Growth pattern analysis of sphenoid wing meningiomas

Acta Neurochir (Wien). 2010 Jan;152(1):99-103; discussion 103. doi: 10.1007/s00701-009-0556-2.

Abstract

Purpose: Complete resection is crucial for the management of sphenoid wing meningiomas (SWM). We hypothesized that specific anatomical growth patterns are predictive for recurrence and worse prognosis. We therefore analyzed the extension patterns of SWM and correlated them with intraoperative findings, extent of resection and recurrence rate.

Methods: MRI and CT scans were utilized to analyze soft tissue and bone extension, respectively. Soft tissue extension was quantified using four, bone infiltration using eight anatomical landmarks. The extent of resection was graded according to the Simpson classification (grade I-V). Finally,the growth pattern analysis was correlated with recurrence rate.

Results: We included 44 patients, 37 female (84.1%) and 7 male (15.9%). Tumor recurrence was observed in 13 patients (29.5%). Patients with recurrent tumors had a significantly worse Simpson score (p=0.01). Soft tissue spread into the cavernous sinus and bony infiltration of the superior orbital fissure was associated with a poor Simpson grade (p=0.001). Bony infiltration of the orbital roof superior orbital fissure was highly predictive for tumor recurrence (p=0.002).

Conclusions: Structured radiological and anatomical analysis of the SWM growth pattern may influence the surgical strategy and facilitate the management and prognostication of patients with SWM.

MeSH terms

  • Adult
  • Aged
  • Cavernous Sinus / diagnostic imaging
  • Cavernous Sinus / pathology
  • Female
  • Humans
  • Magnetic Resonance Imaging
  • Male
  • Meningeal Neoplasms / diagnosis*
  • Meningeal Neoplasms / surgery*
  • Meningioma / diagnosis*
  • Meningioma / surgery*
  • Middle Aged
  • Neoplasm Invasiveness
  • Neoplasm Recurrence, Local / radiotherapy
  • Orbit / diagnostic imaging
  • Orbit / pathology
  • Predictive Value of Tests
  • Prognosis
  • Retrospective Studies
  • Severity of Illness Index
  • Time Factors
  • Tomography, X-Ray Computed