Towards Reliable Automatic Characterization of Neonatal Hip Dysplasia from 3D Ultrasound Images

Ultrasound (US) imaging is recommended for early detection of developmental dysplasia of the hip (DDH), which includes a spectrum of hip joint abnormalities in infants. However, the currently standard 2-dimensional (2D) US-based approach to measuring the dysplasia metric (DM), namely the \(\alpha \) angle, suffers from high within-hip variability with standard deviations typically ranging between \(3^{\circ }-7^{\circ }\). Such high variability leads to elevated over- and under-treatment rates in hip classification. To reduce this high variability inherent to the 2D \(\alpha \) angle, \(\alpha _{2D}\), we propose a 3D US-based DM in the form of a 3D \(\alpha \) angle, \(\alpha _{3D}\), that more accurately characterizes the morphology of an infant’s hip joint. Our method leverages phase symmetry features that automatically identify the 3D bone/cartilage structures to compute \(\alpha _{3D}\). Validating on 30 clinical patient hip examinations, we demonstrate the within-hip variability of \(\alpha _{3D}\) to be significantly smaller than \(\alpha _{2D}\) (\(28.9\,\%\) reduction, \(p<0.01\)). Our findings indicate that \(\alpha _{3D}\) may be significantly more reproducible than the conventional 2D measure, which will likely reduce misclassification rates.