Levine-Sekhar grading system for prediction of the extent of resection of cranial base meningiomas revisited: study of 124 cases.
BACKGROUND
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.


METHODS
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.


RESULTS
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).


CONCLUSIONS
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.
Saberi
Hooshang
H
Department of Neurosurgery, Imam Khomeini Hospital, Tehran University of Medical Sciences, Iran. hgsaberi@yahoo.com
Meybodi
Ali Tayebi
AT
Rezai
Abdolreza Sheikh
AS
D000328:Adult; D000368:Aged; D001808:Blood Vessels / Q000473:pathology; D003391:Cranial Nerves / Q000473:pathology; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008297:Male; D008577:Meningeal Neoplasms / Q000145:classification* / Q000473:pathology / Q000601:surgery*; D008579:Meningioma / Q000145:classification* / Q000473:pathology / Q000601:surgery*; D008875:Middle Aged; D009361:Neoplasm Invasiveness / Q000473:pathology; D011379:Prognosis; D012044:Regression Analysis; D012189:Retrospective Studies; D019291:Skull Base / Q000473:pathology / Q000601:surgery; D019292:Skull Base Neoplasms / Q000145:classification* / Q000473:pathology / Q000601:surgery*; D013223:Statistics as Topic