Purpose: This pilot study aimed to evaluate the potential synergistic role of three-dimensional power Doppler angiography ultrasound and the expression of Leukemia Inhibitory Factor (LIF) protein in predicting the endometrial receptivity of fresh In-Vitro Fertilization (IVF) cycles.
Materials And Methods: This prognostic cohort study involved 29 good prognosis women who underwent fresh IVF cycles with fresh blastocysts transfer. Serial measurements of sub-endometrial parameters including vascularity index (VI), flow index (FI), and vascularization flow index (VFI) were conducted consecutively via power Doppler angiography on the day of oocyte maturation trigger, oocyte retrieval, and blastocyst transfer. Aspiration of endometrial secretion was performed on the day of embryo transfer.
Results: The mean index of VI and VFI on the trigger and oocyte retrieval day and also LIF protein concentration at the window of implantation were significantly higher in clinically pregnant women than that of the non-pregnant women (p < 0.05). The area under the curve (AUC) of VI and VFI was shown to have a powerful predictive value to forecast receptive endometrium on either trigger day (0.788 and 0.813, respectively) or oocyte retrieval day (0.813 and 0.818). Likewise, LIF concentration on the day of embryo transfer was adequate to become a predictor for endometrial receptivity (AUC 0.874). A combination of the VI and VFI on the trigger day and LIF concentration at specific cut-off values (VI > 5.381, VFI > 1.483, LIF 703.5 pg/mL) produced an algorithm with high AUC (0.881) and high specificity (94.4%) for an adequate prediction of non-receptive endometrium.
Conclusion: VI and VFI index assessed on maturation trigger day and the expression of LIF protein concentration at the window of implantation provided sufficient information to predict endometrial receptivity. A large randomized control trial is needed to validate these findings.
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http://dx.doi.org/10.1007/s00404-022-06450-2 | DOI Listing |
Diagnostics (Basel)
January 2025
Department of Obstetrics and Gynecology, IVF-Unit, Acibadem Kayseri Hospital, 38140 Kayseri, Türkiye.
The downregulation of anti-adhesive regulatory proteins and upregulation of adhesive genes are critical for the receptive endometrium. This study was designed to determine whether switching between the anti-adhesive podocalyxin (PDX) and adhesive HOXA10 receptivity modulator occurs in the endometrium of women with recurrent implantation failure (RIF). Twenty-four patients with RIF who could not conceive for three or more cycles despite good-quality embryo transfer constituted the study group.
View Article and Find Full Text PDFMol Med
January 2025
Department of Obstetrics and Gynecology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Reduced lymphoid enhancer-binding factor 1 (LEF1) expression in patients with adenomyosis during the mid-secretory phase leads to impaired endometrial receptivity, affecting embryo implantation. This study investigated the molecular mechanisms underlying reduced endometrial receptivity in 25 adenomyosis patients and 25 controls. Functional experiments were conducted using human endometrial stromal cells (HESCs) and TERT-immortalized HESCs(T-HESCs), with final validation performed using a mouse model.
View Article and Find Full Text PDFBMC Womens Health
January 2025
OVIklinika Infertility Center, Połczyńska 31, Warsaw, 01-377, Poland.
Background: Embryo implantation involves two key elements: a good quality embryo and receptive endometrium. Endometrial receptivity abnormalities are known as one of the possible causes of recurrent implantation failure (RIF), especially when the embryo is euploid. This study was aimed to evaluate the impact of age and other clinical factors on endometrial receptivity in women with RIF.
View Article and Find Full Text PDFFront Physiol
December 2024
Department of Obstetrics and Gynecology, Deyang People's Hospital, Deyang, Sichuan, China.
Background: Recurrent pregnancy loss (RPL) poses significant challenges in clinical management due to an unclear etiology in over half the cases. Traditional screening methods, including ultrasonographic evaluation of endometrial receptivity (ER), have been debated for their efficacy in identifying high-risk individuals. Despite the potential of artificial intelligence, notably deep learning (DL), to enhance medical imaging analysis, its application in ER assessment for RPL risk stratification remains underexplored.
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