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Updated: Oct 26, 2025

Methods for Studying Uterine Contributions to Pregnancy Establishment in an Ovariectomized Mouse Model
Published on: April 7, 2023
Development and validation of a pregnancy prediction model based on ultrasonographic features related to endometrial
Xujuan Shui1,2, Caicha Yu1,2, Jianxin Li1,2
1Department of Ultrasound, Wenzhou People's Hospital Wenzhou, China.
Objective:
Our aim was to identify multiple endometrial receptivity related factors by applying non-invasive, repeatable multimodal ultrasound methods. We further established a practical prediction model for pregnancy prediction.
Materials And Methods:
Our study included 152 participants from Wenzhou People's Hospital, Wenzhou Maternal and Child Health Care Hospital, and the Third Affiliated Hospital of Wenzhou Medical University. Clinical information including age and ultrasonographic data were collected. By applying t-test and Wilcoxon rank sum tests, we obtained endometrial receptivity related factors, and by using logistic regression, we established a prediction model for possibility of successful pregnancy.
Results:
Among all the factors associated with endometrial receptivity, uterine peristaltic wave frequency, uterine spiral artery resistant index, endometrial flow index, ultrasound elastography strain radio (SR), and age showed significant statistical difference between nonpregnant and pregnant volunteers. Consequently, we developed and validated a nomogram prediction model with its value of area under the receiver operating curve up to 0.949 for predicting pregnancy by using age and ultrasonographic factors including uterine peristalsis, uterine spiral artery, and ultrasound elastographic features. The sensitivity was 0.83 and specificity was 0.96. In addition, its performance was better than that of a direct scoring system.
Conclusion:
By employing the pregnancy prediction model with endometrial receptivity associated ultrasonographic factors, clinicians can give a quantitative evaluation and a real time screen of the uterus condition as well as optimal guiding, treatment, and management recommendations for infertility-related patients.

