We investigate the correlation between diffusion tensor imaging (DTI)-derived metric statistics and motor strength grade of insular glioma patients after optimizing the pyramidal tract (PT) delineation. Motor strength grades of 45 insular glioma patients were assessed. All the patients underwent structural and diffusion MRI examination before and after surgery. We co-registered pre- and post-op datasets, and a two-tensor unscented Kalman filter (UKF) algorithm was employed to delineate bilateral PTs after DWI pre-processing. The tractography results were voxelized, and their labelmaps were cropped according to the location of frontal and insular parts of the lesion. Both the whole and cropped labelmaps were used as regions of interest to analyze fractional anisotropy (FA) and Trace statistics; hence, their ratios were calculated (lesional side tract/contralateral normal tract). The combination of DWI pre-processing and two-tensor UKF algorithm successfully delineated bilateral PTs of all the patients. It effectively accomplished both full fiber delineation within the edema and an extensive lateral fanning that had a favorable correspondence to the bilateral motor cortices. Before surgery, correlations were found between patients' motor strength grades and ratios of PT volume and FA standard deviation (SD). Nearly 3 months after surgery, correlations were found between motor strength grades and the ratios of metric statistics as follows: whole PT volume, whole mean FA, and FA SD. We substantiated the correlation between DTI-derived metric statistics and motor strength grades of insular glioma patients. Moreover, we posed a workflow for comprehensive pre- and post-op DTI quantitative research of glioma patients.
Keywords: 3D Slicer; Diffusion tensor imaging; Insular glioma; Pyramidal tracts.
© 2022. The Author(s) under exclusive licence to Society for Imaging Informatics in Medicine.