• Annals of Saudi medicine · Jan 2006

    Evaluation of argyrophilic nucleolar organizer region staining in predicting the behavior of meningiomas.

    • Sayed Ali Ahmadi and Nasrin Samadi.
    • Department of Pathology, Sina Hospital, Hassan Abad Square, Tehran, Iran. ahmadise@tums.ac.ir
    • Ann Saudi Med. 2006 Jan 1; 26 (1): 384238-42.

    BackgroundThe number of argyrophilic nucleolar organizer regions (AgNOR) correlates with cellular proliferative activity. Comparing nonrecurrent, recurrent, atypical and malignant meningiomas we studied the value of the routine applicability of the AgNOR count in the prognostication of this tumor.Patients And MethodsTwo hundred and thirty-eight meningiomas were reviewed blindly and graded using WHO grading schema. Eighty-one cases were selected and arranged in six groups according to clinical data and grading: 14 benign non-recurrent meningiomas; 14 primary benign recurrent meningiomas and their subsequent benign recurrences; 14 atypical; 11 malignant and 14 spinal meningiomas. Silver-stained slides were prepared and mean, median and standard deviation of AgNOR dots determined.ResultsThere was a proportionate increase of AgNOR dots with increasing tumor grade. There was a significant difference between benign non-recurrenttumors versus benign recurrent (P<0.0001) and atypical or malignant (P<0.0001) tumors. A difference was also noted between the recurring tumors versus malignant ones (P = 0.002) but no significant difference was seen between recurrent and atypical; atypical and malignant; intracranial and intraspinal; and primary of recurring meningiomas with their subsequent recurrences. A mean AgNOR count of <2.3 could separate benign tumors from atypical or malignant meningiomas with 93% specificity; and 93% of tumors with benign histology had no recurrence potential if their mean AgNOR count was less than 1.8.ConclusionThis study indicates that in meningioma, the AgNOR count has a good correlation with tumor grading and recurrence, which may aid pathologists and clinicians in predicting tumor behavior.

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