Self-injurious behaviours are associated with alterations in the somatosensory system in children with autism spectrum disorder.

Children with autism spectrum disorder (ASD) frequently engage in self-injurious behaviours, often in the absence of reporting pain. Previous research suggests that altered pain sensitivity and repeated exposure to noxious stimuli are associated with morphological changes in somatosensory and limbic cortices. Further evidence from postmortem studies with self-injurious adults has indicated alterations in the structure and organization of the temporal lobes; however, the effect of self-injurious behaviour on cortical development in children with ASD has not yet been determined. Thirty children and adolescents (mean age = 10.6 ± 2.5 years; range 7-15 years; 29 males) with a clinical diagnosis of ASD and 30 typically developing children (N = 30, mean age = 10.7 ± 2.5 years; range 7-15 years, 26 males) underwent T1-weighted magnetic resonance and diffusion tensor imaging. No between-group differences were seen in cerebral volume, surface area or cortical thickness. Within the ASD group, self-injury scores negatively correlated with thickness in the right superior parietal lobule t = 6.3, p \u3c 0.0001, bilateral primary somatosensory cortices (SI) (right: t = 4.4, p = 0.02; left: t = 4.48, p = 0.004) and the volume of the left ventroposterior (VP) nucleus of the thalamus (r = -0.52, p = 0.008). Based on these findings, we performed an atlas-based region-of-interest diffusion tensor imaging analysis between SI and the VP nucleus and found that children who engaged in self-injury had significantly lower fractional anisotropy (r = -0.4, p = 0.04) and higher mean diffusivity (r = 0.5, p = 0.03) values in the territory of the left posterior limb of the internal capsule. Additionally, greater incidence of self-injury was associated with increased radial diffusivity values in bilateral posterior limbs of the internal capsule (left: r = 0.5, p = 0.02; right: r = 0.5, p = 0.009) and corona radiata (left: r = 0.6, p = 0.005; right: r = 0.5, p = 0.009). Results indicate that self-injury is related to alterations in somatosensory cortical and subcortical regions and their supporting white-matter pathways. Findings could reflect use-dependent plasticity in the somatosensory system or disrupted brain development that could serve as a risk marker for self-injury

Tract-Based Spatial Statistics in Preterm-Born Neonates Predicts Cognitive and Motor Outcomes at 18 Months.

BACKGROUND AND PURPOSE: Adverse neurodevelopmental outcome is common in children born preterm. Early sensitive predictors of neurodevelopmental outcome such as MR imaging are needed. Tract-based spatial statistics, a diffusion MR imaging analysis method, performed at term-equivalent age (40 weeks) is a promising predictor of neurodevelopmental outcomes in children born very preterm. We sought to determine the association of tract-based spatial statistics findings before term-equivalent age with neurodevelopmental outcome at 18-months corrected age. MATERIALS AND METHODS: Of 180 neonates (born at 24-32-weeks\u27 gestation) enrolled, 153 had DTI acquired early at 32 weeks\u27 postmenstrual age and 105 had DTI acquired later at 39.6 weeks\u27 postmenstrual age. Voxelwise statistics were calculated by performing tract-based spatial statistics on DTI that was aligned to age-appropriate templates. At 18-month corrected age, 166 neonates underwent neurodevelopmental assessment by using the Bayley Scales of Infant Development, 3rd ed, and the Peabody Developmental Motor Scales, 2nd ed. RESULTS: Tract-based spatial statistics analysis applied to early-acquired scans (postmenstrual age of 30-33 weeks) indicated a limited significant positive association between motor skills and axial diffusivity and radial diffusivity values in the corpus callosum, internal and external/extreme capsules, and midbrain (P \u3c .05, corrected). In contrast, for term scans (postmenstrual age of 37-41 weeks), tract-based spatial statistics analysis showed a significant relationship between both motor and cognitive scores with fractional anisotropy in the corpus callosum and corticospinal tracts (P \u3c .05, corrected). Tract-based spatial statistics in a limited subset of neonates (n = 22) scanned at CONCLUSIONS: The strength of the association between fractional anisotropy values and neurodevelopmental outcome scores increased from early-to-late-acquired scans in preterm-born neonates, consistent with brain dysmaturation in this population

Quantitative assessment of white matter injury in preterm neonates: Association with outcomes.

OBJECTIVE: To quantitatively assess white matter injury (WMI) volume and location in very preterm neonates, and to examine the association of lesion volume and location with 18-month neurodevelopmental outcomes. METHODS: Volume and location of WMI was quantified on MRI in 216 neonates (median gestational age 27.9 weeks) who had motor, cognitive, and language assessments at 18 months corrected age (CA). Neonates were scanned at 32.1 postmenstrual weeks (median) and 68 (31.5%) had WMI; of 66 survivors, 58 (87.9%) had MRI and 18-month outcomes. WMI was manually segmented and transformed into a common image space, accounting for intersubject anatomical variability. Probability maps describing the likelihood of a lesion predicting adverse 18-month outcomes were developed. RESULTS: WMI occurs in a characteristic topology, with most lesions occurring in the periventricular central region, followed by posterior and frontal regions. Irrespective of lesion location, greater WMI volumes predicted poor motor outcomes ( CONCLUSIONS: The predictive value of frontal lobe WMI volume highlights the importance of lesion location when considering the neurodevelopmental significance of WMI. Frontal lobe lesions are of particular concern

Effects of age and symptomatology on cortical thickness in autism spectrum disorders

Several brain regions show structural and functional abnormalities in individuals with autism spectrum disorders (ASD), but the developmental trajectory of abnormalities in these structures and how they may relate to social and communicative impairments are still unclear. We assessed the effects of age on cortical thickness in individuals with ASD, between the ages of 7 and 39 years in comparison to typically developing controls. Additionally, we examined differences in cortical thickness in relation to symptomatology in the ASD group, and their association with age. Analyses were conducted using a general linear model, controlling for sex. Social and communication scores from the Autism Diagnostic Interview-Revised (ADI-R) were correlated with the thickness of regions implicated in those functions. Controls showed widespread cortical thinning relative to the ASD group. Within regions-of-interest, increased thickness in the rostral anterior cingulate cortex was associated with poorer social scores. Additionally, a significant interaction between age and social impairment was found in the orbitofrontal cortex, with more impaired younger children having decreased thickness in this region. These results suggest that differential neurodevelopmental trajectories are present in individuals with ASD and some differences are associated with diagnostic behaviours. © 2012 Elsevier Ltd. All rights reserved

Manual-protocol inspired technique for improving automated MR image segmentation during label fusion

Recent advances in multi-atlas based algorithms address many of the previous limitations in model-based and probabilistic segmentation methods. However, at the label fusion stage, a majority of algorithms focus primarily on optimizing weight-maps associated with the atlas library based on a theoretical objective function that approximates the segmentation error. In contrast, we propose a novel method-Autocorrecting Walks over Localized Markov Random Fields (AWoL-MRF)-that aims at mimicking the sequential process of manual segmentation, which is the gold-standard for virtually all the segmentation methods. AWoL-MRF begins with a set of candidate labels generated by a multi-atlas segmentation pipeline as an initial label distribution and refines low confidence regions based on a localized Markov random field (L-MRF) model using a novel sequential inference process (walks). We show that AWoL-MRF produces state-of-the-art results with superior accuracy and robustness with a small atlas library compared to existing methods. We validate the proposed approach by performing hippocampal segmentations on three independent datasets: (1) Alzheimer\u27s Disease Neuroimaging Database (ADNI); (2) First Episode Psychosis patient cohort; and (3) A cohort of preterm neonates scanned early in life and at term-equivalent age. We assess the improvement in the performance qualitatively as well as quantitatively by comparing AWoL-MRF with majority vote, STAPLE, and Joint Label Fusion methods. AWoL-MRF reaches a maximum accuracy of 0.881 (dataset 1), 0.897 (dataset 2), and 0.807 (dataset 3) based on Dice similarity coefficient metric, offering significant performance improvements with a smaller atlas library (\u3c 10) over compared methods. We also evaluate the diagnostic utility of AWoL-MRF by analyzing the volume differences per disease category in the ADNI1: Complete Screening dataset. We have made the source code for AWoL-MRF public at: https://github.com/CobraLab/AWoL-MRF

Automatic segmentation of the hippocampus for preterm neonates from early-in-life to term-equivalent age.

INTRODUCTION: The hippocampus, a medial temporal lobe structure central to learning and memory, is particularly vulnerable in preterm-born neonates. To date, segmentation of the hippocampus for preterm-born neonates has not yet been performed early-in-life (shortly after birth when clinically stable). The present study focuses on the development and validation of an automatic segmentation protocol that is based on the MAGeT-Brain (Multiple Automatically Generated Templates) algorithm to delineate the hippocampi of preterm neonates on their brain MRIs acquired at not only term-equivalent age but also early-in-life. METHODS: First, we present a three-step manual segmentation protocol to delineate the hippocampus for preterm neonates and apply this protocol on 22 early-in-life and 22 term images. These manual segmentations are considered the gold standard in assessing the automatic segmentations. MAGeT-Brain, automatic hippocampal segmentation pipeline, requires only a small number of input atlases and reduces the registration and resampling errors by employing an intermediate template library. We assess the segmentation accuracy of MAGeT-Brain in three validation studies, evaluate the hippocampal growth from early-in-life to term-equivalent age, and study the effect of preterm birth on the hippocampal volume. The first experiment thoroughly validates MAGeT-Brain segmentation in three sets of 10-fold Monte Carlo cross-validation (MCCV) analyses with 187 different groups of input atlases and templates. The second experiment segments the neonatal hippocampi on 168 early-in-life and 154 term images and evaluates the hippocampal growth rate of 125 infants from early-in-life to term-equivalent age. The third experiment analyzes the effect of gestational age (GA) at birth on the average hippocampal volume at early-in-life and term-equivalent age using linear regression. RESULTS: The final segmentations demonstrate that MAGeT-Brain consistently provides accurate segmentations in comparison to manually derived gold standards (mean Dice\u27s Kappa \u3e 0.79 and Euclidean distance CONCLUSIONS: MAGeT-Brain is capable of segmenting hippocampi accurately in preterm neonates, even at early-in-life. Hippocampal asymmetry with a larger right side is demonstrated on early-in-life images, suggesting that this phenomenon has its onset in the 3rd trimester of gestation. Hippocampal volume assessed at the time of early-in-life and term-equivalent age is linearly associated with GA at birth, whereby smaller volumes are associated with earlier birth

Improving medication management in multimorbidity: development of the MultimorbiditY COllaborative Medication Review And DEcision Making (MY COMRADE) intervention using the Behaviour Change Wheel.

BACKGROUND: Multimorbidity, the presence of two or more chronic conditions, affects over 60 % of patients in primary care. Due to its association with polypharmacy, the development of interventions to optimise medication management in patients with multimorbidity is a priority. The Behaviour Change Wheel is a new approach for applying behavioural theory to intervention development. Here, we describe how we have used results from a review of previous research, original research of our own and the Behaviour Change Wheel to develop an intervention to improve medication management in multimorbidity by general practitioners (GPs), within the overarching UK Medical Research Council guidance on complex interventions. METHODS: Following the steps of the Behaviour Change Wheel, we sought behaviours associated with medication management in multimorbidity by conducting a systematic review and qualitative study with GPs. From the modifiable GP behaviours identified, we selected one and conducted a focused behavioural analysis to explain why GPs were or were not engaging in this behaviour. We used the behavioural analysis to determine the intervention functions, behavioural change techniques and implementation plan most likely to effect behavioural change. RESULTS: We identified numerous modifiable GP behaviours in the systematic review and qualitative study, from which active medication review (rather than passive maintaining the status quo) was chosen as the target behaviour. Behavioural analysis revealed GPs' capabilities, opportunities and motivations relating to active medication review. We combined the three intervention functions deemed most likely to effect behavioural change (enablement, environmental restructuring and incentivisation) to form the MultimorbiditY COllaborative Medication Review And DEcision Making (MY COMRADE) intervention. MY COMRADE primarily involves the technique of social support: two GPs review the medications prescribed to a complex multimorbid patient together. Four other behavioural change techniques are incorporated: restructuring the social environment, prompts/cues, action planning and self-incentives. CONCLUSIONS: This study is the first to use the Behaviour Change Wheel to develop an intervention targeting multimorbidity and confirms the usability and usefulness of the approach in a complex area of clinical care. The systematic development of the MY COMRADE intervention will facilitate a thorough evaluation of its effectiveness in the next phase of this work

White matter injury predicts disrupted functional connectivity and microstructure in very preterm born neonates

© 2018 The Authors Objective: To determine whether the spatial extent and location of early-identified punctate white matter injury (WMI) is associated with regionally-specific disruptions in thalamocortical-connectivity in very-preterm born neonates. Methods: 37 very-preterm born neonates (median gestational age: 28.1 weeks; interquartile range [IQR]: 27–30) underwent early MRI (median age 32.9 weeks; IQR: 32–35), and WMI was identified in 13 (35%) neonates. Structural T1-weighted, resting-state functional Magnetic Resonance Imaging (rs-fMRI, n = 34) and Diffusion Tensor Imaging (DTI, n = 31) sequences were acquired using 3 T-MRI. A probabilistic map of WMI was developed for the 13 neonates demonstrating brain injury. A neonatal atlas was applied to the WMI maps, rs-fMRI and DTI analyses to extract volumetric, functional and microstructural data from regionally-specific brain areas. Associations of thalamocortical-network strength and alterations in fractional anisotropy (FA, a measure of white-matter microstructure) with WMI volume were assessed in general linear models, adjusting for age at scan and cerebral volumes. Results: WMI volume in the superior (β = −0.007; p =.02) and posterior corona radiata (β = −0.01; p =.01), posterior thalamic radiations (β = −0.01; p =.005) and superior longitudinal fasciculus (β = −0.02; p =.001) was associated with reduced connectivity strength between thalamus and parietal resting-state networks. WMI volume in the left (β = −0.02; p =.02) and right superior corona radiata (β = −0.03; p =.008), left posterior corona radiata (β = −0.03; p =.01), corpus callosum (β = −0.11; p \u3c.0001) and right superior longitudinal fasciculus (β = −0.02; p =.02) was associated with functional connectivity strength between thalamic and sensorimotor networks. Increased WMI volume was also associated with decreased FA values in the corpus callosum (β = −0.004, p =.015). Conclusions: Regionally-specific alterations in early functional and structural network complexity resulting from WMI may underlie impaired outcomes