Assessing efficacy of day 3 embryo time-lapse algorithms retrospectively: impacts of dataset type and confounding factors

Abstract

This study investigated the efficacy of four published day 3 embryo time-lapse algorithms based on different types of datasets (known implantation data [KID] and single embryo transfer [SET]), and the confounding effect of female age and conventional embryo morphology. Four algorithms were retrospectively applied to three types of datasets generated at Fertility North between February 2013 and December 2014: (a) KID dataset (n = 270), (b) a subset of SET (n = 144, end-point = implantation), and (c) SET (n = 144, end-point = live birth), respectively. All four algorithms showed progressively reduced predictive power (expressed as area under the receiver operating characteristics curve and 95% confidence interval [CI]) after application to the three datasets (a-c): Liu (0.762 [0.701-0.824] vs. 0.724 [0.641-0.807] vs. 0.707 [0.620-0.793]), KIDScore (0.614 [0.539-0.688] vs. 0.548 [0.451-0.645] vs. 0.536 [0.434-0.637]), Meseguer (0.585 [0.508-0.663] vs. 0.56 [0.462-0.658] vs. 0.549 [0.445-0.652]), and Basile (0.582 [0.505-0.659] vs. 0.519 [0.421-0.618] vs. 0.509 [0.406-0.612]). Furthermore, using KID dataset, the association (expressed as odds ratio and 95% CI) between time-lapse algorithms and implantation outcomes lost statistical significance after adjusting for conventional embryo morphology and female age in 3 of the 4 algorithms (KIDScore 1.832 [1.118-3.004] vs. 1.063 [0.659-1.715], Meseguer 1.150 [1.021-1.295] vs. 1.122 [0.981-1.284] and Basile 1.122 [1.008-1.249] vs. 1.038 [0.919-1.172]). In conclusion, SET is a preferred dataset to KID when developing or validating time-lapse algorithms, and day 3 conventional embryo morphology and female age should be considered as confounding factors.

Time-lapse technology for embryo culture and selection

“…Future studies could refine the models by including other variables such as day of transfer or patient's age. It was for example shown by Liu et al that embryos with similar morphology but originating from women of different age show different implantation rates (70).…”

Time-Lapse Microscopy

“…By now, various algorithms are designed for quantifying and tracking cell migration [3] and Time-Lapse Microscopy http://dx.doi.org/10.5772/intechopen.81199 single cell motility [261,263]; cell proliferation [264]; cell cycle and cell lineage analysis [107]; changes in mitotic and interphase duration [141]; cell-cell contacts [52]; studying specific cells and tissues [265] and specific intracellular processes such as transcription [99] or morphogenesis [266]; colocalization of cells and intracellular markers [184]; tracking cellular organelles [258]; highlighting the certain cell type within tissues or mixed cell cultures [267]; clustered, overlapping or dying cells [268]; in toto imaging of developing organisms, tissues and organs [241] and assessing development and selection of embryos for in vitro fertilization [269,270].…”

2018 Impact factor

“…Therefore, in this issue, please find a review article by C¸ekici and Akdevelio glu (2019) on the effects of trans fatty acids on male and female infertility. There then follows nine original research articles ranging from the ongoing debate about use of time-lapse algorithms to try and predict reproductive outcomes (Faramarzi, Khalili, & Omidi, 2019;Liu, Feenan, Chapple, & Matson, 2019) to the obstetric outcomes of women with a history of recurrent pregnancy loss (Cozzolino, Rizzello, Riviello, Romanelli, & Coccia, 2019) as well as many others. I sincerely hope that you enjoy reading them.…”