BACKGROUND: Anterior clinoid region @entity1653 may infiltrate the bone over which they arise, therefore requiring an anterior clinoidectomy to achieve a Simpson grade 1 resection. A clinoidectomy, however, is not without risks. OBJECTIVE: We performed a study of diagnostic accuracy investigating whether preoperative imaging could predict @entity5 involvement of the clinoid, and thereby tailor the degree of bony removal. METHODS: @entity1 having undergone resection of a clinoid region meningioma between 2001 and 2011 were identified. Included in further analysis were those @entity1 in whom a clinoidectomy was performed with subsequent pathologically confirmed presence or absence of @entity5 in the clinoid process on decalcified specimens. Two neuroradiologists, blinded to pathology results, independently reviewed available preoperative imaging and stated whether or not they anticipated the clinoid to be involved by @entity5 . Interobserver agreement and the ability to accurately predict @entity5 involvement of the clinoid were then analyzed. RESULTS: Sixty-two @entity1 were included in the final analysis. Interobserver agreement was 100%. Sensitivity and specificity of preoperative imaging to predict @entity5 involvement was 89% and 52%, respectively, with positive and negative likelihood ratios of 1.85 and 0.20. Positive and negative predictive values were 73% and 76%, respectively. CONCLUSION: Preoperative imaging of clinoid region @entity1653 can accurately predict the presence or absence of @entity5 involvement of the clinoid in only approximately 75% of cases. In light of the fact that a quarter of @entity1 with radiographically negative clinoids will have @entity5 present on pathological analysis, we recommend a clinoidectomy for all clinoid region @entity1653 . ABBREVIATIONS: CI, confidence intervalNPV, negative predictive valuePPV, positive predictive value.

Can Preoperative Imaging Predict Tumor Involvement of the Anterior Clinoid in Clinoid Region XXXX ?

@entity5 :: ('MESH:D009369', 'Disease') :: ['tumor'] @entity1 :: ('9606', 'Species') :: ['Patients', 'patients'] @entity1653 :: ('MESH:D008579', 'Disease') :: ['meningiomas']
@entity1653 :: (MESH:D008579,Disease) :: ['Meningiomas']
