Pallidum and lateral ventricle volume enlargement in autism spectrum disorder

Turner, Andia H.; Greenspan, Kiefer S.; Erp, Theo G.M. van

doi:10.1016/j.pscychresns.2016.04.003

Cited by 63 publications

(65 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our findings could be indicative of autistic patients exhibiting an initial period of overgrowth, followed by a normalization that eventually results in autistic patients exhibiting volumetric reductions at later ages, in agreement with previous research (Courchesne et al, 2001, 2003), however, more research is needed to interpret these findings. Our findings include known increases in ventricular volumes among the autistic group, in agreement with the literature (Turner et al, 2016). However, we've extended those findings by showing that patients with autism also have, on average, larger volumes of the choroid plexuses.…”

Section: Discussionsupporting

confidence: 93%

Regional volumetric abnormalities in pediatric autism revealed by structural magnetic resonance imaging

Levman

Vasung

MacDonald

et al. 2018

Intl J of Devlp Neuroscience

View full text Add to dashboard Cite

Autism is a group of complex neurodevelopmental disorders characterized by impaired social interaction, restricted and repetitive behavior. We performed a large-scale retrospective analysis of 1,996 structural magnetic resonance imaging (MRI) examinations of the brain from 1,769 autistic and neurologically typically developing patients (aged 0-32 years), and extracted regional volumetric measurements distributed across 463 brain regions of each patient. The youngest autistic patients (<2.5 years) were diagnosed after imaging and identified retrospectively. Our study demonstrates corpus callosum volumetric abnormalities among autistic patients that are associated with brain overgrowth in early childhood (0-5 years old), followed by a shift towards known decreased volumes in later ages. Results confirm known increases in ventricular volumes among autistic populations and extends those findings to increased volumes of the choroid plexus. Our study also demonstrates distributed volumetric abnormalities among autistic patients that affect a variety of key regional white and grey matter areas of the brain potentially associated with known symptoms of autism.

show abstract

Section: Discussionsupporting

confidence: 93%

Regional volumetric abnormalities in pediatric autism revealed by structural magnetic resonance imaging

Levman

Vasung

MacDonald

et al. 2018

Intl J of Devlp Neuroscience

View full text Add to dashboard Cite

show abstract

“…However the volume of the CSF may indirectly reflect tissue loss in regions of the brain (Pagnozzi et al, 2016), and so may prove to be an important biomarkers for brain related changes occurring due to ASD. Among the studies that have characterised cerebrospinal (CSF) volumes shown in Supplementary Table 4, there was a consistent finding of increased CSF volumes globally (Katuwal et al, 2016b), in extra‐axial or subarachnoid spaces (Shen et al, 2017, 2013), and in the lateral ventricles (Haar et al, 2016; Turner et al, 2016). This latter finding of ventricular enlargement was also commonly observed in low birth weight adult survivors (Movsas et al, 2013), a population with an increased risk of ASD, suggesting ventricular volume is a risk factor of altered development leading to ASD.…”

Section: Structural Biomarkers Of Asdmentioning

confidence: 86%

“…Commonly studies aim to quantify intracranial volume (ICV), which consists of both grey matter (GM) and white matter (WM), or GM and WM volume individually. All of these measures can be obtained with similar techniques, including the propagation of WM/GM labels from an atlas (Nordahl et al, 2011), or modelling tissue distributions with the EM algorithm as is done by both FSL's FAST (Knaus et al, 2017; Libero et al, 2016) and Statistical Parametric Mapping (SPM) (Grecucci et al, 2016; Riddle et al, 2017), or a combination of the two performed implicitly within FreeSurfer (Mahajan et al, 2016; Turner et al, 2016).…”

Section: Structural Biomarkers Of Asdmentioning

confidence: 99%

“…Although it is not yet understood how CSF relates to the aetiology of ASD, it may be an early structural sign of improper filtering and draining of waste particles, potentially leading to neuro‐inflammation and autism (Chez et al, 2007; Zimmerman et al, 2005). Furthermore, CSF volume can be segmented relatively easily from sMRI using FreeSurfer (Haar et al, 2016; Turner et al, 2016) or atlas‐based approaches (Shen et al, 2017) due to its high contrast boundary. This makes CSF volume, particularly in the extra‐axial space, a robust correlate of autism severity that can be easily identified even very early in infancy.…”

Section: Structural Biomarkers Of Asdmentioning

confidence: 99%

“…One of these studies utilised the MAGeT‐Brain multi‐atlas segmentation approach, which has been shown to achieve more accurate hippocampal volumes than FreeSurfer or FIRST on an Alzheimer's disease dataset (Pipitone et al, 2014). However, of the large‐scale studies using the ABIDE dataset, one study reported an increase in hippocampal volume using FreeSurfer (Turner et al, 2016), and another reporting no observable difference using FSL's FIRST (Zhang et al, 2018) To ascertain if hippocampal volume is a biomarker for autism, studies could look to utilise the MAGeT approach, or alternatively incorporate tailored atlases into FreeSurfer, which have been previously constructed using Bayesian inference (Saygin et al, 2017).…”

Section: Structural Biomarkers Of Asdmentioning

confidence: 99%

See 2 more Smart Citations

A systematic review of structural MRI biomarkers in autism spectrum disorder: A machine learning perspective

Pagnozzi

Conti

Calderoni

et al. 2018

Intl J of Devlp Neuroscience

119

101

View full text Add to dashboard Cite

Autism Spectrum Disorder (ASD) affects approximately 1% of the population and leads to impairments in social interaction, communication and restricted, repetitive behaviours. Establishing robust neuroimaging biomarkers of ASD using structural magnetic resonance imaging (MRI) is an important step for diagnosing and tailoring treatment, particularly early in life when interventions can have the greatest effect. However currently, there is mixed findings on the structural brain changes associated with autism. Therefore in this systematic review, recent (post-2007), high-resolution (3 T) MRI studies investigating brain morphology associated with ASD have been collated to identify robust neuroimaging biomarkers of ASD. A systematic search was conducted on three databases; PubMed, Web of Science and Scopus, resulting in 123 reviewed articles. Patients with ASD were observed to have increased whole brain volume, particularly under 6 years of age. Other consistent changes observed in ASD patients include increased volume in the frontal and temporal lobes, increased cortical thickness in the frontal lobe, increased surface area and cortical gyrification, and increased cerebrospinal fluid volume, as well as reduced cerebellum volume and reduced corpus callosum volume, compared to typically developing controls. Findings were inconsistent regarding the developmental trajectory of brain volume and cortical thinning with age in ASD, as well as potential volume differences in the white matter, hippocampus, amygdala, thalamus and basal ganglia. To elucidate these inconsistencies, future studies should look towards aggregating MRI data from multiple sites or available repositories to avoid underpowered studies, as well as utilising methods which quantify larger-scale image features to reduce the number of statistical tests performed, and hence risk of false positive findings. Additionally, studies should look to perform a thorough validation strategy, to ensure generalisability of study findings, as well as look to leverage the improved image resolution of 3 T scanning to identify subtle brain changes related to ASD.

show abstract

Familial risk of autism alters subcortical and cerebellar brain anatomy in infants and predicts the emergence of repetitive behaviors in early childhood

et al. 2019

View full text Add to dashboard Cite

Autism spectrum disorder (ASD) is a common neurodevelopmental condition, and infant siblings of children with ASD are at a higher risk of developing autistic traits or an ASD diagnosis, when compared to those with typically developing siblings. Reports of differences in brain anatomy and function in high‐risk infants which predict later autistic behaviors are emerging, but although cerebellar and subcortical brain regions have been frequently implicated in ASD, no high‐risk study has examined these regions. Therefore, in this study, we compared regional MRI volumes across the whole brain in 4–6‐month‐old infants with (high‐risk, n = 24) and without (low‐risk, n = 26) a sibling with ASD. Within the high‐risk group, we also examined whether any regional differences observed were associated with autistic behaviors at 36 months. We found that high‐risk infants had significantly larger cerebellar and subcortical volumes at 4–6‐months of age, relative to low‐risk infants; and that larger volumes in high‐risk infants were linked to more repetitive behaviors at 36 months. Our preliminary observations require replication in longitudinal studies of larger samples. If correct, they suggest that the early subcortex and cerebellum volumes may be predictive biomarkers for childhood repetitive behaviors. Autism Res 2019, 12: 614–627 . © 2019 The Authors. Autism Research published by International Society for Autism Research published byWiley Periodicals, Inc. Lay Summary Individuals with a family history of autism spectrum disorder (ASD) are at risk of ASD and related developmental difficulties. This study revealed that 4–6‐month‐old infants at high‐risk of ASD have larger cerebellum and subcortical volumes than low‐risk infants, and that larger volumes in high‐risk infants are associated with more repetitive behaviors in childhood.

show abstract

Pallidum and lateral ventricle volume enlargement in autism spectrum disorder

Cited by 63 publications

References 33 publications

Regional volumetric abnormalities in pediatric autism revealed by structural magnetic resonance imaging

Regional volumetric abnormalities in pediatric autism revealed by structural magnetic resonance imaging

A systematic review of structural MRI biomarkers in autism spectrum disorder: A machine learning perspective

Familial risk of autism alters subcortical and cerebellar brain anatomy in infants and predicts the emergence of repetitive behaviors in early childhood

Contact Info

Product

Resources

About