Landmark-referenced voxel-based analysis of diffusion tensor images of the brainstem white matter tracts: Application in patients with middle cerebral artery stroke

Abstract

Although DTI can provide detailed information about white matter anatomy, it is not yet straightforward enough to quantify the anatomical information it visualizes. In this study, we developed and tested a new tool to perform brain normalization and voxel-based analysis of DTI data. For the normalization part, manually placed landmarks ensured that the visualized white matter tracts were well-registered among the populations. A standard landmark set in ICBM-152 space and an interface to remap them to subject data were integrated in the procedure. After landmark placement, highly elastic non-linear Large Deformation Diffeomorphic Metric Mapping (LDDMM) was driven by the landmarks to normalize the brainstem anatomy of normal subjects. The approach was then applied to delineate brainstem tract abnormalities in patients with left chronic middle cerebral artery (MCA) stroke. The voxel-based comparison between control and patient groups identified abnormalities in the ipsilesional corticospinal tract and contralesional cerebellar peduncles. We believe that this tool is useful for regional brain normalization of patients with severe anatomical alterations, such as stroke, brain tumor, and lobectomy, for whom standard automated normalization tools may not work properly.