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      A template-based procedure for determining white matter integrity in the internal capsule early after stroke

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          Abstract

          The integrity of descending white matter pathways, measured by fractional anisotropy from DW-MRI, is a key prognostic indicator of motor recovery after stroke. Barriers to translation of fractional anisotropy measures into routine clinical practice include the time required for manually delineating volumes of interest (VOIs), and inter-examiner variability in this process. This study investigated whether registering and then editing template volumes of interest ‘as required’ would improve inter-examiner reliability compared with manual delineation, without compromising validity. MRI was performed with 30 sub-acute stroke patients with motor deficits (mean NIHSS = 11, range 0–17). Four independent examiners manually delineated VOIs for the posterior limbs of the internal capsules on T1 images, or edited template VOIs that had been registered to the T1 images if they encroached on ventricles or basal ganglia. Fractional anisotropy within each VOI and interhemispheric asymmetry were then calculated. We found that 13/30 registered template VOIs required editing. Edited template VOIs were more spatially similar between examiners than the manually delineated VOIs (p = 0.005). Both methods produced similar asymmetry values that correlated with clinical scores with near perfect levels of agreement between examiners. Contralesional fractional anisotropy correlated with age when edited template VOIs were used but not when VOIs were manually delineated. Editing template VOIs as required is reliable, increases the validity of fractional anisotropy measurements in the posterior limb of the internal capsule, and is less time-consuming compared to manual delineation. This approach could support the use of FA asymmetry measures in routine clinical practice.

          Highlights

          • Fractional anisotropy in the PLIC is a key prognostic indicator of motor recovery after stroke.

          • Editing template PLIC volumes of interest is valid, reliable and efficient.

          • A template-based approach may translate FA asymmetry measures to clinical practice.

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          Most cited references39

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          A performance test for assessment of upper limb function in physical rehabilitation treatment and research.

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            A probabilistic atlas of the human brain: theory and rationale for its development. The International Consortium for Brain Mapping (ICBM).

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              Inferring microstructural features and the physiological state of tissues from diffusion-weighted images.

              P Basser (1995)
              We review several methods that have been developed to infer microstructural and physiological information about isotropic and anisotropic tissues from diffusion weighted images (DWIs). These include Diffusion Imaging (DI), Diffusion Tensor Imaging (DTI), isotropically weighted imaging, and q-space imaging. Just as DI provides useful information about molecular displacements in one dimension with which to characterize diffusion in isotropic tissues, DTI provides information about molecular displacements in three dimensions needed to characterize diffusion is anisotropic tissues. DTI also furnishes scalar parameters that behave like quantitative histological or physiological 'stains' for different features of diffusion. These include Trace(D), which is related to the mean diffusivity, and a family of parameters derived from the diffusion tensor, D, which characterize different features of anisotropic diffusion. Simple thought experiments and geometrical constructs, such as the diffusion ellipsoid, can be used to understand water diffusion in isotropic and anisotropic media, and the NMR experiments used to characterize it.
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                Author and article information

                Contributors
                Journal
                Neuroimage Clin
                Neuroimage Clin
                NeuroImage : Clinical
                Elsevier
                2213-1582
                26 December 2013
                26 December 2013
                2014
                : 4
                : 695-700
                Affiliations
                [a ]Department of Medicine, University of Auckland, Auckland, New Zealand
                [b ]Centre for Brain Research, University of Auckland, Auckland, New Zealand
                [c ]Department of Sport & Exercise Science, University of Auckland, Auckland, New Zealand
                [d ]Neurology Department, Auckland City Hospital, Auckland, New Zealand
                Author notes
                [* ]Corresponding author at: Department of Medicine and Centre for Brain Research, University of Auckland, Private Bag 92019, Auckland 1142, New Zealand. Tel.: + 64 9 92 33 779. c.stinear@ 123456auckland.ac.nz
                Article
                S2213-1582(13)00165-4
                10.1016/j.nicl.2013.12.006
                4053651
                24936407
                fe095182-2016-4b7b-83e4-712b57682cad
                © 2013 The Authors

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

                History
                : 16 October 2013
                : 17 December 2013
                : 17 December 2013
                Categories
                Article

                stroke,magnetic resonance imaging,diffusion-weighted imaging,prognosis

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