A semi-automated method for measuring thickness and white matter integrity of the corpus callosum

Abstract

Many diseases affect human brain white matter, multifocally or diffusely, in adults and children. These may be metabolic (e.g. Leigh's disease), toxic (e.g. carbon monoxide poisoning), hypoxic (e.g. hypoxic ischaemic injury), infective (e.g. HIV or syphilis), inflammatory (e.g. multiple sclerosis) or vascular (e.g. microvascular dementia). Two important conditions that result in significant loss of global white matter volume in affected children are hypoxic ischaemic injury and HIV encephalopathy. These diseases result in the thinning of associated fibre bundles and may be reflected by atrophy of inter-hemispheric connections -most importantly the corpus callosum (CC) (Fig. 1).A simple automated method of determining normal values of the CC according to age is desirable. A tool which is also applicable for diagnosing white matter disorders and offering prognosis in children with global white matter insults will have a wide clinical application. This article describes a semi-automated system that divides the midline CC into a number of segments, determines thickness at each, and performs fibre tracking from these segments. Aim.Diseases affecting cerebral white matter may lead to left-right asymmetries and atrophy of interhemispheric connections, i.e. the corpus callosum (CC). Our aim was to describe and test a semi-automated system that divides the midline CC into a number of segments and determines thickness at each, then performs fibre tracking from these segments. Methods. Six normal female volunteers (average age 25.8 ± 6.7 years) and a female patient with diagnosed multiple sclerosis (age 26 years) were scanned on a 3T MRI. We performed diffusion-weighted imaging in 12 directions, and calculated diffusion tensors and fractional anisotropy (FA) maps from this pre-processed data. Fibre tracking from a region-of-interest encompassing the entire CC was done. This fibre data, together with FA maps and the unweighted diffusion tensor imaging (DTI) image (b = 0 s/mm 2 ), were imported into a custom tool written in MATLAB. The midline sagittal position was carefully defined by selecting multiple midline points in coronal and axial views and rotating the image volume and fibre co-ordinates accordingly.Using the customised tool, dorsal and ventral CC contours were manually drawn on the mid-sagittal FA image, initiating automated calculation of a contour midway between these manually drawn lines. The programme was designed to then divide the midline contour into a pre-selected number of segments; from each segment border, perpendicular spokes were projected until they intersected with the dorsal and ventral contours. This technique divided the CC into a pre-set amount of segments, the number of which was limited by the spatial resolution. It was decided to set the number at 40 to ensure that each segment depicted a contiguous strip of voxels across the CC from the dorsal to the ventral contour. The system allows these segments to then be used as seeds for separate fibre tracking in each cerebral hemisphere, and various...

Corpus callosum thickness on mid-sagittal MRI as a marker of brain volume: a pilot study in children with HIV-related brain disease and controls

“…MATLAB is a high-level language and interactive environment that enables you to perform computationally intensive tasks faster than with traditional programming languages such as C, C++ and Fortran. A description of this method was published in 2012 [12] and is similar to the method of Luders and colleagues [13] but creates up to 40 thickness measures rather than 100. The operator (S.A.) selected the midline sagittal T1-weighted image for each patient and then dorsal (top) and ventral (bottom) corpus callosum contours were manually drawn using a point depositing system.…”

“…It was designed for use with diffusion tensor imaging where segments serve as seeds for fiber tracking and ensures that segments consist of a contiguous strip of voxels [12]. It should be noted, however, that this tool was only validated with regard to its functionality and was initially used in only seven subjects.…”

Corpus callosum thickness in children: an MR pattern-recognition approach on the midsagittal image

“…This occurs from Wallerian degeneration (a process of antegrade neural disintegration that occurs after injury to the proximal axon or cell body). Digital tools can measure thickness of the corpus callosum to enable correlation with clinical parameters in a number of medical conditions [11,19] (Fig. 3).…”