Evaluation of embryonic ploidy

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Embryo aneuploidy is a leading cause of implantation failure and miscarriage during early pregnancy. Preimplantation genetic testing for aneuploidies (PGT-A) enables the assessment of embryo ploidy before transfer; however, it has several limitations. The integration of automated analysis algorithms into embryologists' workflows can significantly enhance embryo selection and mitigate human errors.

Objective: To evaluate the effectiveness of automated analysis algorithms in determining embryo ploidy across different age groups.

Materials and methods: This retrospective study was conducted from January to May 2022 at the Family Medical Center and included embryos from 51 patients who underwent in vitro fertilization (IVF) with PGT-A. The effectiveness of determining euploidy based on blastocyst images was compared with the results obtained through PGT-A. The study utilized the Embryo Ranking Intelligent Classification Algorithm (ERICA 1.0) software.

Results: A total of 117 blastocysts were obtained, of which 101 were subjected to PGT-A and automated analysis: 31 blastocysts from women under 35 years of age (mean age 30.7 years), 39 blastocysts from women aged 35–39 years (mean age 37.4 years), and 31 blastocysts from women over 40 years of age (mean age 42 years). According to the PGT-A results for 101 embryos, the euploidy rate was 51.5%. The accuracy, positive predictive value, negative predictive value, sensitivity, specificity, and area under the ROC curve were 0.74, 0.76, 0.73, 0.73, 0.76, and 0.78, respectively. The most significant results were observed in patients aged < 35 years.

Conclusion: Automated image analysis shows promise as an auxiliary tool for decision-making in embryo selection, particularly in patients over 35 years of age.

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作者简介

Alfiya Yashchuk

Bashkir State Medical University, Ministry of Health of the Russian Federation

Email: dasha.gromenko@mail.ru

Dr. Med. Sci., Professor, Head of the Department of Obstetrics and Gynaecology No. 2

俄罗斯联邦, 450008, Republic of Bashkortostan, Ufa, Lenina str., 3

Daria Gromenko

Bashkir State Medical University, Ministry of Health of the Russian Federation

编辑信件的主要联系方式.
Email: dasha.gromenko@mail.ru
ORCID iD: 0000-0001-5638-1779

PhD student at the Department of Obstetrics and Gynaecology No. 2

俄罗斯联邦, 450008, Republic of Bashkortostan, Ufa, Lenina str., 3

Svetlana Nasyrova

Bashkir State Medical University, Ministry of Health of the Russian Federation

Email: dasha.gromenko@mail.ru
ORCID iD: 0000-0002-2313-7232

PhD, Associate Professor, Department of Obstetrics and Gynaecology No. 2

俄罗斯联邦, 450008, Republic of Bashkortostan, Ufa, Lenina str., 3

Iuliia Gromenko

Medical Center "Family"

Email: dasha.gromenko@mail.ru
ORCID iD: 0000-0002-3373-0873

PhD, Chief Physician

俄罗斯联邦, 450054, Republic of Bashkortostan, Ufa, Oktyabrya Ave., 73 build. 1

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