Prenatal ultrasound for the diagnosis of the cerebellar abnormalities: a meta-analysis.

Objective: Fetal cerebellar abnormalities are associated with neurodevelopmental disorders and structural brain malformations. Accurate and early diagnosis is crucial for prenatal counseling and planning postnatal interventions. While prenatal ultrasound is a key tool for detecting fetal brain abnormalities, variations in diagnostic accuracy across studies necessitate a systematic evaluation of its effectiveness in diagnosing cerebellar abnormalities.

Methods: A comprehensive literature search was conducted across major databases to identify relevant studies on prenatal ultrasound for diagnosing cerebellar anomalies. Inclusion criteria included studies with clear diagnostic outcomes, diverse patient populations, and standardized ultrasound protocols. Meta-analytic techniques were employed to assess overall diagnostic accuracy, sensitivity, specificity, and heterogeneity using Meta Disk. The quality of the included studies was evaluated using the QUADAS-2 tool.

Results: The meta-analysis included fifteen studies involving 1,902 fetuses with suspected cerebellar abnormalities. The pooled sensitivity and specificity of prenatal ultrasound were 0.83 (95% CI: 0.80-0.86) and 0.97 (95% CI: 0.96-0.98), respectively. The positive likelihood ratio was 7.96 (95% CI: 3.23-19.64), the negative likelihood ratio was 0.18 (95% CI: 0.09-0.36), and the odds ratio was 46.76 (95% CI: 14.06-155.53). The combined area under the curve (AUC) reached 0.93, indicating robust diagnostic performance. Heterogeneity was observed, influenced by factors such as gestational age at screening, operator expertise, and ultrasound equipment quality.

Conclusions: Prenatal ultrasound is a reliable tool for detecting cerebellar abnormalities with high sensitivity and specificity. However, variability in diagnostic performance suggests the need for standardized protocols and advanced imaging techniques to enhance accuracy. Future research should focus on integrating multiple imaging modalities to optimize prenatal screening outcomes.