ArticlePloS one2025
Utilizing MV-FLOW™ and multidimensional ultrasound characteristics for prognosticating FET outcomes in RIF patients: Study Protocol for a cross-sectional study.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Assessment of fetal lung maturity and prediction of neonatal respiratory distress syndrome by MV-Flow imaging.Ultrasonography (Seoul, Korea) · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recurrent implantation failure (RIF) is a common issue in frozen-thawed embryo transfer (FET). Prior to transfer, uterine endometrial receptivity of FET patients can be assessed using multimodal transvaginal ultrasound indicators to predict the success rate of the current FET cycle. Endometrial blood flow is a crucial element in evaluating endometrial receptivity. MV-FLOW™ is an advanced two-dimensional superb microvascular imaging technology that can detect and display blood flow in micro-vessels. The data for this study were obtained from an ongoing cross-sectional study comprising 323 RIF patients and 323 first implantation (FI) patients, who underwent transvaginal ultrasound before FET. We collected basic clinical data and multimodal ultrasound data from these patients as predictive features, with clinical pregnancy as the predictive label, for model training. Based on the above, this study aims to establish and validate a clinical prediction model for FET outcomes using support vector classification (SVC) algorithms, based on MV-FLOW™ and multidimensional transvaginal ultrasound imaging features. The objective is to determine the predictive role of multimodal transvaginal ultrasound in embryo transfer outcomes and provide evidence for the clinical application of MV-FLOW™. Trial registration: Trial Registration: ChiCTR2400086401.
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Registered trials
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