Predictive factors in in vitro fertilization (IVF): a systematic review and meta-analysis.
L L van Loendersloot, M van Wely, J Limpens...
https://pubmed.ncbi.nlm.nih.gov/20581128Actively Recruiting
Age: 18Years - 49Years
All Genders
ID06539104
Scanning the Meiotic Spindle in Assisted Reproductive Techniques to Assess Oocyte Quality and Embryo Ploidy Evaluated by Artificial Intelligence (SMARTAI Study)
Led by Charles University, Czech Republic · Updated on 2025-01-22
1000
Participants Needed
4
Research Sites
13 weeks
Total Duration
On this page
Sponsors
C
Charles University, Czech Republic
Lead Sponsor
C
Czech Academy of Sciences
Collaborating Sponsor
AI-Summary
What this Trial Is About
Researchers are studying infertility in men and women to improve assisted reproductive techniques using artificial intelligence (AI). The study focuses on key factors affecting in vitro fertilization (IVF) success, such as the age of the woman, oocyte quality, maturation state, and sperm quality. AI will analyze a sequence of data starting with imaging the meiotic spindle in the oocyte, followed by paternal factors and early embryo development to predict embryo ploidy and pregnancy success. This approach aims to increase treatment efficiency and reduce costs by selecting the most promising candidates and minimizing the need for expensive laboratory tests. The intervention involves applying AI to automatically analyze microscopic images of oocytes and time-lapse videos of embryo development after intracytoplasmic sperm injection (ICSI). The study uses image analysis and machine learning to assess the meiotic spindle and other oocyte features that may correlate with fertilization, pregnancy success, or genetic defects. Collaboration with technical and scientific institutes aims to develop software capable of predicting pregnancy probability and embryo ploidy status from these images and videos. Participants will undergo procedures including ICSI, preimplantation genetic testing, and time-lapse embryo recording. Data collected will be paired with pregnancy outcomes and embryo ploidy status. Researchers will evaluate sperm parameters in relation to fertilization and early embryo development. The primary outcome measured is the accuracy of AI in predicting embryo ploidy. The study involves detailed image and video analysis but does not involve treatment randomization. Participants' involvement will include consent, image recording, and genetic testing, with the study expected to continue through March 2028.
CONDITIONS
Brief Title
Aftificial Inteligence in Assisted Reproductive Techniques to Assess Oocyte Quality and Embryo Ploidy
Who Can Participate
Age: 18Years - 49Years
All Genders
Eligibility Criteria
You may qualify if you...
- Undergoing intracytoplasmic sperm injection (ICSI)
- Undergoing preimplantation genetic testing
- Having time-lapse embryo recording
- Signed informed consent
You will not qualify if you...
- Presence of gynecological diseases
- Genetic diseases in either parent
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
1
2
3
Your Study Journey
Screening
Duration - 2 to 4 weeks
Participants are screened for eligibility to participate in the trial.
1 visit (in-person)
Diagnostic Evaluation
Duration - Up to 1 day
Participants undergo imaging and data recording including meiotic spindle imaging, sperm parameter evaluation, and time-lapse embryo recording to assess oocyte quality and embryo development using artificial intelligence.
1 visit (in-person)
Long-term Monitoring
Duration - Up to several months until study completion
Participants are observed over time to correlate AI predictions with embryo ploidy status and pregnancy outcomes.
Visit schedule depends on routine clinical care; no additional visits required for the study
Trial Site Locations
Total: 4 locations
1
General University Hospital in Prague
Prague, Czechia, 128 08
Actively Recruiting
2
Czech Technical University in Prague
Prague, Czechia
Actively Recruiting
3
Institute of Physics AS CR
Prague, Czechia
Actively Recruiting
4
Biocev As Cr
Vestec, Czechia
Actively Recruiting
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Research Team
J
Jaromir Masata, MD
How is the study designed?
Study Type
OBSERVATIONAL
Masking
N/A
Allocation
N/A
Model
N/A
Primary Purpose
N/A
Number of Arms
0
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Published Research Related To This Trial
Understanding reproducibility of human IVF traits to predict next IVF cycle outcome.
Bin Wu, Juanzi Shi, Wanqiu Zhao...
https://pubmed.ncbi.nlm.nih.gov/25119191IVF and human evolution.
Hans Ivar Hanevik, Dag O Hessen
https://pubmed.ncbi.nlm.nih.gov/35355060Relationship between meiotic spindle location with regard to the polar body position and oocyte developmental potential after ICSI.
L Rienzi, F Ubaldi, F Martinez...
https://pubmed.ncbi.nlm.nih.gov/12773461Maternal effect factors that contribute to oocytes developmental competence: an update.
Federica Innocenti, Giulia Fiorentino, Danilo Cimadomo...
https://pubmed.ncbi.nlm.nih.gov/35165782