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Completed

NCT Number: NCT07383480

Retrospective Evaluation Blastocyst Development by Artificial Intelligency

In assisted reproductive technology (ART), selecting the most viable embryos from a large number of fertilized eggs is crucial. While techniques like morphological assessment, time-lapse monitoring systems, and pre-implantation genetic testing have improved the process, implantation success rates remain limited. The introduction of artificial intelligence in embryo evaluation, such as automated systems like EMA by AIVFTM, provides a promising alternative to enhance the accuracy and effectiveness of embryo selection. This study aims to assess the performance of the EMA system compared to traditional methods by examining its ability to rank embryos based on their potential for successful implantation, with the goal of increasing the chances of a successful pregnancy. This is the first clinical evaluation of this platform in France, offering new opportunities to improve decision-making in in-vitro fertilization.

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Key information

Conditions

Reproductive Techniques, Assisted Artificial Intelligence Behavior Embryo Transfer Helping Behavior Social Behavior

Age range

18 year–60 year

Sex eligibility

All sexes

Study type

Observational

Primary location

CHU de Clermont-Ferrand

Clermont-Ferrand, France

About this study

This monocentric study analyzes 420 ART cycles from the Clermont-Ferrand University Hospital, conducted between January 2022 and December 2023. It includes IVF/ICSI cycles with embryos cultured in a Time-Lapse Incubator (Geri) and both fresh and frozen blastocyst transfers. A total of 1211 embryos were analyzed, with 619 used to train algorithms for predicting reproductive outcomes. This included 551 single and 34 double embryo transfer cycles, divided into 274 fresh and 345 frozen blastocyst transfers. For all blastocyst-stage embryos, the Geri score, Gardner classification, and EMA score based on time-lapse video were recorded for statistical analysis and evaluation of reproductive outcome predictions

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • IVF or ICSI treatment between January 2022 and December 2023
  • Fresh or frozen sperm from the partner or a donor
  • Embryo culture up to the 105th hour
  • Fresh or frozen embryo transfer on Day 5
  • Known implantation data (clinical pregnancy assessed by the presence of cardiac activity at 6 weeks via ultrasound)

Exclusion criteria

  • Epididymal or testicular sperm
  • Embryo culture with transfer on Day 2 or Day 3
  • ICSI with oocyte donation or the use of thawed oocytes
  • Transfer of two embryos resulting in a singleton pregnancy
  • No blastocyst obtained on Day 5

Treatment and study plan

Primary outcomes

  1. Comparison of artificial intelligence (AI) Score and Laboratory Embryo Classification

    Time frame: 01/01/2022-31/12/2023

    The study aims to compare the EMA score assigned by the EMA platform (AiVFTM), an artificial intelligence-based tool, with the manual embryo classification performed by embryologists in the laboratory. This manual classification includes morphological assessment using the Gardner grading system and morphokinetic evaluation through the GERI score. The goal is to determine the level of concordance between the AI-generated scores and traditional embryologist assessments, and to evaluate the relationship and possible variability between the EMA score and the manual scoring methods.

Secondary outcomes

  1. To determine the association between EMA Score and implantation and live birth rates

    Time frame: 01/01/2022-31/12/2023

    To analyze the correlation between EMA scores and these key reproductive outcomes (implatation and live birth rate)

  2. To evaluate the optimal EMA score threshold for maximizing live birth rates

    Time frame: 01/01/2022-31/12/2023

    To identify the optimal EMA score threshold that is most strongly associated with the highest live brith rates in assisted reproductive technology (ART). By analyzing the relationship between different EMA score levels and live birth outcomes, the study seeks to establish a predictive threshold that could guide embryo selection, thereby improving the likelihood of successful live birth following embryo transfer.

Sponsors and collaborators

Lead sponsor

University Hospital, Clermont-Ferrand

Other

Registry information

Official study title

Enhancing Embryo Selection With AiVF: A Major Advancement in ART - A Retrospective Study

Acronym: EBAI

Important dates

Study start
2022
Primary completion
2023
Study completion
2025
First posted
Feb 3, 2026
Registry last updated
Feb 6, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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