Automatic curvilinear reformatting of three-dimensional MRI data of the cerebral cortex

Abstract

Curvilinear reformatting of three-dimensional (3D) MRI data of the cerebral cortex is a well-established tool which improves the display of the gyral structure, permits a precise localization of lesions, and helps to identify subtle abnormalities difficult to detect in planar slices due to the brain's complex convolutional pattern. However, the method is time consuming because it requires interactive manual delineation of the brain surface contour. Therefore, a novel technique for automatic curvilinear reformatting is presented. A T1-weighted MRI volume data set is normalized using SPM2. Due to the normalization to a common stereotactic space, predefined masks can be applied to cover skull and outer brain regions in different depths from the brain surface. Thereby, the outer brain regions are subsequently removed in 2-mm layers parallel to the brain surface like ‘peeling an onion’. The serial convex planes enclosing the residual inner part of the brain are presented 3-dimensionally. If necessary (e.g., for intraoperative navigation), the normalized data can be transferred to native space by inverse normalization. Compared to cross-sectional images, curvilinear reformatting offers a markedly superior visualization of topographic relations between lesions and cortical structures, helps to detect subtle cortical malformations and to assess the spatial extent of lesions, thus allowing a better planning of neurosurgical procedures. Compared to alternative methods, it is largely based on freely available software and does not require observer-dependent manual input. In conclusion, we present a simple, easy-to-use and fully automated method for curvilinear reformatting of 3D MRI.