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NCT Number: NCT06408389

Mechanics of Human Pre Implantation Development

The time-lapse is a closed tri-gas incubator of the latest generation that provides optimal and stable culture conditions for the culture of embryos in In Vitro Fertilization (IVF). The integration of a camera within this incubator allows for continuous image capture, thus facilitating the monitoring of the entire embryonic development, from the day of fertilization to the moment of transfer into the uterus.

The contribution of the time-lapse system allows an evaluation of the embryos not only by their morphology, but also by their cell division kinetics, both being direct markers of cell mechanics. Together, these morpho-kinetic data finally allow for the best identification of embryos with greater implantation potential. Time-lapse imaging represents a further step towards an objective assessment of the embryo, but inter- and intra-embryologist variations in annotations partly compromise this objectivity. In addition, many decision algorithms based on the evaluation of morpho-kinetic parameters have been developed, but the lack of reproducibility from one Assisted Reproductive Technology (ART) center to another is a hindrance to the generalization of any particular algorithm. The aim of this retrospective study is to determine morpho-kinetic factors predictive of implantation using machine learning and to link these factors to human embryo mechanistic properties.

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Key information

Conditions

Infertility Genital Diseases Urogenital Diseases

Age range

18 year–43 year

Sex eligibility

All sexes

Study type

Observational

About this study

The time-lapse is a closed tri-gas incubator of the latest generation that provides optimal and stable culture conditions for the culture of embryos in In Vitro Fertilization (IVF). The integration of a camera within this incubator allows for continuous image capture, thus facilitating the monitoring of the entire embryonic development, from the day of fertilization to the moment of transfer into the uterus.

The contribution of the time-lapse system allows an evaluation of the embryos not only by their morphology, but also by their cell division kinetics, both being direct markers of cell mechanics. Together, these morpho-kinetic data finally allow for the best identification of embryos with greater implantation potential. Time-lapse imaging represents a further step towards an objective assessment of the embryo, but inter- and intra-embryologist variations in annotations partly compromise this objectivity. In addition, many decision algorithms based on the evaluation of morpho-kinetic parameters have been developed, but the lack of reproducibility from one Assisted Reproductive Technology (ART) center to another is a hindrance to the generalization of any particular algorithm.

Machine learning is one of the main methods of data analysis that could define algorithms that are unbiased, more robust and applicable to all centers. But the optimal algorithm is not yet defined. Recently, an artificial intelligence approach applied to a large collection of time-lapse embryo images was developed to determine the embryo with the highest grade of evolution, with an AUC> 0.98. Using clinical data, the authors created a decision tree to integrate embryo quality and female age and identify the chances of pregnancy. However, this approach did not take into account the whole kinetics of development, focusing on certain particular stages, nor the influence of parental and extrinsic factors other than age.

The aim of this retrospective study is to determine morpho-kinetic factors predictive of implantation and embryo development in IVF/ICSI using machine learning algorithms and relate these morpho-kinetic factors to the mechanical characteristics of cells.

Who can participate

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

Inclusion criteria

  • Couples enrolled in an IVF process and with embryos cultured in time-lapse
  • Couples informed non opposed to research

Exclusion criteria

  • Couples opposed to research
  • Couples under curator or tutorship
  • Couples under state xxx

Treatment and study plan

Primary outcomes

  1. Prediction of embryo implantation by the machine learning algorithm from embryo morphokinetic parameters and patient health data.

    Time frame: 2 years

    The algorithm outcome will be evaluated retrospectively on human embryos which have been transferred, for which we know whether its implantation was successful and led to birth. Using embryo morphokinetic and health patient data, we will predict a probability of implantion and compare its value (<0.5: no implantation or >0.5: implantation) to the true result of the embryo transfer (no implantation or implantation). This will allow us to evaluate the potential of the algorithm to support clinical decision-making in the future.

Secondary outcomes

  1. Link between couples' parameters and embryo morpho-kinetics

    Time frame: 3 years

    Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :

    Age (years) : female / male

  2. Link between couples' parameters and embryo morpho-kinetics

    Time frame: 3 years

    Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :

    Weight (kg) : female / male

  3. Link between couples' parameters and embryo morpho-kinetics

    Time frame: 3 years

    Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :

    Height (cm) : female / male

  4. Link between couples' parameters and embryo morpho-kinetics

    Time frame: 3 years

    Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :

    Weight and height combined for BMI (kg/M2) : female / male

  5. Link between couples' parameters and embryo morpho-kinetics

    Time frame: 3 years

    Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :

    Female : Day-3 FSH (IU/l)

  6. Link between couples' parameters and embryo morpho-kinetics

    Time frame: 3 years

    Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :

    Female : Day-3 LH (IU/l)

  7. Link between couples' parameters and embryo morpho-kinetics

    Time frame: 3 years

    Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :

    Female : Day-3 Estradiol (pg/ml)

  8. Link between couples' parameters and embryo morpho-kinetics

    Time frame: 3 years

    Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :

    Female : Day-3 AMH (ng/ml)

  9. Link between couples' parameters and embryo morpho-kinetics

    Time frame: 3 years

    Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :

    Female : Day-3 Antral Follicular count

  10. Link between couples' parameters and embryo morpho-kinetics

    Time frame: 3 years

    Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :

    Female : cause of infertility (endometriosis (yes/no))

  11. Link between couples' parameters and embryo morpho-kinetics

    Time frame: 3 years

    Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :

    Female : cause of infertility (tubal (yes/no))

  12. Link between couples' parameters and embryo morpho-kinetics

    Time frame: 3 years

    Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :

    Female : cause of infertility (diminished ovarian reserve (yes/no))

  13. Link between couples' parameters and embryo morpho-kinetics

    Time frame: 3 years

    Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :

    Male : sperm parameters (volume (ml))

  14. Link between couples' parameters and embryo morpho-kinetics

    Time frame: 3 years

    Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :

    Male : sperm parameters (concentration (10^6/ml))

  15. Link between couples' parameters and embryo morpho-kinetics

    Time frame: 3 years

    Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :

    Male : sperm parameters (progressive mobility (%))

  16. Link between couples' parameters and embryo morpho-kinetics

    Time frame: 3 years

    Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :

    Male : sperm parameters (vitality (%))

  17. Link between couples' parameters and embryo morpho-kinetics

    Time frame: 3 years

    Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :

    Male : sperm parameters (normal form (%))

  18. Link between couples' parameters and embryo morpho-kinetics

    Time frame: 3 years

    Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :

    Male : FSH (IU/l)

  19. Link between couples' parameters and embryo morpho-kinetics

    Time frame: 3 years

    Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :

    Male : LH (IU/l)

  20. Link between couples' parameters and embryo morpho-kinetics

    Time frame: 3 years

    Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :

    Male : total testosterone (ng/ml)

  21. Link between couples' parameters and embryo morpho-kinetics

    Time frame: 3 years

    Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :

    caryotype : Female/male

  22. Link between couples' parameters and embryo morpho-kinetics

    Time frame: 3 years

    Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :

    Male : cause of male infertility (obstructive azoospermia (yes/no))

  23. Link between couples' parameters and embryo morpho-kinetics

    Time frame: 3 years

    Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :

    Male : cause of male infertility (non-obstructive azoospermia (yes/no))

  24. Link between couples' parameters and embryo morpho-kinetics

    Time frame: 3 years

    Identify statistical links between parental or extrinsic factors (linked to the attempt) and morpho-kinetic parameters :

    Male : cause of male infertility (oligoasthenoteratospermia (yes/no))

  25. Statistical correlation between embryo implantation prediction and morphokinetic parameters

    Time frame: 3 years

    The machine learning algorithm (neural network) trained for the primary outcome will be used to quantify the average percentage contributed by each morphokinetic parameter in the prediction of implantation success or failure ("explainable artificial intelligence"). This will allow us to determine what morphokinetic parameters influence the most positively or negatively the prediction of implantation.

  26. Embryo reconstruction in 3D

    Time frame: 3 years

    Develop an automatic method for reconstructing the morphology of embryos in 3 dimensions from 2-dimensional images in transmitted light (Geri incubator or Embryoscope type)

  27. Software developing

    Time frame: 3 years

    Develop decision support software for the benefit of embryologists as part of an ART attempt

Study contacts

Contact information is provided by the study sponsor or research team.

Catherine PATRAT, MD,PhD

CONTACT

[email protected]

00 33 1 58 41 37 34

Marie BNEHAMMANI-GODARD

CONTACT

[email protected]

00 33 1 58 41 11 90

Sponsors and collaborators

Lead sponsor

Assistance Publique - Hôpitaux de Paris

Other

Collaborators

  • Centre National de la Recherche Scientifique, France
  • Collège de France
  • Institut Curie
  • URC-CIC Paris Descartes Necker Cochin

Registry information

Official study title

From Oocyte to Embryo: Analysis of Mechanics of Human Pre Implantation Development

Acronym: MECANEMB

Important dates

Study start
2025
Primary completion
2028
Study completion
2028
First posted
May 10, 2024
Registry last updated
Sep 12, 2025

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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