医学
放射科
磁共振成像
接收机工作特性
胎盘植入
无线电技术
诊断准确性
作者
Yin Xi,Maysam Shahedi,Quyen N. Do,James D. Dormer,Matthew A. Lewis,Baowei Fei,Catherine Y. Spong,Ananth J. Madhuranthakam,Diane M. Twickler
摘要
A Deep-Learning (DL) based segmentation tool was applied to a new magnetic resonance imaging dataset of pregnant women with suspected Placenta Accreta Spectrum (PAS). Radiomic features from DL segmentation were compared to those from expert manual segmentation via intraclass correlation coefficients (ICC) to assess reproducibility. An additional imaging marker quantifying the placental location within the uterus (PLU) was included. Features with an ICC < 0.7 were used to build logistic regression models to predict hysterectomy. Of 2059 features, 781 (37.9%) had ICC <0.7. AUC was 0.69 (95% CI 0.63-0.74) for manually segmented data and 0.78 (95% CI 0.73-0.83) for DL segmented data.
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