Detection of local growth patterns in longitudinally imaged low-grade gliomas

Abstract

BackgroundDiffuse low-grade gliomas (LGGs) are primary brain tumors with infiltrative, anisotropic growth related to surrounding white and grey matter structures. In this study, we illustrate the use of deformation-based morphometry (DBM) as a simple and objective method to study the local change in growth patterns of LGGs. MethodsAn imaging pipeline was developed involving the creation of patient-specific average templates and nonlinear registration of pre-treatment follow-up MRIs to the average template. Jacobian maps were derived and analyzed to identify areas of tissue expansion and contraction over time. ResultsOur analysis demonstrates that tissue expansion occurs primarily around the edges of the tumor, while the lesion core and areas adjacent to obstacles, such as the skull, show no significant growth. Tumors also appeared to grow faster and predominantly in areas of white matter. Regions of the brain surrounding the lesion showed slight contraction over time, likely representing compression due to mass effect of the tumor. ConclusionsWe demonstrate that DBM is a useful clinical tool to understand the long-term clinical course of an individuals tumor and identify areas of rapid growth, which can explain the clinical signs and symptoms, predict future symptoms, and guide targeted diagnostics and therapy. HighlightsO_LILow-grade glioma expansion occurs primarily around the edges of the tumor. C_LIO_LITumor cores and tissue next to obstacles show no significant growth over time. C_LIO_LIDBM provides a clinically valuable assessment of local tumor growth and activity. C_LI