Journal of Hebei Medical University ›› 2024, Vol. 44 ›› Issue (5): 608-614.doi: 10.3969/j.issn.1007-3205.2024.05.020

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Study on the construction of a model to predict adhesions after interventional recanalisation for infertility based on 2D and 3D ultrasound imaging and clinical factors

  

  1. 1.Department of Ultrasound, the Second Maternal and Child Health Hospital of Ji′nan City, Shandong 
    Province, Ji′nan 271100, China; 2.Department of Gynecology, the Second Maternal and 
    Child Health Hospital of Ji′nan City
    ,Shandong Province, Ji′nan 271100, China

  • Online:2024-05-25 Published:2024-05-22

Abstract: Objective To investigate the predictive value of constructing models based on two-dimensional and three-dimensional ultrasound imaging and clinical factors for adhesions after interventional recanalization for infertility, so as to determine reasonable diagnostic and treatment modalities, thereby improving clinical pregnancy rates. 
Methods A total of 335 patients after interventional recanalisation for infertility in our hospital were selected and divided into a modeling population (n=235) and a validation population (n=100) according to the ratio of 7〖DK〗∶3. Tubal adhesions, clinical factors, 2D and 3D ultrasound imaging performance at 3 months after surgery were recorded, and logistic regression equations were used to analyse the influencing factors of adhesions after interventional recanalisation for infertility, a nomogram model was constructed, and internal and external validation was conducted. 
Results There were significant differences in the comparison of pelvic inflammation, location of tubal occlusion, history of uterine manipulation, history of miscarriage, and 2D and 3D ultrasound imaging performance between the adhesion and non-adhesion groups (P<0.05). Pelvic inflammation, location of tubal occlusion, history of uterine manipulation, ovarian annular strong echogenicity, tubal alignment distortion, pelvic homogeneous diffusion, and ovarian encapsulation were factors influencing adhesions after recanalization intervention for infertility (P<0.05). A nomogram prediction model was constructed, which had AUCs of 0.929 and 0.919 in the modeling and validation populations, respectively, and DCA curves showed that the model had good net benefit values ranging from 0.2 to 0.9 and from 0.0 to 0.85 in the modeling and validation populations. 
Conclusion A model based on 2D and 3D ultrasound imaging and clinical factors can be used to predict adhesions after interventional recanalization for infertility, and clinical follow-up treatment combined with relevant factors can be tailored to reduce the risk of postoperative adhesions. 


Key words: infertility, female, tissue adhesions, echocardiography