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      Age related diffusion and tractography changes in typically developing pediatric cervical and thoracic spinal cord

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          Abstract

          Background and objective

          Diffusion tensor imaging (DTI) and diffusion tensor tractography (DTT) are two techniques that can measure white matter integrity of the spinal cord. Recently, DTI indices have been shown to change with age. The purpose of this study is (a) to evaluate the maturational states of the entire pediatric spinal cord using DTI and DTT indices including fractional anisotropy (FA), mean diffusivity (MD), mean length of white matter fiber tracts and tract density and (b) to analyze the DTI and DTT parameters along the entire spinal cord as a function of spinal cord levels and age.

          Method

          A total of 23 typically developing (TD) pediatric subjects ranging in age from 6 to 16 years old (11.94 ± 3.26 (mean ± standard deviation), 13 females and 10 males) were recruited, and scanned using 3.0 T MR scanner. Reduced FOV diffusion tensor images were acquired axially in the same anatomical location prescribed for the T2-weighted images to cover the entire spinal cord (C1-mid L1 levels). To mitigate motion induced artifacts, diffusion directional images were aligned with the reference image (b0) using a rigid body registration algorithm performed by in-house software developed in Matlab (MathWorks, Natick, Massachusetts). Diffusion tensor maps (FA and MD) and streamline deterministic tractography were then generated from the motion corrected DTI dataset. DTI and DTT parameters were calculated by using ROIs drawn to encapsulate the whole cord along the entire spinal cord by an independent board certified neuroradiologist. These indices then were compared between two age groups (age group A = 6–11 years ( n = 11) and age group B = 12–16 years ( n = 12)) based on similar standards and age definitions used for reporting spinal cord injury in the pediatric population. Standard least squared linear regression based on a restricted maximum likelihood (REML) method was used to evaluate the relationship between age and DTI and DTT parameters.

          Results

          An increase in FA (group A = 0.42 ± 0.097, group B = 0.49 ± 0.116), white matter tract density (group A = 368.01 ± 236.88, group B = 440.13 ± 245.24) and mean length of fiber tracts (group A = 48.16 ± 20.48 mm, group B = 60.28 ± 23.87 mm) and a decrease in MD (group A = 1.06 ± 0.23 × 10 −3 mm 2/s, group B = 0.82 ± 0.24 × 10 −3 mm 2/s) were observed with age along the entire spinal cord. Statistically significant increases have been shown in FA ( p = 0.004, R 2 = 0.57), tract density ( p = 0.0004, R 2 = 0.58), mean length of fiber tracts ( p < 0.001, R 2 = 0.5) and a significant decrease has been shown in MD ( p = 0.002, R 2 = 0.59) between group A and group B. Also, it has been shown DTI and DTT parameters vary along the spinal cord as a function of intervertebral disk and mid-vertebral body level.

          Conclusion

          This study provides an initial understanding of age related changes of DTI values as well as DTT metrics of the spinal cord. The results show significant differences in DTI and DTT parameters which may result from decreasing water content, myelination of fiber tracts, and the thickening diameter of fiber tracts during the maturation process. Consequently, when quantitative DTI and DTT of the spinal cord is undertaken in the pediatric population an age and level matched normative dataset should be used to accurately interpret the quantitative results.

          Highlights

          • DTI and DTT are effective techniques in the investigation and quantification of neurological development of the brain in pediatric subjects.

          • This type of analysis could potentially help facilitate a more thorough understanding of the maturation process in pediatrics.

          • This study evaluates the maturational states of the entire pediatric spinal cord using DTI and DTT indices.

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          Most cited references38

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          Robust determination of the fibre orientation distribution in diffusion MRI: non-negativity constrained super-resolved spherical deconvolution.

          Diffusion-weighted (DW) MR images contain information about the orientation of brain white matter fibres that potentially can be used to study human brain connectivity in vivo using tractography techniques. Currently, the diffusion tensor model is widely used to extract fibre directions from DW-MRI data, but fails in regions containing multiple fibre orientations. The spherical deconvolution technique has recently been proposed to address this limitation. It provides an estimate of the fibre orientation distribution (FOD) by assuming the DW signal measured from any fibre bundle is adequately described by a single response function. However, the deconvolution is ill-conditioned and susceptible to noise contamination. This tends to introduce artefactual negative regions in the FOD, which are clearly physically impossible. In this study, the introduction of a constraint on such negative regions is proposed to improve the conditioning of the spherical deconvolution. This approach is shown to provide FOD estimates that are robust to noise whilst preserving angular resolution. The approach also permits the use of super-resolution, whereby more FOD parameters are estimated than were actually measured, improving the angular resolution of the results. The method provides much better defined fibre orientation estimates, and allows orientations to be resolved that are separated by smaller angles than previously possible. This should allow tractography algorithms to be designed that are able to track reliably through crossing fibre regions.
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            RESTORE: robust estimation of tensors by outlier rejection.

            Signal variability in diffusion weighted imaging (DWI) is influenced by both thermal noise and spatially and temporally varying artifacts such as subject motion and cardiac pulsation. In this paper, the effects of DWI artifacts on estimated tensor values, such as trace and fractional anisotropy, are analyzed using Monte Carlo simulations. A novel approach for robust diffusion tensor estimation, called RESTORE (for robust estimation of tensors by outlier rejection), is proposed. This method uses iteratively reweighted least-squares regression to identify potential outliers and subsequently exclude them. Results from both simulated and clinical diffusion data sets indicate that the RESTORE method improves tensor estimation compared to the commonly used linear and nonlinear least-squares tensor fitting methods and a recently proposed method based on the Geman-McClure M-estimator. The RESTORE method could potentially remove the need for cardiac gating in DWI acquisitions and should be applicable to other MR imaging techniques that use univariate or multivariate regression to fit MRI data to a model. Copyright 2005 Wiley-Liss, Inc.
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              The development of brain white matter microstructure

              Throughout infancy, childhood, and adolescence, our brains undergo remarkable changes. Processes including myelination and synaptogenesis occur rapidly across the first 2–3 years of life, and ongoing brain remodeling continues into young adulthood. Studies have sought to characterize the patterns of structural brain development, and early studies predominately relied upon gross anatomical measures of brain structure, morphology, and organization. MRI offers the ability to characterize and quantify a range of microstructural aspects of brain tissue that may be more closely related to fundamental neurodevelopmental processes. Techniques such as diffusion, magnetization transfer, relaxometry, and myelin water imaging provide insight into changing cyto- and myeloarchitecture, neuronal density, and structural connectivity. In this review, we focus on the growing body of literature exploiting these MRI techniques to better understand the microstructural changes that occur in brain white matter during maturation. Our review focuses on studies of normative brain development from birth to early adulthood (~25 years), and places particular emphasis on longitudinal studies and newer techniques that are being used to study microstructural white matter development. All imaging methods demonstrate consistent, rapid microstructural white matter development over the first 3 years of life, suggesting increased myelination and axonal packing. Diffusion studies clearly demonstrate continued white matter maturation during later childhood and adolescence, though the lack of consistent findings in other modalities suggests changes may be mainly due to axonal packing. An emerging literature details differential microstructural development in boys and girls, and connects developmental trajectories to cognitive abilities, behavior, and/or environmental factors, though the nature of these relationships remains unclear. Future research will need to focus on newer imaging techniques and longitudinal studies to provide more detailed information about microstructural white matter development, particularly in the childhood years.
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                Author and article information

                Contributors
                Journal
                Neuroimage Clin
                Neuroimage Clin
                NeuroImage : Clinical
                Elsevier
                2213-1582
                15 March 2018
                2018
                15 March 2018
                : 18
                : 784-792
                Affiliations
                [a ]Department of Neurosurgery, Thomas Jefferson University, Philadelphia, PA, United States
                [b ]Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, Philadelphia, PA, United States
                [c ]Department of Biology, Drexel University, Philadelphia, PA, United States
                [d ]Department of Occupational Therapy, Thomas Jefferson University, Philadelphia, PA, United States
                [e ]Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
                [f ]Department of Radiology, Johns Hopkins University, Baltimore, MD, United States
                Author notes
                [* ]Corresponding author at: 909 Walnut Street, Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, Philadelphia, PA 19107, United States. feroze.mohamed@ 123456jefferson.edu
                Article
                S2213-1582(18)30084-6
                10.1016/j.nicl.2018.03.014
                5988463
                29876264
                b97e0987-ecfb-4fc2-b330-7c02a4a4cd0e
                © 2018 The Authors

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 24 May 2017
                : 2 March 2018
                : 14 March 2018
                Categories
                Regular Article

                diffusion tensor imaging,fiber tractography,age,pediatric spinal cord

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