Saberi Hooshang, Meybodi Ali Tayebi, Rezai Abdolreza Sheikh
Department of Neurosurgery, Imam Khomeini Hospital, Tehran University of Medical Sciences, Iran.
Neurosurg Rev. 2006 Apr;29(2):138-44. doi: 10.1007/s10143-005-0006-4. Epub 2006 Jan 11.
Skull base meningiomas comprise an intricate kingdom in neurological surgery. Due to their proximity to critical neurovascular structures, these tumours impose a cumbersome burden on the surgeon regarding surgical intervention and the clinical outcome. Preoperative prediction of the meningioma resectability will help the surgeon seek a rational result from surgery. This study tries to re-examine and promote the Levine-Sekhar (LS) grading system proposed to predict the resectability of basal meningiomas.
A retrospective study was performed on 124 eligible patients (90 female and 34 male) suffering from cranial base meningioma that had been operated on between April 1996 and February 2003. The patients were classified according to LS and our modified grading systems. The modified grading system deploys six groups of variables: optic apparatus involvement, cavernous sinus neural involvement, facial-auditory involvement, caudal cranial nerve dysfunction, data derived from imaging studies (multiple fossa involvement and/or vessel encasement), and history of previous radiosurgery. Each criterion scores 1 if present and the total score is the sum of scores obtained from the aforementioned criteria.
Amongst 124 patients, 66 (52%) underwent gross total removal of the tumour. Regression and correlation analysis were performed for both LS (r(2) = 0.9683) and our modified grading systems (r(2) = 0.990) to evaluate the relationship of tumour grade versus the proportion of total resection. The correlations were significantly different (P < 0.01).
Although the LS grading system is reported to be a good predictor of the extent of tumour resection, we believe that application of the six aforementioned variables will enhance the accuracy of this system, while preserving simplicity and communicability.
颅底脑膜瘤在神经外科领域是一个复杂的范畴。由于它们紧邻关键的神经血管结构,这些肿瘤在手术干预和临床结果方面给外科医生带来了沉重负担。术前预测脑膜瘤的可切除性将有助于外科医生从手术中寻求合理的结果。本研究试图重新审视并推广用于预测颅底脑膜瘤可切除性的莱文-塞卡尔(LS)分级系统。
对1996年4月至2003年2月间接受手术治疗的124例符合条件的颅底脑膜瘤患者(90例女性,34例男性)进行了回顾性研究。患者根据LS分级系统和我们改良的分级系统进行分类。改良分级系统采用六组变量:视器受累情况、海绵窦神经受累情况、面听神经受累情况、后组颅神经功能障碍、影像学研究数据(多颅窝受累和/或血管包绕)以及既往放射外科治疗史。每个标准若存在则得1分,总分是上述标准得分的总和。
124例患者中,66例(52%)实现了肿瘤全切。对LS分级系统(r(2) = 0.9683)和我们改良的分级系统(r(2) = 0.990)均进行了回归和相关性分析,以评估肿瘤分级与全切比例之间的关系。相关性存在显著差异(P < 0.01)。
尽管据报道LS分级系统是肿瘤切除范围的良好预测指标,但我们认为应用上述六个变量将提高该系统的准确性,同时保持其简单性和实用性。