Surgical management of anterior clinoidal meningiomas: a 26-case report.

BACKGROUND: Resection of anterior clinoidal meningiomas remains a major neurosurgical challenge. We determine the surgical technique for removal of tumor and improvement of patient's outcome. METHODS: A retrospective analysis was performed on 26 consecutive patients with anterior clinoidal meningiomas who underwent surgical resection at the Department of Neurosurgery, Renji Hospital, from January 1999 to August 2006. All patients had surgery through the pterional or extended pterional approach. Microvascular Doppler probe was used to protect the internal carotid artery and its branching arteries during dissection of the tumor. Twenty-two of them had severe visual deficits preoperatively. The follow-up period ranged from 3 to 36 months (22.3 +/- 8.8 months). RESULTS: In this series, Simpson grade II resection in 16 cases (61.5%), Simpson grade III resection in 4 cases (15.4%), Simpson grade IV resection in 6 cases (23.1%) were achieved. Sixteen of the patients with preoperative visual impairment experienced significant improvement. No patients died. There was no evidence of tumor recurrence during follow-up. CONCLUSIONS: In the majority of patients, surgery is still the first choice for total resection of the tumors without major complications. Protection of nerves and blood vessels must be a priority concern during removal of tumors.

[Electroacupuncture intervention combined with general anesthesia for craniocerebral operations].

OBJECTIVE: To determine the safety and effectiveness of electroacupuncture (EA) intervention combined with general anesthesia (GA) for craniocerebral tumor-removal surgery involving cerebral eloquent areas. METHODS: A total of 20 patients with cerebral tumors (durosarcoma, neurogliocytoma, metastatic tumor) involving the cerebral eloquent areas were recruited in the present summary. They were equally divided into general anesthesia (GA) group and EA + GA group. Patients of the EA + GA group were treated with EA stimulation (2 Hz/100 Hz) of the bilateral Fengchi (GB 20), Shuaigu (GB 8) and acupuncture stimulation of Quanliao (SI 18), Zulinqi (GB 41) and Taichong (LR 3), and not given intubation during surgery. Patients of the GA group were treated with intravenous administration of Propofol, Fentanyl, Midazolam, Isopropanol, etc. In addition, all the patients were given with controlled hypotension by intravenous injection of Propofol and Fentanyl. Dosages of Propofol and Sulfentanyl used were recorded. Karnofsky performance status scale was used to assess the patient's general well-being and activities of daily life. RESULTS: The craniocerebral tumor-removal surgery was successful in all the 20 patients. Compared with the GA group, the dosages of Sulfentanyl and Propofol of the EA+ GA group were significantly lower (P < 0.05). No significant difference was found between the GA and EA+ GA groups in Karnofsky performance scores (P > 0.05). Patients of the EA+GA group experienced successful tumour-removal surgery without trachea cannula, were awake and could make a good cooperation with the operator during surgery. They had no aggravation of neurofunctional disturbance following the operation. CONCLUSION: EA combined with general anesthesia is safe and effective for patients with craniocerebral tumor-removal operations involving cerebral eloquent areas.

Evaluation of driver fatigue on two channels of EEG data.

Electroencephalogram (EEG) data is an effective indicator to evaluate driver fatigue. The 16 channels of EEG data are collected and transformed into three bands (θ, α, and ß) in the current paper. First, 12 types of energy parameters are computed based on the EEG data. Then, Grey Relational Analysis (GRA) is introduced to identify the optimal indicator of driver fatigue, after which, the number of significant electrodes is reduced using Kernel Principle Component Analysis (KPCA). Finally, the evaluation model for driver fatigue is established with the regression equation based on the EEG data from two significant electrodes (Fp1 and O1). The experimental results verify that the model is effective in evaluating driver fatigue.