Application of Spectral Methods to Assess Gametes, Embryos, and Human Reproductive Capabilities

Application of Spectral Methods to Assess the Potential of Gametes and Embryos, as Well as Human Reproductive Capabilities

Relevance of the research topic: At present, in the world, a kind of "plateau" in the efficiency of assisted reproductive technologies has been achieved, which ensures a birth rate of 30% per embryo transfer. At the same time, a relatively high (15-20%) and stable rate of miscarriages is preserved. Until now, no effective methods for assessing the potential of gametes and embryos, as well as human reproductive capabilities, have been offered. In these conditions, to increase the rate of births after IVF, clinicians have to increase the number of transferred embryos at a time, however, this leads to a sharp increase in complications of IVF, such as multiple pregnancy. In addition, until today, the clinical effectiveness of assessing the potential of endometrium using gene expression determination methods has not been shown. Therefore, to ensure the effectiveness and safety of infertility treatment, it is necessary to develop methods for predicting the potential of gametes and embryos, as well as human reproductive capabilities. For this purpose, the investigators assume to use Raman spectroscopy of the environment obtained from the objects of research, as well as fluorescent spectroscopy of endometrium. The objects of the research are gametes (spermatozoa) and embryos, used culture medium, endometrium. The subject of the study is the set of factors, that exists in the objects of research and their ability to determine the outcomes of infertility treatment.

Study Overview

Detailed Description

The goal of the planned work is to build a system for assessing and predicting the potential of gametes and embryos, as well as human reproductive capabilities, based on spectral data obtained from the objects of investigation, followed by prospective validation of the developed system. The study protocol consists of a retrospective and prospective stages. The task of the retrospective stage is to study gametes, embryos, and endometrium using the declared methods and build a machine learning model, determine the predictive capabilities of the obtained models. The task of the prospective stage is to determine the practical efficiency of applying models for making clinically significant decisions in infertility treatment with IVF. Hypothesis of the study: at the moment, a large number of approaches and protocols for deselecting and selecting embryos / gametes, assessing endometrial receptivity has been proposed. Approaches related to deselection are mainly based on determining the genetic constitution (aneuploidy) of the investigated object. However, there are no models linking such testing results and the outcome of infertility treatment with clinically significant effectiveness. There are many publications when, after transferring aneuploid embryos, pregnancy develops with a healthy fetus. It is known that the concordance of aneuploidy test results between the internal cell mass and trophoblasts is about 60%. Moreover, when using PGT-a, the birth rate among women with a single available blastocyst is reduced twice. Approaches related to selection, i.e. predicting a positive outcome of treatment, are built on morphological, morphometric, metabolic, and gene expression approaches. However, their effectiveness either has not been proven, or has (if it has) relatively low predictive importance. This is due to the fact that, from the point of modern views on reproductive biology, for the occurrence and development of successful pregnancy, it is necessary to combine factors that belong to gametes, embryos, and the maternal organism. Also, other undetectable technical or other circumstances may play a role in influencing the chance of ongoing pregnancy. Therefore, for effective prediction of a positive outcome, it is necessary to develop and apply complex models that take into account variables from different sources, from all parties involved. However, there will always be additional variability, caused by a series of unspecified or difficult to specify factors, which makes the task of such prediction quite challenging. In this connection, predicting a negative outcome of treatment (deselecting objects) seems more sensible, as it is entirely feasible for cases, where the cause of the negative outcome is attributable to this object (for example, the state of the embryo). This will not only optimize patient care protocols (for example, not to transfer obviously incapable to implant embryos), but also determine the possible cause of the negative outcome in each specific case, and in a population scale determine the share of variability of the phenomenon (development of ongoing pregnancy), which may be related to a specific object. The last one is necessary for adequate development and testing of new therapeutic and diagnostic methods

Study Type

Interventional

Enrollment (Estimated)

1064

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

    • Pushkin
      • Saint Petersburg, Pushkin, Russian Federation, 196608
        • Recruiting
        • Family planning center
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult

Accepts Healthy Volunteers

No

Description

Inclusion Criteria:

  • Embryos: embryos that have reached the blastocyst stage
  • Sperm: samples used for IVF during infertility treatment
  • Endometrium: endometrial spectra in cases where an embryo transfer was performed into the uterus

Exclusion Criteria:

  • For all groups: ectopic pregnancy
  • Embryos: presence of only one blastocyst, and that embryo prognosed by the model as negative
  • Sperm: a cycle where less than 3 oocytes suitable for fertilization were obtained; total pathological fertilization; 60% or more immature oocytes at the time of fertilization registration

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Other
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: Single

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: intervention
People undergoing IVF treatment with developed medical decisions support models
The method of Raman spectroscopy is based on the registration of inelastic scattering of photons. Each compound has its own spectral pattern when using a certain type of monochromatic radiation (laser). With this method, it is possible to obtain metabolic fingerprints from the objects being studied. Luminescent spectroscopy is a type of spectroscopy used to register emission from objects that occurred after absorbing the exciting (primary) radiation. Spectrophotometry is the detection of radiation in the visible area of the spectrum. Raman spectroscopy is used for the spent medium and semen to build artificial intelligence model and make prognosis of function for each object. For endometrium, luminescent spectroscopy and spectrophotometry are used to build the model and test its clinical relevance
No Intervention: control
People undergoing IVF treatment without developed medical decisions support models

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Embryonic model performance
Time Frame: 14 weeks
Positive predictive value for negative outcomes of single embryo transfers (%)
14 weeks
Gamete model performance
Time Frame: 2 weeks
Positive predictive value for cycles with impaired embryo development in vitro (%)
2 weeks
Endometrial model performance
Time Frame: 14 weeks
Positive predictive value for negative outcomes of single embryo transfers (%)
14 weeks
Embryonic model clinical efficiency
Time Frame: 14 weeks
Ongoing pregnancy rate per single embryo transfer (%)
14 weeks
Endometrial model clinical efficiency
Time Frame: 14 weeks
Ongoing pregnancy rate per single embryo transfer (%)
14 weeks

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Principal Investigator: Alexey Gryaznov, Family planning center of SPB SBHI "Maternity welfare clinic" #44 of Pushkin district

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

September 20, 2023

Primary Completion (Estimated)

February 28, 2024

Study Completion (Estimated)

December 31, 2025

Study Registration Dates

First Submitted

February 1, 2024

First Submitted That Met QC Criteria

February 12, 2024

First Posted (Actual)

February 20, 2024

Study Record Updates

Last Update Posted (Actual)

February 20, 2024

Last Update Submitted That Met QC Criteria

February 12, 2024

Last Verified

February 1, 2024

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • fpc-2023-ivf-01

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

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

Clinical Trials on Infertility

Clinical Trials on making artificial intelligence based decisions of gamete, embryo and endometrial potential

3
Subscribe