暂无摘要。

This article provides a nuanced exploration of the state and exigencies of neurosurgical training in sub-Saharan Africa (SSA), viewed through the discerning lens of a medical student. The region has a pronounced scarcity of neurosurgical services, further compounded by sociocultural intricacies and infrastructural inadequacies, resulting in elevated mortality and morbidity rates. The insufficiency of neurosurgeons, facilities, and training centers, particularly in remote areas, exacerbates this predicament. The imperative to fortify neurosurgical training programs is underscored, necessitating a multifaceted approach inclusive of international collaborations and innovative strategies. The challenges impeding neurosurgical training program implementation range from constrained infrastructure to faculty shortages and financial constraints. Recommendations encompass infrastructural investments, faculty development initiatives, and augmented community engagement. An exploration of neurosurgical training programs across diverse African regions reveals commendable strides and imminent deficits, warranting heightened international collaboration. Furthermore, technological innovations, including virtual reality, robotics, and artificial intelligence, are posited as transformative conduits for augmenting neurosurgical training in SSA. The article concludes with a sagacious compendium of recommendations, encompassing standardized curricula, mentorship paradigms, and stringent evaluation mechanisms, all combining efficaciously fortifying neurosurgical insight in SSA and producing transformative improvements in healthcare outcomes.

BACKGROUND: Endoscopic surgery has shown promise in treating Spontaneous Intracerebral Hemorrhage (sICH), but its adoption in county-level hospitals has been hindered by the high level of surgical expertise required.
METHODS: In this retrospective study at a county hospital, we utilized a Cumulative Sum (CUSUM) control chart to visualize the learning curve for two neurosurgeons. We compared patient outcomes in the learning and proficient phases, and compared them with expected outcomes based on ICH score and ICH functional outcome score, respectively.
RESULTS: The learning curve peaked at the 12th case for NS1 and the 8th case for NS2, signifying the transition to the proficient stage. This stage saw reductions in operation time, blood loss, rates of evacuation < 90 %, rebleeding rates, intensive care unit stay, hospital stay, and overall costs for both neurosurgeons. In the learning stage, 6 deaths occurred within 30 days, less than the 10.66 predicted by the ICH score. In the proficient stage, 3 deaths occurred, less than the 15.88 predicted. In intermediate and high-risk patients by the ICH functional outcome score, the proficient stage had fewer patients with an mRS ≥ 3 at three months than the learning stage (23.8 % vs. 69.2 %, P = 0.024; 40 % vs. 80 %, P = 0.360). Micromanipulating bipolar precision hemostasis and aspiration devices in the endoport\'s channels sped up the transition from learning to proficient.
CONCLUSIONS: The data shows a learning curve, with better surgical outcomes as surgeons gain proficiency. This suggests cost benefits of surgical proficiency and the need for ongoing surgical education and training in county hospitals.

Mixed-reality simulation is an emerging tool for creating anatomical models for preoperative planning. Its use in neurosurgical training (NT) has been limited because of the difficulty in real-time interactive teaching. This study describes the development of a patient-specific, interactive mixed-reality NT system. The authors took cases of intracranial tumor resection or neurovascular compression (NVC) as examples to verify the technical feasibility and efficacy of the mixed-reality NT system for residents\' training and preoperative planning.
This study prospectively enrolled 40 patients who suffered from trigeminal neuralgia, hemifacial spasms, or intracranial tumors. The authors used a series of software programs to process the multimodal imaging data, followed by uploading the holographic models online. They used a HoloLens or a standard iOS device to download and display the holographic models for training. Ten neurosurgical residents with different levels of surgical experience were trained with this mixed-reality NT system. Change in surgical strategy was recorded, and a questionnaire survey was conducted to evaluate the efficacy of the mixed-reality NT system.
The system allows the trainer and trainee to view the mixed-reality model with either a HoloLens or an iPad/iPhone simultaneously online at different locations. Interactive manipulation and instant updates were able to be achieved during training. A clinical efficacy validation test was conducted. The surgeons changed their exploration strategy in 48.3% of the NVC cases. For residents with limited experience in surgery, the exploration strategy for 75.0% of all patients with NVC was changed after the residents were trained with the mixed-reality NT system. Of the 60 responses for intracranial tumors, the trainee changed the surgical posture in 19 (31.7%) cases. The change of the location (p = 0.0338) and size (p = 0.0056) of craniotomy are significantly related to the experience of the neurosurgeons.
The mixed-reality NT system is available for local or real-time remote neurosurgical resident training. It may effectively help neurosurgeons in patient-specific training and planning of surgery for cases of NVC and intracranial tumor. The authors expect the system to have a broader application in neurosurgery in the near future.

The purpose of this study is to explore the evolution of brain edema after minimally invasive surgery in deep spontaneous cerebral hemorrhage (DSICH) treatment and to analyze the differences in edema after different surgical methods. The clinical data of 105 patients with DSICH treated at Renmin Hospital of Wuhan University from January 2020 to June 2022 were analyzed retrospectively. Among them, 54 patients were treated with minimally invasive puncture and drainage surgery (MIPDS group), and 51 were treated with neuroendoscopic surgery (NES group). Continuous computed tomography images of patients in the hospital and 3D Slicer software were used to quantitatively calculate the edematous area to explore the changes in perihematomal edema volume in the two groups after the operation. The peak volume of postoperative edema (37.36±10.51 mL) in the MIPDS group was more extensive than that in the NES group, and its net increase in edema volume was 16.86±10.01 mL more than that in the NES group. The relative edema index (0.86±0.26) was lower in the NES group than in the MIPDS group (P < 0.05). The peak of postoperative edema in the MIPDS group was at 6-8 days after the operation, and that in the NES group was most often at 3-5 days after the operation. There are differences in perihematomal edema of DSICH treated by different minimally invasive methods. Compared with the MIPDS group, the NES group showed earlier peak of cerebral edema and lower degree of cerebral edema. The absolute regression volume of edema in the MIDPs group was greater than that in the NEs group, but there was no difference in the regression rate of edema between the two groups.

鼻颅底外科的发展迫切需要多学科团队的协作，优化诊疗策略。通过构建鼻科与神经外科为核心的多学科团队协作（multiple disciplinary team，MDT），可对肿瘤患者进行全过程管理，从而产生更好的临床结果，并在多个维度对患者产生积极影响。我们的团队协作经验表明，对于晚期鼻颅底肿瘤患者，由于瘤体大、侵犯广、重要神经血管等结构受累，鼻科与神经外科的联合手术利于肿瘤的完全切除及缺损的修补，可减少并发症及复发，利于鼻腔功能的保留和术后的恢复，也会扩大内镜颅底肿瘤手术的适应证等。但临床上对于鼻颅底肿瘤的MDT团队协作也存在诸多问题，如医生的价值无法体现，MDT合作形式不够灵活，手术界限不清等，迫切需要在多个层面进行解决。.

BACKGROUND: Vasospasm and delayed cerebral ischemia (DCI) are the leading causes of morbidity and mortality after intracranial aneurysmal subarachnoid hemorrhage (aSAH). Vasospasm detection, prevention and management, especially endovascular management varies from center to center and lacks standardization. We aimed to evaluate this variability via an international survey of how neurointerventionalists approach vasospasm diagnosis and endovascular management.
METHODS: We designed an anonymous online survey with 100 questions to evaluate practice patterns between December 2021 and September 2022. We contacted endovascular neurosurgeons, neuroradiologists and neurologists via email and via two professional societies - the Society of NeuroInterventional Surgery (SNIS) and the European Society of Minimally Invasive Neurological Therapy (ESMINT). We recorded the physicians\' responses to the survey questions.
RESULTS: A total of 201 physicians (25% [50/201] USA and 75% non-USA) completed the survey over 10 months, 42% had >7 years of experience, 92% were male, median age was 40 (IQR 35-46). Both high-volume and low-volume centers were represented. Daily transcranial Doppler was the most common screening method (75%) for vasospasm. In cases of symptomatic vasospasm despite optimal medical management, endovascular treatment was directly considered by 58% of physicians. The most common reason to initiate endovascular treatment was clinical deficits associated with proven vasospasm/DCI in 89%. The choice of endovascular treatment and its efficacy was highly variable. Nimodipine was the most common first-line intra-arterial therapy (40%). Mechanical angioplasty was considered the most effective endovascular treatment by 65% of neurointerventionalists.
CONCLUSIONS: Our study highlights the considerable heterogeneity among the neurointerventional community regarding vasospasm diagnosis and endovascular management. Randomized trials and guidelines are needed to improve standard of care, determine optimal management approaches and track outcomes.

GPT4 is the newest multimodal language model released by OpenAI. With its powerful capabilities, GPT4 has great potential to revolutionize the healthcare industry. In this study, we proposed various ways GPT4 could display its talents in the field of neurosurgery in future. We believe that GPT4 is prone to become an indispensable assistant for neurosurgeons in the new era.

Neurosurgery, a highly specialized and sophisticated branch of medicine, is devoted to the surgical intervention of maladies impacting both the central and peripheral nervous systems. The intricate nature and meticulous precision demanded by neurosurgery has piqued the interest of artificial intelligence experts. In our comprehensive analysis, we encapsulate the prospective applications of the revolutionary GPT-4 technology within the sphere of neurosurgery, encompassing areas such as preoperative evaluation and preparation, tailored surgical simulations, postoperative care and rehabilitation, enriched patient communication, fostering collaboration and knowledge dissemination, as well as training and education. Furthermore, we plunge into the complex and intellectually stimulating conundrums that arise when integrating the cutting-edge GPT-4 technology into neurosurgery, taking into account the moral considerations and substantial hurdles intrinsic to its adoption. Our stance is that GPT-4 will not supplant neurosurgeons; on the contrary, it possesses the potential to serve as an invaluable instrument in augmenting the precision and effectiveness of neurosurgical procedures, ultimately enhancing patient outcomes and propelling the field forward.

Intracranial hemorrhage is a cerebral vascular disease with high mortality. Automotive diagnosing and segmentation of intracranial hemorrhage in Computed Tomography (CT) could assist the neurosurgeon in making treatment plans, which improves the survival rate. In this paper, we design a grouped capsule network named GroupCapsNet to segment the hemorrhage region from a Non-contract CT scan. In grouped capsule network, we constrain the prediction capsules for output capsules produced from different groups of input capsules with various types in each layer. This method can reduce the number of intermediate prediction capsules and accelerate the capsule network. In addition, we modify the squashing function to further accelerate the forward procedure without sacrificing its performance. We evaluate our proposed method with a collected dataset containing 210 intracranial hemorrhage CT scan slices. In experiments, our proposed method achieves competitive results in intracranial hemorrhage area segmentation compared to the existing methods.