AI-Based Ultrasound Prediction of Pregnancy Outcomes in Placental-Related Fetal Growth Restriction (MVM-FGR): A Prospective Cohort Study

Establishment of a Cohort of Maternal Vascular Malperfusion-Related Fetal Growth Restriction (MVM-FGR) Based on an Etiology-Oriented Diagnostic Pathway: Artificial Intelligence-Assisted Multiparametric Ultrasound Prediction of Pregnancy Outcomes

The goal of this prospective cohort study is to enroll pregnancies complicated by placental-related fetal growth restriction (FGR) and to develop predictive models for adverse short- and long-term outcomes. This will be achieved by collecting novel intrauterine monitoring indicators along the fetal brain-placenta-heart axis, combined with conventional fetal surveillance parameters, in order to improve risk stratification and guide clinical management, ultimately improving pregnancy outcomes.

The study will include pregnant women with singleton pregnancies complicated by isolated early-onset placental insufficiency-related FGR, preferably those with abnormal umbilical artery Doppler findings, who elect to continue the pregnancy.

The main question it aims to answer is:

• Whether a predictive model integrating novel intrauterine monitoring indicators along the fetal brain-placenta-heart axis with conventional monitoring parameters can accurately predict perinatal and neonatal adverse outcomes in pregnancies complicated by placental-related FGR.

Inclusion Criteria:

• Singleton pregnancy.
• Isolated early-onset placental insufficiency-related fetal growth restriction (FGR), with priority given to cases with abnormal umbilical artery Doppler flow.
• Pregnancies in which expectant management is continued.

Exclusion Criteria:

• Multiple pregnancy complicated by selective fetal growth restriction (sFGR).
• FGR caused by fetal structural anomalies, genetic abnormalities, or intrauterine infection.
• Twin pregnancy with intrauterine fetal demise (IUFD) of one fetus.