Research status of ultrasound parameters and blood indicators in predicting fetal growth restriction
10.3969/j.issn.1674-8115.2025.08.014
- VernacularTitle:超声指标和血液指标预测胎儿生长受限的研究现状
- Author:
Shuyuan LIANG
1
;
Baoying YE
;
Weiwei CHENG
Author Information
1. 上海交通大学医学院附属国际和平妇幼保健院产科,上海 200030;上海市胚胎源性疾病重点实验室,上海 200030
- Publication Type:Journal Article
- Keywords:
fetal growth restriction(FGR);
ultrasound parameter;
blood indicator;
artificial intelligence(AI);
prediction
- From:
Journal of Shanghai Jiaotong University(Medical Science)
2025;45(8):1059-1065
- CountryChina
- Language:Chinese
-
Abstract:
Fetal growth restriction(FGR)refers to the failure of a fetus to reach the level of growth potential determined by its genetic potential.It is a common obstetric complication,occurring in 5%to 10%of pregnancies.As a major risk factor for perinatal death and adverse neonatal outcomes,early prediction of FGR is crucial for optimizing pregnancy management.Existing evidence suggests that FGR is significantly associated with a variety of adverse pregnancy outcomes,including intrauterine hypoxia,preterm birth,neonatal asphyxia,and even neonatal mortality.It may also affect long-term neurological development and increase the risk of metabolic diseases in adulthood.Its pathogenesis is complex,which may involve placental blood flow perfusion insufficiency and genetic factors.Ultrasound parameters are the main basis for the diagnosis of FGR,among which fetal biological and hemodynamic parameters are of great value.Elevated umbilical artery blood flow resistance index,absent or reversed end-diastolic blood flow,and placental insufficiency are associated with the severity of FGR.However,approximately 10%of fetuses diagnosed by ultrasound as having FGR are later confirmed to be healthy small-for-gestational-age(SGA)infants after birth,and this false positive result may lead to unnecessary clinical interventions.Currently,there is no recognized accurate prediction model for FGR in clinical practice.Future research should focus on establishing unified diagnostic criteria and developing multi-index joint prediction tools based on artificial intelligence(AI).Early prediction and intervention for FGR are of great significance to improve perinatal outcomes.This paper reviewed the predictive value of ultrasound parameters,blood indicators,and their integration with AI for FGR,in order to provide a basis for clinical decision-making.
