A New MRI-Based Pediatric Subcortical Segmentation Technique (PSST)

被引:0
作者
Wai Yen Loh
Alan Connelly
Jeanie L. Y. Cheong
Alicia J. Spittle
Jian Chen
Christopher Adamson
Zohra M. Ahmadzai
Lillian Gabra Fam
Sandra Rees
Katherine J. Lee
Lex W. Doyle
Peter J. Anderson
Deanne K. Thompson
机构
[1] Murdoch Childrens Research Institute,Victorian Infant Brain Studies
[2] University of Melbourne,Florey Institute of Neuroscience and Mental Health
[3] University of Melbourne,Department of Obstetrics and Gynecology
[4] Royal Women’s Hospital,Department of Physiotherapy
[5] University of Melbourne,Department of Medicine, Stroke and Ageing Research Group, Southern Clinical School
[6] Monash University,Developmental Imaging
[7] Murdoch Childrens Research Institute,Department of Pediatrics
[8] University of Melbourne,Department of Anatomy and Neuroscience
[9] University of Melbourne,undefined
来源
Neuroinformatics | 2016年 / 14卷
关键词
Magnetic resonance imaging; Segmentation; Pediatric; Subcortical; Basal ganglia; Thalamus;
D O I
暂无
中图分类号
学科分类号
摘要
Volumetric and morphometric neuroimaging studies of the basal ganglia and thalamus in pediatric populations have utilized existing automated segmentation tools including FIRST (Functional Magnetic Resonance Imaging of the Brain’s Integrated Registration and Segmentation Tool) and FreeSurfer. These segmentation packages, however, are mostly based on adult training data. Given that there are marked differences between the pediatric and adult brain, it is likely an age-specific segmentation technique will produce more accurate segmentation results. In this study, we describe a new automated segmentation technique for analysis of 7-year-old basal ganglia and thalamus, called Pediatric Subcortical Segmentation Technique (PSST). PSST consists of a probabilistic 7-year-old subcortical gray matter atlas (accumbens, caudate, pallidum, putamen and thalamus) combined with a customized segmentation pipeline using existing tools: ANTs (Advanced Normalization Tools) and SPM (Statistical Parametric Mapping). The segmentation accuracy of PSST in 7-year-old data was compared against FIRST and FreeSurfer, relative to manual segmentation as the ground truth, utilizing spatial overlap (Dice’s coefficient), volume correlation (intraclass correlation coefficient, ICC) and limits of agreement (Bland-Altman plots). PSST achieved spatial overlap scores ≥90 % and ICC scores ≥0.77 when compared with manual segmentation, for all structures except the accumbens. Compared with FIRST and FreeSurfer, PSST showed higher spatial overlap (pFDR < 0.05) and ICC scores, with less volumetric bias according to Bland-Altman plots. PSST is a customized segmentation pipeline with an age-specific atlas that accurately segments typical and atypical basal ganglia and thalami at age 7 years, and has the potential to be applied to other pediatric datasets.
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页码:69 / 81
页数:12
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