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      Advanced MRI analysis to detect white matter brain injury in growth restricted newborn lambs

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          Abstract

          Background

          Fetal growth restriction (FGR) is a serious pregnancy complication associated with increased risk of adverse neurodevelopment and neuromorbidity. Current imaging techniques, including conventional magnetic resonance imaging (MRI), are not sensitive enough to detect subtle structural abnormalities in the FGR brain. We examined whether advanced MRI analysis techniques have the capacity to detect brain injury (particularly white matter injury) caused by chronic hypoxia-induced fetal growth restriction in newborn preterm lambs.

          Methods

          Surgery was undertaken in twin bearing pregnant ewes at 88–90 days gestation (term = 150 days) to induce FGR in one fetus. At 127 days gestation (~32 weeks human brain development), FGR and control (appropriate for gestational age, AGA) lambs were delivered by caesarean section, intubated and ventilated. Conventional and advanced brain imaging was conducted within the first two hours of life using a 3T MRI scanner. T1-weighted (T1w) and T2-weighted (T2w) structural imaging, magnetic resonance spectroscopy (MRS), and diffusion MRI (dMRI) data were acquired. Diffusion tensor imaging (DTI) modelling and analysis of dMRI data included the following regions of interest (ROIs): subcortical white matter, periventricular white matter, cerebellum, hippocampus, corpus callosum and thalamus. Fixel-based analysis of 3-tissue constrained spherical deconvolution (CSD) of the dMRI data was performed and compared between FGR and AGA lambs. Lambs were euthanised immediately after the scans and brain histology performed in the regions of interest to correlate with imaging.

          Results

          FGR and AGA lamb (body weight, mean (SD): 2.2(0.5) vs. 3.3(0.3) kg, p = .002) MRI brain scans were analysed. There were no statistically significant differences observed between the groups in conventional T1w, T2w or MRS brain data. Mean, axial and radial diffusivity, and fractional anisotropy indices obtained from DTI modelling also did not show any statistically significant differences between groups in the ROIs. Fixel-based analysis of 3-tissue CSD, however, did reveal a decrease in fibre cross-section (FC, p < .05) but not in fibre density (FD) or combined fibre density and cross-section (FDC) in FGR vs. AGA lamb brains. The specific tracts that showed a decrease in FC were in the regions of the periventricular white matter, hippocampus and cerebellar white matter, and were supported by histological evidence of white matter hypomyelination and disorganisation in corresponding FGR lamb brain regions.

          Conclusions

          The neuropathology associated with FGR in neonatal preterm lambs is subtle and imaging detection may require advanced MRI and tract-based analysis techniques. Fixel-based analysis of 3-tissue CSD demonstrates that the preterm neonatal FGR brain shows evidence of macrostructural (cross-sectional) deficits in white matter subsequent to altered antenatal development. These findings can inform analysis of similar brain pathology in neonatal infants.

          Highlights

          • FGR brain injury can be subtle, and not easily detected on conventional imaging.

          • Fixel-based analysis showed differences in fibre content of FGR lamb brain tracts.

          • Histological stain confirmed myelination deficits in corresponding brain regions.

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          Most cited references27

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          The consequences of fetal growth restriction on brain structure and neurodevelopmental outcome.

          Fetal growth restriction (FGR) is a significant complication of pregnancy describing a fetus that does not grow to full potential due to pathological compromise. FGR affects 3-9% of pregnancies in high-income countries, and is a leading cause of perinatal mortality and morbidity. Placental insufficiency is the principal cause of FGR, resulting in chronic fetal hypoxia. This hypoxia induces a fetal adaptive response of cardiac output redistribution to favour vital organs, including the brain, and is in consequence called brain sparing. Despite this, it is now apparent that brain sparing does not ensure normal brain development in growth-restricted fetuses. In this review we have brought together available evidence from human and experimental animal studies to describe the complex changes in brain structure and function that occur as a consequence of FGR. In both humans and animals, neurodevelopmental outcomes are influenced by the timing of the onset of FGR, the severity of FGR, and gestational age at delivery. FGR is broadly associated with reduced total brain volume and altered cortical volume and structure, decreased total number of cells and myelination deficits. Brain connectivity is also impaired, evidenced by neuronal migration deficits, reduced dendritic processes, and less efficient networks with decreased long-range connections. Subsequent to these structural alterations, short- and long-term functional consequences have been described in school children who had FGR, most commonly including problems in motor skills, cognition, memory and neuropsychological dysfunctions.
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            Connectivity-based fixel enhancement: Whole-brain statistical analysis of diffusion MRI measures in the presence of crossing fibres

            In brain regions containing crossing fibre bundles, voxel-average diffusion MRI measures such as fractional anisotropy (FA) are difficult to interpret, and lack within-voxel single fibre population specificity. Recent work has focused on the development of more interpretable quantitative measures that can be associated with a specific fibre population within a voxel containing crossing fibres (herein we use fixel to refer to a specific fibre population within a single voxel ). Unfortunately, traditional 3D methods for smoothing and cluster-based statistical inference cannot be used for voxel-based analysis of these measures, since the local neighbourhood for smoothing and cluster formation can be ambiguous when adjacent voxels may have different numbers of fixels, or ill-defined when they belong to different tracts. Here we introduce a novel statistical method to perform whole-brain fixel-based analysis called connectivity-based fixel enhancement (CFE). CFE uses probabilistic tractography to identify structurally connected fixels that are likely to share underlying anatomy and pathology. Probabilistic connectivity information is then used for tract-specific smoothing (prior to the statistical analysis) and enhancement of the statistical map (using a threshold-free cluster enhancement-like approach). To investigate the characteristics of the CFE method, we assessed sensitivity and specificity using a large number of combinations of CFE enhancement parameters and smoothing extents, using simulated pathology generated with a range of test-statistic signal-to-noise ratios in five different white matter regions (chosen to cover a broad range of fibre bundle features). The results suggest that CFE input parameters are relatively insensitive to the characteristics of the simulated pathology. We therefore recommend a single set of CFE parameters that should give near optimal results in future studies where the group effect is unknown. We then demonstrate the proposed method by comparing apparent fibre density between motor neurone disease (MND) patients with control subjects. The MND results illustrate the benefit of fixel-specific statistical inference in white matter regions that contain crossing fibres.
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              Primary cortical folding in the human newborn: an early marker of later functional development.

              In the human brain, the morphology of cortical gyri and sulci is complex and variable among individuals, and it may reflect pathological functioning with specific abnormalities observed in certain developmental and neuropsychiatric disorders. Since cortical folding occurs early during brain development, these structural abnormalities might be present long before the appearance of functional symptoms. So far, the precise mechanisms responsible for such alteration in the convolution pattern during intra-uterine or post-natal development are still poorly understood. Here we compared anatomical and functional brain development in vivo among 45 premature newborns who experienced different intra-uterine environments: 22 normal singletons, 12 twins and 11 newborns with intrauterine growth restriction (IUGR). Using magnetic resonance imaging (MRI) and dedicated post-processing tools, we investigated early disturbances in cortical formation at birth, over the developmental period critical for the emergence of convolutions (26-36 weeks of gestational age), and defined early 'endophenotypes' of sulcal development. We demonstrated that twins have a delayed but harmonious maturation, with reduced surface and sulcation index compared to singletons, whereas the gyrification of IUGR newborns is discordant to the normal developmental trajectory, with a more pronounced reduction of surface in relation to the sulcation index compared to normal newborns. Furthermore, we showed that these structural measurements of the brain at birth are predictors of infants' outcome at term equivalent age, for MRI-based cerebral volumes and neurobehavioural development evaluated with the assessment of preterm infant's behaviour (APIB).
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                Author and article information

                Contributors
                Journal
                Neuroimage Clin
                Neuroimage Clin
                NeuroImage : Clinical
                Elsevier
                2213-1582
                23 August 2019
                2019
                23 August 2019
                : 24
                : 101991
                Affiliations
                [a ]Monash Newborn, Monash Children's Hospital, Melbourne, Australia
                [b ]Department of Paediatrics, Monash University, Melbourne, Australia
                [c ]The Ritchie Centre, Hudson Institute of Medical Research, Melbourne, Australia
                [d ]Monash Biomedical Imaging, Monash University, Melbourne, Australia
                [e ]The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia
                [f ]The Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia
                [g ]Department of Neuroscience, Central Clinical School, Monash University, Australia
                [h ]Department of Obstetrics and Gynaecology, Monash University, Melbourne, Australia
                [i ]Diagnostic Imaging, Monash Health, Melbourne, Australia
                [j ]Commonwealth Scientific and Industrial Research Organisation, Brisbane, Australia
                [k ]The Turner Institute for Brain and Mental Health, Monash University, Melbourne, Australia
                [l ]CSIRO Health and Biosecurity, Parkville, Victoria, Australia
                Author notes
                [* ]Corresponding author at: Monash Children's Hospital, 246 Clayton Road, Clayton, Melbourne, VIC 3168, Australia. atul.malhotra@ 123456monash.edu
                Article
                S2213-1582(19)30341-9 101991
                10.1016/j.nicl.2019.101991
                6728876
                31473545
                1a9dadcf-7b30-45d0-af52-7e659a2da3e5
                © 2019 The Authors

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

                History
                : 23 June 2019
                : 6 August 2019
                : 21 August 2019
                Categories
                Regular Article

                fixel-based analysis,tractography,myelination,structure,fibre

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