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Probabilistic anatomical connectivity using persistent angular structure obtained from diffusion weighted imaging
Parker GJM, D.C. Alexander
Philosophical transactions of the Royal Society of London [B] Biological Sciences. 2005;360:893-902.
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Abstract
Recently developed methods to extract the persistent angular structure (PAS) of axonal fibre bundlesfrom diffusion-weighted magnetic resonance imaging (MRI) data are applied to drive probabilisticfibre tracking, designed to provide estimates of anatomical cerebral connectivity. The behaviour ofthe PAS function in the presence of realistic data noise is modelled for a range of single and multiplefibre configurations. This allows probability density functions (PDFs) to be generated that areparametrized according to the anisotropy of individual fibre populations. The PDFs are incorporatedin a probabilistic fibre-tracking method to allow the estimation of whole-brain maps of anatomicalconnection probability. These methods are applied in two exemplar experiments in the corticospinaltract to show that it is possible to connect the entire primary motor cortex (M1) when tracing fromthe cerebral peduncles, and that the reverse experiment of tracking from M1 successfully identifieshigh probability connection via the pyramidal tracts. Using the extracted PAS in probabilistic fibretracking allows higher specificity and sensitivity than previously reported fibre tracking usingdiffusion-weighted MRI in the corticospinal tract.Keywords: anatomical connectivity; persistent angular structure; tractography;magnetic resonance imaging; diffusion-weighted imaging; probabilistic methods