Morphokinetic trajectory analysis for conservative embryo deselection in two-embryo transfer cycle: A pilot time-lapse imaging study
DOI:
https://doi.org/10.18203/2320-1770.ijrcog20263447Keywords:
Compaction, IVF, ICSI, Embryo, Morphokinetics, Time-lapse imagingAbstract
Background: Time-lapse imaging enhances conventional morphological assessment by providing continuous developmental monitoring and novel morphokinetic parameters; however, its potential application as a conservative embryo deselection strategy remains inadequately explored. Therefore, this pilot study aimed to evaluate the feasibility of time-lapse morphokinetic analysis for identifying embryos with the lowest developmental viability in the in vitro fertilization (IVF)/intracytoplasmic sperm injection (ICSI) cycle.
Methods: A retrospective, observational, single-center, case-control, pilot study was conducted over a 3-month period at a tertiary care center in India. Morphokinetic parameters were compared between embryos associated with successful twin live births and failed pregnancies using generalized estimating equation models with a Gaussian distribution. A reference morphokinetic trajectory was derived from successful embryos using empirical 5th and 95th percentile limits for each developmental parameter.
Results: Twenty-nine IVF/ICSI cycles contributed 58 embryos, including 32 embryos from 16 cycles resulting in successful twin live birth and 26 embryos from 13 cycles resulting in pregnancy failure. Women in the successful outcome group were younger and had higher anti-Mullerian hormone concentrations than those with failed pregnancies. Embryos from successful cycles exhibited significantly greater morphokinetic progression and a more consistent developmental trajectory than embryos from failed cycles. About 81.3% of embryos from successful cycles remained within the reference developmental window, compared with only 34.6%of embryos from failed cycles.
Conclusions: The study suggests that time-lapse morphokinetic trajectory analysis may provide a feasible framework for a conservative embryo deselection by identifying embryos with markedly deviant developmental kinetics. These findings are hypothesis-generating and require validation in larger, independent cohorts before clinical implementation.
References
Mina A, Younesi M, Doohandeh T, Darzi S, Ardehjani NA, Sheibani S, et al. Predicting pregnancy outcomes in IVF cycles: a systematic review and diagnostic meta- analysis of artificial intelligence in embryo assessment. Contracept Reprod Med. 2025;28;10:59.
Garbhini PG, Suardika A, Anantasika A, Adnyana IBP, Darmayasa IM, Tondohusodo N, et al. Day-3 vs. Day-5 fresh embryo transfer. JBRA Assist Reprod. 2023;27(2):163–8.
Sciorio R, Tramontano L, Gullo G. Use of time-lapse technology and artificial intelligence in the embryology laboratory: an updated review. JBRA Assist Reprod. 2025;29(2):338–50.
Nuñez-Calonge R, Santamaria N, Rubio T, Manuel Moreno J. Making and Selecting the Best Embryo in In vitro Fertilization. Arch Med Res. 2024;55(8):103068.
Coticchio G, Mignini Renzini M, Novara PV, Lain M, De Ponti E, Turchi D, et al. Focused time-lapse analysis reveals novel aspects of human fertilization and suggests new parameters of embryo viability. Hum Reprod. 2018;1;33(1):23–31.
Giménez C, Conversa L, Murria L, Meseguer M. Time-lapse imaging: Morphokinetic analysis of in vitro fertilization outcomes. Fertil Steril. 2023;120(2):218–27.
Polyakov A, Rozen G, Gyngell C, Savulescu J. Novel embryo selection strategies-finding the right balance. Front Reprod Health. 2023;5:1287621.
Zhang XD, Zhang Q, Han W, Liu WW, Shen XL, Yao GD, et al. Comparison of embryo implantation potential between time-lapse incubators and standard incubators: a randomized controlled study. Reprod Biomed Online. 2022;45(5):858–66.
Meseguer M, Herrero J, Tejera A, Hilligsøe KM, Ramsing NB, Remohí J. The use of morphokinetics as a predictor of embryo implantation. Hum Reprod. 2011;26(10):2658–71.
Lundin K, Park H. Time-lapse technology for embryo culture and selection. Ups J Med Sci. 2020;125(2):77–84.
Basile N, Vime P, Florensa M, Aparicio Ruiz B, García Velasco JA, Remohí J, et al. The use of morphokinetics as a predictor of implantation: a multicentric study to define and validate an algorithm for embryo selection. Hum Reprod. 2015;30(2):276–83.
Kovacs P. Embryo selection: the role of time-lapse monitoring. Reprod Biol Endocrinol RBE. 2014;12:124.
Liu Y, Chapple V, Feenan K, Roberts P, Matson P. Time-lapse deselection model for human day 3 in vitro fertilization embryos: the combination of qualitative and quantitative measures of embryo growth. Fertil Steril. 2016;105(3):656-62.
Lawton MT, Kim H, McCulloch CE, Mikhak B, Young WL. A supplementary grading scale for selecting patients with brain arteriovenous malformations for surgery. Neurosurgery. 2010;66(4):702.
Maghiar L, Naghi P, Zaha IA, Sandor M, Bodog A, Sachelarie L, et al. Correlation between human embryo morphokinetics observed through time-lapse incubator and life birth Rate. J Pers Med. 2024;14(10):76.
Márquez-Hinojosa S, Noriega-Hoces L, Guzmán L. Time-Lapse Embryo culture: A better understanding of embryo development and clinical application. JBRA Assist Reprod. 2022;26(3):432–43.
Aslan Öztürk S, Cincik M, Donmez Cakil Y, Sayan S, Selam B. Early compaction might be a parameter to determine good quality embryos and day of embryo transfer in patients undergoing intracytoplasmic sperm injection. Cureus. 2020;14(3):23593.
Ezoe K, Takahashi T, Miki T, Kato K. Developmental perturbation in human embryos: Clinical and biological significance learned from time‐lapse images. Reprod Med Biol. 2024;9;23(1):12593.
de Martin H, Sá EG, Lima AM, Queiroz EC, Alam GS dos S, de Freitas TAF, et al. Introducing the Blastocyst Fragmentation Indicator (BFI): A Novel Time-Lapse Metric for Enhanced Aneuploidy Risk Stratification in Non-Invasive Embryo Assessment. JBRA Assist Reprod. 2026;30(1):132–41.
Davis SE, Matheny ME, Balu S, Sendak MP. A framework for understanding label leakage in machine learning for health care. J Am Med Inform Assoc JAMIA. 2023;31(1):274–80.
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