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Publication - Dr Philip Clatworthy

    Probabilistic tractography of the optic radiations-An automated method and anatomical validation

    Citation

    Clatworthy, P, Williams, G, Acosta-Cabronero, J, Jones, S, Harding, S, Johansen-Berg, H & Baron, J-C, 2010, ‘Probabilistic tractography of the optic radiations-An automated method and anatomical validation’. NeuroImage, vol 49., pp. 2001 - 2012

    Abstract

    Accurately tracing the optic radiations in living humans has important implications for studying the relationship between tract structure or integrity and visual function, in health and disease. Probabilistic tractography is an established method for tracing white matter tracts in humans. Prior studies have used this method to trace the optic radiations, but operator-dependent factors, particularly variability in seed voxel placement and choice of connectivity threshold to select between tract and non-tract voxels, remain potential causes of significant variability. Methods using prior information to modify tract images risk introducing error by underestimating individual variability, particularly in subjects with abnormal anatomy. Finally, existing methods lack thorough validation against a histological standard, causing difficulty in evaluating individual methods, and quantitatively comparing methods.

    Here we describe a method for producing binary optic radiation images using an existing, well-validated tractography method. All stages are automated, including mask image generation, and thresholds are objectively selected by comparing tract images with existing probabilistic histological data in stereotaxic space. Data from two subject groups are presented; the first used to derive analysis parameters, and the second to test these parameters in an independent sample. Validation utilised a novel variant of receiver operating characteristic analysis, providing both justification for this method and a metric by which tractography methods might be compared generally. The resulting tracts match the histological data well; images generated in individuals matched the histological group data about as well as did images derived in individuals from that histological data set, with a low false positive rate.

    Full details in the University publications repository