Brain White Matter Development Over the First 13 Years in Very Preterm and Typically Developing Children Based on the T 1-w/T 2-w Ratio.

BACKGROUND AND OBJECTIVES: To investigate brain regional white matter development in full-term (FT) and very preterm (VP) children at term equivalent and 7 and 13 years of age based on the ratio of T 1- and T 2-weighted MRI (T 1-w/T 2-w), including (1) whether longitudinal changes differ between birth groups or sexes, (2) associations with perinatal risk factors in VP children, and (3) relationships with neurodevelopmental outcomes at 13 years. METHODS: Prospective longitudinal cohort study of VP (born <30 weeks' gestation or <1,250 g) and FT infants born between 2001 and 2004 and followed up at term equivalent and 7 and 13 years of age, including MRI studies and neurodevelopmental assessments. T 1-w/T 2-w images were parcellated into 48 white matter regions of interest. RESULTS: Of 224 VP participants and 76 FT participants, 197 VP and 55 FT participants had useable T 1-w/T 2-w data from at least one timepoint. T 1-w/T 2-w values increased between term equivalent and 13 years of age, with little evidence that longitudinal changes varied between birth groups or sexes. VP birth, neonatal brain abnormalities, being small for gestational age, and postnatal infection were associated with reduced regional T 1-w/T 2-w values in childhood and adolescence. Increased T 1-w/T 2-w values across the white matter at 13 years were associated with better motor and working memory function for all children. Within the FT group only, larger increases in T 1-w/T 2-w values from term equivalent to 7 years were associated with poorer attention and executive function, and higher T 1-w/T 2-w values at 7 years were associated with poorer mathematics performance. DISCUSSION: VP birth and multiple known perinatal risk factors are associated with long-term reductions in the T 1-w/T 2-w ratio in white matter regions in childhood and adolescence, which may relate to alterations in microstructure and myelin content. Increased T 1-w/T 2-w ratio at 13 years appeared to be associated with better motor and working memory function and there appeared to be developmental differences between VP and FT children in the associations for attention, executive functioning, and mathematics performance.

Automated Perfusion-Diffusion Magnetic Resonance Imaging in Childhood Arterial Ischemic Stroke.

Background and Purpose: Recent studies using automated perfusion imaging software have identified adults most likely to benefit from reperfusion therapies in extended time windows. The time course of penumbral tissue is poorly characterized in childhood arterial ischemic stroke (AIS). We explore the feasibility of using automated perfusion-diffusion imaging software to characterize penumbra in childhood AIS. Methods: An observational cohort study of children with acute unilateral AIS presenting to our institution. Diffusion-weighted imaging and dynamic susceptibility contrast perfusion magnetic resonance imaging performed within 72 hours of symptom onset were necessary for inclusion. Perfusion-diffusion mismatch was estimated using RAPID software. Ischemic core was defined as apparent diffusion coefficient <620×10−6 mm2/s and hypoperfusion as Tmax >6 seconds. Favorable mismatch profile was defined as core volume <70 mL, mismatch volume ≥15 mL, and a mismatch ratio ≥1.8. Results: Twenty-nine children (median 8 years old, interquartile range, 4.4­14.6) were included (26 unilateral middle cerebral artery and 3 unilateral cerebellar infarcts). Median Pediatric National Institutes of Health Stroke Scale was 4 (interquartile range, 3­11). Most cases had cryptogenic (n=11) or focal cerebral arteriopathy (n=9) causes. Median time-to-imaging =13.7 hours (interquartile range, 7.5­25.3). RAPID detected an ischemic core in 19 (66%) patients. In the remaining cases, the mean apparent diffusion coefficient values were mostly higher than the threshold as the majority of these presentations were delayed (median >21 hours) and infarct volumes were small (<3.5 mL). Overall, 3 children, imaged at 3.75, 11, and 23.5 hours had favorable mismatch profiles. Conclusions: This study demonstrates it is feasible to rapidly assess perfusion-diffusion mismatch in childhood AIS using automated software. Favorable mismatch profiles, using adult-based parameters, persisted beyond the standard 4.5 hours window for thrombolysis, suggesting potential therapeutic benefit of RAPID use. Further work is required to determine the utility of perfusion-based imaging to guide clinical decision making, whether adult thresholds require modification in childhood AIS, and to investigate the effect of time-delay and cause on mismatch characteristics.

Axon density and axon orientation dispersion in children born preterm.

BACKGROUND: Very preterm birth (VPT, <32 weeks' gestation) is associated with altered white matter fractional anisotropy (FA), the biological basis of which is uncertain but may relate to changes in axon density and/or dispersion, which can be measured using Neurite Orientation Dispersion and Density Imaging (NODDI). This study aimed to compare whole brain white matter FA, axon dispersion, and axon density between VPT children and controls (born ≥37 weeks' gestation), and to investigate associations with perinatal factors and neurodevelopmental outcomes. METHODS: FA, neurite dispersion, and neurite density were estimated from multishell diffusion magnetic resonance images for 145 VPT and 33 control 7-year-olds. Diffusion values were compared between groups and correlated with perinatal factors (gestational age, birthweight, and neonatal brain abnormalities) and neurodevelopmental outcomes (IQ, motor, academic, and behavioral outcomes) using Tract-Based Spatial Statistics. RESULTS: Compared with controls, VPT children had lower FA and higher axon dispersion within many major white matter fiber tracts. Neonatal brain abnormalities predicted lower FA and higher axon dispersion in many major tracts in VPT children. Lower FA, higher axon dispersion, and lower axon density in various tracts correlated with poorer neurodevelopmental outcomes in VPT children. CONCLUSIONS: FA and NODDI measures distinguished VPT children from controls and were associated with neonatal brain abnormalities and neurodevelopmental outcomes. This study provides a more detailed and biologically meaningful interpretation of white matter microstructure changes associated with prematurity. Hum Brain Mapp 37:3080-3102, 2016. © 2016 Wiley Periodicals, Inc.

Structural connectivity relates to perinatal factors and functional impairment at 7years in children born very preterm.

OBJECTIVE: To use structural connectivity to (1) compare brain networks between typically and atypically developing (very preterm) children, (2) explore associations between potential perinatal developmental disturbances and brain networks, and (3) describe associations between brain networks and functional impairments in very preterm children. METHODS: 26 full-term and 107 very preterm 7-year-old children (born <30weeks' gestational age and/or <1250g) underwent T1- and diffusion-weighted imaging. Global white matter fibre networks were produced using 80 cortical and subcortical nodes, and edges were created using constrained spherical deconvolution-based tractography. Global graph theory metrics were analysed, and regional networks were identified using network-based statistics. Cognitive and motor function were assessed at 7years of age. RESULTS: Compared with full-term children, very preterm children had reduced density, lower global efficiency and higher local efficiency. Those with lower gestational age at birth, infection or higher neonatal brain abnormality score had reduced connectivity. Reduced connectivity within a widespread network was predictive of impaired IQ, while reduced connectivity within the right parietal and temporal lobes was associated with motor impairment in very preterm children. CONCLUSIONS: This study utilised an innovative structural connectivity pipeline to reveal that children born very preterm have less connected and less complex brain networks compared with typically developing term-born children. Adverse perinatal factors led to disturbances in white matter connectivity, which in turn are associated with impaired functional outcomes, highlighting novel structure-function relationships.

Brain extraction using the watershed transform from markers.

Isolation of the brain from other tissue types in magnetic resonance (MR) images is an important step in many types of neuro-imaging research using both humans and animal subjects. The importance of brain extraction is well appreciated-numerous approaches have been published and the benefits of good extraction methods to subsequent processing are well known. We describe a tool-the marker based watershed scalper (MBWSS)-for isolating the brain in T1-weighted MR images built using filtering and segmentation components from the Insight Toolkit (ITK) framework. The key elements of MBWSS-the watershed transform from markers and aggressive filtering with large kernels-are techniques that have rarely been used in neuroimaging segmentation applications. MBWSS is able to reliably isolate the brain without expensive preprocessing steps, such as registration to an atlas, and is therefore useful as the first stage of processing pipelines. It is an informative example of the level of accuracy achievable without using priors in the form of atlases, shape models or libraries of examples. We validate the MBWSS using a publicly available dataset, a paediatric cohort, an adolescent cohort, intra-surgical scans and demonstrate flexibility of the approach by modifying the method to extract macaque brains.

Saccadic eye movement characteristics in adult Niemann-Pick Type C disease: relationships with disease severity and brain structural measures.

Niemann-Pick Type C disease (NPC) is a rare genetic disorder of lipid metabolism. A parameter related to horizontal saccadic peak velocity was one of the primary outcome measures in the clinical trial assessing miglustat as a treatment for NPC. Neuropathology is widespread in NPC, however, and could be expected to affect other saccadic parameters. We compared horizontal saccadic velocity, latency, gain, antisaccade error percentage and self-paced saccade generation in 9 adult NPC patients to data from 10 age-matched controls. These saccadic measures were correlated with appropriate MRI-derived brain structural measures (e.g., dorsolateral prefrontal cortex, frontal eye fields, supplemental eye fields, parietal eye fields, pons, midbrain and cerebellar vermis) and with measures of disease severity and duration. The best discriminators between groups were reflexive saccade gain and the two volitional saccade measures. Gain was also the strongest correlate with disease severity and duration. Most of the saccadic measures showed strongly significant correlations with neurophysiologically appropriate brain regions. While our patient sample is small, the apparent specificity of these relationships suggests that as new diagnostic methods and treatments become available for NPC, a broader range of saccadic measures may be useful tools for the assessment of disease progression and treatment efficacy.

Thickness profile generation for the corpus callosum using Laplace's equation.

The corpus callosum facilitates communication between the cerebral hemispheres. Morphological abnormalities of the corpus callosum have been identified in numerous psychiatric and neurological disorders. To quantitatively analyze the thickness profile of the corpus callosum, we adapted an automatic thickness measurement method, which was originally used on magnetic resonance (MR) images of the cerebral cortex (Hutton et al. [2008]: NeuroImage 40:1701-10; Jones et al. [2002]: Hum Brain Mapp 11:12-32; Schmitt and Böhme [2002]: NeuroImage 16:1103-9; Yezzi and Prince [2003]: IEEE Trans Med Imaging 22:1332-9), to MR images of the corpus callosum. The thickness model was derived by computing a solution to Laplace's equation evaluated on callosal voxels. The streamlines from this solution form non-overlapping, cross-sectional contours the lengths of which are modeled as the callosal thickness. Apart from the semi-automated segmentation and endpoint selection procedures, the method is fully automated, robust, and reproducible. We compared the Laplace method with the orthogonal projection technique previously published (Walterfang et al. [2009a]: Psych Res Neuroimaging 173:77-82; Walterfang et al. [2008a]: Br J Psychiatry 192:429-34; Walterfang et al. [2008b]: Schizophr Res 103:1-10) on a cohort of 296 subjects, composed of 86 patients with chronic schizophrenia (CSZ), 110 individuals with first-episode psychosis, 100 individuals at ultra-high risk for psychosis (UHR; 27 of whom later developed psychosis, UHR-P, and 73 who did not, UHR-NP), and 55 control subjects (CTL). We report similar patterns of statistically significant differences in regional callosal thickness with respect to the comparisons CSZ vs. CTL, UHR vs. CTL, UHR-P vs. UHR-NP, and UHR vs. CTL.

DFBIdb: a software package for neuroimaging data management.

We present DFBIdb: a suite of tools for efficient management of neuroimaging project data. Specifically, DFBIdb was designed to allow users to quickly perform routine management tasks of sorting, archiving, exploring, exporting and organising raw data. DFBIdb was implemented as a collection of Python scripts that maintain a project-based, centralised database that is based on the XCEDE 2 data model. Project data is imported from a filesystem hierarchy of raw files, which is an often-used convention of imaging devices, using a single script that catalogues meta-data into a modified XCEDE 2 data model. During the import process data are reversibly anonymised, archived and compressed. The import script was designed to support multiple file formats and features an extensible framework that can be adapted to novel file formats. An ACL-based security model, with accompanying graphical management tools, was implemented to provide a straightforward method to restrict access to raw and meta-data. Graphical user interfaces are provided for data exploration. DFBIdb includes facilities to export, convert and organise customisable subsets of project data according to user-specified criteria. The command-line interface was implemented to allow users to incorporate database commands into more complex scripts that may be utilised to automate data management tasks. By using DFBIdb, neuroimaging laboratories will be able to perform routine data management tasks in an efficient manner.