Improving diagnosis accuracy of brain volume abnormalities during childhood with an automated MP2RAGE-based magnetic resonance imaging brain segmentation.

Details

Serval ID
serval:BIB_04CB0BDA3735
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Improving diagnosis accuracy of brain volume abnormalities during childhood with an automated MP2RAGE-based magnetic resonance imaging brain segmentation.
Journal
Journal of neuroradiology = Journal de neuroradiologie
Author(s)
Serru M., Marechal B., Kober T., Ribier L., Taveau C.S., Sirinelli D., Cottier J.P., Morel B.
ISSN
0150-9861 (Print)
ISSN-L
0150-9861
Publication state
In Press
Peer-reviewed
Oui
Language
english
Notes
Publication types: Journal Article
Publication Status: aheadofprint
Abstract
It can be challenging to depict brain volume abnormalities in the pediatric population on magnetic resonance imaging (MRI). The aim of the study was to evaluate the inter-radiologist reliability in brain MRI interpretation, including brain volume assessment and the efficiency of an automated brain segmentation.
We performed a single-center prospective study including 44 patients aged six months to five years recruited from the University Hospital, having a 1.5T brain MRI using a MP2RAGE sequence. All MRI were randomly and blindly reviewed by one junior and two senior pediatric radiologists. Inter-observer agreements were assessed using Fleiss' kappa coefficient. Brain volumetry (total intracranial volume (TIV), brain parenchyma, and cerebrospinal fluid volumes) was estimated using the MorphoBox prototype. Clinical head circumference (HC) and z scores were reported. A Pearson correlation coefficient was calculated between brain volumes with HC.
Twenty-four brain MRI examinations were normal and twenty were pathological. Brain volume abnormalities were poorly detected by junior and senior radiologists: sensitivities 16.67% [confidence interval 4.7-44.8], 33.33% [13-60] and 30.7% [12-58] and specificities 93.75% [79-98], 84.38% [68-93] and 77% [60-88], respectively. Brain volume apart, interobserver kappa coefficients were 0.93 between junior and seniors as well as between seniors. Brain volumes were significantly correlated with HC (p<0.0001). In patients with normal MRI, brain parenchyma volumes increased regularly with age. Low brain volume was easier to identify with automated quantification.
Brain volume was poorly appreciated by radiologists. The fully automated brain segmentation used can provide quantitative data to better diagnose, describe, and follow-up brain volume abnormalities.
Keywords
brain segmentation, magnetic resonance imaging, observer variation, pediatric brain diseases, radiologists
Pubmed
Create date
16/08/2019 20:55
Last modification date
22/10/2019 17:34
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