Corpus callosum in children with neurodevelopmental delay: MRI standard qualitative assessment versus automatic quantitative analysis.

Details

Serval ID
serval:BIB_13D3200696FE
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Corpus callosum in children with neurodevelopmental delay: MRI standard qualitative assessment versus automatic quantitative analysis.
Journal
European radiology experimental
Author(s)
Mandine N., Tavernier E., Hülnhagen T., Maréchal B., Kober T., Tauber C., Guichard M., Castelnau P., Morel B.
ISSN
2509-9280 (Electronic)
ISSN-L
2509-9280
Publication state
Published
Issued date
13/10/2023
Peer-reviewed
Oui
Volume
7
Number
1
Pages
61
Language
english
Notes
Publication types: Journal Article
Publication Status: epublish
Abstract
The corpus callosum (CC) is a key brain structure. In children with neurodevelopmental delay, we compared standard qualitative radiological assessments with an automatic quantitative tool.
We prospectively enrolled 73 children (46 males, 63.0%) with neurodevelopmental delay at single university hospital between September 2020 and September 2022. All of them underwent 1.5-T brain magnetic resonance imaging (MRI) including a magnetization-prepared 2 rapid acquisition gradient echoes - MP2RAGE sequence. Two radiologists blindly reviewed the images to classify qualitatively the CC into normal, hypoplasic, hyperplasic, and/or dysgenetic classes. An automatic tool (QuantiFIRE) was used to provide brain volumetry and T1 relaxometry automatically as well as deviations of those parameters compared with a healthy age-matched cohort. The MRI reference standard for CC volumetry was based on the Garel et al. study. Cohen κ statistics was used for interrater agreement. The radiologists and QuantiFIRE's diagnostic accuracy were compared with the reference standard using the Delong test.
The CC was normal in 42 cases (57.5%), hypoplastic in 20 cases (27.4%), and hypertrophic in 11 cases (15.1%). T1 relaxometry values were abnormal in 26 children (35.6%); either abnormally high (18 cases, 24.6%) or low (8 cases, 11.0%). The interrater Cohen κ coefficient was 0.91. The diagnostic accuracy of the QuantiFIRE prototype was higher than that of the radiologists for hypoplastic and normal CC (p = 0.003 for both subgroups, Delong test).
An automated volumetric and relaxometric assessment can assist the evaluation of brain structure such as the CC, particularly in the case of subtle abnormalities.
Automated brain MRI segmentation combined with statistical comparison to normal volume and T1 relaxometry values can be a useful diagnostic support tool for radiologists.
• Corpus callosum abnormality detection is challenging but clinically relevant. • Automated quantitative volumetric analysis had a higher diagnostic accuracy than that of visual appreciation of radiologists. • Quantitative T1 relaxometric analysis might help characterizing corpus callosum better.
Keywords
Male, Humans, Child, Corpus Callosum/diagnostic imaging, Magnetic Resonance Imaging/methods, Brain, Corpus callosum, Magnetic resonance imaging, Segmentation
Pubmed
Web of science
Open Access
Yes
Create date
19/10/2023 16:25
Last modification date
19/12/2023 8:12
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