radiologic sign in patients with leptomeningeal metastasis (LM) from solid tumors which can be assessed using the Evans index (EI). Here, we explored the prognostic value of ventricular size in LM. METHODS: We identified patients with LM from solid tumors by chart review at 3 academic hospitals to explore the prognostic associations of the EI at diagnosis, first follow-up, and progression. RESULTS: We included 113 patients. The median age was 58.3 years (interquartile range [IQR] 46.1-65.8), 41 patients (36%) were male, and 72 patients (64%) were female. The most frequent cancers were lung cancer (n = 39), breast cancer (n = 36), and melanoma (n = 23). The median EI at baseline was 0.28 (IQR 0.26-0.31); the EI value was 0.27 or more in 67 patients (59%) and 0.30 or more in 37 patients (33%). Among patients with MRI follow-up, the EI increased by 0.01 or more in 16 of 31 patients (52%), including 8 of 30 patients (30%) without and 10 of 17 patients (59%) with LM progression at first follow-up. At LM progression, an increase of EI of 0.01 or more was noted in 18 of 34 patients (53%). The median survival was 2.9 months (IQR 1-7.2). Patients with a baseline EI below 0.27 had a longer survival than those with an EI of 0.27 or more (5.3 months, IQR 2.4-10.8, vs 1.3 months, IQR 0.6-4.1) (HR 1.70, 95% CI 1.135-2.534, p = 0.0099). The median survival was 3.7 months (IQR 1.4-8.3) with an EI below 0.30 vs 1.8 months (IQR 0.8-4.1) with an EI of 0.30 or more (HR 1.40, 95% CI 0.935-1.243, p = 0.1113). Among patients with follow-up scans available, the overall survival was 9.4 months (IQR 5.6-21.0) for patients with stable or decreased EI at first follow-up as opposed to 5.6 months (IQR 2.5-10.5) for those with an increase in the EI (HR 1.08, 95% CI 0.937-1.243; p = 0.300). DISCUSSION: The EI at baseline is prognostic in LM. An increase of EI during follow-up may be associated with inferior LM progression-free survival. Independent validation cohorts with larger sample size and evaluation of confounding factors will help to better define the clinical utility of EI assessments in LM.

Whole Spine Segmentation Using Object Detection and Semantic Segmentation.

OBJECTIVE: Virtual and augmented reality have enjoyed increased attention in spine surgery. Preoperative planning, pedicle screw placement, and surgical training are among the most studied use cases. Identifying osseous structures is a key aspect of navigating a 3-dimensional virtual reconstruction. To automate the otherwise time-consuming process of labeling vertebrae on each slice individually, we propose a fully automated pipeline that automates segmentation on computed tomography (CT) and which can form the basis for further virtual or augmented reality application and radiomic analysis. METHODS: Based on a large public dataset of annotated vertebral CT scans, we first trained a YOLOv8m (You-Only-Look-Once algorithm, Version 8 and size medium) to detect each vertebra individually. On the then cropped images, a 2D-U-Net was developed and externally validated on 2 different public datasets. RESULTS: Two hundred fourteen CT scans (cervical, thoracic, or lumbar spine) were used for model training, and 40 scans were used for external validation. Vertebra recognition achieved a mAP50 (mean average precision with Jaccard threshold of 0.5) of over 0.84, and the segmentation algorithm attained a mean Dice score of 0.75 ± 0.14 at internal, 0.77 ± 0.12 and 0.82 ± 0.14 at external validation, respectively. CONCLUSION: We propose a 2-stage approach consisting of single vertebra labeling by an object detection algorithm followed by semantic segmentation. In our externally validated pilot study, we demonstrate robust performance for our object detection network in identifying individual vertebrae, as well as for our segmentation model in precisely delineating the bony structures.

TomoRay: Generating Synthetic Computed Tomography of the Spine From Biplanar Radiographs.

OBJECTIVE: Computed tomography (CT) imaging is a cornerstone in the assessment of patients with spinal trauma and in the planning of spinal interventions. However, CT studies are associated with logistical problems, acquisition costs, and radiation exposure. In this proof-of-concept study, the feasibility of generating synthetic spinal CT images using biplanar radiographs was explored. This could expand the potential applications of x-ray machines pre-, post-, and even intraoperatively. METHODS: A cohort of 209 patients who underwent spinal CT imaging from the VerSe2020 dataset was used to train the algorithm. The model was subsequently evaluated using an internal and external validation set containing 55 from the VerSe2020 dataset and a subset of 56 images from the CTSpine1K dataset, respectively. Digitally reconstructed radiographs served as input for training and evaluation of the 2-dimensional (2D)-to-3-dimentional (3D) generative adversarial model. Model performance was assessed using peak signal to noise ratio (PSNR), structural similarity index (SSIM), and cosine similarity (CS). RESULTS: At external validation, the developed model achieved a PSNR of 21.139 ± 1.018 dB (mean ± standard deviation). The SSIM and CS amounted to 0.947 ± 0.010 and 0.671 ± 0.691, respectively. CONCLUSION: Generating an artificial 3D output from 2D imaging is challenging, especially for spinal imaging, where x-rays are known to deliver insufficient information frequently. Although the synthetic CT scans derived from our model do not perfectly match their ground truth CT, our proof-of-concept study warrants further exploration of the potential of this technology.

Safety and Effectiveness of an Enhanced Recovery Protocol in Patients Undergoing Burr Hole Evacuation for Chronic Subdural Hematoma.

BACKGROUND AND OBJECTIVES: Enhanced recovery programs may be especially useful in patients with chronic subdural hematoma or hygroma (cSDH), who frequently exhibit frailty and multimorbidity. We aim to evaluate the real-world safety and effectiveness of an enhanced recovery protocol in this population. METHODS: From a prospective registry, burr hole evacuations for cSDH carried out under the protocol (including early thromboprophylaxis, no flat bed rest, early mobilization without drain clamping, and early resumption of antithrombotic medication) were extracted, along with those procedures carried out within the past year before protocol change. Propensity score-based matching was carried out. A range of clinical and imaging outcomes were analyzed, including modified Rankin Scale as effectiveness and Clavien-Dindo adverse event grading as safety primary end points. RESULTS: Per group, 91 procedures were analyzed. At discharge, there was no significant difference in the modified Rankin Scale among the standard and enhanced recovery groups (1 [1; 2] vs 1 [1; 3], P = .552), or in Clavien-Dindo adverse event grading classifications of adverse events (P = .282) or occurrence of any adverse events (15.4% vs 20.9%, P = .442). There were no significant differences in time to drain removal (2.00 [2.00; 2.00] vs 2.00 [1.25; 2.00] days, P = .058), time from procedure to discharge (4.0 [3.0; 6.0] vs 4.0 [3.0; 6.0] days, P = .201), or total hospital length of stay (6.0 [5.0; 9.0] vs 5.0 [4.0; 8.0] days, P = .113). All-cause mortality was similar in both groups (8.8% vs 4.4%, P = .289), as was discharge disposition (P = .192). Other clinical and imaging outcomes were similar too (all P > .05). CONCLUSION: In a matched cohort study comparing perioperative standard of care with a novel enhanced recovery protocol focusing on evidence-based drainage, mobilization, and thromboprophylaxis regimens as well as changes to the standardized reuptake of oral anticoagulants and antiaggregants, no differences in safety or effectiveness were observed after burr hole evacuation of cSDH.

NnU-Net versus mesh growing algorithm as a tool for the robust and timely segmentation of neurosurgical 3D images in contrast-enhanced T1 MRI scans.

PURPOSE: This study evaluates the nnU-Net for segmenting brain, skin, tumors, and ventricles in contrast-enhanced T1 (T1CE) images, benchmarking it against an established mesh growing algorithm (MGA). METHODS: We used 67 retrospectively collected annotated single-center T1CE brain scans for training models for brain, skin, tumor, and ventricle segmentation. An additional 32 scans from two centers were used test performance compared to that of the MGA. The performance was measured using the Dice-Sørensen coefficient (DSC), intersection over union (IoU), 95th percentile Hausdorff distance (HD95), and average symmetric surface distance (ASSD) metrics, with time to segment also compared. RESULTS: The nnU-Net models significantly outperformed the MGA (p < 0.0125) with a median brain segmentation DSC of 0.971 [95CI: 0.945-0.979], skin: 0.997 [95CI: 0.984-0.999], tumor: 0.926 [95CI: 0.508-0.968], and ventricles: 0.910 [95CI: 0.812-0.968]. Compared to the MGA's median DSC for brain: 0.936 [95CI: 0.890, 0.958], skin: 0.991 [95CI: 0.964, 0.996], tumor: 0.723 [95CI: 0.000-0.926], and ventricles: 0.856 [95CI: 0.216-0.916]. NnU-Net performance between centers did not significantly differ except for the skin segmentations Additionally, the nnU-Net models were faster (mean: 1139 s [95CI: 685.0-1616]) than the MGA (mean: 2851 s [95CI: 1482-6246]). CONCLUSIONS: The nnU-Net is a fast, reliable tool for creating automatic deep learning-based segmentation pipelines, reducing the need for extensive manual tuning and iteration. The models are able to achieve this performance despite a modestly sized training set. The ability to create high-quality segmentations in a short timespan can prove invaluable in neurosurgical settings.

A critical moment in machine learning in medicine: on reproducible and interpretable learning.

Over the past two decades, advances in computational power and data availability combined with increased accessibility to pre-trained models have led to an exponential rise in machine learning (ML) publications. While ML may have the potential to transform healthcare, this sharp increase in ML research output without focus on methodological rigor and standard reporting guidelines has fueled a reproducibility crisis. In addition, the rapidly growing complexity of these models compromises their interpretability, which currently impedes their successful and widespread clinical adoption. In medicine, where failure of such models may have severe implications for patients' health, the high requirements for accuracy, robustness, and interpretability confront ML researchers with a unique set of challenges. In this review, we discuss the semantics of reproducibility and interpretability, as well as related issues and challenges, and outline possible solutions to counteracting the "black box". To foster reproducibility, standard reporting guidelines need to be further developed and data or code sharing encouraged. Editors and reviewers may equally play a critical role by establishing high methodological standards and thus preventing the dissemination of low-quality ML publications. To foster interpretable learning, the use of simpler models more suitable for medical data can inform the clinician how results are generated based on input data. Model-agnostic explanation tools, sensitivity analysis, and hidden layer representations constitute further promising approaches to increase interpretability. Balancing model performance and interpretability are important to ensure clinical applicability. We have now reached a critical moment for ML in medicine, where addressing these issues and implementing appropriate solutions will be vital for the future evolution of the field.

Flow-augmentation STA-MCA bypass for acute and subacute ischemic stroke due to internal carotid artery occlusion and the role of advanced neuroimaging with hemodynamic and flow-measurement in the decision-making: preliminary data.

Background: A major clinical challenge is the adequate identification of patients with acute (<1 week) and subacute (1-6 weeks) ischemic stroke due to internal carotid artery (ICA) occlusion who could benefit from a surgical revascularization after a failure of endovascular and/or medical treatment. Recently, two novel quantitative imaging modalities have been introduced: (I) quantitative magnetic resonance angiography (qMRA) with non-invasive optimal vessel analysis (NOVA) for quantification of blood flow in major cerebral arteries (in mL/min), and (II) blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging to assess cerebrovascular reactivity (CVR). The aim of this study is to present our cohort of patients who underwent surgical revascularization in the acute and subacute phase of ischemic stroke as well as to demonstrate the importance of hemodynamic and flow assessment for the decision-making regarding surgical revascularization in patients with acute and subacute stroke and ICA-occlusion. Methods: Symptomatic patients with acute and subacute ischemic stroke because of persistent ICA-occlusion despite optimal medical/endovascular recanalization therapy who were treated at the Neuroscience Clinical Center of the University Hospital Zurich underwent both BOLD-CVR and qMRA-NOVA to study the hemodynamic and collateral vessel status. Patients selected for surgical revascularization according to our previously published flowchart were included in this prospective cohort study. Repeated NOVA and BOLD-CVR investigations were done after bypass surgery as follow up as well as clinical follow up. Continuous BOLD-CVR and qMRA-NOVA variables were compared using paired Student t-test. Results: Between May 2019 and September 2022, superficial temporal artery-middle cerebral artery (STA-MCA) bypass surgery was performed in 12 patients with acute and subacute stroke because of ICA-occlusion despite of optimal endovascular and/or medical treatment prior to the surgery. Impaired BOLD-CVR in the occluded vascular territory [MCA territory: ipsilateral vs. contralateral: -0.03±0.07 vs. 0.11±0.07 %BOLD/mmHgCO2, P<0.001] as well as reduced hemispheric flow with qMRA-NOVA (ipsilateral vs. contralateral: 228.00±54.62 vs. 384.50±70.99 mL/min, P=0.01) were measured indicating insufficient collateralization. Post-operative qMRA-NOVA showed improved hemispheric flow (via bypass) (pre-bypass vs. post-bypass: 236.60±76.45 vs. 334.20±131.33 mL/min, P=0.02) and the 3-month-follow-up with BOLD-CVR showed improved cerebral hemodynamics (MCA territory: pre-bypass vs. post-bypass: -0.01±0.05 vs. 0.06±0.03 %BOLD/mmHgCO2, P=0.02) in all patients studied. Conclusions: Quantitative assessment with BOLD-CVR and qMRA-NOVA allows us to evaluate the pre- and post-operative cerebral hemodynamics and collateral vessel status in patients with acute/subacute stroke due to ICA occlusion who may benefit from surgical revascularization after failure of endovascular/medical treatment.

Improved prognostic stratification of patients with isocitrate dehydrogenase-mutant astrocytoma.

Prognostic factors and standards of care for astrocytoma, isocitrate dehydrogenase (IDH)-mutant, CNS WHO grade 4, remain poorly defined. Here we sought to explore disease characteristics, prognostic markers, and outcome in patients with this newly defined tumor type. We determined molecular biomarkers and assembled clinical and outcome data in patients with IDH-mutant astrocytomas confirmed by central pathology review. Patients were identified in the German Glioma Network cohort study; additional cohorts of patients with CNS WHO grade 4 tumors were identified retrospectively at two sites. In total, 258 patients with IDH-mutant astrocytomas (114 CNS WHO grade 2, 73 CNS WHO grade 3, 71 CNS WHO grade 4) were studied. The median age at diagnosis was similar for all grades. Karnofsky performance status at diagnosis inversely correlated with CNS WHO grade (p < 0.001). Despite more intensive treatment upfront with higher grade, CNS WHO grade was strongly prognostic: median overall survival was not reached for grade 2 (median follow-up 10.4 years), 8.1 years (95% CI 5.4-10.8) for grade 3, and 4.7 years (95% CI 3.4-6.0) for grade 4. Among patients with CNS WHO grade 4 astrocytoma, median overall survival was 5.5 years (95% CI 4.3-6.7) without (n = 58) versus 1.8 years (95% CI 0-4.1) with (n = 12) homozygous CDKN2A deletion. Lower levels of global DNA methylation as detected by LINE-1 methylation analysis were strongly associated with CNS WHO grade 4 (p < 0.001) and poor outcome. MGMT promoter methylation status was not prognostic for overall survival. Histomolecular stratification based on CNS WHO grade, LINE-1 methylation level, and CDKN2A status revealed four subgroups of patients with significantly different outcomes. In conclusion, CNS WHO grade, global DNA methylation status, and CDKN2A homozygous deletion are prognostic in patients with IDH-mutant astrocytoma. Combination of these parameters allows for improved prediction of outcome. These data aid in designing upcoming trials using IDH inhibitors.

Intraoperative ultrasonography in microsurgical resection of vestibular schwannomas via retrosigmoid approach: surgical technique and proof-of-concept illustrative case series.

PURPOSE: Intraoperative ultrasonography (ioUS) is an established tool for the real-time intraoperative orientation and resection control in intra-axial oncological neurosurgery. Conversely, reports about its implementation in the resection of vestibular schwannomas (VS) are scarce. The aim of this study is to describe the role of ioUS in microsurgical resection of VS. METHODS: ioUS (Craniotomy Transducer N13C5, BK5000, B Freq 8 MHz, BK Medical, Burlington, MA, USA) is integrated into the surgical workflow according to a 4-step protocol (transdural preresection, intradural debulking control, intradural resection control, transdural postclosure). Illustrative cases of patients undergoing VS resection through a retrosigmoid approach with the use of ioUS are showed to illustrate advantages and pitfalls of the technique. RESULTS: ioUS allows clear transdural identification of the VS and its relationships with surgically relevant structures of the posterior fossa and of the cerebellopontine cistern prior to dural opening. Intradural ioUS reliably estimates the extent of tumor debulking, thereby helping in the choice of the right moment to start peripheral preparation and in the optimization of the extent of resection in those cases where subtotal resection is the ultimate goal of surgery. Transdural postclosure ioUS accurately depicts surgical situs. CONCLUSION: ioUS is a cost-effective, safe, and easy-to-use intraoperative adjunctive tool that can provide a significant assistance during VS surgery. It can potentially improve patient safety and reduce complication rates. Its efficacy on clinical outcomes, operative time, and complication rate should be validated in further studies.

Automated volumetric assessment of pituitary adenoma.

PURPOSE: Assessment of pituitary adenoma (PA) volume and extent of resection (EOR) through manual segmentation is time-consuming and likely suffers from poor interrater agreement, especially postoperatively. Automated tumor segmentation and volumetry by use of deep learning techniques may provide more objective and quick volumetry. METHODS: We developed an automated volumetry pipeline for pituitary adenoma. Preoperative and three-month postoperative T1-weighted, contrast-enhanced magnetic resonance imaging (MRI) with manual segmentations were used for model training. After adequate preprocessing, an ensemble of convolutional neural networks (CNNs) was trained and validated for preoperative and postoperative automated segmentation of tumor tissue. Generalization was evaluated on a separate holdout set. RESULTS: In total, 193 image sets were used for training and 20 were held out for validation. At validation using the holdout set, our models (preoperative / postoperative) demonstrated a median Dice score of 0.71 (0.27) / 0 (0), a mean Jaccard score of 0.53 ± 0.21/0.030 ± 0.085 and a mean 95th percentile Hausdorff distance of 3.89 ± 1.96./12.199 ± 6.684. Pearson's correlation coefficient for volume correlation was 0.85 / 0.22 and -0.14 for extent of resection. Gross total resection was detected with a sensitivity of 66.67% and specificity of 36.36%. CONCLUSIONS: Our volumetry pipeline demonstrated its ability to accurately segment pituitary adenomas. This is highly valuable for lesion detection and evaluation of progression of pituitary incidentalomas. Postoperatively, however, objective and precise detection of residual tumor remains less successful. Larger datasets, more diverse data, and more elaborate modeling could potentially improve performance.

COveRs to impRove EsthetiC ouTcome after Surgery for Chronic subdural hemAtoma by buRr hole trepanation-Results of a Swiss Single-Blinded, Randomized Controlled Trial.

BACKGROUND AND OBJECTIVES: Burr hole trepanation to evacuate chronic subdural hematoma (cSDH) results in bony skull defects that can lead to skin depressions. We intend to study the effect of burr hole covers to prevent skin depressions and improve the esthetic result. METHODS: In a randomized trial, we enrolled adult patients with symptomatic cSDH. Patients received burr hole trepanation with (intervention) vs without burr hole covers (control) in a 1:1 ratio. Patients requiring evacuation of bilateral cSDHs served as their internal control. Primary outcome was satisfaction with the esthetic result of the scar, measured from 0 (dissatisfied) to 10 (very satisfied) on the Esthetic Numeric Analog (ANA) scale at 90 days. Secondary outcomes included ANA scale, rates of skin depression, complications, as well as neurological, disability, and health-related quality of life outcomes until 12 months. RESULTS: We included 78 patients (55 with unilateral and 23 with bilateral cSDH; median age 78 years, 83% male) between 03/2019 and 05/2021, 50 trepanations for the intervention and 51 for the control group. In an intention-to-treat analysis, the ANA scale scores were 9.0 (intervention) and 8.5 (control arm) at 90 days (P = .498). At 12 months, the ANA scale scores were 9.0 and 8.0 for the intervention and control groups, respectively (P = .183). Skin depressions over the frontal burr hole were noted by 35% (intervention) and 63% (control) of patients at 90 days (P = .009) and by 35% and 79% (P < .001) at 12 months, respectively. There were no differences in complications, neurological, disability, and health-related quality of life outcomes. CONCLUSION: Satisfaction with the esthetic result of the scar was inherently high. This study does not show evidence for improvement on the ANA scale by applying a burr hole cover. The application of burr hole covers resulted in less skin depressions and did not negatively affect complication rates or outcomes.

Hemodynamic Failure Staging With Blood Oxygenation Level-Dependent Cerebrovascular Reactivity and Acetazolamide-Challenged (15O-)H2O-Positron Emission Tomography Across Individual Cerebrovascular Territories.

BACKGROUND: Staging of hemodynamic failure (HF) in symptomatic patients with cerebrovascular steno-occlusive disease is required to assess the risk of ischemic stroke. Since the gold standard positron emission tomography-based perfusion reserve is unsuitable as a routine clinical imaging tool, blood oxygenation level-dependent cerebrovascular reactivity (BOLD-CVR) with CO2 is a promising surrogate imaging approach. We investigated the accuracy of standardized BOLD-CVR to classify the extent of HF. METHODS AND RESULTS: Patients with symptomatic unilateral cerebrovascular steno-occlusive disease, who underwent both an acetazolamide challenge (15O-)H2O-positron emission tomography and BOLD-CVR examination, were included. HF staging of vascular territories was assessed using qualitative inspection of the positron emission tomography perfusion reserve images. The optimum BOLD-CVR cutoff points between HF stages 0-1-2 were determined by comparing the quantitative BOLD-CVR data to the qualitative (15O-)H2O-positron emission tomography classification using the 3-dimensional accuracy index to the randomly assigned training and test data sets with the following determination of a single cutoff for clinical application. In the 2-case scenario, classifying data points as HF 0 or 1-2 and HF 0-1 or 2, BOLD-CVR showed an accuracy of >0.7 for all vascular territories for HF 1 and HF 2 cutoff points. In particular, the middle cerebral artery territory had an accuracy of 0.79 for HF 1 and 0.83 for HF 2, whereas the anterior cerebral artery had an accuracy of 0.78 for HF 1 and 0.82 for HF 2. CONCLUSIONS: Standardized and clinically accessible BOLD-CVR examinations harbor sufficient data to provide specific cerebrovascular reactivity cutoff points for HF staging across individual vascular territories in symptomatic patients with unilateral cerebrovascular steno-occlusive disease.

Mixed Reality for Cranial Neurosurgical Planning: A Single-Center Applicability Study With the First 107 Subsequent Holograms.

BACKGROUND AND OBJECTIVES: Mixed reality (MxR) benefits neurosurgery by improving anatomic visualization, surgical planning and training. We aim to validate the usability of a dedicated certified system for this purpose. METHODS: All cases prepared with MxR in our center in 2022 were prospectively collected. Holographic rendering was achieved using an incorporated fully automatic algorithm in the MxR application, combined with contrast-based semiautomatic rendering and/or manual segmentation where necessary. Hologram segmentation times were documented. Visualization during surgical preparation (defined as the interval between finalized anesthesiological induction and sterile draping) was performed using MxR glasses and direct streaming to a side screen. Surgical preparation times were compared with a matched historical cohort of 2021. Modifications of the surgical approach after 3-dimensional (3D) visualization were noted. Usability was assessed by evaluating 7 neurosurgeons with more than 3 months of experience with the system using a Usefulness, Satisfaction and Ease of use (USE) questionnaire. RESULTS: One hundred-seven neurosurgical cases prepared with a 3D hologram were collected. Surgical indications were oncologic (63/107, 59%), cerebrovascular (27/107, 25%), and carotid endarterectomy (17/107, 16%). Mean hologram segmentation time was 39.4 ± 20.4 minutes. Average surgical preparation time was 48.0 ± 17.3 minutes for MxR cases vs 52 ± 17 minutes in the matched 2021 cohort without MxR (mean difference 4, 95% CI 1.7527-9.7527). Based on the 3D hologram, the surgical approach was modified in 3 cases. Good usability was found by 57% of the users. CONCLUSION: The perioperative use of 3D holograms improved direct anatomic visualization while not significantly increasing intraoperative surgical preparation time. Usability of the system was adequate. Further technological development is necessary to improve the automatic algorithms and reduce the preparation time by circumventing manual and semiautomatic segmentation. Future studies should focus on quantifying the potential benefits in teaching, training, and the impact on surgical and functional outcomes.

Safety of microneurosurgical interventions for superficial and deep-seated brain metastases: single-center cohort study of 637 consecutive cases.

PURPOSE: Microneurosurgical techniques have greatly improved over the past years due to the introduction of new technology and surgical concepts. To reevaluate the role of micro-neurosurgery in brain metastases (BM) resection in the era of new systemic and local treatment options, its safety profile needs to be reassessed. The aim of this study was to analyze the rate of adverse events (AEs) according to a systematic, comprehensive and reliably reproducible grading system after microneurosurgical BM resection in a large and modern microneurosurgical series with special emphasis on anatomical location. METHODS: Prospectively collected cases of BM resection between 2013 and 2022 were retrospectively analyzed. Number of AEs, defined as any deviations from the expected postoperative course according to Clavien-Dindo-Grade (CDG) were evaluated. Patient, surgical, and lesion characteristics, including exact anatomic tumor locations, were analyzed using uni- and multivariate logistic regression and survival analysis to identify predictive factors for AEs. RESULTS: We identified 664 eligible patients with lung cancer being the most common primary tumor (44%), followed by melanoma (25%) and breast cancer (11%). 29 patients (4%) underwent biopsy only whereas BM were resected in 637 (96%) of cases. The overall rate of AEs was 8% at discharge. However, severe AEs (≥ CDG 3a; requiring surgical intervention under local/general anesthesia or ICU treatment) occurred in only 1.9% (n = 12) of cases with a perioperative mortality of 0.6% (n = 4). Infratentorial tumor location (OR 5.46, 95% 2.31-13.8, p = .001), reoperation (OR 2.31, 95% 1.07-4.81, p = .033) and central region tumor location (OR 3.03, 95% 1.03-8.60) showed to be significant predictors in a multivariate analysis for major AEs (CDG ≥ 2 or new neurological deficits). Neither deep supratentorial nor central region tumors were associated with more major AEs compared to convexity lesions. CONCLUSIONS: Modern microneurosurgical resection can be considered an excellent option in the management of BM in terms of safety, as the overall rate of major AEs are very rare even in eloquent and deep-seated lesions.