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Evidence-Based Approaches to Embryo Selection by Morphology and Kinetics

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Emerging Topics in Reproduction

Abstract

The success of IVF-based assisted reproductive technologies (ART) depends critically on viability and sustained in utero development of the in vitro-grown embryo. Selection of that embryo for transfer involves a judgment on the part of the clinical embryologist. For a good part of the past nearly 40 years, this judgment has been based primarily on embryo appearance—or morphology—assessed at discreet time points during culture. Some key morphological markers of viability have been identified through a multitude of retrospective observational studies. Although obviously useful and serving an important function, morphology is subjective and does not always reveal development potential. Two emerging and evolving technologies hold the promise to complement morphology: preimplantation genetic testing for aneuploidy (PGT-A) and time-lapse microscopy (TLM) for continuous monitoring of embryo development and precise timing of key developmental events. Scrutiny of time-lapse images has helped successful identification of events associated with blastulation, but predicting implantation and pregnancy still proves to be a challenge. It is clear that, to be efficacious, embryo selection platforms and algorithms must be able to select for embryos with low risk of aneuploidy or, alternatively, reliably predict implantation.

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References

  1. Dhont M. Evidence-based reproductive medicine: a critical appraisal. Facts Views Vis Obgyn. 2013;5(3):233–40.

    PubMed  PubMed Central  CAS  Google Scholar 

  2. Campbell M, Fitzpatrick R, Haines A, Kinmonth AL, Sandercock P, Spiegelhalter D, Tyrer P. Framework for design and evaluation of complex interventions to improve health. BMJ. 2000;321(7262):694–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Cohen J, Alikani M. Evidence-based medicine and its application in clinical preimplantation embryology. Reprod Biomed Online. 2013;27(5):547–61. https://doi.org/10.1016/j.rbmo.2013.08.003.

    Article  PubMed  Google Scholar 

  4. Armstrong S, Vail A, Mastenbroek S, Jordan V, Farquhar C. Time-lapse in the IVF-lab: how should we assess potential benefit? Hum Reprod. 2015;30(1):3–8. https://doi.org/10.1093/humrep/deu250.

    Article  PubMed  CAS  Google Scholar 

  5. Racowsky C, Kovacs P, Martins WP. A critical appraisal of time-lapse imaging for embryo selection: where are we and where do we need to go? J Assist Reprod Genet. 2015;32(7):1025–30. https://doi.org/10.1007/s10815-015-0510-6.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Racowsky C, Martins WP. Effectiveness and safety of time-lapse imaging for embryo culture and selection: it is still too early for any conclusions? Fertil Steril. 2017;108(3):450–2. https://doi.org/10.1016/j.fertnstert.2017.07.1156.

    Article  PubMed  Google Scholar 

  7. Pribenszky C, Nilselid AM, Montag M. Time-lapse culture with morphokinetic embryo selection improves pregnancy and live birth chances and reduces early pregnancy loss: a meta-analysis. Reprod Biomed Online. 2017;35(5):511–20. https://doi.org/10.1016/j.rbmo.2017.06.022.

    Article  PubMed  Google Scholar 

  8. Alikani M, Fauser BCJM, Anderson R, García-Velasco JA, Johnson M. Response from the Editors: time-lapse systems for ART—meta-analyses and the issue of bias. Reprod BioMed Online. 2018;36(3):293. In press, corrected proof. Accessed 26 Dec 2017.

    Article  PubMed  Google Scholar 

  9. Insua MF, Cobo AC, Larreategui Z, Ferrando M, Serra V, Meseguer M. Obstetric and perinatal outcomes of pregnancies conceived with embryos cultured in a time-lapse monitoring system. Fertil Steril. 2017;108(3):498–504. https://doi.org/10.1016/j.fertnstert.2017.06.031.

    Article  PubMed  Google Scholar 

  10. Dolinko AV, Farland LV, Kaser DJ, Missmer SA, Racowsky C. National survey on use of time-lapse imaging systems in IVF laboratories. J Assist Reprod Genet. 2017;34(9):1167–72. https://doi.org/10.1007/s10815-017-0964-9.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Alpha Scientists in Reproductive Medicine, Embryology ESIGo. The Istanbul consensus workshop on embryo assessment: proceedings of an expert meeting. Hum Reprod. 2011;26(6):1270–83. https://doi.org/10.1093/humrep/der037.

    Article  Google Scholar 

  12. Racowsky C, Vernon M, Mayer J, Ball GD, Behr B, Pomeroy KO, Wininger D, Gibbons W, Conaghan J, Stern JE. Standardization of grading embryo morphology. Fertil Steril. 2010;94(3):1152–3. https://doi.org/10.1016/j.fertnstert.2010.05.042.

    Article  PubMed  Google Scholar 

  13. Ebner T, Maurer M, Shebl O, Moser M, Mayer RB, Duba HC, Tews G. Planar embryos have poor prognosis in terms of blastocyst formation and implantation. Reprod Biomed Online. 2012;25(3):267–72. https://doi.org/10.1016/j.rbmo.2012.05.007.

    Article  PubMed  CAS  Google Scholar 

  14. Wright G, Wiker S, Elsner C, Kort H, Massey J, Mitchell D, Toledo A, Cohen J. Observations on the morphology of pronuclei and nucleoli in human zygotes and implications for cryopreservation. Hum Reprod. 1990;5(1):109–15.

    Article  CAS  PubMed  Google Scholar 

  15. Scott LA, Smith S. The successful use of pronuclear embryo transfers the day following oocyte retrieval. Hum Reprod. 1998;13(4):1003–13.

    Article  CAS  PubMed  Google Scholar 

  16. Alikani M, Calderon G, Tomkin G, Garrisi J, Kokot M, Cohen J. Cleavage anomalies in early human embryos and survival after prolonged culture in-vitro. Hum Reprod. 2000;15(12):2634–43.

    Article  CAS  PubMed  Google Scholar 

  17. Lewis EI, Farhadifar R, Farland LV, Needleman DJ, Missmer SA, Racowsky C. Use of imaging software for assessment of the associations among zona pellucida thickness variation, assisted hatching, and implantation of day 3 embryos. J Assist Reprod Genet. 2017;34(10):1261–9. https://doi.org/10.1007/s10815-017-0978-3.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Huang D, Yin C, Leung M, Ahn H-J, Kosasa T, Kessel B, Huang TTF. Blastocyst expansion morphokinetics and aneuploidy in human preimplantation embryos (Abstract). Geneva: ESHRE; 2017.

    Google Scholar 

  19. Alikani M. Morphological expressions of human egg and embryo quality. In: Coward K, Wells D, editors. Testbook of clinical embryology. Cambridge: Cambridge University Press; 2013. p. 313–26.

    Google Scholar 

  20. Bradley CK, Traversa MV, Gee AJ, Hobson N, McArthur SJ. Clinical use of monopronucleated zygotes following blastocyst culture and preimplantation genetic screening, including verification of biparental chromosome inheritance. Reprod Biomed Online. 2017;34:567–74.

    Article  PubMed  Google Scholar 

  21. Yao G, Xu J, Xin Z, Niu W, Shi S, Jin H, Song W, Wang E, Yang Q, Chen L, Sun Y. Developmental potential of clinically discarded human embryos and associated chromosomal analysis. Sci Rep. 2016;6:23995. https://doi.org/10.1038/srep23995.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. Bouillon C, Celton N, Kassem S, Frapsauce C, Guerif F. Obstetric and perinatal outcomes of singletons after single blastocyst transfer: is there any difference according to blastocyst morphology? Reprod Biomed Online. 2017;35(2):197–207. https://doi.org/10.1016/j.rbmo.2017.04.009.

    Article  PubMed  Google Scholar 

  23. Wirleitner B, Schuff M, Stecher A, Murtinger M, Vanderzwalmen P. Pregnancy and birth outcomes following fresh or vitrified embryo transfer according to blastocyst morphology and expansion stage, and culturing strategy for delayed development. Hum Reprod. 2016;31(8):1685–95. https://doi.org/10.1093/humrep/dew127.

    Article  CAS  PubMed  Google Scholar 

  24. Paternot G, Devroe J, Debrock S, D'Hooghe TM, Spiessens C. Intra- and inter-observer analysis in the morphological assessment of early-stage embryos. Reprod Biol Endocrinol. 2009;7:105. https://doi.org/10.1186/1477-7827-7-105.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Filho ES, Noble JA, Wells D. A review on automatic analysis of human embryo microscope images. Open Biomed Eng J. 2010;4:170–7. https://doi.org/10.2174/1874120701004010170.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Paternot G, Debrock S, De Neubourg D, D'Hooghe TM, Spiessens C. Semi-automated morphometric analysis of human embryos can reveal correlations between total embryo volume and clinical pregnancy. Hum Reprod. 2013;28(3):627–33. https://doi.org/10.1093/humrep/des427.

    Article  PubMed  CAS  Google Scholar 

  27. Lagalla C, Barberi M, Orlando G, Sciajno R, Bonu MA, Borini A. A quantitative approach to blastocyst quality evaluation: morphometric analysis and related IVF outcomes. J Assist Reprod Genet. 2015;32(5):705–12. https://doi.org/10.1007/s10815-015-0469-3.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Richter KS, Harris DC, Daneshmand ST, Shapiro BS. Quantitative grading of a human blastocyst: optimal inner cell mass size and shape. Fertil Steril. 2001;76:1157–67.

    Article  CAS  PubMed  Google Scholar 

  29. Ziebe S. Morphometric analysis of human embryos to predict developmental competence. Reprod Fertil Dev. 2013;26(1):55–64. https://doi.org/10.1071/RD13296.

    Article  PubMed  Google Scholar 

  30. Gleicher N, Orvieto R. Is the hypothesis of preimplantation genetic screening (PGS) still supportable? A review. J Ovarian Res. 2017;10(1):21. https://doi.org/10.1186/s13048-017-0318-3.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Forman EJ, Hong KH, Ferry KM, Tao X, Taylor D, Levy B, Treff NR, Scott RT Jr. In vitro fertilization with single euploid blastocyst transfer: a randomized controlled trial. Fertil Steril. 2013;100(1):100–7.e101. https://doi.org/10.1016/j.fertnstert.2013.02.056.

    Article  PubMed  Google Scholar 

  32. Forman EJ, Hong KH, Franasiak JM, Scott RT Jr. Obstetrical and neonatal outcomes from the BEST Trial: single embryo transfer with aneuploidy screening improves outcomes after in vitro fertilization without compromising delivery rates. Am J Obstet Gynecol. 2014;210(2):157.e151–156. https://doi.org/10.1016/j.ajog.2013.10.016.

    Article  Google Scholar 

  33. Alfarawati S, Fragouli E, Colls P, Stevens J, Gutierrez-Mateo C, Schoolcraft WB, Katz-Jaffe MG, Wells D. The relationship between blastocyst morphology, chromosomal abnormality, and embryo gender. Fertil Steril. 2011;95(2):520–4. https://doi.org/10.1016/j.fertnstert.2010.04.003.

    Article  PubMed  Google Scholar 

  34. Minasi MG, Colasante A, Riccio T, Ruberti A, Casciani V, Scarselli F, Spinella F, Fiorentino F, Varricchio MT, Greco E. Correlation between aneuploidy, standard morphology evaluation and morphokinetic development in 1730 biopsied blastocysts: a consecutive case series study. Hum Reprod. 2016;31(10):2245–54. https://doi.org/10.1093/humrep/dew183.

    Article  PubMed  Google Scholar 

  35. Capalbo A, Rienzi L, Cimadomo D, Maggiulli R, Elliott T, Wright G, Nagy ZP, Ubaldi FM. Correlation between standard blastocyst morphology, euploidy and implantation: an observational study in two centers involving 956 screened blastocysts. Hum Reprod. 2014;29(6):1173–81. https://doi.org/10.1093/humrep/deu033.

    Article  PubMed  Google Scholar 

  36. Irani M, Reichman D, Robles A, Melnick A, Davis O, Zaninovic N, Xu K, Rosenwaks Z. Morphologic grading of euploid blastocysts influences implantation and ongoing pregnancy rates. Fertil Steril. 2017;107(3):664–70. https://doi.org/10.1016/j.fertnstert.2016.11.012.

    Article  PubMed  Google Scholar 

  37. Fragouli E, Alfarawati S, Spath K, Wells D. Morphological and cytogenetic assessment of cleavage and blastocyst stage embryos. Mol Hum Reprod. 2014;20(2):117–26. https://doi.org/10.1093/molehr/gat073.

    Article  PubMed  CAS  Google Scholar 

  38. Ahlstrom A, Westin C, Reismer E, Wikland M, Hardarson T. Trophectoderm morphology: an important parameter for predicting live birth after single blastocyst transfer. Hum Reprod. 2011;26(12):3289–96. https://doi.org/10.1093/humrep/der325.

    Article  PubMed  CAS  Google Scholar 

  39. Honnma H, Baba T, Sasaki M, Hashiba Y, Ohno H, Fukunaga T, et al. Trophectoderm morphology significantly affects the rates of ongoing pregnancy and miscarriage in frozen-thawed single-blastocyst transfer cycle in vitro fertilization. Fertil Steril. 2012;98(2):361–7. https://doi.org/10.1016/j.fertnstert.2012.05.014.

    Article  PubMed  Google Scholar 

  40. Ebner T, Tritscher K, Mayer RB, Oppelt P, Duba HC, Maurer M, Schappacher-Tilp G, Petek E, Shebl O. Quantitative and qualitative trophectoderm grading allows for prediction of live birth and gender. J Assist Reprod Genet. 2016;33(1):49–57. https://doi.org/10.1007/s10815-015-0609-9.

    Article  PubMed  Google Scholar 

  41. Gardner DK, Schoolcraft WB. A randomized trial of blastocyst culture and transfer in in-vitro fertilization: reply. Hum Reprod. 1999;14(6):1663A–1663.

    Article  CAS  PubMed  Google Scholar 

  42. Lemmen JG, Agerholm I, Ziebe S. Kinetic markers of human embryo quality using time-lapse recordings of IVF/ICSI-fertilized oocytes. Reprod Biomed Online. 2008;17(3):385–91.

    Article  CAS  PubMed  Google Scholar 

  43. Pribenszky C, Losonczi E, Molnar M, Lang Z, Matyas S, Rajczy K, Molnar K, Kovacs P, Nagy P, Conceicao J, Vajta G. Prediction of in-vitro developmental competence of early cleavage-stage mouse embryos with compact time-lapse equipment. Reprod Biomed Online. 2010;20(3):371–9. https://doi.org/10.1016/j.rbmo.2009.12.007.

    Article  PubMed  Google Scholar 

  44. Wong CC, Loewke KE, Bossert NL, Behr B, De Jonge CJ, Baer TM, Reijo Pera RA. Non-invasive imaging of human embryos before embryonic genome activation predicts development to the blastocyst stage. Nat Biotechnol. 2010;28(10):1115–21. https://doi.org/10.1038/nbt.1686.

    Article  PubMed  CAS  Google Scholar 

  45. Conaghan J, Chen AA, Willman SP, Ivani K, Chenette PE, Boostanfar R, Baker VL, Adamson GD, Abusief ME, Gvakharia M, Loewke KE, Shen S. Improving embryo selection using a computer-automated time-lapse image analysis test plus day 3 morphology: results from a prospective multicenter trial. Fertil Steril. 2013;100(2):412–419.e415. https://doi.org/10.1016/j.fertnstert.2013.04.021.

    Article  PubMed  Google Scholar 

  46. VerMilyea MD, Tan L, Anthony JT, Conaghan J, Ivani K, Gvakharia M, Boostanfar R, Baker VL, Suraj V, Chen AA, Mainigi M, Coutifaris C, Shen S. Computer-automated time-lapse analysis results correlate with embryo implantation and clinical pregnancy: a blinded, multi-centre study. Reprod Biomed Online. 2014;29(6):729–36. https://doi.org/10.1016/j.rbmo.2014.09.005.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Diamond MP, Suraj V, Behnke EJ, Yang X, Angle MJ, Lambe-Steinmiller JC, Watterson R, Athayde Wirka K, Chen AA, Shen S. Using the Eeva test adjunctively to traditional day 3 morphology is informative for consistent embryo assessment within a panel of embryologists with diverse experience. J Assist Reprod Genet. 2015;32(1):61–8. https://doi.org/10.1007/s10815-014-0366-1.

    Article  PubMed  Google Scholar 

  48. Adamson GD, Abusief ME, Palao L, Witmer J, Palao LM, Gvakharia M. Improved implantation rates of day 3 embryo transfers with the use of an automated time-lapse-enabled test to aid in embryo selection. Fertil Steril. 2016;105(2):369–375.e366. https://doi.org/10.1016/j.fertnstert.2015.10.030.

    Article  PubMed  Google Scholar 

  49. Aparicio-Ruiz B, Basile N, Perez Albala S, Bronet F, Remohi J, Meseguer M. Automatic time-lapse instrument is superior to single-point morphology observation for selecting viable embryos: retrospective study in oocyte donation. Fertil Steril. 2016;106(6):1379–1385.e1310. https://doi.org/10.1016/j.fertnstert.2016.07.1117.

    Article  PubMed  Google Scholar 

  50. Kaser DJ, Farland LV, Missmer SA, Racowsky C. Prospective study of automated versus manual annotation of early time-lapse markers in the human preimplantation embryo. Hum Reprod. 2017;32(8):1604–11. https://doi.org/10.1093/humrep/dex229.

    Article  PubMed  Google Scholar 

  51. Kaser DJ, Bormann CL, Missmer SA, Farland LV, Ginsburg ES, Racowsky C. A pilot randomized controlled trial of day 3 single embryo transfer with adjunctive time-lapse selection versus day 5 single embryo transfer with or without adjunctive time-lapse selection. Hum Reprod. 2017;32(8):1598–603. https://doi.org/10.1093/humrep/dex231.

    Article  PubMed  Google Scholar 

  52. Cruz M, Gadea B, Garrido N, Pedersen KS, Martinez M, Perez-Cano I, Munoz M, Meseguer M. Embryo quality, blastocyst and ongoing pregnancy rates in oocyte donation patients whose embryos were monitored by time-lapse imaging. J Assist Reprod Genet. 2011;28(7):569–73. https://doi.org/10.1007/s10815-011-9549-1.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Meseguer M, Rubio I, Cruz M, Basile N, Marcos J, Requena A. Embryo incubation and selection in a time-lapse monitoring system improves pregnancy outcome compared with a standard incubator: a retrospective cohort study. Fertil Steril. 2012;98(6):1481–1489.e1410. https://doi.org/10.1016/j.fertnstert.2012.08.016.

    Article  PubMed  Google Scholar 

  54. Chavez SL, Loewke KE, Han J, Moussavi F, Colls P, Munne S, Behr B, Reijo Pera RA. Dynamic blastomere behaviour reflects human embryo ploidy by the four-cell stage. Nat Commun. 2012;3:1251. https://doi.org/10.1038/ncomms2249.

    Article  PubMed  CAS  Google Scholar 

  55. Kirkegaard K, Kesmodel US, Hindkjaer JJ, Ingerslev HJ. Time-lapse parameters as predictors of blastocyst development and pregnancy outcome in embryos from good prognosis patients: a prospective cohort study. Hum Reprod. 2013;28(10):2643–51. https://doi.org/10.1093/humrep/det300.

    Article  PubMed  CAS  Google Scholar 

  56. Chamayou S, Patrizio P, Storaci G, Tomaselli V, Alecci C, Ragolia C, Crescenzo C, Guglielmino A. The use of morphokinetic parameters to select all embryos with full capacity to implant. J Assist Reprod Genet. 2013;30(5):703–10. https://doi.org/10.1007/s10815-013-9992-2.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Desai N, Ploskonka S, Goodman LR, Austin C, Goldberg J, Falcone T. Analysis of embryo morphokinetics, multinucleation and cleavage anomalies using continuous time-lapse monitoring in blastocyst transfer cycles. Reprod Biol Endocrinol. 2014;12:54. https://doi.org/10.1186/1477-7827-12-54.

    Article  PubMed  PubMed Central  Google Scholar 

  58. Motato Y, de los Santos MJ, Escriba MJ, Ruiz BA, Remohi J, Meseguer M. Morphokinetic analysis and embryonic prediction for blastocyst formation through an integrated time-lapse system. Fertil Steril. 2016;105(2):376–384.e379. https://doi.org/10.1016/j.fertnstert.2015.11.001.

    Article  PubMed  Google Scholar 

  59. Kaser DJ, Racowsky C. Reply: clinical outcomes following selection of human preimplantation embryos with time-lapse monitoring: a systematic review. Hum Reprod Update. 2014;20(5):802–3. https://doi.org/10.1093/humupd/dmu045.

    Article  PubMed  Google Scholar 

  60. Montag M. Morphokinetics and embryo aneuploidy: has time come or not yet? Reprod Biomed Online. 2013;26(6):528–30. https://doi.org/10.1016/j.rbmo.2013.03.011.

    Article  PubMed  Google Scholar 

  61. Montag M, Toth B, Strowitzki T. New approaches to embryo selection. Reprod Biomed Online. 2013;27(5):539–46. https://doi.org/10.1016/j.rbmo.2013.05.013.

    Article  PubMed  Google Scholar 

  62. Gardner DK, Meseguer M, Rubio C, Treff NR. Diagnosis of human preimplantation embryo viability. Hum Reprod Update. 2015;21(6):727–47. https://doi.org/10.1093/humupd/dmu064.

    Article  PubMed  CAS  Google Scholar 

  63. Petersen BM, Boel M, Montag M, Gardner DK. Development of a generally applicable morphokinetic algorithm capable of predicting the implantation potential of embryos transferred on day 3. Hum Reprod. 2016;31(10):2231–44. https://doi.org/10.1093/humrep/dew188.

    Article  PubMed  PubMed Central  Google Scholar 

  64. Rubio I, Galan A, Larreategui Z, Ayerdi F, Bellver J, Herrero J, Meseguer M. Clinical validation of embryo culture and selection by morphokinetic analysis: a randomized, controlled trial of the EmbryoScope. Fertil Steril. 2014;102(5):1287–1294.e1285. https://doi.org/10.1016/j.fertnstert.2014.07.738.

    Article  PubMed  Google Scholar 

  65. Basile N, Vime P, Florensa M, Aparicio Ruiz B, Garcia Velasco JA, Remohi J, Meseguer M. 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. https://doi.org/10.1093/humrep/deu331.

    Article  PubMed  CAS  Google Scholar 

  66. 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):656–662.e651. https://doi.org/10.1016/j.fertnstert.2015.11.003.

    Article  PubMed  Google Scholar 

  67. Barrie A, Homburg R, McDowell G, Brown J, Kingsland C, Troup S. Examining the efficacy of six published time-lapse imaging embryo selection algorithms to predict implantation to demonstrate the need for the development of specific, in-house morphokinetic selection algorithms. Fertil Steril. 2017;107(3):613–21. https://doi.org/10.1016/j.fertnstert.2016.11.014.

    Article  PubMed  Google Scholar 

  68. Freour T, Le Fleuter N, Lammers J, Splingart C, Reignier A, Barriere P. External validation of a time-lapse prediction model. Fertil Steril. 2015;103(4):917–22. https://doi.org/10.1016/j.fertnstert.2014.12.111.

    Article  PubMed  Google Scholar 

  69. Lagalla C, Tarozzi N, Sciajno R, Wells D, Di Santo M, Nadalini M, Distratis V, Borini A. Embryos with morphokinetic abnormalities may develop into euploid blastocysts. Reprod Biomed Online. 2017;34(2):137–46. https://doi.org/10.1016/j.rbmo.2016.11.008.

    Article  PubMed  CAS  Google Scholar 

  70. Barrie A, Homburg R, McDowell G, Brown J, Kingsland C, Troup S. Preliminary investigation of the prevalence and implantation potential of abnormal embryonic phenotypes assessed using time-lapse imaging. Reprod Biomed Online. 2017;34(5):455–62. https://doi.org/10.1016/j.rbmo.2017.02.011.

    Article  PubMed  Google Scholar 

  71. Athayde Wirka K, Chen AA, Conaghan J, Ivani K, Gvakharia M, Behr B, Suraj V, Tan L, Shen S. Atypical embryo phenotypes identified by time-lapse microscopy: high prevalence and association with embryo development. Fertil Steril. 2014;101(6):1637–1648.e1–5. https://doi.org/10.1016/j.fertnstert.2014.02.050.

    Article  PubMed  Google Scholar 

  72. Mumusoglu S, Yarali I, Bozdag G, Ozdemir P, Polat M, Sokmensuer LK, Yarali H. Time-lapse morphokinetic assessment has low to moderate ability to predict euploidy when patient- and ovarian stimulation-related factors are taken into account with the use of clustered data analysis. Fertil Steril. 2017;107(2):413–421.e414. https://doi.org/10.1016/j.fertnstert.2016.11.005.

    Article  PubMed  Google Scholar 

  73. Swain JE. Could time-lapse embryo imaging reduce the need for biopsy and PGS? J Assist Reprod Genet. 2013;30(8):1081–90. https://doi.org/10.1007/s10815-013-0048-4.

    Article  PubMed  PubMed Central  Google Scholar 

  74. Kirkegaard K, Ahlstrom A, Ingerslev HJ, Hardarson T. Choosing the best embryo by time lapse versus standard morphology. Fertil Steril. 2015;103(2):323–32. https://doi.org/10.1016/j.fertnstert.2014.11.003.

    Article  PubMed  Google Scholar 

  75. Campbell A, Fishel S, Bowman N, Duffy S, Sedler M, Hickman CF. Modelling a risk classification of aneuploidy in human embryos using non-invasive morphokinetics. Reprod Biomed Online. 2013;26(5):477–85. https://doi.org/10.1016/j.rbmo.2013.02.006.

    Article  PubMed  Google Scholar 

  76. Campbell A, Fishel S, Bowman N, Duffy S, Sedler M, Thornton S. Retrospective analysis of outcomes after IVF using an aneuploidy risk model derived from time-lapse imaging without PGS. Reprod Biomed Online. 2013;27(2):140–6. https://doi.org/10.1016/j.rbmo.2013.04.013.

    Article  PubMed  Google Scholar 

  77. Rienzi L, Capalbo A, Stoppa M, Romano S, Maggiulli R, Albricci L, Scarica C, Farcomeni A, Vajta G, Ubaldi FM. No evidence of association between blastocyst aneuploidy and morphokinetic assessment in a selected population of poor-prognosis patients: a longitudinal cohort study. Reprod Biomed Online. 2015;30(1):57–66. https://doi.org/10.1016/j.rbmo.2014.09.012.

    Article  PubMed  CAS  Google Scholar 

  78. Kramer YG, Kofinas JD, Melzer K, Noyes N, McCaffrey C, Buldo-Licciardi J, McCulloh DH, Grifo JA. Assessing morphokinetic parameters via time lapse microscopy (TLM) to predict euploidy: are aneuploidy risk classification models universal? J Assist Reprod Genet. 2014;31(9):1231–42. https://doi.org/10.1007/s10815-014-0285-1.

    Article  PubMed  PubMed Central  Google Scholar 

  79. Orr B, Godek KM, Compton D. Aneuploidy. Curr Biol. 2015;25(13):R538–42. https://doi.org/10.1016/j.cub.2015.05.010.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  80. Santaguida S, Amon A. Short- and long-term effects of chromosome mis-segregation and aneuploidy. Nat Rev Mol Cell Biol. 2015;16(8):473–85. https://doi.org/10.1038/nrm4025.

    Article  PubMed  CAS  Google Scholar 

  81. Sheltzer JM, Torres EM, Dunham MJ, Amon A. Transcriptional consequences of aneuploidy. Proc Natl Acad Sci U S A. 2012;109(31):12644–9. https://doi.org/10.1073/pnas.1209227109.

    Article  PubMed  PubMed Central  Google Scholar 

  82. Tang Y-C, Williams BR, Siegel JJ, Amon A. The energy and proteotoxic stress-inducing compounds AICAR and 17-AAG antagonize proliferation in aneuploidy cells. Cell. 2011;144(4):499–512.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Torres EM, Williams BR, Amon A. Aneuploidy: cells losing their balance. Genetics. 2008;179(2):737–46. https://doi.org/10.1534/genetics.108.090878.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  84. Torres EM, Williams BR, Tang YC, Amon A. Thoughts on aneuploidy. Cold Spring Harb Symp Quant Biol. 2010;75:445–51. https://doi.org/10.1101/sqb.2010.75.025.

    Article  PubMed  CAS  Google Scholar 

  85. Oromendia AB, Amon A. Aneuploidy: implications for protein homeostasis and disease. Dis Model Mech. 2014;7(1):15–20. https://doi.org/10.1242/dmm.013391.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  86. Williams BR, Prabhu VR, Hunter KE, Glazier CM, Whittaker CA, Housman DE, Amon A. Aneuploidy affects proliferation and spontaneous immortalization in mammalian cells. Science. 2008;322(5902):703–9. https://doi.org/10.1126/science.1160058.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  87. Munne S, Grifo J, Cohen J, Weier HU. Chromosome abnormalities in human arrested preimplantation embryos: a multiple-probe FISH study. Am J Hum Genet. 1994;55(1):150–9.

    PubMed  PubMed Central  CAS  Google Scholar 

  88. Nogales MDC, Bronet F, Basile N, Martinez EMM, et al. Type of chromosome abnormality affects embryo morphology dynamics. Fert Steril. 2017;107:229–35.

    Article  Google Scholar 

  89. Huang D, Yin C, Leung M, Ahn H-J, Kosasa T, Kessel B, Huang TTF. Blastocyst expansion morphokinetics and aneuploidy in human preimplantation embryos (Abstract). Geneva: ESHRE; 2017.

    Google Scholar 

  90. Huang TT, Chinn K, Kosasa T, Ahn HJ, Kessel B. Morphokinetics of human blastocyst expansion in vitro. Reprod Biomed Online. 2016;33(6):659–67. https://doi.org/10.1016/j.rbmo.2016.08.020.

    Article  PubMed  CAS  Google Scholar 

  91. Niimura S. Time-lapse videomicrographic analyses of contractions in mouse blastocysts. J Reprod Dev. 2003;49(6):413–23.

    Article  PubMed  Google Scholar 

  92. Schimmel T, Cohen J, Saunders H, Alikani M. Laser-assisted zona pellucida thinning does not facilitate hatching and may disrupt the in vitro hatching process: a morphokinetic study in the mouse. Hum Reprod. 2014;29(12):2670–9. https://doi.org/10.1093/humrep/deu245.

    Article  PubMed  PubMed Central  Google Scholar 

  93. Marcos J, Perez-Albala S, Mifsud A, Molla M, Landeras J, Meseguer M. Collapse of blastocysts is strongly related to lower implantation success: a time-lapse study. Hum Reprod. 2015;30(11):2501–8. https://doi.org/10.1093/humrep/dev216.

    Article  PubMed  CAS  Google Scholar 

  94. Cohen J, Simons RF, Edwards RG, Fehilly CB, Fishel SB. Pregnancies following the frozen storage of expanding human blastocysts. J In Vitro Fert Embryo Transf. 1985;2(2):59–64.

    Article  CAS  PubMed  Google Scholar 

  95. Cohen J, Simons RS, Fehilly CB, Edwards RG. Factors affecting survival and implantation of cryopreserved human embryos. J In Vitro Fert Embryo Transf. 1986;3(1):46–52.

    Article  CAS  PubMed  Google Scholar 

  96. Goodman LR, Goldberg J, Falcone T, Austin C, Desai N. Does the addition of time-lapse morphokinetics in the selection of embryos for transfer improve pregnancy rates? A randomized controlled trial. Fertil Steril. 2016;105(2):275–285.e210. https://doi.org/10.1016/j.fertnstert.2015.10.013.

    Article  PubMed  Google Scholar 

  97. Polanski LT, Coelho Neto MA, Nastri CO, Navarro PA, Ferriani RA, Raine-Fenning N, Martins WP. Time-lapse embryo imaging for improving reproductive outcomes: systematic review and meta-analysis. Ultrasound Obstet Gynecol. 2014;44(4):394–401. https://doi.org/10.1002/uog.13428.

    Article  PubMed  CAS  Google Scholar 

  98. Armstrong S, Arroll N, Cree LM, Jordan V, Farquhar C. Time-lapse systems for embryo incubation and assessment in assisted reproduction. Cochrane Database Syst Rev. 2015;(2). https://doi.org/10.1002/14651858.CD011320.pub2.

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Huang, T., Alikani, M. (2018). Evidence-Based Approaches to Embryo Selection by Morphology and Kinetics. In: Carrell, D., Racowsky, C., Schlegel, P., DeCherney, A. (eds) Emerging Topics in Reproduction. Springer, Cham. https://doi.org/10.1007/978-3-319-90823-6_10

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