Artificial intelligence assistance for fetal development: evaluation of an automated software for biometry measurements in the mid-trimester

作者：Xuesong Han, Junxuan Yu, Xin Yang, Chao‐Yu Chen, Han Zhou, Chuangxin Qiu, Yan Cao, Tianjing Zhang, Meiran Peng, Guiyao Zhu, Dong Ni, Yuanji Zhang, Nana Liu · 发表于：BMC Pregnancy and Childbirth · 年份：2024 · DOI：10.1186/s12884-024-06336-y · 被引用次数：9 · 研究领域：Fetal and Pediatric Neurological Disorders、Prenatal Screening and Diagnostics、Neonatal and fetal brain pathology

BACKGROUND: This study presents CUPID, an advanced automated measurement software based on Artificial Intelligence (AI), designed to evaluate nine fetal biometric parameters in the mid-trimester. Our primary objective was to assess and compare the CUPID performance of experienced senior and junior radiologists. MATERIALS AND METHODS: This prospective cross-sectional study was conducted at Shenzhen University General Hospital between September 2022 and June 2023, and focused on mid-trimester fetuses. All ultrasound images of the six standard planes, that enabled the evaluation of nine biometric measurements, were included to compare the performance of CUPID through subjective and objective assessments. RESULTS: There were 642 fetuses with a mean (±SD) age of 22 ± 2.82 weeks at enrollment. In the subjective quality assessment, out of 642 images representing nine biometric measurements, 617-635 images (90.65-96.11%) of CUPID caliper placements were determined to be accurately placed and did not require any adjustments. Whereas, for the junior category, 447-691 images (69.63-92.06%) were determined to be accurately placed and did not require any adjustments. In the objective measurement indicators, across all nine biometric parameters and estimated fetal weight (EFW), the intra-class correlation coefficients (ICC) (0.843-0.990) and Pearson correlation coefficients (PCC) (0.765-0.978) between the senior radiologist and CUPID reflected good reliability compared with the ICC (0.306-...