Literature DB >> 29398421

Can time-lapse parameters predict embryo ploidy? A systematic review.

Arnaud Reignier1, Jenna Lammers2, Paul Barriere1, Thomas Freour3.   

Abstract

Embryo morphology assessment performs relatively poorly in predicting implantation. Embryo aneuploidy screening (PGS) has recently improved, but its clinical value is still debated, and the development of a cheap non-invasive method for the assessment of embryo ploidy status is a highly desirable goal. The growing implementation of time-lapse devices led some teams to test the effectiveness of morphokinetic parameters as predictors of embryo ploidy, with conflicting results. The aim of this study was to conduct a comprehensive review of the literature on the predictive value of morphokinetic parameters for embryo ploidy status. A systematic search on PubMed was conducted using the following key words: time-lapse, morphokinetic, aneuploidy, IVF, preimplantation genetic screening, PGS, chromosomal status. A total of 13 studies were included in the analysis. They were heterogeneous in design, patients, day of embryo biopsy, statistical approach and outcome measures. No single or combined morphokinetic parameter was consistently identified as predictive of embryo ploidy status. In conclusion, the available studies are too heterogeneous for firm conclusions to be drawn on the predictive value of time-lapse analysis for embryo aneuploidy screening. Hence, morphokinetic parameters should not be used yet as a surrogate for PGS to determine embryo ploidy in vitro.
Copyright © 2018 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Aneuploidy; Morphokinetic; Preimplantation genetic screening; Time-lapse

Mesh:

Year:  2018        PMID: 29398421     DOI: 10.1016/j.rbmo.2018.01.001

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


  17 in total

Review 1.  Are computational applications the "crystal ball" in the IVF laboratory? The evolution from mathematics to artificial intelligence.

Authors:  Mara Simopoulou; Konstantinos Sfakianoudis; Evangelos Maziotis; Nikolaos Antoniou; Anna Rapani; George Anifandis; Panagiotis Bakas; Stamatis Bolaris; Agni Pantou; Konstantinos Pantos; Michael Koutsilieris
Journal:  J Assist Reprod Genet       Date:  2018-07-27       Impact factor: 3.412

2.  Euploid embryos selected by an automated time-lapse system have superior SET outcomes than selected solely by conventional morphology assessment.

Authors:  E Rocafort; M Enciso; A Leza; J Sarasa; J Aizpurua
Journal:  J Assist Reprod Genet       Date:  2018-07-20       Impact factor: 3.412

3.  Validation of Non-Invasive Preimplantation Genetic Screening Using a Routine IVF Laboratory Workflow.

Authors:  Ni-Chin Tsai; Yun-Chiao Chang; Yi-Ru Su; Yi-Chi Lin; Pei-Ling Weng; Yin-Hua Cheng; Yi-Ling Li; Kuo-Chung Lan
Journal:  Biomedicines       Date:  2022-06-11

Review 4.  Chromosomal Analysis of Pre-implantation Embryos: Its Place in Current IVF Practice.

Authors:  Sadhana K Desai; Vijay S Mangoli
Journal:  J Obstet Gynaecol India       Date:  2020-11-22

5.  Day 5 vs day 6 single euploid blastocyst frozen embryo transfers: which variables do have an impact on the clinical pregnancy rates?

Authors:  Andrea Abdala; Ibrahim Elkhatib; Aşina Bayram; Ana Arnanz; Ahmed El-Damen; Laura Melado; Barbara Lawrenz; Human M Fatemi; Neelke De Munck
Journal:  J Assist Reprod Genet       Date:  2022-01-22       Impact factor: 3.412

6.  End-to-end deep learning for recognition of ploidy status using time-lapse videos.

Authors:  Chun-I Lee; Yan-Ru Su; Chien-Hong Chen; T Arthur Chang; Esther En-Shu Kuo; Wei-Lin Zheng; Wen-Ting Hsieh; Chun-Chia Huang; Maw-Sheng Lee; Mark Liu
Journal:  J Assist Reprod Genet       Date:  2021-05-22       Impact factor: 3.357

Review 7.  Risks in Surrogacy Considering the Embryo: From the Preimplantation to the Gestational and Neonatal Period.

Authors:  M Simopoulou; K Sfakianoudis; P Tsioulou; A Rapani; G Anifandis; A Pantou; S Bolaris; P Bakas; E Deligeoroglou; K Pantos; M Koutsilieris
Journal:  Biomed Res Int       Date:  2018-07-17       Impact factor: 3.411

8.  Good practice recommendations for the use of time-lapse technology.

Authors:  Susanna Apter; Thomas Ebner; Thomas Freour; Yves Guns; Borut Kovacic; Nathalie Le Clef; Monica Marques; Marcos Meseguer; Debbie Montjean; Ioannis Sfontouris; Roger Sturmey; Giovanni Coticchio
Journal:  Hum Reprod Open       Date:  2020-03-19

9.  Time-lapse imaging derived morphokinetic variables reveal association with implantation and live birth following in vitro fertilization: A retrospective study using data from transferred human embryos.

Authors:  Shabana Sayed; Marte Myhre Reigstad; Bjørn Molt Petersen; Arne Schwennicke; Jon Wegner Hausken; Ritsa Storeng
Journal:  PLoS One       Date:  2020-11-19       Impact factor: 3.240

Review 10.  Time-lapse technology for embryo culture and selection.

Authors:  Kersti Lundin; Hannah Park
Journal:  Ups J Med Sci       Date:  2020-02-25       Impact factor: 2.384

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