Dynamics of tumor evolution after Gamma Knife radiosurgery for sporadic vestibular schwannoma: Defining volumetric patterns characterizing individual trajectory

Abstract

Background: The definition of tumor control and treatment failure after Gamma Knife radiosurgery (GKRS) for vestibular schwannoma (VS) is still debated. The lack of knowledge on the dynamics of tumor evolution can lead to misinterpretation and subsequent inappropriate second treatment. The aim of this study was to evaluate the post-GKRS dynamics of the evolution of tumor volume and characterize volumetric patterns.

Methods: We included patients with sporadic VS treated by GKRS with an MRI follow-up of a minimum of 3 years. A clustering was performed in 2 steps: Definition of the patterns of evolution based on a subset of patients with the most comprehensive follow-up, and then the assignment of the remaining patients on a best-fit basis. The minimum length of follow-up was assessed by measuring the consistency of the clusters over time (adjusted rand index and normalized mutual information). An analysis of the discriminant variables was finally performed.

Results: A total of 1607 patients were included (median follow-up: 67 months). Five patterns were defined with 1 pattern gathering almost all cases of treatment failure. The clustering at 5 years afforded the highest consistency with long-term follow-up. Discriminant variables for clusters were as follows: sex, initial symptoms, delay of diagnosis, Koos grading, fundus invasion, and number of isocenters.

Conclusions: The definition of these robust distinct patterns is likely to help the physicians tremendously to distinguish tumor control from potential failure. We advocate for no retreatment decision before 5 years post-GKRS. Further investigations are required to decide if the dynamics of evolution can be predicted at GKRS on an individual basis.

Keywords: failure; patterns; radiosurgery; vestibular schwannoma; volumetry.

Figure 1.

Dendogram of clustering representing the 5 patterns of volumetric evolution with a detailed trajectory for each pattern and standard deviation. Pattern 1 (red) includes 9.9% of the cohort, pattern 2 (yellow) 17.0%, pattern 3 (green) 24.2%, pattern 4 (blue) 13.2%, and pattern 5 (pink) 35.7%.

Figure 2.

Tumor average trajectory per pattern is defined by the clustering (on the left). Individual tumor volume evolution for each pattern (on the right). These data include both patients used to define the patterns and those assigned a posteriori to a cluster. Patterns are represented in red (1), yellow (2), green (3), blue (4), and pink (5), respectively.

Figure 3.

Description, distribution, and failure rate for each pattern with average trajectory on the left and individual trajectories on the right (red trajectories for controlled cases and blue for failures). The patterns are sorted based on failure rate (increasing from top to bottom). Patterns are represented in red (1), yellow (2), green (3), blue (4), and pink (5), respectively.