Does pretreatment growth rate of vestibular schwannomas predict response to radiosurgery and adverse radiation effects?Gelareh Zadeh1, Soroush Larjani2, Houman Pebdani2, Caroline Hayhurst2, Caroline Chung1, Ab Kulkarni2, Michael D. Cusimano21Toronto, Canada 2University of Toronto Keywords: radiosurgery, natural history, gamma knife, Imaging, vestibular schwannoma
Stereotactic radiosurgery (SRS) is a well-established treatment option for vestibular schwannomas (VS).
An important clinical question is whether pre-treatment tumor growth
rate (TGR) predicts pattern of growth response to SRS and is a
determinant of adverse radiation effects (ARE).
Patients with clinical and radiological follow-up at least 12 months before and after SRS were selected.
A retrospective review of a prospectively maintained database of all VS patients treated at our institution between December 2005 to 2011 using Model 4C Gamma Knife Unit was carried out. All ARE were recorded. Tumor volume was determined from T1-weighted and FIESTA MRI scans obtained at every six-month intervals (pre- and post-SRS) using the ITK-SNAP software. Linear regression and multivariate analysis were performed with SPSS version 19.0.
Mean growth rate pre-SRS was +94.6%/year, and post-SRS was -10.8%/year. We classified tumors into three categories based on volumetric growth rate: class I (<52%), class II (52%–73%), and class III (>73%). We did not find a direct correlation between pre- and post-treatment TGR (p>0.40). A significant correlation was found between pre-treatment TGR and the extent of reduction in TGR post-SRS (p<0.001). 33% of VS patients treated GKRS experienced non-auditory ARE. Pre-treatment growth rate did not correlate with the occurrence of any ARE. Post-treatment TGR was a predictor of facial nerve dysfunction.
This was a retrospective analysis of prospectively collected data.
Tumors with greatest pre-treatment growth rate had the most favorable response to SRS. TGR pre-SRS did not predict ARE, though target volume predicted facial nerve dysfunction.
This data will aid in patient counseling and decision making for best treatment options. Project Roles:
G. Zadeh (), S. Larjani (), H. Pebdani (), C. Hayhurst (), C. Chung (), A. Kulkarni (), M. Cusimano ()