Noninvasive methods for preimplantation blastocyst quality assessment in in vitro fertilization programs

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Abstract

Since the first in vitro fertilization (IVF) procedure, assisted reproductive technologies have helped many patients overcome infertility. However, according to the 2022 National Registry of Assisted Reproductive Technologies of the Russian Association of Human Reproduction, the probability of achieving pregnancy through IVF remains below 50%. Morphological assessment of blastocyst quality remains the gold standard. Implantation rates have increased to some extent due to the selection of high-quality embryos. However, given the subjectivity of morphological evaluation, further research is needed to establish the correlation between embryo reproductive potential and morphology. Time-lapse imaging combined with artificial intelligence may enhance the objectivity of assessment and identify additional morphological features indicative of blastocyst quality. The detection of exosomes, proteins, and metabolites secreted into the culture medium during embryo development may provide insights into the physiological state of the embryo and its interactions with the surrounding environment, potentially serving as markers of implantation potential. This review provides an overview of the morphological and biochemical markers of blastocyst quality, their interrelationships, and the use of artificial intelligence in embryo selection for transfer. A literature search was conducted in the electronic databases PubMed and Google Scholar using the following keywords: IVF, blastocyst, human embryo, culture media, timelapse system, embryo string, embryo exosomes, morphology, artificial intelligence, proteome, and metabolome. The analysis included studies published in the past five years.

About the authors

Daria D. Abasheva

I.M. Sechenov First Moscow State Medical University

Author for correspondence.
Email: daryaabash5@gmail.com
ORCID iD: 0009-0002-9859-7601

Student

Russian Federation, 8 Trubetskaya st, bldg 2, Moscow, 119991

Ekaterina E. Rudenko

I.M. Sechenov First Moscow State Medical University

Email: redikor2@yandex.ru
ORCID iD: 0000-0002-0000-1439
SPIN-code: 4833-3586

MD, Cand. Sci. (Medicine), Assistant Professor

Russian Federation, 8 Trubetskaya st, bldg 2, Moscow, 119991

Natalia S. Trifonova

I.M. Sechenov First Moscow State Medical University

Email: Trifonova.nataly@mail.ru
ORCID iD: 0000-0002-2891-3421
SPIN-code: 4753-5430

MD, Dr. Sci. (Medicine)

Russian Federation, 8 Trubetskaya st, bldg 2, Moscow, 119991

Svetlana E. Korolenko

Tyumen State Medical University

Email: korolenko.svt@gmail.com
ORCID iD: 0009-0001-4062-4817

Student

Russian Federation, Tyumen

Yulia I. Utkina

North-Western State Medical University named after I.I. Mechnikov

Email: utknes@mail.ru
ORCID iD: 0009-0003-1960-9027

Student

Russian Federation, Saint Petersburg

Polina I. Tikhomirova

Kursk State Medical University

Email: p.tikhomiirova@yandex.ru
ORCID iD: 0009-0008-8309-0940

Student

Russian Federation, Kursk

References

  1. Farquhar C, Rishworth JR, Brown J, Nelen WL, Marjoribanks J. Assisted reproductive technology: an overview of Cochrane reviews. Cochrane Database Syst Rev. 2014;(12):CD010537. doi: 10.1002/14651858.CD010537.pub3
  2. Gardner DK, Lane M, Stevens J, et al. Blastocyst score affects implantation and pregnancy outcome: towards a single blastocyst transfer. Fertil Steril. 2000;73(6):1155–1158. doi: 10.1016/s0015-0282(00)00518-5
  3. Wang C, Shu J, Lin R, et al. Choosing the optimal blastocyst by morphology score versus developmental rate in frozen-thawed embryo transfer cycles. Hum Fertil (Camb). doi: 10.1080/14647273.2020.1778199
  4. Li N, Guan Y, Ren B, et al. Effect of blastocyst morphology and developmental rate on euploidy and live birth rates in preimplantation genetic testing for aneuploidy cycles with single-embryo transfer. Front Endocrinol (Lausanne). 2022;13:858042. doi: 10.3389/fendo.2022.858042
  5. Zhang WY, Johal JK, Gardner RM, et al. The impact of euploid blastocyst morphology and maternal age on pregnancy and neonatal outcomes in natural cycle frozen embryo transfers. J Assist Reprod Genet. 2022;39(3):647–654. doi: 10.1007/s10815-022-02423-1
  6. Wang T, Si J, Wang B, et al. Prediction of live birth in vitrified-warmed 1PN-derived blastocyst transfer: Overall quality grade, ICM, TE, and expansion degree. Front Physiol. 2022;13:964360. doi: 10.3389/fphys.2022.964360
  7. Baatarsuren M, Sengebaljir D, Ganbaatar C, et al. The trophectoderm could be better predictable parameter than inner cellular mass (ICM) for live birth rate and gender imbalance. Reprod Biol. 2022;22(1):100596. doi: 10.1016/j.repbio.2021.100596
  8. Hamidova A, İsenlik BS, Hidisoğlu E, et al. Investigation of the effects of trophectoderm morphology on obstetric outcomes in fifth day blastocyst transfer in patients undergoing in-vitro-fertilization. J Turk Ger Gynecol Assoc. 2022;23(3):167–176. doi: 10.4274/jtgga.galenos.2022.2021-10-8
  9. Utsuno H, Ishimaru T, Matsumoto M, et al. Morphometric assessment of blastocysts: relationship with the ongoing pregnancy rate. F S Rep. 2022;4(1):85–92. doi: 10.1016/j.xfre.2022.11.001
  10. Carson DD, Bagchi I, Dey SK, et al. Embryo implantation. Dev Biol. 2000;223(2):217–237. doi: 10.1006/dbio.2000.9767
  11. Han EJ, Park JK, Eum JH, Bang S, Kim JW, Lee WS. Spontaneously hatching human blastocyst is associated with high development potential and live birth rate in vitrified-warmed single blastocyst transfer: a retrospective cohort study. Int J Gynaecol Obstet. 2024;164(1):315–323. doi: 10.1002/ijgo.15084
  12. Kim JH, Park EA, Yoon TK, et al. In vitro fertilization outcomes of frozen-thawed embryo transfer with hatched blastocysts versus with hatching blastocysts. Reprod Sci. 2025;32(1):74–84. doi: 10.1007/s43032-024-01499-7
  13. Rodriguez-Purata J, Gingold J, Lee J, et al. Hatching status before embryo transfer is not correlated with implantation rate in chromosomally screened blastocysts. Hum Reprod. 2016;31(11):2458–2470. doi: 10.1093/humrep/dew205
  14. Canon CM, Hernandez-Nieto C, Slifkin RE, et al. Expansion grade of post thaw embryos and implantation potential. Fertil Steril. 2022;118(4):e83–e84.
  15. Michailov Y, Friedler S, Saar-Ryss B. Methods to improve frozen-thawed blastocyst transfer outcomes- the IVF laboratory perspective. Journal of IVF-Worldwide. 2023;1(1-3):1–13. doi: 10.46989/001c.87541
  16. Vanderzwalmen P, Zech N, Greindl AJ, Ectors F, Lejeune B. Cryopréservation des embryons humains par vitrification [Cryopreservation of human embryos by vitrification]. Gynecol Obstet Fertil. 2006;34(9):760–769. doi: 10.1016/j.gyobfe.2006.07.010
  17. Allen M, Hale L, Lantsberg D, et al. Post-warming embryo morphology is associated with live birth: a cohort study of single vitrified-warmed blastocyst transfer cycles. J Assist Reprod Genet. 2022;39(2):417–425. doi: 10.1007/s10815-021-02390-z
  18. Park JK, Ahn SY, Seok SH, et al. Clinical usability of embryo development using a combined qualitative and quantitative approach in a single vitrified-warmed blastocyst transfer: assessment of pre-vitrified blastocyst diameter and post-warmed blastocyst re-expansion speed. J Clin Med. 2022;11(23):7085. doi: 10.3390/jcm11237085
  19. Hershko-Klement A, Raviv S, Nemerovsky L, et al. Standardization of post-vitrification human blastocyst expansion as a tool for implantation prediction. J Clin Med. 2022;11(9):2673. doi: 10.3390/jcm11092673
  20. Rubio I, Galán A, Larreategui Z, et al. Clinical validation of embryo culture and selection by morphokinetic analysis: a randomized, controlled trial of the EmbryoScope. Fertil Steril. 2014;102(5):1287–1294.e5. doi: 10.1016/j.fertnstert.2014.07.738
  21. Salas-Vidal E, Lomelí H. Imaging filopodia dynamics in the mouse blastocyst. Dev Biol. 2004;265(1):75–89. doi: 10.1016/j.ydbio.2003.09.012
  22. Scott LA. Oocyte and embryo polarity. Semin Reprod Med. 2000;18(2):171–183. doi: 10.1055/s-2000-12556
  23. ESHRE Capri Workshop Group. Europe the continent with the lowest fertility. Hum Reprod Update. 2010;16(6):590–602. doi: 10.1093/humupd/dmq023
  24. Ebner T, Sesli Ö, Kresic S, et al. Time-lapse imaging of cytoplasmic strings at the blastocyst stage suggests their association with spontaneous blastocoel collapse. Reprod Biomed Online. 2020;40(2):191–199. doi: 10.1016/j.rbmo.2019.11.004
  25. Ma B-X, Jin L, Huang B, et al. Cytoplasmic string between ICM and mTE is a positive predictor of clinical pregnancy and live birth outcomes in elective frozen-thawed single blastocyst transfer cycles: a time-lapse study. 11 December 2020, PREPRINT (Version 1) available at Research Square. doi: 10.21203/rs.3.rs-122470/v1
  26. Joo K, Nemes A, Dudas B, et al. The importance of cytoplasmic strings during early human embryonic development. Front Cell Dev Biol. 2023;11:1177279. doi: 10.3389/fcell.2023.1177279
  27. Park JK, Park JE, Bang S, et al. Development and validation of a nomogram for predicting ongoing pregnancy in single vitrified-warmed blastocyst embryo transfer cycles. Front Endocrinol (Lausanne). 2023;14:1257764. doi: 10.3389/fendo.2023.1257764
  28. Rajendran S, Brendel M, Barnes J, et al. Automatic ploidy prediction and quality assessment of human blastocyst using time-lapse imaging. Preprint. bioRxiv. 2023;2023.08.31.555741. doi: 10.1101/2023.08.31.555741
  29. Wang S, Fan J, Li H, Zhao M, Li X, Leung Chan DY. A dataset for deep learning based cleavage-stage blastocyst prediction with time-lapse images. bioRxiv. Published online December 27, 2023. doi: 10.1101/2023.12.26.573382
  30. Lee C, Kim G, Shin T, et al. Noninvasive time-lapse 3D subcellular analysis of embryo development for machine learning-enabled prediction of blastocyst formation. bioRxiv. Published online May 8, 2024. doi: 10.1101/2024.05.07.592317
  31. Nasiri N, Eftekhari-Yazdi P. An overview of the available methods for morphological scoring of pre-implantation embryos in in vitro fertilization. Cell J. 2015;16(4):392–405. doi: 10.22074/cellj.2015.486
  32. Hawke DC, Watson AJ, Betts DH. Extracellular vesicles, microRNA and the preimplantation embryo: non-invasive clues of embryo well-being. Reprod Biomed Online. 2021;42(1):39–54. doi: 10.1016/j.rbmo.2020.11.011
  33. Rubio C, Rodrigo L, Garcia-Pascual C, et al. Clinical application of embryo aneuploidy testing by next-generation sequencing. Biol Reprod. 2019;101(6):1083–1090. doi: 10.1093/biolre/ioz019
  34. Rudenko EE, Trifonova NS, Demura TA, et al. The role of placental exosomes in the development of pregnancy complications. Gynecology, Obstetrics and Perinatology. 2018;17(2):89–97. doi: 10.20953/1726-1678-2018-2-89-96 EDN: UUTZVO
  35. Tiegs AW, Tao X, Zhan Y, et al. A multicenter, prospective, blinded, nonselection study evaluating the predictive value of an aneuploid diagnosis using a targeted next-generation sequencing-based preimplantation genetic testing for aneuploidy assay and impact of biopsy. Fertil Steril. 2021;115(3):627–637. doi: 10.1016/j.fertnstert.2020.07.052
  36. Gellersen B, Reimann K, Samalecos A, et al. Invasiveness of human endometrial stromal cells is promoted by decidualization and by trophoblast-derived signals. Hum Reprod. 2010;25(4):862–873. doi: 10.1093/humrep/dep468
  37. Doyle LM, Wang MZ. Overview of extracellular vesicles, their origin, composition, purpose, and methods for exosome isolation and analysis. Cells. 2019;8(7):727. doi: 10.3390/cells8070727
  38. Vyas N, Dhawan J. Exosomes: mobile platforms for targeted and synergistic signaling across cell boundaries. Cell Mol Life Sci. 2017;74(9):1567–1576. doi: 10.1007/s00018-016-2413-9
  39. Giacomini E, Vago R, Sanchez AM, et al. Secretome of in vitro cultured human embryos contains extracellular vesicles that are uptaken by the maternal side. Sci Rep. 2017;7(1):5210. doi: 10.1038/s41598-017-05549-w
  40. Saadeldin IM, Kim SJ, Choi YB, Lee BC. Improvement of cloned embryos development by co-culturing with parthenotes: a possible role of exosomes/microvesicles for embryos paracrine communication. Cell Reprogram. 2014;16(3):223–234. doi: 10.1089/cell.2014.0003
  41. Kreth S, Hübner M, Hinske LC. MicroRNAs as clinical biomarkers and therapeutic tools in perioperative medicine. Anesth Analg. 2018;126(2):670–681. doi: 10.1213/ANE.0000000000002444
  42. Gombos K, Oldal M, Kalacs KI, et al. Droplet digital PCR analysis of miR-191-3p in the spent blastocyst culture media might reflect the reproductive competence of the 3rd day human embryo. J Clin Chem Lab Med. 2019;2(2):1000132.
  43. Borges E Jr, Setti AS, Braga DP, et al. miR-142-3p as a biomarker of blastocyst implantation failure — A pilot study. JBRA Assist Reprod. 2016;20(4):200–205. doi: 10.5935/1518-0557.20160039
  44. Abu-Halima M, Häusler S, Backes C, et al. Micro-ribonucleic acids and extracellular vesicles repertoire in the spent culture media is altered in women undergoing In Vitro Fertilization. Sci Rep. 2017;7(1):13525. doi: 10.1038/s41598-017-13683-8
  45. Cimadomo D, Rienzi L, Giancani A, et al. Definition and validation of a custom protocol to detect miRNAs in the spent media after blastocyst culture: searching for biomarkers of implantation. Hum Reprod. 2019;34(9):1746–1761. doi: 10.1093/humrep/dez119
  46. Pallinger E, Bognar Z, Bodis J, et al. A simple and rapid flow cytometry-based assay to identify a competent embryo prior to embryo transfer. Sci Rep. 2017;7:39927. doi: 10.1038/srep39927
  47. Horgan RP, Clancy OH, Myers JE, Baker PN. An overview of proteomic and metabolomic technologies and their application to pregnancy research. BJOG. 2009;116(2):173–181. doi: 10.1111/j.1471-0528.2008.01997.x
  48. Leese HJ, Baumann CG, Brison DR, et al. Metabolism of the viable mammalian embryo: quietness revisited. Mol Hum Reprod. 2008;14(12):667–672. doi: 10.1093/molehr/gan065
  49. Kanaka V, Proikakis S, Drakakis P, et al. Implementing a preimplantation proteomic approach to advance assisted reproduction technologies in the framework of predictive, preventive, and personalized medicine. EPMA J. 2022;13(2):237–260. doi: 10.1007/s13167-022-00282-5
  50. Deng S, Xu Y, Warden AR, et al. Quantitative proteomics and metabolomics of culture medium from single human embryo reveal embryo quality-related multiomics biomarkers. Anal Chem. 2024;96(29):11832–11844. doi: 10.1021/acs.analchem.4c01494
  51. Ji H, Shi X, Wang J, et al. Peptidomic analysis of blastocyst culture medium and the effect of peptide derived from blastocyst culture medium on blastocyst formation and viability. Mol Reprod Dev. 2020;87(1):191–201. doi: 10.1002/mrd.23308
  52. Freis A, Roesner S, Marshall A, et al. Non-invasive embryo assessment: altered individual protein profile in spent culture media from embryos transferred at day 5. Reprod Sci. 2021;28(7):1866–1873. doi: 10.1007/s43032-020-00362-9
  53. Fujiwara H, Tatsumi K, Kosaka K, et al. Human blastocysts and endometrial epithelial cells express activated leukocyte cell adhesion molecule (ALCAM/CD166). J Clin Endocrinol Metab. 2003;88(7):3437–3443. doi: 10.1210/jc.2002-021888
  54. Liu X, Liu X, Liu W, et al. HOXA9 transcriptionally regulates the EPHB4 receptor to modulate trophoblast migration and invasion. Placenta. 2017;51:38–48. doi: 10.1016/j.placenta.2017.01.127
  55. Parris JJ, Cooke VG, Skarnes WC, et al. JAM-A expression during embryonic development. Dev Dyn. 2005;233(4):1517–1524. doi: 10.1002/dvdy.20481
  56. Feng Y, Ma X, Deng L, et al. Role of selectins and their ligands in human implantation stage. Glycobiology. 2017;27(5):385–391. doi: 10.1093/glycob/cwx009
  57. Chau SE, Murthi P, Wong MH, et al. Control of extravillous trophoblast function by the eotaxins CCL11, CCL24 and CCL26. Hum Reprod. 2013;28(6):1497–1507. doi: 10.1093/humrep/det060
  58. Zhao XM, Cui LS, Hao HS, et al. Transcriptome analyses of inner cell mass and trophectoderm cells isolated by magnetic-activated cell sorting from bovine blastocysts using single cell RNA-seq. Reprod Domest Anim. 2016;51(5):726–735. doi: 10.1111/rda.12737
  59. Xiong Y, Zhang D. Effect of retinoic acid on apoptosis and expression of Fas proteins in mouse blastocysts cultured in vitro. J Huazhong Univ Sci Technolog Med Sci. 2008;28(3):239–242. doi: 10.1007/s11596-008-0302-7
  60. Basak S, Das MK, Duttaroy AK. Fatty acid-induced angiogenesis in first trimester placental trophoblast cells: possible roles of cellular fatty acid-binding proteins. Life Sci. 2013;93(21):755–762. doi: 10.1016/j.lfs.2013.09.024
  61. Jeong W, Song G, Kim J. Mitogen activated protein kinase pathway-dependent effects of platelet-derived growth factor on migration of trophectoderm cells. Biochem Biophys Res Commun. 2015;463(4):575–581. doi: 10.1016/j.bbrc.2015.05.098

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