Brainstem enlargement in preschool children with autism: Results from an intermethod agreement study of segmentation algorithms

Paolo Bosco, Alessia Giuliano, Jonathan Delafield-Butt, Filippo Muratori, Sara Calderoni, Alessandra Retico

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

The intermethod agreement between automated algorithms for brainstem segmentation is investigated, focusing on the potential involvement of this structure in Autism Spectrum Disorders (ASD). Inconsistencies highlighted in previous studies on brainstem in the population with ASD may in part be a result of poor agreement in the extraction of structural features between different methods. A sample of 76 children with ASD and 76 age-, gender-, and intelligence-matched controls was considered. Volumetric analyses were performed using common tools for brain structures segmentation, namely FSL-FIRST, FreeSurfer (FS), and Advanced Normalization Tools (ANTs). For shape analysis SPHARM-MAT was employed. Intermethod agreement was quantified in terms of Pearson correlations between pairs of volumes obtained by the different methods. The degree of overlap between segmented masks was quantified in terms of the Dice index. Both Pearson correlations and Dice indices, showed poor agreement between FSL-FIRST and the other methods (ANTs and FS), which by contrast, yielded Pearson correlations greater than 0.93 and average Dice indices greater than 0.76 when compared with each other. As with volume, shape analyses exhibited discrepancies between segmentation methods, with particular differences noted between FSL-FIRST and the others (ANT and FS), with under- and over-segmentation in specific brainstem regions. These data suggest that research on brain structure alterations should cross-validate findings across multiple methods. We consistently detected an enlargement of brainstem volume in the whole sample and in the male cohort across multiple segmentation methods, a feature particularly driven by the subgroup of children with idiopathic intellectual disability associated with ASD.

Original languageEnglish
JournalHuman Brain Mapping
DOIs
Publication statusAccepted/In press - Jan 1 2018

Fingerprint

Preschool Children
Autistic Disorder
Brain Stem
Brain
Masks
Intelligence
Intellectual Disability
Autism Spectrum Disorder
Research
Population

Keywords

  • autism spectrum disorders
  • brainstem
  • brainstem volume
  • segmentation
  • T1-weighted MRI

ASJC Scopus subject areas

  • Anatomy
  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Neurology
  • Clinical Neurology

Cite this

Brainstem enlargement in preschool children with autism : Results from an intermethod agreement study of segmentation algorithms. / Bosco, Paolo; Giuliano, Alessia; Delafield-Butt, Jonathan; Muratori, Filippo; Calderoni, Sara; Retico, Alessandra.

In: Human Brain Mapping, 01.01.2018.

Research output: Contribution to journalArticle

@article{84484db73e00461d8b7816b438b77408,
title = "Brainstem enlargement in preschool children with autism: Results from an intermethod agreement study of segmentation algorithms",
abstract = "The intermethod agreement between automated algorithms for brainstem segmentation is investigated, focusing on the potential involvement of this structure in Autism Spectrum Disorders (ASD). Inconsistencies highlighted in previous studies on brainstem in the population with ASD may in part be a result of poor agreement in the extraction of structural features between different methods. A sample of 76 children with ASD and 76 age-, gender-, and intelligence-matched controls was considered. Volumetric analyses were performed using common tools for brain structures segmentation, namely FSL-FIRST, FreeSurfer (FS), and Advanced Normalization Tools (ANTs). For shape analysis SPHARM-MAT was employed. Intermethod agreement was quantified in terms of Pearson correlations between pairs of volumes obtained by the different methods. The degree of overlap between segmented masks was quantified in terms of the Dice index. Both Pearson correlations and Dice indices, showed poor agreement between FSL-FIRST and the other methods (ANTs and FS), which by contrast, yielded Pearson correlations greater than 0.93 and average Dice indices greater than 0.76 when compared with each other. As with volume, shape analyses exhibited discrepancies between segmentation methods, with particular differences noted between FSL-FIRST and the others (ANT and FS), with under- and over-segmentation in specific brainstem regions. These data suggest that research on brain structure alterations should cross-validate findings across multiple methods. We consistently detected an enlargement of brainstem volume in the whole sample and in the male cohort across multiple segmentation methods, a feature particularly driven by the subgroup of children with idiopathic intellectual disability associated with ASD.",
keywords = "autism spectrum disorders, brainstem, brainstem volume, segmentation, T1-weighted MRI",
author = "Paolo Bosco and Alessia Giuliano and Jonathan Delafield-Butt and Filippo Muratori and Sara Calderoni and Alessandra Retico",
year = "2018",
month = "1",
day = "1",
doi = "10.1002/hbm.24351",
language = "English",
journal = "Human Brain Mapping",
issn = "1065-9471",
publisher = "John Wiley and Sons Inc.",

}

TY - JOUR

T1 - Brainstem enlargement in preschool children with autism

T2 - Results from an intermethod agreement study of segmentation algorithms

AU - Bosco, Paolo

AU - Giuliano, Alessia

AU - Delafield-Butt, Jonathan

AU - Muratori, Filippo

AU - Calderoni, Sara

AU - Retico, Alessandra

PY - 2018/1/1

Y1 - 2018/1/1

N2 - The intermethod agreement between automated algorithms for brainstem segmentation is investigated, focusing on the potential involvement of this structure in Autism Spectrum Disorders (ASD). Inconsistencies highlighted in previous studies on brainstem in the population with ASD may in part be a result of poor agreement in the extraction of structural features between different methods. A sample of 76 children with ASD and 76 age-, gender-, and intelligence-matched controls was considered. Volumetric analyses were performed using common tools for brain structures segmentation, namely FSL-FIRST, FreeSurfer (FS), and Advanced Normalization Tools (ANTs). For shape analysis SPHARM-MAT was employed. Intermethod agreement was quantified in terms of Pearson correlations between pairs of volumes obtained by the different methods. The degree of overlap between segmented masks was quantified in terms of the Dice index. Both Pearson correlations and Dice indices, showed poor agreement between FSL-FIRST and the other methods (ANTs and FS), which by contrast, yielded Pearson correlations greater than 0.93 and average Dice indices greater than 0.76 when compared with each other. As with volume, shape analyses exhibited discrepancies between segmentation methods, with particular differences noted between FSL-FIRST and the others (ANT and FS), with under- and over-segmentation in specific brainstem regions. These data suggest that research on brain structure alterations should cross-validate findings across multiple methods. We consistently detected an enlargement of brainstem volume in the whole sample and in the male cohort across multiple segmentation methods, a feature particularly driven by the subgroup of children with idiopathic intellectual disability associated with ASD.

AB - The intermethod agreement between automated algorithms for brainstem segmentation is investigated, focusing on the potential involvement of this structure in Autism Spectrum Disorders (ASD). Inconsistencies highlighted in previous studies on brainstem in the population with ASD may in part be a result of poor agreement in the extraction of structural features between different methods. A sample of 76 children with ASD and 76 age-, gender-, and intelligence-matched controls was considered. Volumetric analyses were performed using common tools for brain structures segmentation, namely FSL-FIRST, FreeSurfer (FS), and Advanced Normalization Tools (ANTs). For shape analysis SPHARM-MAT was employed. Intermethod agreement was quantified in terms of Pearson correlations between pairs of volumes obtained by the different methods. The degree of overlap between segmented masks was quantified in terms of the Dice index. Both Pearson correlations and Dice indices, showed poor agreement between FSL-FIRST and the other methods (ANTs and FS), which by contrast, yielded Pearson correlations greater than 0.93 and average Dice indices greater than 0.76 when compared with each other. As with volume, shape analyses exhibited discrepancies between segmentation methods, with particular differences noted between FSL-FIRST and the others (ANT and FS), with under- and over-segmentation in specific brainstem regions. These data suggest that research on brain structure alterations should cross-validate findings across multiple methods. We consistently detected an enlargement of brainstem volume in the whole sample and in the male cohort across multiple segmentation methods, a feature particularly driven by the subgroup of children with idiopathic intellectual disability associated with ASD.

KW - autism spectrum disorders

KW - brainstem

KW - brainstem volume

KW - segmentation

KW - T1-weighted MRI

UR - http://www.scopus.com/inward/record.url?scp=85052921806&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85052921806&partnerID=8YFLogxK

U2 - 10.1002/hbm.24351

DO - 10.1002/hbm.24351

M3 - Article

AN - SCOPUS:85052921806

JO - Human Brain Mapping

JF - Human Brain Mapping

SN - 1065-9471

ER -