OBJECTIVES: Prenatal diagnosis of central nervous system (CNS) anomalies by 2-dimensional sonography is challenging because of difficulties in obtaining complete visualization of the fetal brain during routine examinations, which is necessary for identification of its axial, coronal, and sagittal planes. Three-dimensional (3D) sonography has been introduced as a tool for studying the fetal CNS because of its ability to facilitate examinations of the fetal brain. The objective of this study was to determine inter-center agreement in diagnosing CNS defects by review of 3D volume data sets. METHODS: This study included 11 centers with expertise in 3D fetal neurosonography. A total of 217 fetuses with and without confirmed CNS defects were scanned after 18 weeks' gestation, and their volume data sets were uploaded onto a centralized file transfer protocol server and later analyzed by all of the centers. Intercenter agreement was determined using a κ statistic for multiple raters. RESULTS: All volumes were made anonymous and sent to the centers for blinded analysis with the exception of the data sets they had themselves previously uploaded. For identification of fetuses with CNS defects, the sensitivity, specificity, positive and negative predictive values, and false-positive and -negative rates were 93.3%, 96.5%, 96.5%, 93.3%, 3.5%, and 6.7%, respectively. No differences were found in the efficacy of the diagnostic indices according to either the route of acquisition (transabdominal or trans-vaginal) or the gestational age at diagnosis (18-24 or >24 weeks). Intercenter agreement was excellent (κ = 0.92; 95% confidence interval, 0.88-0.97). CONCLUSIONS: Among centers with technical expertise, remote review of 3D sonographic volumes of the fetal CNS resulted in an accurate and reliable method for diagnosis of fetal brain malformations.
OBJECTIVES: Prenatal diagnosis of central nervous system (CNS) anomalies by 2-dimensional sonography is challenging because of difficulties in obtaining complete visualization of the fetal brain during routine examinations, which is necessary for identification of its axial, coronal, and sagittal planes. Three-dimensional (3D) sonography has been introduced as a tool for studying the fetal CNS because of its ability to facilitate examinations of the fetal brain. The objective of this study was to determine inter-center agreement in diagnosing CNS defects by review of 3D volume data sets. METHODS: This study included 11 centers with expertise in 3D fetal neurosonography. A total of 217 fetuses with and without confirmed CNS defects were scanned after 18 weeks' gestation, and their volume data sets were uploaded onto a centralized file transfer protocol server and later analyzed by all of the centers. Intercenter agreement was determined using a κ statistic for multiple raters. RESULTS: All volumes were made anonymous and sent to the centers for blinded analysis with the exception of the data sets they had themselves previously uploaded. For identification of fetuses with CNS defects, the sensitivity, specificity, positive and negative predictive values, and false-positive and -negative rates were 93.3%, 96.5%, 96.5%, 93.3%, 3.5%, and 6.7%, respectively. No differences were found in the efficacy of the diagnostic indices according to either the route of acquisition (transabdominal or trans-vaginal) or the gestational age at diagnosis (18-24 or >24 weeks). Intercenter agreement was excellent (κ = 0.92; 95% confidence interval, 0.88-0.97). CONCLUSIONS: Among centers with technical expertise, remote review of 3D sonographic volumes of the fetal CNS resulted in an accurate and reliable method for diagnosis of fetal brain malformations.