Improving embryo selection using a computer-automated time-lapse image analysis test plus day 3 morphology: results from a prospective multicenter trial

Abstract

Objective: To assess the first computer-automated platform for time-lapse image analysis and blastocyst prediction and to determine how the screening information may assist embryologists in day 3 (D3) embryo selection.

Design: Prospective, multicenter, cohort study.

Setting: Five IVF clinics in the United States.

Patient(s): One hundred sixty women ≥ 18 years of age undergoing fresh IVF treatment with basal antral follicle count ≥ 8, basal FSH <10 IU/mL, and ≥ 8 normally fertilized oocytes.

Intervention(s): A noninvasive test combining time-lapse image analysis with the cell-tracking software, Eeva (Early Embryo Viability Assessment), was used to measure early embryo development and generate usable blastocyst predictions by D3.

Main outcome measure(s): Improvement in the ability of experienced embryologists to select which embryos are likely to develop to usable blastocysts using D3 morphology alone, compared with morphology plus Eeva.

Result(s): Experienced embryologists using Eeva in combination with D3 morphology significantly improved their ability to identify embryos that would reach the usable blastocyst stage (specificity for each of three embryologists using morphology vs. morphology plus Eeva: 59.7% vs. 86.3%, 41.9% vs. 84.0%, 79.5% vs. 86.6%). Adjunctive use of morphology plus Eeva improved embryo selection by enabling embryologists to better discriminate which embryos would be unlikely to develop to blastocyst and was particularly beneficial for improving selection among good-morphology embryos. Adjunctive use of morphology plus Eeva also reduced interindividual variability in embryo selection.

Conclusion(s): Previous studies have shown improved implantation rates for blastocyst transfer compared with cleavage-stage transfer. Addition of Eeva to the current embryo grading process may improve the success rates of cleavage-stage ETs.

Keywords: Embryo selection; cell division; image analysis; noninvasive assessment; time-lapse imaging.