Three-dimensional facial gestalt analysis for three neurodevelopmental disorders: Koolen-de Vries, Jansen-de Vries and KBG syndrome.

Diagnosing children with developmental disorders is often challenging due to the large number of rare syndromes and their variable clinical presentations. While next-generation sequencing has improved diagnostic yield, results are frequently inconclusive, highlighting the continued importance of detailed phenotypic assessment. Three-dimensional (3D) facial imaging has shown advantages over traditional two-dimensional (2D) photographs in syndrome identification, offering new opportunities for more accurate diagnosis. In this study, we explored the benefits of 3D shape analysis for three syndromes seen at the Radboudumc expertise clinic for neurodevelopmental disorders: Koolen-de Vries syndrome (KdVS, N = 16), Jansen-de Vries syndrome (JdVS, N = 9) and KBG syndrome (N = 16). Each patient's facial shape was aligned with a 3D growth curve derived from healthy controls, which allowed us to objectively evaluate how their features compared to their age- and sex-matched average. This analysis aligned with previously recognized features for all three syndromes and led to the identification of a novel phenotypical feature for JdVS, supraorbital grooves. The consistency of the facial features for each of these three syndromes was calculated using a cosine distance analysis and compared with that of 19 other dysmorphically well-characterized syndromes, for the overall face as well as for eight facial segments. In line with current understanding facial phenotypic consistency was highest for KdVS, whereas features of JdVS and KBG syndrome were more diverse in this cohort. These small cohort derived results indicate the potential of 3D imaging for neurodevelopmental disorders, enhance current phenotypical knowledge and provide a foundation for future 3D shape analysis of these three syndromes.