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

European Radiology Experimental

Original Article

Tobias Kober¹  Bénédicte Maréchal¹  Till Hülnhagen¹  Elsa Tavernier²  Pierre Castelnau³  Marine Guichard³  Natacha Mandine⁴  Baptiste Morel⁵  Clovis Tauber⁶ 

[1] Advanced Clinical Imaging Technology, Siemens Healthineers International, Lausanne, Switzerland;Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland;LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland;Clinical Investigation Center, INSERM 1415, CHRU Tours, Tours, France;Pediatric Neurology Department, CHRU of Tours, Clocheville Hospital, Tours, France;Pediatric Radiology Department, CHRU of Tours, Clocheville Hospital, Tours, France;Pediatric Radiology Department, CHRU of Tours, Clocheville Hospital, Tours, France;UMR 1253, iBrain, Université de Tours, Inserm, Tours, France;UMR 1253, iBrain, Université de Tours, Inserm, Tours, France;

关键词: Brain;    Child;    Corpus callosum;    Segmentation;    Magnetic resonance imaging;   

DOI  :  10.1186/s41747-023-00375-4

 received in 2023-03-15, accepted in 2023-08-07,  发布年份 2023

来源: Springer

【 摘 要 】

BackgroundThe corpus callosum (CC) is a key brain structure. In children with neurodevelopmental delay, we compared standard qualitative radiological assessments with an automatic quantitative tool.MethodsWe 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.ResultsThe 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).ConclusionsAn automated volumetric and relaxometric assessment can assist the evaluation of brain structure such as the CC, particularly in the case of subtle abnormalities.Relevance statementAutomated brain MRI segmentation combined with statistical comparison to normal volume and T1 relaxometry values can be a useful diagnostic support tool for radiologists.Key points• 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.Graphical Abstract

【 授权许可】

CC BY   
© European Society of Radiology (ESR) 2023

【 图 表 】

Fig. 1

Fig. 6

Fig. 5

Fig. 5

Fig. 2

12951_2015_155_Article_IEq58.gif