Biology subjects

Arulkumaran, S.

Publications and source records attributed to Arulkumaran, S..

3 recordsLinked to original sources

bioRxiv2024

Verifying the concordance between motion corrected and conventional MPRAGE for pediatric morphometric analysis

PurposeTo validate a retrospective motion correction technique, Distributed and Incoherent Sample Orders for Reconstruction Deblurring using Encoding Redundancy (DISORDER), for pediatric brain morphometry. MethodsTwo T1-weighted MPRAGE 3D datasets were acquired at 3T in thirty-seven children, median age 7.75 years; one with conventional linear phase encoding and one using DISORDER. MPRAGE images were scored as motion-free or motion-corrupt. Cortical morphometry and regional brain volumes were measured with FreeSurfer, subcortical grey matter (GM) with FSL-FIRST, and hippocampal volumes with HippUnfold. Intraclass correlation coefficient (ICC) was used to determine agreement between the 2 MPRAGE acquisitions. Mann-Whitney U was used to test the difference between measures obtained using DISORDER and (i) motion-free and (ii) motion-corrupt conventional MPRAGE data. ResultsICC measures were good/excellent for most subcortical GM (motion-free, 0.75-0.96; motion-corrupt, 0.62-0.98) and regional brain volumes (motion-free 0.47-0.99; motion-corrupt, 0.54-0.99) between conventional MPRAGE and DISORDER data, except for the amygdala and nucleus accumbens (motion-free, 0.38-0.65; motion- corrupt, 0.1-0.42). However, these values were less consistent for motion-corrupt conventional MPRAGE data for hippocampal volumes (motion-free 0.65-0.99; motion-corrupt, 0.11-0.91) and cortical measures (motion-free 0.76-0.98; motion- corrupt, 0.09-0.74). Mann-Whitney U showed percentage differences in measures obtained with motion-corrupt conventional MPRAGE compared to DISORDER data were significantly greater than in those obtained using motion-free conventional MPRAGE data in 22/58 structures. ConclusionIn the absence of motion, morphometric measures obtained using DISORDER are largely consistent with those from conventional MPRAGE data, whereas improved reliability is obtained by DISORDER for motion-degraded scans. This study validates DISORDER for brain morphometric studies in children.

neuroscience↗

bioRxiv2020

Individualized characterization of volumetric development in the preterm brain

The diverse cerebral consequences of preterm birth create significant challenges for understanding pathogenesis or predicting later outcome. Instead of focusing on describing effects common to the group, comparing individual infants against robust normative data offers a powerful alternative to study brain maturation. Here we used Gaussian process regression to create normative curves characterising brain volumetric development in 274 term-born infants, modelling for age at scan and sex. We then compared 89 preterm infants scanned at termequivalent age to these normative charts, relating individual deviations from typical volumetric development to perinatal risk factors and later neurocognitive scores. To test generalisability, we used a second independent dataset comprising of 253 preterm infants scanned using different acquisition parameters and scanner. We describe rapid, non-uniform brain growth during the neonatal period. In both preterm cohorts, cerebral atypicalities were widespread, often multiple, and varied highly between individuals. Deviations from normative development were associated with respiratory support, nutrition, birth weight, and later neurocognition, demonstrating their clinical relevance. Group-level understanding of the preterm brain disguise a large degree of individual differences. We provide a method and normative dataset that offer a more precise characterisation of the cerebral consequences of preterm birth by profiling the individual neonatal brain.

neuroscience↗

bioRxiv2019

ADHD symptoms and their neurodevelopmental correlates in children born very preterm

This study investigated the association between attention-deficit/hyperactivity disorder (ADHD) symptomatology in preschool-aged children who were born very preterm (<32 weeks) and cognitive outcomes, clinical risk and socio-demographic characteristics. 119 very preterm children who participated in the Evaluation of Preterm Imaging Study at term-equivalent age were assessed at a mean age of 4.5 years. Parents completed the ADHD Rating Scale IV, a norm-referenced checklist that evaluates ADHD symptomatology according to diagnostic criteria, and the Behavior Rating Inventory of Executive Function-Preschool version. Children completed the Wechsler Preschool and Primary Scales of Intelligence and the Forward Digit Span task. Longitudinal data including perinatal clinical, qualitative MRI classification, socio-demographic variables and neurodevelopmental disabilities were investigated in relation to ADHD symptomatology. All results were corrected for multiple comparisons using false discovery rate. Results showed that although the proportion of very preterm children with clinically significant ADHD did not differ from normative data after excluding those with neurodevelopmental disabilities, 32.7% met criteria for subthreshold ADHD inattentive type and 33.6% for combined type, which was higher than the expected 20% in normative samples. Higher ADHD symptom scores (all) were associated with greater executive dysfunction (inhibitory self-control, flexibility, and emergent metacognition, corrected p<0.001 for all tests). Higher inattentive ADHD symptom scores were associated with lower IQ ({rho}=-0.241, p=0.036) and higher perinatal clinical risk (more days on mechanical ventilation ({rho}=0.206, p=0.025) and more days on parenteral nutrition ({rho}=0.223, p=0.015)). Higher hyperactive ADHD symptom scores instead were associated with lower socio-economic status ({rho}=0.278, p=0.002). These results highlight the importance of monitoring and supporting the development of very preterm children throughout the school years, as subthreshold ADHD symptoms represent risk factors for psychosocial problems and for receiving a future clinical diagnosis of ADHD.

neuroscience↗