Deformation-based morphometry analysis of longitudinal low-grade glioma growth
Chloe Gui, Dr. Jonathan C Lau, Jason Kai, Dr. Ali R Khan, Dr. Joseph F Megyesi
Introduction: Diffuse low-grade gliomas (LGGs) are primary brain tumours with infiltrative, anisotropic growth related to surrounding white and grey matter structures. Deformation-based morphometry (DBM) is an image analysis method that can identify areas of local volume change over time. In this study, we illustrate the use of DBM to study the local expansion patterns of LGGs monitored by serial magnetic resonance imaging (MRI).
Methods: We developed an image processing pipeline optimized for the study of LGG growth involving the fusion of follow-up MRIs for a given patient into an average template space using nonlinear registration. The displacement maps derived from nonlinear registration were converted to Jacobian maps, which estimate local tissue expansion and contraction over time.
Results: Our results demonstrate that neoplastic growth occurs primarily around the edges of the tumour while the lesion core and areas adjacent to obstacles, such as the skull, show no significant expansion. Regions of normal brain tissue surrounding the lesion show slight contraction over time, which may represent compression due to mass effect of the tumour.
Conclusion: Deformation-based morphometry may be a useful clinical tool to understand the long-term clinical course of individual tumours and identify areas of rapid growth, which may explain the current presentation and/or predict future symptoms.