Bendok, Bernard R

BACKGROUND AND OBJECTIVES: The artery of Davidoff and Schechter (ADS) is a dural branch of the posterior cerebral artery, supplying the falcotentorial junction. It is not commonly depicted on angiography due to its small size; thus, its visibility is usually indicative of a pathology, such as a dural arteriovenous fistula (DAVF). Recognizing the ADS as a feeder could be vital in enhancing management success, and understanding its anatomy is important for preventing complications during embolization or microsurgery. We present a scoping review of DAVFs fed by the ADS followed by an illustrative case report encountered at our institution. METHODS: An extensive literature review was conducted using PubMed, Embase, Web of Science, Scopus, and Cochrane databases. The search included the keywords: “Davidoff,” “Schechter,” “Davidoff and Schechter,” “dural branch,” “tentorial branch,” “medial branch,” and “meningeal branch,” in combination with “arteriovenous fistula,” “posterior cerebral artery,” and “superior cerebellar artery.” Only articles published in English or Spanish were included, with no restriction on publication date. Case reports and series were further screened based on best relevance. Data extraction and synthesis were performed in accordance with Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines. RESULTS: A total of 16 articles describing 32 cases of DAVFs supplied by the ADS were identified. The most common onset was headache (43.8%), followed by altered mental status (21.2%). Most DAVFs were classified as high grade based on Borden/Cognard scales. Transarterial embolization was the most used treatment (81.3%), achieving complete occlusion in 76.9% of cases. Among patients with complete occlusion, approximately half experienced full resolution of symptoms. In a mean follow-up of 27.4 months (IQR: 30), 2 cases reported complications due to reflux of the embolic agent. CONCLUSION: A comprehensive understanding of the ADS's angioarchitecture is essential to take full advantage of this artery's features in the treatment, mitigating potential complications and optimizing patient outcomes.

BACKGROUND AND OBJECTIVES: While many trials of the last decade have shifted the paradigm of stroke care toward endovascular therapy, a lack of timely access to centers with neurointerventional capabilities for many patients has remained a significant barrier to care. Endovascular robotic systems are poised to address this need for expanded access through telerobotic procedures, while also benefiting clinical team safety and raising the possibility of improved procedural precision. METHODS: A telerobotic setup consisting of a magnetic field generator and a mechanical advancer was placed with a silicone vascular phantom in an interventional suite in Switzerland and connected by wireless internet to an operator console in Arizona. From the operator console, the neurosurgeon navigated a guidewire and aspiration catheter to simulated middle cerebral artery (MCA) (n = 10) and basilar artery (n = 10) clots in consecutive timed procedural trials in evaluation of system feasibility and operator learning curve. RESULTS: From over 5700 miles away, the neurosurgeon navigated an aspiration catheter to 10 MCA and 10 basilar artery simulated large vessel occlusions. Clot aspiration was attempted in 4 trials and successful in each. Endovascular navigational time over 10 procedural trials to the M1 segment of the MCA and 10 trials to the basilar artery were completed on average in 114 seconds (SD 44.4 seconds) and 134 seconds (SD 65.8 seconds), respectively. Sufficient operator mastery was demonstrated in 20 procedural iterations with an average 77% reduction in navigational time from aortic arch initial to final trials. CONCLUSION: To our knowledge, we present the first intercontinental aspiration thrombectomy in the preclinical setting in comparable time to the clinical practice and demonstrate the early potential of telerobotic navigation. A lack of haptic feedback did not pose a hindrance, and the potential for intuitive operation offers to drive future research and adoption of this telesurgery system.

BACKGROUND AND OBJECTIVES: Aneurysm risk prediction remains an imprecise science that places patients at risk for either over or undertreatment. Machine learning (ML) models may improve clinical practice by adding precision to risk assessment. This study aims to comprehensively assess the current landscape of ML applications in predicting the risk of aneurysm rupture and compare the performance with the widely used PHASES score. METHODS: A systematic review of PubMed, Scopus, and Web of Science was conducted. All studies using ML tools to predict the rupture risk of intracranial aneurysms were included. Meta-analysis was conducted with consideration to the ML algorithms and compared with the PHASES score. RESULTS: Thirty-six studies involving 22 462 patients were included in the final analysis. ML techniques, including 124 models using 25 algorithms, were employed. Among various ML models, while they had comparable diagnostic performance, deep learning exhibited a slightly better performance profile (sensitivity = 0.792, specificity = 0.788, and accuracy = 0.778 in external validation). Based on our analysis, ML, regardless of the algorithm, provides comparable sensitivity (0.743 vs 0.771, P = .60) and higher specificity (0.763 vs 0.507, P < .01) compared with the PHASES score. Consistently, pooling the area under the receiver operating characteristic curve (AUC) for 60 ML models and 5 PHASES score data, ML models exhibited higher AUC (0.84 vs 0.64, P < .01). Using hemodynamic parameters as input for models improved specificity ( P < .01) in the test sets without any significant changes in the sensitivity. The later improvement was not observed in the external validation sets. CONCLUSION: ML techniques have the potential to enhance the prediction of intracranial aneurysm rupture compared with traditional approaches, like the PHASES score. Incorporating hemodynamic parameters may further enhance the accuracy of ML models. Feature prospective studies are required to validate the utility of ML models for clinical integration.

Abstract Purpose: Monitoring disease progression in patients with high-grade gliomas (HGG) is challenging due to treatment-related changes in imaging and the requirement for neurosurgical intervention to obtain diagnostic tissue. DNA junctions in HGG often amplify oncogenes, making these DNA fragments potentially more abundant in blood than monoallelic mutations. In this study, we piloted a cell-free DNA approach for disease detection in the plasma of patients with HGG by leveraging patient-specific DNA junctions associated with oncogene amplifications. Experimental Design: Whole-genome sequencing of grade 3 or 4 isocitrate dehydrogenase–mutant or wild-type astrocytomas was utilized to identify amplified junctions. Individualized qPCR assays were developed using patient-specific primers designed for the amplified junction. ctDNA levels containing these junctions were measured in patient plasma samples. Results: Unique amplified junctions were evaluated by individualized semi-qPCR assays in presurgical plasma of 18 patients, 15 with tumor-associated focal amplifications and three without tumor-associated focal amplifications. high copy-number junctions were robustly detected in the plasma of 14 of 15 (93.3%) patients with amplified junctions and none of the controls. Changes in junction abundance correlated with disease trajectory in serial plasma samples from five patients, including increased abundance of amplified junctions preceding radiographic disease progression. Conclusions: In patients with grade 3 or 4 astrocytomas who had tumor-associated amplifications, patient-specific amplified junctions were successfully detected in assayed plasma from most patients. Longitudinal analysis of plasma samples correlated with disease trajectory, including cytoreduction and progression.