World Neurosurg
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External Ventricular Drain (EVD) is a fundamental neurosurgical procedure that is commonly performed by junior neurosurgeons. Expedient, successful cannulation of the ventricles can be lifesaving. Yet, the free-hand technique of EVD insertion is associated with significant mal-positioning rates. This study aims to improve EVD placement by junior neurosurgeons with the aid of a customized 3D printed surgical guide. ⋯ For inexperienced surgeons, the 3D printed EVD guide can improve ventricular cannulation even in cases of altered ventricular anatomy. The benefit of 3D printing would also allow the guide to be widely adopted by other institutions worldwide.
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Intraventricular cavernous malformations (IVCs) are rare vascular lesions of the central nervous system. Surgical resection remains a challenging endeavor, with conventional microsurgical techniques associated with morbidity due to direct brain tissue manipulation. Neuroendoscopic approaches offer a minimally invasive alternative, though their efficacy and safety in treating IVCs remain underexplored. ⋯ Neuroendoscopic surgery offers several advantages in treating IVCs, including minimally invasive access, precise visualization, and reduced brain tissue manipulation. Our findings support the efficacy and safety of ETVA, underscoring its potential as a valuable therapeutic strategy for selected IVCs.
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Cerebrospinal fluid (CSF) leaks are a known complication of lumbar fusion surgery. There is a scarcity of literature describing the management of this complication. The aim of this study was to identify patients who are at risk of requiring further intervention for managing CSF leaks. ⋯ Spine surgeons should be aware of certain patient and procedure-specific characteristics that increase the risk of requiring an intervention for CSF leak management after lumbar fusion to improve patient outcomes.
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Deep learning enables precise hand tracking without the need for physical sensors, allowing for unsupervised quantitative evaluation of surgical motion and tasks. We quantitatively assessed the hand motions of experienced cerebrovascular neurosurgeons during simulated microvascular anastomosis using deep learning. We explored the extent to which surgical motion data differed among experts. ⋯ Hand tracking data showed similarities among experts, with low movements from baseline, minimal excess motion, and rhythmic suturing patterns. The data revealed unique patterns related to each expert's habits and techniques. The results showed that surgical motion can be correlated with hand motion and assessed using mathematical algorithms. We also demonstrated the feasibility and potential of deep learning-based motion detection to enhance surgical training.