• Juan C Fernandez-Miranda, Nathan T Zwagerman, Kumar Abhinav, Stefan Lieber, Eric W Wang, Carl H Snyderman, and Paul A Gardner.
• 1Department of Neurological Surgery, University of Pittsburgh Medical Center; and.
• J. Neurosurg. 2018 Aug 1; 129 (2): 430-441.

AbstractOBJECTIVE Tumors with cavernous sinus (CS) invasion represent a neurosurgical challenge. Increasing application of the endoscopic endonasal approach (EEA) requires a thorough understanding of the CS anatomy from an endonasal perspective. In this study, the authors aimed to develop a surgical anatomy-based classification of the CS and establish its utility for preoperative surgical planning and intraoperative guidance in adenoma surgery. METHODS Twenty-five colored silicon-injected human head specimens were used for endonasal and transcranial dissections of the CS. Pre- and postoperative MRI studies of 98 patients with pituitary adenoma with intraoperatively confirmed CS invasion were analyzed. RESULTS Four CS compartments are described based on their spatial relationship with the cavernous ICA: superior, posterior, inferior, and lateral. Each compartment has distinct boundaries and dural and neurovascular relationships: the superior compartment relates to the interclinoidal ligament and oculomotor nerve, the posterior compartment bears the gulfar segment of the abducens nerve and inferior hypophyseal artery, the inferior compartment contains the sympathetic nerve and distal cavernous abducens nerve, and the lateral compartment includes all cavernous cranial nerves and the inferolateral arterial trunk. Twenty-nine patients had a single compartment invaded, and 69 had multiple compartments involved. The most commonly invaded compartment was the superior (79 patients), followed by the posterior (n = 64), inferior (n = 45), and lateral (n = 23) compartments. Residual tumor rates by compartment were 79% in lateral, 17% in posterior, 14% in superior, and 11% in inferior. CONCLUSIONS The anatomy-based classification presented here complements current imaging-based classifications and may help to identify involved compartments both preoperatively and intraoperatively.

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