Prenatal diagnosis of abnormal morphology of Sylvian fissure and malformations of cortical development / 中华围产医学杂志

ABSTRACT

Objective:To investigate the significance of abnormal morphology of Sylvian fissure detected by fetal neurosonogram (NSG) in prenatal diagnosis of malformations of cortical development (MCD).Methods:This retrospective study involved fetuses with abnormal morphology of Sylvian fissure on prenatal NSG in Peking University First Hospital between January 2016 and December 2021. Clinical data including the basic information as well as the results of NSG, genetic examinations and MRI were collected. The diagnosis of MCD could be made when both brain morphological abnormalities and pathogenic/likely pathogenic genetic abnormalities were presented. The association between the abnormal morphology of Sylvian fissure and MCD was analyzed by descriptive analysis.Results:Thirteen participants who had complete genetic information were included in this study [defined as those who were found with pathogenic/likely pathogenic copy number variation (CNV) or those who further underwent whole-exome sequencing (WES) as no pathogenic/likely pathogenic CNV were detected]. Twelve fetuses (12/13) were eventually diagnosed with MCD. Pathogenic CNV were found in seven fetuses and pathogenic point mutations in five, involving six pathogenic genes and four genetic syndromes. Symmetric morphologic abnormality of Sylvian fissure was detected in 10 cases by prenatal NSG with shallow and broad shape in six and abnormal angle of Sylvian fissure in four. The other two fetuses showed asymmetric abnormal morphology of Sylvian fissure that was shallow and broad shape on one side and abnormal angle on the other. The imaging features of MCD present by prenatal NSG and were consistent with those of MRI.Conclusions:Abnormal morphology of Sylvian fissure detected by prenatal NSG is important in MCD diagnosis. Genetic examination are recommended to the fetuses with abnormal morphology of Sylvian fissure. For those requiring for genetic analysis, chromosomal microarray analysis together with WES might be an optimal choice.