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Application of Deep Learning to Jointly Assess Embryo Development to Improve Pregnancy Outcome of Embryo Transfer

Not yet recruiting
Conditions
Reproductive Medicine
Interventions
Diagnostic Test: Automatic picture recognition
Diagnostic Test: Manual Assessment Group
Registration Number
NCT05671601
Lead Sponsor
The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School
Brief Summary

Aim of this research is to apply the deep learning automation based on Time-lapse imaging to jointly assess embryo development,so that it can ensure the consistency of embryo evaluation and improve the accuracy of evaluation.

Detailed Description

This study is an observational prospective study after a retrospective analysis. It is a single-center study without randomization or blindness. In the early stage, 1000 patients are collected from three periods of embryo culture through Time-lapse to establish an automated joint evaluation system for the whole process of embryo development. At the later stage, the patients are divided into two groups: Time-Lapse imaging (TLI) +Artificial Intelligence(AI) assessment group and morphological assessment group. 100 patients with Day 5 single blastocyst transplantation are carried out to follow up the pregnancy outcome.

Recruitment & Eligibility

Status
NOT_YET_RECRUITING
Sex
Female
Target Recruitment
100
Inclusion Criteria
  • (1) Age < 40 years old; (2) Routine IVF cycles; (3) Period number ≤ 2; (4) The number of ova collected is 5-15; (5) BMI: 18-25 kg/m 2, follicle stimulating hormone(FSH) ≤ 12 IU/L on the third day; (6) Patients with more than 3 high-quality embryos on Day3 and performed single blastocyst transplantation on day 5. (7) Patient without endometrial factors.
Exclusion Criteria
  • (1) Preimplantation Genetic Testing(PGT) is needed due to male infertility, ovulation cycle and chromosome abnormalities; (2) there are systemic diseases of clinical significance; (3) Pictures of blastocysts are not formed or available; (4) Incomplete or unclear image collection in prokaryotic, mitotic and blastocyst phases affected AI evaluation.

Study & Design

Study Type
OBSERVATIONAL
Study Design
Not specified
Arm && Interventions
GroupInterventionDescription
TLI+AI Assessment GroupAutomatic picture recognition-
Morphological Assessment GroupManual Assessment Group-
Primary Outcome Measures
NameTimeMethod
implantation rate2022-2023

the probability of successful implantation of the embryo into the uterus

Secondary Outcome Measures
NameTimeMethod
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