Literature DB >> 30314885

Time-lapse imaging algorithms rank human preimplantation embryos according to the probability of live birth.

Simon Fishel1, Alison Campbell2, Sue Montgomery3, Rachel Smith4, Lynne Nice5, Samantha Duffy3, Lucy Jenner6, Kathryn Berrisford6, Louise Kellam6, Rob Smith7, Fiona Foad8, Ashley Beccles1.   

Abstract

RESEARCH QUESTION: Can blastocysts leading to live births be ranked according to morphokinetic-based algorithms?
DESIGN: Retrospective analysis of 781 single blastocyst embryo transfers, including all patient clinical factors that might be potential confounders for the primary outcome measure of live birth, was weighed using separate multi-variable logistic regression models.
RESULTS: There was strong evidence of effect of embryo rank on odds of live birth. Embryos were classified A, B, C or D according to calculated variables; time to start (tSB) and duration (dB{tB - tSB}) of blastulation. Embryos of rank D were less likely to result in live birth than embryos of rank A (odds ratio [OR] 0.3046; 95% confidence interval [CI] 0.129, 0.660; P < 0.005). Embryos ranked B were less likely to result in live birth than those ranked A (OR 0.7114; 95% Cl 0.505, 1.001; P < 0.01), and embryos ranked C were less likely to result in live birth than those ranked A (OR 0.6501, 95% Cl 0.373, 1.118; P < 0.01). Overall, the LRT (Likelihood Ratio Test) p-value for embryo rank shows that there is strong evidence that embryo rank is informative as a whole in discriminating between live birth and no live birth outcomes (p = 0.0101). The incidence of live birth was 52.5% from rank A, 39.2% from rank B, 31.4% from rank C and 13.2% from rank D.
CONCLUSIONS: Time-lapse imaging morphokinetic-based algorithms for blastocysts can provide objective hierarchical ranking of embryos for predicting live birth and may have greater discriminating power than conventional blastocyst morphology assessment.
Copyright © 2018. Published by Elsevier Ltd.

Entities:  

Keywords:  Embryo imaging; Embryo morphology; Human; IVF; Live birth; Selection algorithm; Time lapse

Mesh:

Year:  2018        PMID: 30314885     DOI: 10.1016/j.rbmo.2018.05.016

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


  10 in total

1.  Between-laboratory reproducibility of time-lapse embryo selection using qualitative and quantitative parameters: a systematic review and meta-analysis.

Authors:  Yanhe Liu; Fang Qi; Phillip Matson; Dean E Morbeck; Ben W Mol; Sai Zhao; Masoud Afnan
Journal:  J Assist Reprod Genet       Date:  2020-05-02       Impact factor: 3.412

2.  Embryo Morphokinetics and Blastocyst Development After GnRH Agonist versus hCG Triggering in Normo-ovulatory Women: a Secondary Analysis of a Multicenter Randomized Controlled Trial.

Authors:  Evaggelia Alexopoulou; Sacha Stormlund; Kristine Løssl; Lisbeth Prætorius; Negjyp Sopa; Jeanette Wulff Bogstad; Anne Lis Mikkelsen; Julie Forman; Nina la Cour Freiesleben; Janni Vikkelsø Jeppesen; Christina Bergh; Peter Samir Heskjær Al Humaidan; Marie Louise Grøndahl; Anne Zedeler; Anja Bisgaard Pinborg
Journal:  Reprod Sci       Date:  2021-04-13       Impact factor: 3.060

3.  Deep learning as a predictive tool for fetal heart pregnancy following time-lapse incubation and blastocyst transfer.

Authors:  D Tran; S Cooke; P J Illingworth; D K Gardner
Journal:  Hum Reprod       Date:  2019-06-04       Impact factor: 6.918

4.  The Future of IVF: The New Normal in Human Reproduction.

Authors:  Vitaly A Kushnir; Gary D Smith; Eli Y Adashi
Journal:  Reprod Sci       Date:  2022-01-03       Impact factor: 3.060

5.  Faster Fertilization and Cleavage Kinetics Reflect Competence to Achieve a Live Birth: Data from Single-Embryo Transfer Cycles.

Authors:  Yongle Yang; Xiyuan Dong; Jian Bai; Lei Jin; Bo Huang
Journal:  Biomed Res Int       Date:  2022-07-15       Impact factor: 3.246

6.  Correlation between an annotation-free embryo scoring system based on deep learning and live birth/neonatal outcomes after single vitrified-warmed blastocyst transfer: a single-centre, large-cohort retrospective study.

Authors:  Satoshi Ueno; Jørgen Berntsen; Motoki Ito; Tadashi Okimura; Keiichi Kato
Journal:  J Assist Reprod Genet       Date:  2022-07-26       Impact factor: 3.357

7.  Morphology of inner cell mass: a better predictive biomarker of blastocyst viability.

Authors:  Sargunadevi Sivanantham; Mahalakshmi Saravanan; Nidhi Sharma; Jayashree Shrinivasan; Ramesh Raja
Journal:  PeerJ       Date:  2022-08-26       Impact factor: 3.061

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.  From "Every Day" Hormonal to Oxidative Stress Biomarkers in Blood and Follicular Fluid, to Embryo Quality and Pregnancy Success?

Authors:  Katarzyna Olszak-Wąsik; Anna Bednarska-Czerwińska; Anita Olejek; Andrzej Tukiendorf
Journal:  Oxid Med Cell Longev       Date:  2019-11-26       Impact factor: 6.543

10.  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

  10 in total

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