Literature DB >> 33189576

Assessment of embryo implantation potential with a cloud-based automatic software.

Lucía Alegre1, Raquel Del Gallego2, Lorena Bori2, Kevin Loewke3, Mahnaz Maddah3, Belén Aparicio-Ruiz2, Ana Paula Palma-Govea4, Julián Marcos5, Marcos Meseguer2.   

Abstract

RESEARCH QUESTION: Is embryo selection by Dana (automatic software for embryo evaluation) associated with a higher implantation rate in IVF treatments?
DESIGN: A three-phase study for Dana system's validation: creation of a data-cloud of known implantation data (KID) embryos from 1676 transferred embryos; embryo evaluation by Dana considering manual annotations and embryo development videos (389 transferred embryos); and validation of Dana automatic selection, without embryologist's intervention (147 transferred embryos);
RESULTS: The implantation rate of the 1021 KID embryos from phase 1 served to set four grades of embryos referring to implantation rate: A = 34%, B = 25%, C = 24%, and D = 19%. Phase 2: a classification ranking according to the unit average distance (UAD) and implantation potential was established: top (UAD ≤0.50), high (UAD = 0.51-0.66), medium (UAD = 0.67-1.03) and low (UAD >1.03). Pregnancy rates were 59%, 46%, 36% and 28%, respectively (P < 0.001). Phase 3: embryos were automatically categorized according to Dana's classification ranking. Most implanted embryos were found in groups top, high and medium (UAD ≤1.03), whereas the implantation rate in group low (UAD >1.03) was significantly lower: 46% versus 25%, respectively (P = 0.037). The twin gestation rate was higher when number of top embryos (UAD ≤0.5) transferred were two (52%) versus one (25%) (P < 0.001).
CONCLUSIONS: Embryo selection based on Dana ranking increases the success of IVF treatments at least in oocyte donation programmes. The multicentre nature of the study supports its applicability at different clinics, standardizing the embryo development's interpretation. Dana's innovation is that the system increases its accuracy as the database grows.
Copyright © 2020 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Data cloud; Embryo selection software; Implantation potential; Machine learning; Time-lapse technology

Year:  2020        PMID: 33189576     DOI: 10.1016/j.rbmo.2020.09.032

Source DB:  PubMed          Journal:  Reprod Biomed Online        ISSN: 1472-6483            Impact factor:   3.828


  1 in total

1.  Human menstrual blood-derived mesenchymal stem cells regulation of the EGF/Ras p21 pathway as a potential therapeutic target for thin endometrium.

Authors:  Mei Zhao; Fengli Chi; Tingyu Zhang; Xiaoming Teng; Kunming Li
Journal:  Ann Transl Med       Date:  2021-09
  1 in total

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