From Diagnosis to Decision—Fetal Limb Abnormalities

Background/Objectives: Our aim was to investigate the diagnostic accuracy of prenatal ultrasound (US) in fetal limb abnormalities. As a secondary target, we wanted to correlate various predictors for the diagnosis accuracy. Methods: We prospectively enrolled cases with routine prenatal US performed in five participating centers. Subsequently, we selected and processed all cases with limb abnormalities: suspected, diagnosed, and missed on the prenatal diagnosis scans. We collected data on the type of anomaly, the US equipment and probes used, the operator’s expertise, the gestational age at the diagnosis, the length of the examination, and the use of US reporting form. SPSS 22.0 software was applied to perform the analyses using non-parametric statistical methods. Associations between categorical variables were evaluated using Fisher’s exact test and Chi-square tests. For correlations between the gestational age and the anomaly severity, we used Spearman’s rank-order correlation. Predictive performance of operator- and scan-related variables for diagnostic accuracy was assessed using receiver operating characteristic (ROC) curve analysis, with area under the curve (AUC) estimates, standard errors (SE), confidence intervals (95% CI), and p-values reported. Results: Our data showed that most US examinations were performed as part of routine screening (79.7%), and the most frequent anomaly diagnosed was clubfoot. Operators’ expertise demonstrated the highest predictive performance, while technical parameters—scan duration (AUC = 0.20, p = 0.1188) and US equipment (AUC = 0.30, p = 0.3478)—did not significantly predict diagnostic accuracy. Conclusions: The overall diagnostic accuracy of prenatal US was 85.5%. Our findings indicate that diagnostic performance is driven primarily by operator expertise and training, rather than by gestational age at scan and technical parameters.