The Impact of Image Acquisition in Cervical Ultrasound on AI-Based Prediction of Preterm Birth in Clinical Practice

The Impact of Image Acquisition in Cervical Ultrasound on AI-Based Prediction of Preterm Birth in Clinical Practice: A Prospective Observational Study

This study prospectively evaluates whether the performance of an already-developed artificial intelligence (AI) model for predicting spontaneous preterm birth changes when cervical ultrasound images are obtained using different ultrasound image settings.

The primary research question is whether the AI model performs differently across images acquired with different imaging settings.

Inclusion Criteria:

• Pregnant women aged ≥18 years
• Attending routine second-trimester scan (and scheduled transvaginal cervical assessment per local protocol/workflow)

Exclusion Criteria:

• Absence of transvaginal cervical assessment at the second-trimester scan
• Missing follow-up data on pregnancy outcome (gestational age at delivery)
• Inadequate image quality or missing required cervical ultrasound image