Aftificial Inteligence in Assisted Reproductive Techniques to Assess Oocyte Quality and Embryo Ploidy

NCT06539104 | Recruiting

• 1 other identifier: NW24-08-00048
• Study Type: observational
• Target: 1,000
• Locations: 1 country
• Sites: 4

Brief Summary

The assisted reproduction success rate is affected by several factors including the age of the women, oocyte quality and maturation state, as well as sperm quality. Imaging of the meiotic spindle may be crucial for determining the oocyte maturation. Artificial intelligence (AI) will be applied to establish the complex oocyte quality, embryo ploidy and pregnancy success probability from the sequence of data, starting with the recording of the meiotic spindle in polarized light, through paternal factors up to the time lapse recording of early embryo development. This strategy should reduce the cost of fertility treatment thanks to increased efficiency in choosing the most promising candidates and reducing the need for costly laboratory analyses.

Conditions

Infertility; Infertility, Female; Infertility, Male; Infertility Unexplained

Keywords

infertility; humant oocyte; IVF; arteficial inteligence; Sperm count; meiotic spindle; time lapse

Outcome Measures

Primary Outcomes (1)

• The relative number of embryos whose ploidy was correctly predicted by AI

  Using an AI based non-invasive method of selecting a high-quality and genetically healthy embryos will undoubtably improve clinical and diagnostic practice and reduce costs in the field of infertility treatment. Both the segmentation and classification training will be based on expert annotations. The approach should lead to a classification accuracy at least 70%.

  1 hour

Interventions

arteficial inteligence evaluation of oocyte and embryo development PROCEDURE

apply AI to find out the complex oocyte quality, embryo development, embryo ploidy and pregnancy success probability from the sequence of the data starting from the recording of the meiotic spindle in polarized light, through paternal factors up to the time lapse record of early embryo development.

Also known as: Preimplantation Genetic Testing (PDT), Computer Assisted Sperm Analysis (CASA), DNA Sperm Fragmentation Index (DFI), Intracytoplasmatic Sperm Injection (ICSI)

Eligibility Criteria

• Age: 18 Years - 49 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64)
• Sampling Method: Non-Probability Sample

Study Population

Infertility couples, where ICSI and PDT are indicated

You may qualify if:

• Intracytoplasmatic Sperm Injection
• Preimplantation genetic testing
• Time lapse embryo record
• Singned informed consent

You may not qualify if:

• Gynecological diseases
• Genetical diseases of parents

Sponsors & Collaborators

• Charles University, Czech Republic: lead
• Czech Academy of Sciences: collaborator
• Czech Technical University in Prague: collaborator
• General University Hospital, Prague: collaborator

Study Sites (4)

General University Hospital in Prague

Prague, 128 08, Czechia

RECRUITING

Czech Technical University in Prague

Prague, Czechia

RECRUITING

Institute of Physics AS CR

Prague, Czechia

RECRUITING

Biocev As Cr

Vestec, Czechia

RECRUITING

Related Publications (5)

• van Loendersloot LL, van Wely M, Limpens J, Bossuyt PM, Repping S, van der Veen F. Predictive factors in in vitro fertilization (IVF): a systematic review and meta-analysis. Hum Reprod Update. 2010 Nov-Dec;16(6):577-89. doi: 10.1093/humupd/dmq015. Epub 2010 Jun 25.

  PMID: 20581128 BACKGROUND

• Wu B, Shi J, Zhao W, Lu S, Silva M, Gelety TJ. Understanding reproducibility of human IVF traits to predict next IVF cycle outcome. J Assist Reprod Genet. 2014 Oct;31(10):1323-30. doi: 10.1007/s10815-014-0288-y. Epub 2014 Aug 15.

  PMID: 25119191 BACKGROUND

• Hanevik HI, Hessen DO. IVF and human evolution. Hum Reprod Update. 2022 Jun 30;28(4):457-479. doi: 10.1093/humupd/dmac014.

  PMID: 35355060 BACKGROUND

• Rienzi L, Ubaldi F, Martinez F, Iacobelli M, Minasi MG, Ferrero S, Tesarik J, Greco E. Relationship between meiotic spindle location with regard to the polar body position and oocyte developmental potential after ICSI. Hum Reprod. 2003 Jun;18(6):1289-93. doi: 10.1093/humrep/deg274.

  PMID: 12773461 BACKGROUND

• Innocenti F, Fiorentino G, Cimadomo D, Soscia D, Garagna S, Rienzi L, Ubaldi FM, Zuccotti M; SIERR. Maternal effect factors that contribute to oocytes developmental competence: an update. J Assist Reprod Genet. 2022 Apr;39(4):861-871. doi: 10.1007/s10815-022-02434-y. Epub 2022 Feb 15.

  PMID: 35165782 BACKGROUND

Biospecimen

Retention: SAMPLES WITH DNA

Sperms

MeSH Terms

Conditions

Infertility; Infertility, Female; Infertility, Male

Interventions

Embryonic Development; 1-phenyl-3,3-dimethyltriazene

Condition Hierarchy (Ancestors)

Genital Diseases; Urogenital Diseases; Genital Diseases, Female; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Genital Diseases, Male; Male Urogenital Diseases

Intervention Hierarchy (Ancestors)

Embryonic and Fetal Development; Morphogenesis; Growth and Development; Physiological Phenomena; Reproduction; Reproductive Physiological Phenomena; Reproductive and Urinary Physiological Phenomena

Central Study Contacts

Jaromir Masata, MD

CONTACT

+420603444662; masata@volny.cz

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Leading doctor of the Center of Urogynecology and Pelvic Recontructive Surgery

Study Record Dates

• First Submitted: August 1, 2024
• First Posted: August 6, 2024
• Study Start: January 5, 2024
• Primary Completion (Estimated): December 31, 2027
• Study Completion (Estimated): March 31, 2028
• Last Updated: January 22, 2025

Record last verified: 2025-01

Data Sharing

• IPD Sharing: Will not share

Locations

CZ (4)