ArticleJournal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine2025
Development of a Novel Nomogram Based on Ultrasonic Radiomics for Predicting Intrauterine Pregnancy After Frozen Embryo Transfer Cycle.
Article in Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Machine learning-based endometrial ultrasound radiomics habitat analysis for predicting pregnancy outcomes after embryo transfer.Journal of ovarian research · 2026Article
- Development and Validation of An Interpretable Machine Learning-Based Prediction Model of Postpartum Hemorrhage in Placenta Previa Following Cesarean Section: A Multicenter Study.Reproductive sciences (Thousand Oaks, Calif.) · 2025Article
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8 authors.
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Abstract
objectivesThis study aimed to develop a nomogram for predicting intrauterine pregnancy after an in vitro frozen embryo transfer cycle using endometrial ultrasound radiomics.
methodsA total of 211 patients who underwent ultrasound examination on the day of endometrial transformation before the frozen embryo transfer cycle were enrolled. The patients were divided into an intrauterine pregnancy group and a pregnancy failure group based on ultrasound results. Clinical characteristics and radiomic features were analyzed using univariate and multivariate logistic regression analyses. A nomogram prediction model was established based on radiomic signatures and significant clinical factors. The model's robustness was assessed in training and external validation cohorts.
resultsNine radiomic features were selected using least absolute shrinkage and selection operator (LASSO), and the radiomics score (Rad-score) was calculated as the sum of each feature multiplied by the nonzero coefficient from LASSO. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve based on the Rad-score was 0.72, 0.65, and 0.69 in the training, validation, and combined cohorts, respectively. To improve diagnostic efficiency, the Rad-score was further integrated with clinical factors to form a novel predictive nomogram. The results indicated that the AUC increased to 0.81, 0.67, and 0.77 in the training, validation, and combined cohorts, respectively. Decision curve analysis showed that the radiomics nomogram was clinically useful.
conclusionThe radiomics and clinical predictive nomogram can effectively predict intrauterine pregnancy after in vitro frozen embryo transfer and can be further applied in clinical strategy.
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