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The antenatal evaluation of the fetal central nervous system (CNS) is among the most difficult tasks of prenatal ultrasound (US), requiring technical skills in relation to ultrasound and image acquisition as well as knowledge of CNS anatomy and how this changes with gestation. According to the International Guidelines for fetal neurosonology, the basic assessment of fetal CNS is most frequently performed on the axial planes, whereas the coronal and sagittal planes are required for the multiplanar evaluation of the CNS within the context of fetal neurosonology. It can be even more technically challenging to obtain “nonaxial” views with 2-dimensional (2D) US. The modality of 3-dimensional (3D) US has been suggested as a panacea to overcome the technical difficulties of achieving nonaxial views. The lack of familiarity of most sonologists with the use of 3D US and its related processing techniques may preclude its use even where it could play an important role in complementing antenatal 2D US assessment. Furthermore, once a 3D volume has been acquired, proprietary software allows it to be processed in different ways, leading to multiple ways of displaying and analyzing the same anatomical imaging or plane. These are difficult to learn and time consuming in the absence of specific training. In this article, we describe the key steps for volume acquisition of a 3D US volume, manipulation, and processing with reference to images of the fetal CNS, using a newly developed context-preserving rendering technique.

Background The antenatal detection of facial dysmorphism using 3-dimensional ultrasound may raise the suspicion of an underlying genetic condition but infrequently leads to a definitive antenatal diagnosis. Despite advances in array and noninvasive prenatal testing, not all genetic conditions can be ascertained from such testing. Objectives The aim of this study was to investigate the feasibility of quantitative assessment of fetal face features using prenatal 3-dimensional ultrasound volumes and statistical shape modeling. Study Design Thirteen normal and 7 abnormal stored 3-dimensional ultrasound fetal face volumes were analyzed, at a median gestation of 29 +4 weeks (25 +0 to 36 +1 ). The 20 3-dimensional surface meshes generated were aligned and served as input for a statistical shape model, which computed the mean 3-dimensional face shape and 3-dimensional shape variations using principal component analysis. Results Ten shape modes explained more than 90% of the total shape variability in the population. While the first mode accounted for overall size differences, the second highlighted shape feature changes from an overall proportionate toward a more asymmetric face shape with a wide prominent forehead and an undersized, posteriorly positioned chin. Analysis of the Mahalanobis distance in principal component analysis shape space suggested differences between normal and abnormal fetuses (median and interquartile range distance values, 7.31 ± 5.54 for the normal group vs 13.27 ± 9.82 for the abnormal group) ( P = .056). Conclusion This feasibility study demonstrates that objective characterization and quantification of fetal facial morphology is possible from 3-dimensional ultrasound. This technique has the potential to assist in utero diagnosis, particularly of rare conditions in which facial dysmorphology is a feature.