Automated Approach for Enhancing Fetal Head Station Assessment in Labor with Transperineal Ultrasound

Rationale and Objectives: Accurate assessment of fetal head station (FHS) is crucial during labor management to reduce the risk of complications and plan the mode of delivery. Although digital vaginal examination (DVE) has been associated with inaccuracies in FHS assessment, ultrasound (US) evaluation remains dependent on sonographer expertise. This study aimed at investigating the reliability and accuracy of an automatic approach to assess the FHS during labor with transperineal US (TPU). Materials and Methods: In this prospective observational study, 27 pregnant women in the second stage of labor, with fetuses in cephalic presentation, underwent conventional labor management with additional TPU examination. A total of 45 2D B-mode TPU acquisitions were performed at different FHS, before performing DVE. The FHS was assessed by the algorithm (FHSaut) on TPU images and by DVE (FHSdig). The sonographic assessment of FHS by expert sonographer (FHSexp) on the same TPU acquisition used for the automatic measurement served as gold standard. The performance and accuracy were assessed through Spearman's ρ, the coefficient of determination (R2), root mean square error (RMSE), and Bland–Altman analysis. Results: A strong correlation between FHSaut and FHSexp (ρ = 0.97, p < 0.001) and a high coefficient of determination (R2 = 0.95) were found. A lower correlation with FHSexp (ρ = 0.66, p < 0.001) and coefficient of determination (R2 = 0.52) was found for DVE. Moreover, the RMSE reported higher accuracy of FHSaut (RMSE = 0.32 cm) compared to FHSdig (RMSE = 0.97 cm). Bland–Altman analysis showed that the algorithm performed with smaller bias and narrower limits of agreement compared to DVE. Conclusion: The proposed algorithm can evaluate FHS with high accuracy and low RMSE. This approach could facilitate the use of US in labor, supporting the clinical staff in labor management.