Retrospective Evaluation Blastocyst Development by Artificial Intelligency (EBAI)

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

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.

Study Overview

• Status: Completed
• Conditions: Artificial Intelligence; Reproductive Techniques, Assisted; Embryo Transfer

Detailed Description

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

• Study Type: Observational
• Enrollment (Actual): 333

Contacts and Locations

Study Locations

• France
  • Clermont-Ferrand, France
    • CHU de Clermont-Ferrand

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

Couples, single women, or female couples undergoing assisted reproductive technology (ART) with IVF/ICSI techniques followed by blastocyst transfer.

Description

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

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Comparison of artificial intelligence (AI) Score and Laboratory Embryo Classification	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.	01/01/2022-31/12/2023

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
To determine the association between EMA Score and implantation and live birth rates	To analyze the correlation between EMA scores and these key reproductive outcomes (implatation and live birth rate)	01/01/2022-31/12/2023
To evaluate the optimal EMA score threshold for maximizing live birth rates	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.	01/01/2022-31/12/2023

Collaborators and Investigators

• Sponsor: University Hospital, Clermont-Ferrand
• Investigators: Principal Investigator: Florence Brugnon, University Hospital, Clermont-Ferrand

Study record dates

Study Major Dates

• Study Start (Actual): January 1, 2022
• Primary Completion (Actual): December 1, 2023
• Study Completion (Actual): April 30, 2025

Study Registration Dates

• First Submitted: January 26, 2026
• First Submitted That Met QC Criteria: January 26, 2026
• First Posted (Actual): February 3, 2026

Study Record Updates

• Last Update Posted (Actual): February 6, 2026
• Last Update Submitted That Met QC Criteria: February 4, 2026
• Last Verified: May 1, 2025

More Information

Terms related to this study

• Keywords: Artificial intelligence; IVF outcome; Embryo selection; Time-lapse monitoring
• Additional Relevant MeSH Terms: Behavior; Social Behavior; Helping Behavior
• Other Study ID Numbers: 2023_BRUGNON_retrospectiveEBAI

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No