Identification of neonatal white matter on DTI: influence of more inclusive thresholds for atlas segmentation.

PURPOSE: Semi-automated diffusion tensor imaging (DTI) analysis of white matter (WM) microstructure offers a clinically feasible technique to assess neonatal brain development and provide early prognosis, but is limited by variable methods and insufficient evidence regarding optimal parameters. The purpose of this research was to investigate the influence of threshold values on semi-automated, atlas-based brain segmentation in very-low-birth-weight (VLBW) preterm infants at near-term age. MATERIALS AND METHODS: DTI scans were analyzed from 45 VLBW preterm neonates at near-term-age with no brain abnormalities evident on MRI. Brain regions were selected with a neonatal brain atlas and threshold values: trace <0.006 mm2/s, fractional anisotropy (FA)>0.15, FA>0.20, and FA>0.25. Relative regional volumes, FA, axial diffusivity (AD), and radial diffusivity (RD) were compared for twelve WM regions. RESULTS: Near-term brain regions demonstrated differential effects from segmentation with the three FA thresholds. Regional DTI values and volumes selected in the PLIC, CereP, and RLC varied the least with the application of different FA thresholds. Overall, application of higher FA thresholds significantly reduced brain region volume selected, increased variability, and resulted in higher FA and lower RD values. The lower threshold FA>0.15 selected 78±21% of original volumes segmented by the atlas, compared to 38±12% using threshold FA>0.25. CONCLUSION: Results indicate substantial and differential effects of atlas-based DTI threshold parameters on regional volume and diffusion scalars. A lower, more inclusive FA threshold than typically applied for adults is suggested for consistent analysis of WM regions in neonates

Prediction of cognitive and motor development in preterm children using exhaustive feature selection and cross-validation of near-term white matter microstructure.

BACKGROUND: Advanced neuroimaging and computational methods offer opportunities for more accurate prognosis. We hypothesized that near-term regional white matter (WM) microstructure, assessed on diffusion tensor imaging (DTI), using exhaustive feature selection with cross-validation would predict neurodevelopment in preterm children. METHODS: Near-term MRI and DTI obtained at 36.6 ± 1.8 weeks postmenstrual age in 66 very-low-birth-weight preterm neonates were assessed. 60/66 had follow-up neurodevelopmental evaluation with Bayley Scales of Infant-Toddler Development, 3rd-edition (BSID-III) at 18-22 months. Linear models with exhaustive feature selection and leave-one-out cross-validation computed based on DTI identified sets of three brain regions most predictive of cognitive and motor function; logistic regression models were computed to classify high-risk infants scoring one standard deviation below mean. RESULTS: Cognitive impairment was predicted (100% sensitivity, 100% specificity; AUC = 1) by near-term right middle-temporal gyrus MD, right cingulate-cingulum MD, left caudate MD. Motor impairment was predicted (90% sensitivity, 86% specificity; AUC = 0.912) by left precuneus FA, right superior occipital gyrus MD, right hippocampus FA. Cognitive score variance was explained (29.6%, cross-validated Rˆ2 = 0.296) by left posterior-limb-of-internal-capsule MD, Genu RD, right fusiform gyrus AD. Motor score variance was explained (31.7%, cross-validated Rˆ2 = 0.317) by left posterior-limb-of-internal-capsule MD, right parahippocampal gyrus AD, right middle-temporal gyrus AD. CONCLUSION: Search in large DTI feature space more accurately identified neonatal neuroimaging correlates of neurodevelopment

Prediction of Gait Impairment in Toddlers Born Preterm From Near-Term Brain Microstructure Assessed With DTI, Using Exhaustive Feature Selection and Cross-Validation.

AIM: To predict gait impairment in toddlers born preterm with very-low-birth-weight (VLBW), from near-term white-matter microstructure assessed with diffusion tensor imaging (DTI), using exhaustive feature selection, and cross-validation. METHODS: Near-term MRI and DTI of 48 bilateral and corpus callosum regions were assessed in 66 VLBW preterm infants; at 18-22 months adjusted-age, 52/66 participants completed follow-up gait assessment of velocity, step length, step width, single-limb support and the Toddle Temporal-spatial Deviation Index (TDI). Multiple linear models with exhaustive feature selection and leave-one-out cross-validation were employed in this prospective cohort study: linear and logistic regression identified three brain regions most correlated with gait outcome. RESULTS: Logistic regression of near-term DTI correctly classified infants high-risk for impaired gait velocity (93% sensitivity, 79% specificity), right and left step length (91% and 93% sensitivity, 85% and 76% specificity), single-limb support (100% and 100% sensitivity, 100% and 100% specificity), step width (85% sensitivity, 80% specificity), and Toddle TDI (85% sensitivity, 75% specificity). Linear regression of near-term brain DTI and toddler gait explained 32%-49% variance in gait temporal-spatial parameters. Traditional MRI methods did not predict gait in toddlers. INTERPRETATION: Near-term brain microstructure assessed with DTI and statistical learning methods predicted gait impairment, explaining substantial variance in toddler gait. Results indicate that at near term age, analysis of a set of brain regions using statistical learning methods may offer more accurate prediction of outcome at toddler age. Infants high risk for single-limb support impairment were most accurately predicted. As a fundamental element of biped gait, single-limb support may be a sensitive marker of gait impairment, influenced by early neural correlates that are evolutionarily and developmentally conserved. For infants born preterm, early prediction of gait impairment can help guide early, more effective intervention to improve quality of life. WHAT THIS PAPER ADDS: • Accurate prediction of toddler gait from near-term brain microstructure on DTI.• Use of machine learning analysis of neonatal neuroimaging to predict gait.• Early prediction of gait impairment to guide early treatment for children born preterm

The Unconference Research Initiative

This group responded to the challenge in part with a conceptual piece of creative writing–a “conference snapshot” written by the Unconference Research Initiative (URI). The initiative is a transdisciplinary group of scholars who build conference infrastructure to support conference content. Robots? Check. Karaoke? Check

Neonatal physiological correlates of near-term brain development on MRI and DTI in very-low-birth-weight preterm infants.

Structural brain abnormalities identified at near-term age have been recognized as potential predictors of neurodevelopment in children born preterm. The aim of this study was to examine the relationship between neonatal physiological risk factors and early brain structure in very-low-birth-weight (VLBW) preterm infants using structural MRI and diffusion tensor imaging (DTI) at near-term age. Structural brain MRI, diffusion-weighted scans, and neonatal physiological risk factors were analyzed in a cross-sectional sample of 102 VLBW preterm infants (BW ≤ 1500 g, gestational age (GA) ≤ 32 weeks), who were admitted to the Lucile Packard Childrens Hospital, Stanford NICU and recruited to participate prior to routine near-term brain MRI conducted at 36.6 ± 1.8 weeks postmenstrual age (PMA) from 2010 to 2011; 66/102 also underwent a diffusion-weighted scan. Brain abnormalities were assessed qualitatively on structural MRI, and white matter (WM) microstructure was analyzed quantitatively on DTI in six subcortical regions defined by DiffeoMap neonatal brain atlas. Specific regions of interest included the genu and splenium of the corpus callosum, anterior and posterior limbs of the internal capsule, the thalamus, and the globus pallidus. Regional fractional anisotropy (FA) and mean diffusivity (MD) were calculated using DTI data and examined in relation to neonatal physiological risk factors including gestational age (GA), bronchopulmonary dysplasia (BPD), necrotizing enterocolitis (NEC), retinopathy of prematurity (ROP), and sepsis, as well as serum levels of C-reactive protein (CRP), glucose, albumin, and total bilirubin. Brain abnormalities were observed on structural MRI in 38/102 infants including 35% of females and 40% of males. Infants with brain abnormalities observed on MRI had higher incidence of BPD (42% vs. 25%) and sepsis (21% vs. 6%) and higher mean and peak serum CRP levels, respectively, (0.64 vs. 0.34 mg/dL, p = .008; 1.57 vs. 0.67 mg/dL, p= .006) compared to those without. The number of signal abnormalities observed on structural MRI correlated to mean and peak CRP (rho = .316, p = .002; rho = .318, p= .002). The number of signal abnormalities observed on MRI correlated with thalamus MD (left: r= .382, p= .002; right: r= .400, p= .001), controlling for PMA-at-scan. Thalamus WM microstructure demonstrated the strongest associations with neonatal risk factors. Higher thalamus MD on the left and right, respectively, was associated with lower GA (r = -.322, p = .009; r= -.381, p= .002), lower mean albumin (r = -.276, p= .029; r= -.385, p= .002), and lower mean bilirubin (r = -.293, p= .020; r= -.337 p= .007). Results suggest that at near-term age, thalamus WM microstructure may be particularly vulnerable to certain neonatal risk factors. Interactions between albumin, bilirubin, phototherapy, and brain development warrant further investigation. Identification of physiological risk factors associated with selective vulnerability of certain brain regions at near-term age may clarify the etiology of neurodevelopmental impairment and inform neuroprotective treatment for VLBW preterm infants

The effect of stress on the expression of the amyloid precursor protein in rat brain

AbstractThe abnormal processing of the amyloid precursor protein (APP) is a pivotal event in the development of the unique pathology that defines Alzheimer's disease (AD). Stress, and the associated increase in corticosteroids, appear to accelerate brain ageing and may increase vulnerability to Alzheimer's disease via altered APP processing. In this study, rats were repeatedly exposed to an unavoidable stressor, an open elevated platform. Previous studies in this laboratory have shown that a single exposure produces a marked increase in plasma corticosterone levels but animals develop tolerance to this effect between 10 and 20 daily sessions. Twenty-four hours after stress, there was an increase in the ratio of the deglycosylated form of APP in the particulate fraction of the brain, which subsequently habituated after 20 days. The levels of soluble APP (APPs) tended to be lower in the stress groups compared to controls except for a significant increase in the hippocampus after 20 days of platform exposure. Since APPs is reported to have neurotrophic properties, this increased release may represent a neuroprotective response to repeated stress. It is possible that the ability to mount this response decreases with age thus increasing the vulnerability to stress-induced AD-related pathology

Identification of Neonatal White Matter on DTI: Influence of More Inclusive Thresholds for Atlas Segmentation

<div><p>Purpose</p><p>Semi-automated diffusion tensor imaging (DTI) analysis of white matter (WM) microstructure offers a clinically feasible technique to assess neonatal brain development and provide early prognosis, but is limited by variable methods and insufficient evidence regarding optimal parameters. The purpose of this research was to investigate the influence of threshold values on semi-automated, atlas-based brain segmentation in very-low-birth-weight (VLBW) preterm infants at near-term age.</p><p>Materials and Methods</p><p>DTI scans were analyzed from 45 VLBW preterm neonates at near-term-age with no brain abnormalities evident on MRI. Brain regions were selected with a neonatal brain atlas and threshold values: trace <0.006 mm²/s, fractional anisotropy (FA)>0.15, FA>0.20, and FA>0.25. Relative regional volumes, FA, axial diffusivity (AD), and radial diffusivity (RD) were compared for twelve WM regions.</p><p>Results</p><p>Near-term brain regions demonstrated differential effects from segmentation with the three FA thresholds. Regional DTI values and volumes selected in the PLIC, CereP, and RLC varied the least with the application of different FA thresholds. Overall, application of higher FA thresholds significantly reduced brain region volume selected, increased variability, and resulted in higher FA and lower RD values. The lower threshold FA>0.15 selected 78±21% of original volumes segmented by the atlas, compared to 38±12% using threshold FA>0.25.</p><p>Conclusion</p><p>Results indicate substantial and differential effects of atlas-based DTI threshold parameters on regional volume and diffusion scalars. A lower, more inclusive FA threshold than typically applied for adults is suggested for consistent analysis of WM regions in neonates.</p></div

The Unconference Research Initiative

This group responded to the challenge in part with a conceptual piece of creative writing–a “conference snapshot” written by the Unconference Research Initiative (URI). The initiative is a transdisciplinary group of scholars who build conference infrastructure to support conference content. Robots? Check. Karaoke? Check.</p

Volume of WM regions selected with three FA thresholds, reported as a percent of total volume as defined by the neonatal atlas and trace threshold (mean±95% confidence intervals), in the left and right hemispheres, represented by adjacent left and right bars.

<p>Volume of WM regions selected with three FA thresholds, reported as a percent of total volume as defined by the neonatal atlas and trace threshold (mean±95% confidence intervals), in the left and right hemispheres, represented by adjacent left and right bars.</p

Coefficients of variability (CV) of regional WM volumes for total volume as defined originally by the neonatal atlas and trace threshold, and for volumes defined by FA>0.15, FA>0.20, and FA>0.25 thresholds in the left and right hemispheres represented by adjacent left and right bars.

<p>Coefficients of variability (CV) of regional WM volumes for total volume as defined originally by the neonatal atlas and trace threshold, and for volumes defined by FA>0.15, FA>0.20, and FA>0.25 thresholds in the left and right hemispheres represented by adjacent left and right bars.</p