The ART of Embryo Selection: A Review of Methods to Rank the Most Competent Embryo(s) for Transfer to Optimize IVF Success
Abstract
1. Introduction
2. Under-Recognized Clinical Considerations Impacting Implantation and Embryo Transfer Success
3. Morphological Assessment
4. Preimplantation Genetic Testing
5. Non-Invasive Embryo Assessment
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
| AI | Artificial Intelligence |
| ART | Assisted Reproductive Technologies |
| IVF | In Vitro Fertilization |
| HIP | High Implantation Potential |
| PGT | Pre-implantation Genetic Testing |
| PGT-A | Pre-implantation Genetic Testing for Aneuploidy |
| PGT-M | Pre-implantation Genetic Testing for Monosomic Gene Disorders |
| PGT-SR | Pre-implantation Genetic Testing for Structural Rearrangements |
| PGT-P | Pre-implantation Genetic Testing for Polygenic Genetic Traits |
| Ni-PGT | Non-invasive Pre-implantation Genetic Testing |
| DNA | Deoxyribonucleic Acid |
| RNA | Ribonucleic Acid |
| ICSI | Intracytoplasmic Sperm Injection |
| POI | Primary Ovarian Insufficiency |
| PCOS | Polycystic Ovarian Syndrome |
| ICM | Inner Cell Mass |
| TLI | Timelapse Imaging |
References
- Skakkebæk, N.E.; Lindahl-Jacobsen, R.; Levine, H.; Andersson, A.-M.; Jørgensen, N.; Main, K.M.; Lidegaard, Ø.; Priskorn, L.; Holmboe, S.A.; Bräuner, E.V.; et al. Environmental factors in declining human fertility. Nat. Rev. Endocrinol. 2022, 18, 139–157. [Google Scholar] [CrossRef] [PubMed]
- Richardson, A.; Brearley, S.; Ahitan, S.; Chamberlain, S.; Davey, T.; Zujovic, L.; Hopkisson, J.; Campbell, B.; Raine-Fenning, N. A clinically useful simplified blastocyst grading system. Reprod. Biomed. Online 2015, 31, 523–530. [Google Scholar] [CrossRef] [PubMed]
- Greco, E.; Litwicka, K.; Minasi, M.G.; Cursio, E.; Greco, P.F.; Barillari, P. Preimplantation Genetic Testing: Where We Are Today. Int. J. Mol. Sci. 2020, 21, 4381. [Google Scholar] [CrossRef] [PubMed]
- Márquez-Hinojosa, S.; Noriega-Hoces, L.; Guzmán, L.; García, D.; Meseguer, M. Time-lapse embryo culture: A better understanding of embryo development and clinical application. JBRA Assist. Reprod. 2021, 25, 432–443. [Google Scholar] [CrossRef]
- Bebbere, D.; Coticchio, G.; Borini, A.; Ledda, S. Oocyte aging: Looking beyond chromosome segregation errors. J. Assist. Reprod. Genet. 2022, 39, 793–800. [Google Scholar] [CrossRef]
- Check, J.H.; Jamison, T.; Check, D.; Choe, J.K.; Brasile, D.; Cohen, R. Live delivery and implantation rates of donor oocyte recipients in their late forties are similar to younger recipients. J. Reprod. Med. 2011, 56, 149–152. [Google Scholar]
- Peiro, A.D.; Leon, P.S.; Leo, A.P.; Pellicer, A.; Gimeno, P.D. Breaking the ageing paradigm in endometrium: Endometrial gene expression related to cilia and ageing hallmarks in women over 35 years. Hum. Reprod. 2022, 37, 762–776. [Google Scholar] [CrossRef]
- Friedman, B.E.; Davis, L.B.; Lathi, R.B.; Westphal, L.M.; Baker, V.L.; Milki, A.A. Age-Related Success with Elective Single versus Double Blastocyst Transfer. ISRN Obstet. Gynecol. 2011, 17, 656204. [Google Scholar] [CrossRef]
- Mazzilli, R.; Rucci, C.; Vaiarelli, A.; Cimadomo, D.; Ubaldi, F.M.; Foresta, C.; Ferlin, A. Male factor infertility and assisted reproductive technologies: Indications, minimum access criteria and outcomes. J. Endocrinol. Investig. 2023, 46, 1079–1085. [Google Scholar] [CrossRef]
- Opstal, J.V.; Fieuws, S.; Spiessens, C.; Soubry, A. Male age interferes with embryo growth in IVF treatment. Hum. Rep. 2020, 36, 107–115. [Google Scholar] [CrossRef]
- Elkhatib, I.; Nogueira, D.; Bayram, A.; Abdala, A.; Ata, B.; Melado, L.; Lawrenz, B.; Kalaft, E.; Gianaroli, L.; Fatemi, H.M. The influence of male age and sperm parameters on blastulation and euploidy rates. Fertil. Steril. 2025, 124, 1006–1015. [Google Scholar] [CrossRef] [PubMed]
- Luna, M.; Finkler, E.S.; Barritt, J.; Chama, N.B.; Sandler, B.; Copperman, A.B.; Grunfeld, L. Paternal age and assisted reproductive technology outcome in ovum recipients. Fertil. Steril. 2009, 92, 1772–1775. [Google Scholar] [CrossRef] [PubMed]
- Shabtaie, S.A.; Gerkowicz, S.A.; Kohn, T.P.; Ramasamy, R. Role of Abnormal Sperm Morphology in Predicting Pregnancy Outcomes. Curr. Urol. Rep. 2016, 17, 67. [Google Scholar] [CrossRef]
- Wang, C.; Swerdloff, R.S. Limitations of semen analysis as a test of male fertility and anticipated needs from newer tests. Fertil. Steril. 2014, 102, 1502–1507. [Google Scholar] [CrossRef]
- Buisan, M.V.; Mecca, R.; Jones, C.; Coward, K.; Yeste, M. Contribution of semen to early embryo development: Fertilization and beyond. Hum. Reprod. Update 2023, 29, 395–433. [Google Scholar] [CrossRef]
- Ferlin, A.; Calogero, A.E.; Krausz, C.; Lombardo, F.; Paoli, D.; Rago, R.; Scarica, C.; Simoni, M.; Foresta, C.; Rochira, V.; et al. Management of male factor infertility: Position statement from the Italian Society of Andrology and Sexual Medicine (SIAMS). J. Endocrinol. Investig. 2022, 45, 1085–1113. [Google Scholar] [CrossRef]
- Harton, G.L.; Tempest, H.G. Chromosomal disorders and male infertility. Asian J. Androl. 2011, 14, 32–39. [Google Scholar] [CrossRef]
- Jain, R.; Kazmerski, T.M.; Zuckerwise, L.C.; West, N.E.; Montemayor, K.; Aitken, M.; Cheng, E.; Roe, A.H.; Wilson, A.; Mann, C. Pregnancy in cystic fibrosis: Review of the literature and expert recommendations. J. Cyst. Fibros. 2022, 21, 387–395. [Google Scholar] [CrossRef]
- Taylor-Cousar, J.L.; Jain, R.; Kazmerski, T.M.; Aitken, M.L.; West, N.E.; Wilson, A.; Middleton, P.G.; Nash, E.F. Concerns regarding the safety of azithromycin in pregnancy—Relevance for women with cystic fibrosis. J. Cyst. Fibros. 2020, 20, 395–396. [Google Scholar] [CrossRef]
- van Erven, B.; Berry, G.T.; Cassiman, D.; Connolly, G.; Forga, M.; Gautschi, M.; Gubbels, C.S.; Hollak, C.E.M.; Janssen, M.C.; Knerr, I. Fertility in adult women with classic galactosemia and primary ovarian insufficiency. Fertil. Steril. 2017, 108, 168–174. [Google Scholar] [CrossRef]
- Derks, B.; Greysha, R.C.; Synneva, H.L.; Vos, E.N.; Demirbas, D.; Lai, K.; Treacy, E.P.; Levy, H.L.; Haug, L.E.W.; Golzabo, M.E.R.; et al. The hypergonadotropic hypogonadism conundrum of classic galactosemia. Hum. Reprod. Update 2022, 29, 246–258. [Google Scholar] [CrossRef] [PubMed]
- Abbaspour, S.; Isazadeh, A.; Heidari, M.; Heidari, M.; Hajaziman, S.; Nejad, M.S.; Taskhiri, M.H.; Bolhassani, M.; Ebrahimi, A.H.; Keshavarz, P. Prevalence of Chromosomal Abnormalities in Iranian Patients with Infertility. Arch. Iran. Med. 2023, 26, 110–116. [Google Scholar] [CrossRef] [PubMed]
- Tunç, E.; Ilgaz, S. Robertsonian translocation (13;14) and its clinical manifestations: A literature review. Reprod. Biomed. Online 2022, 45, 563–573. [Google Scholar] [CrossRef] [PubMed]
- Jiang, W.; Xie, Q.; Li, X.; Yang, Y.; Luan, T.; Ni, D.; Chen, Y.; Wang, X.; Zhao, C.; Ling, X. Y chromosome AZFc microdeletion may have negative effect on embryo euploidy: A retrospective cohort study. BMC Med. Genom. 2023, 16, 324. [Google Scholar] [CrossRef]
- Siddiqui, S.; Mateen, S.; Ahmad, R.; Moin, S. A brief insight into the etiology, genetics, and immunology of polycystic ovarian syndrome (PCOS). J. Assist. Reprod. Genet. 2022, 39, 2439–2473. [Google Scholar] [CrossRef]
- Kotlyar, A.; Seifer, D.B. Women with PCOS who undergo IVF: A comprehensive review of therapeutic strategies for successful outcomes. Reprod. Biol. Endocrinol. 2023, 21, 70. [Google Scholar] [CrossRef]
- Allaire, C.; Bedaiwy, M.A.; Yong, P.J. Diagnosis and management of endometriosis. Can. Med. Assoc. J. 2023, 195, 363–371. [Google Scholar] [CrossRef]
- Somigliana, E.; Piani, L.L.; Paffoni, A.; Salmeri, N.; Orsi, M.; Banaglia, L.; Vercellini, P.; Vigano, P. Endometriosis and IVF treatment outcomes: Unpacking the process. Reprod. Biol. Endocrinol. 2023, 21, 107. [Google Scholar] [CrossRef]
- Turner, F.; Powell, S.G.; Al-Lamee, H.; Ghadvi, A.; Palmer, E.; Drakeley, A.; Sprung, V.S.; Hapangama, D.; Tempest, N. Impact of BMI on fertility in an otherwise healthy population: A systematic review and meta-analysis. BMJ Open 2024, 14, e082123. [Google Scholar] [CrossRef]
- Ameratunga, D.; Gebeh, A.K.; Amoako, A. Obesity and Male Infertility. Best Pract. Res. Clin. Obstet. Gynaecol. 2023, 90, 102393. [Google Scholar] [CrossRef]
- Sharma, R.; Biedenharn, K.R.; Fedor, J.M.; Agarwal, A. Lifestyle factors and reproductive health: Taking control of your fertility. Reprod. Biol. Endocrinol. 2013, 11, 66. [Google Scholar] [CrossRef]
- Urman, B.; Yakin, K.; Ata, B.; Balaban, B. How can we improve current blastocyst grading systems? Curr. Opin. Obstet. Gynecol. 2007, 19, 273–278. [Google Scholar] [CrossRef] [PubMed]
- 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, 392–405. [Google Scholar] [CrossRef] [PubMed]
- Tesarik, J.; Greco, E. The probability of abnormal preimplantation development can be predicted by a single static observation on pronuclear stage morphology. Hum. Reprod. 1999, 14, 1318–1323. [Google Scholar] [CrossRef]
- Senn, A.; Urner, F.; Chanson, A.; Primi, M.P.; Wirthner, D.; Germond, M. Morphological scoring of human pronuclear zygotes for prediction of pregnancy outcome. Hum. Reprod. 2005, 21, 234–239. [Google Scholar] [CrossRef]
- Kljajic, M.; Saymé, N.; Krebs, T.; Wagenpfeil, G.; Baus, S.; Solomayer, E.F.; Kasoha, M. Zygote Diameter and Total Cytoplasmic Volume as Useful Predictive Tools of Blastocyst Quality. Geburtshilfe Frauenheilkd. 2022, 83, 97–105. [Google Scholar] [CrossRef]
- Aydin, S.; Cinar, O.; Demir, B.; Korkmaz, C.; Ozdegirmenci, O.; Dilbaz, S.; Goktolga, U. Is pronuclear scoring a really good predictor for ICSI cycles? Gynecol. Endocrinol. 2010, 27, 742–747. [Google Scholar] [CrossRef]
- Racowsky, C.; Jackson, K.V.; Cekleniak, N.A.; Fox, J.H.; Hornstein, M.D.; Ginsburg, E.S. The number of eight-cell embryos is a key determinant for selecting day 3 or day 5 transfer. Fertil. Steril. 2000, 73, 558–564. [Google Scholar] [CrossRef]
- Nomura, M.; Iwase, A.; Furui, K.; Kitagawa, T.; Matsui, Y.; Yoshikawa, M.; Kikkawa, F. Preferable correlation to blastocyst development and pregnancy rates with a new embryo grading system specific for day 3 embryos. J. Assist. Reprod. Genet. 2006, 24, 23–28. [Google Scholar] [CrossRef]
- Shi, C.; Sun, T.C.; Chen, S.W.; Wang, P.; Liang, R.; Duan, S.N.; Han, H.J.; Shen, H.; Chen, X. Effects of embryo density on cell number of day 3 embryos cultured in a 30-μl drop: A retrospective cohort study. Zygote 2022, 30, 487–494. [Google Scholar] [CrossRef]
- Racowsky, C.; Combelles, C.M.H.; Nureddin, A.; Pan, Y.; Finn, A.; Miles, L.; Gale, S.; O’Leary, T.; Jackson, K.V. Day 3 and day 5 morphological predictors of embryo viability. Reprod. Biomed. Online 2003, 6, 323–331. [Google Scholar] [CrossRef] [PubMed]
- Klement, A.H.; Ovadia, M.; Wiser, A.; Berkovitz, A.; Shavit, T.; Nemerovsky, L.; Ghetler, Y.; Cohen, I.; Shulma, A. What we learned from extended culture of “rejected” day-3 cleavage stage embryos: A prospective cohort study. J. Ovarian Res. 2017, 10, 35. [Google Scholar] [CrossRef] [PubMed]
- Cai, J.; Liu, L.; Chen, J.; Liu, Z.; Jiang, X.; Chen, H.; Ren, J. Day-3-embryo fragmentation is associated with singleton birth weight following fresh single blastocyst transfer: A retrospective study. Front. Endocrinol. 2022, 13, 919283. [Google Scholar] [CrossRef] [PubMed]
- Moayeri, S.E.; Allen, R.B.; Brewster, W.R.; Kim, M.H.; Porto, M.; Werlin, L.B. Day-3 embryo morphology predicts euploidy among older subjects. Fertil. Steril. 2008, 89, 118–123. [Google Scholar] [CrossRef]
- Marion, E.S.; Chavli, E.A.; Laven, E.; Theunissen, R.P.M.; Koster, M.P.H.; Baart, E.B. Longitudinal surface measurements of human blastocysts show that the dynamics of blastocoel expansion are associated with fertilization methods and ongoing pregnancy. Reprod. Biol. Endocrinol. 2022, 20, 53. [Google Scholar] [CrossRef]
- Alström, 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, 3289–3296. [Google Scholar] [CrossRef]
- Rozema, D.; Maître, J.L. Forces Shaping the Blastocyst. Cold Spring Harb. Perspect. Biol. 2024, 17, 041519. [Google Scholar] [CrossRef]
- Ozgur, K.; Berkkanoglu, M.; Bulut, H.; Donmez, L.; Isikli, A.; Coetzee, K. Blastocyst age, expansion, trophectoderm morphology, and number cryopreserved are variables predicting clinical implantation in single blastocyst frozen embryo transfers in freeze-only-IVF. J. Assist. Reprod. Genet. 2021, 38, 1077–1087. [Google Scholar] [CrossRef]
- Bayram, A.; Elkhatib, I.; Kalafat, E.; Adbala, A.; Ferracuti, V.; Melado, L.; Lawrenz, B.; Fatemi, H.; Nogueira, D. Steady morphokinetic progression is an independent predictor of live birth: A descriptive reference for euploid embryos. Hum. Reprod. Open 2024, 2024, 59. [Google Scholar] [CrossRef]
- Hardarson, T.; Landuyt, L.V.; Jones, G. The blastocyst. Hum. Reprod. 2012, 27, 72–91. [Google Scholar] [CrossRef]
- Gardner, D.K.; Vella, P.; Lane, M.; Wagley, L.; Schlenker, T.; Schoolcraft, W.B. Culture and transfer of human blastocysts increases implantation rates and reduces the need for multiple embryo transfers. Fertil. Steril. 1998, 69, 84–88. [Google Scholar] [CrossRef]
- Dawson, K.J.; Conaghan, J.; Ostera, G.R.; Winston, R.M.L.; Hardy, K. Delaying transfer to the third day post-insemination, to select non-arrested embryos, increases development to the fetal heart stage. Hum. Reprod. 1995, 10, 177–182. [Google Scholar] [CrossRef] [PubMed]
- Cutting, R. Single embryo transfer for all. Best Pract. Res. Clin. Obstet. Gynaecol. 2018, 53, 30–37. [Google Scholar] [CrossRef] [PubMed]
- Penzias, A.; Bendikson, K.; Butts, S.; Coutifaris, C.; Falcone, T.; Fossum, G.; Gitlin, S.; Gracia, C.; Hansen, K.; Barbera, A.L.; et al. The use of preimplantation genetic testing for aneuploidy (PGT-A): A committee opinion. Fertil. Steril. 2018, 109, 429–436. [Google Scholar] [CrossRef] [PubMed]
- Viotti, M. Preimplantation Genetic Testing for Chromosomal Abnormalities: Aneuploidy, Mosaicism, and Structural Rearrangements. Genes 2020, 11, 602. [Google Scholar] [CrossRef]
- Cimadomo, D.; Rienzi, L.; Conforti, A.; Forman, E.; Canosa, S.; Innocenti, F.; Poli, M.; Hynes, J.; Gemmell, L.; Vaiarelli, A.; et al. Opening the black box: Why do euploid blastocysts fail to implant? A systematic review and meta-analysis. Hum. Reprod. Update 2023, 29, 570–633. [Google Scholar] [CrossRef]
- Casper, R.F. PGT-A: Houston, we have a problem. J. Assist. Reprod. Genet. 2023, 40, 2325–2332. [Google Scholar] [CrossRef]
- Scriven, P.N. Combining PGT-A with PGT-M risks trying to do too much. J. Assist. Reprod. Genet. 2022, 39, 2015–2018. [Google Scholar] [CrossRef]
- Parikh, F.; Athalye, A.; Madon, P.; Khandeparkar, M.; Naik, D.; Sanap, R.; Udumudi, A. Genetic counseling for pre-implantation genetic testing of monogenic disorders (PGT-M). Front. Reprod. Health 2023, 5, 1213546. [Google Scholar] [CrossRef]
- Somigliana, E.; Costantini, M.P.; Filippi, F.; Terenziani, M.; Riccaboni, A.; Nicotra, V.; Rago, R.; Paffoni, A.; Mencaglia, L.; Magnolfi, S.; et al. Fertility counseling in women with hereditary cancer syndromes. Crit. Rev. Oncol./Hematol. 2022, 171, 103604. [Google Scholar] [CrossRef]
- Calosci, D.; Passaglia, L.; Gabbiato, I.; Cartisano, F.; Affuso, R.; Sorrentino, U.; Zuccarello, D. Public Awareness and Acceptability of PGT-M in Cancer Predisposition Syndromes. Genes 2023, 14, 2069. [Google Scholar] [CrossRef]
- Giuliano, R.; Maione, A.; Vallefuoco, A.; Sorrentino, U.; Zuccarello, D. Preimplantation Genetic Testing for Genetic Diseases: Limits and Review of Current Literature. Genes 2023, 14, 2095. [Google Scholar] [CrossRef] [PubMed]
- Scriven, P.N. PGT-SR: The red-herring and the siren; interchromosomal effect and screening for unrelated aneuploidy. J. Assist. Reprod. Genet. 2021, 35, 1015–1018. [Google Scholar] [CrossRef] [PubMed]
- Siermann, M.; Tšuiko, O.; Vermeesch, J.R.; Raivio, T.; Borry, P. A review of normative documents on preimplantation genetic testing: Recommendations for PGT-P. Genet. Med. Off. J. Am. Coll. Med. Genet. 2022, 24, 1165–1175. [Google Scholar] [CrossRef] [PubMed]
- Capalbo, A.; Wert, G.; Mertes, H.; Klausner, L.; Coonen, E.; Spinella, F.; Velde, H.V.; Viville, S.; Sermon, K.; Verneulen, N.; et al. Screening embryos for polygenic disease risk: A review of epidemiological, clinical, and ethical considerations. Hum. Reprod. Update 2024, 30, 529–557. [Google Scholar] [CrossRef]
- Kahraman, S.; Sahin, Y.; Yelke, H.; Kumtepe, Y.; Tufekci, M.A.; Yapan, C.C.; Yesil, M.; Cetinkaya, M. High rates of aneuploidy, mosaicism and abnormal morphokinetic development in cases with low sperm concentration. J. Assist. Reprod. Genet. 2020, 37, 629–640. [Google Scholar] [CrossRef]
- Gazzo, E.; Peña, F.; Valdéz, F.; Chung, A.; Bonomini, C.; Ascenzo, M.; Velit, M.; Escudero, E. The KidscoreTM D5 algorithm as an additional tool to morphological assessment and PGT-A in embryo selection: A time-lapse study. JBRA Assist. Reprod. 2019, 24, 55–60. [Google Scholar] [CrossRef]
- Diamond, M.P.; Suraj, V.; Behnke, E.J.; Yang, X.; Angle, M.J.; Steinmiller, J.C.L.; Watterson, R.; Wirka, K.A.; Chen, A.A.; 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. 2014, 32, 61–68. [Google Scholar] [CrossRef]
- Armstrong, S.; Bhide, P.; Jordan, V.; Pacey, A.; Farquhar, C. Time-lapse systems for embryo incubation and assessment in assisted reproduction. Cochrane Database Syst. Rev. 2018, 5, 11320. [Google Scholar] [CrossRef]
- Leaver, M.; Wells, D. Non-invasive preimplantation genetic testing (niPGT): The next revolution in reproductive genetics? Hum. Reprod. Update 2019, 26, 16–42. [Google Scholar] [CrossRef]
- Jaffe, M.G.K.; McReynolds, S. Embryology in the era of proteomics. Fertil. Steril. 2013, 99, 1073–1077. [Google Scholar] [CrossRef]
- Munne, S.; Horcajadas, J.A.; Seth-Smith, M.L.; Perugini, M.; Griffin, D.K. Non-invasive selection for euploid embryos: Prospects and pitfalls of the three most promising approaches. Reprod. Biomed. Online 2025, 51, 105077. [Google Scholar] [CrossRef] [PubMed]
- Shi, J.; Wu, X.; Qi, H.; Xu, X.; Hong, S. Application and discoveries of metabolomics and proteomics in the study of female infertility. Front. Endocrinol. 2024, 14, 1315099. [Google Scholar] [CrossRef] [PubMed]
- Ren, J.L.; Zhang, A.H.; Kong, L.; Wang, X.J. Advances in mass spectrometry-based metabolomics for investigation of metabolites. RSC Adv. 2018, 8, 22335–22350. [Google Scholar] [CrossRef]
- Whiteaker, J.R.; Lundeen, R.A.; Zhao, L.; Schoeherr, R.M.; Burian, A.; Huang, D.; Voytovich, U.; Wang, T.; Kennedy, J.J.; Ivey, R.G. Targeted Mass Spectrometry Enables Multiplexed Quantification of Immunomodulatory Proteins in Clinical Biospecimens. Front. Immunol. 2021, 12, 765898. [Google Scholar] [CrossRef] [PubMed]
- Rai, A.; Poh, Q.H.; Okae, H.; Arima, T.; Totonchi, M.; Greening, D.W. Dynamic Proteome Landscape During Preimplantation Human Embryo Development and Trophectoderm Stem Cell-Differentiation. Proteomics 2025, 15, 72–89. [Google Scholar] [CrossRef]
- Omes, C.; Conti, A.; Benedetti, L.; Tomasoni, V.; Marchi, D.D.; Nappi, R.E.; Angelis, M.G.C.; Ceccarelli, G. Expression of miRNA from spent pre-implantation embryos culture media. Reprod. Biol. 2024, 24, 100847. [Google Scholar] [CrossRef]
- Babayev, E.; Feinberg, E.C. Embryo through the lens: From time-lapse cinematography to artificial intelligence. Fertil. Steril. 2020, 113, 342–343. [Google Scholar] [CrossRef]
- Salih, M.; Austin, C.; Warty, R.R.; Tiktin, C.; Rolnik, D.L.; Momeni, M.; Rezatofighi, H.; Reddy, S.; Smith, V.; Vollenhoven, B.; et al. Embryo selection through artificial intelligence versus embryologists: A systematic review. Hum. Reprod. Open 2023, 2023, hoad031. [Google Scholar] [CrossRef]
- Koplin, J.J.; Johnston, M.; Webb, A.N.S.; Whittaker, A.; Mills, C. Ethics of artificial intelligence in embryo assessment: Mapping the terrain. Hum. Reprod. 2024, 40, 179–185. [Google Scholar] [CrossRef]
- Liu, H.; Chen, L.; Shan, G.; Sun, C.; Lu, C.; Liao, H.; Zhang, S.; Dong, S.; Xu, X.; Yan, Q.; et al. An interpretable artificial intelligence approach to differentiate between blastocysts with similar or same morphological grades. Hum. Reprod. 2025, 40, 1077–1086. [Google Scholar] [CrossRef]
- Zaninovic, N.; Rosenwaks, Z. Artificial intelligence in human in vitro fertilization and embryology. Fertil. Steril. 2020, 114, 914–920. [Google Scholar] [CrossRef]

| Implantation Factor | Contributing Factors | Possible Clinical Treatment Solutions |
|---|---|---|
| Embryo Quality | Genetics—embryos with chromosome anomalies have a lower likelihood of implantation. Maternal Age—egg quality and increased chance of aneuploidy increase with female age. Sperm Quality—contributes genetic anomalies. | PGT-A is employed to identify euploid embryos. Advanced IVF culture systems and attention to detail in laboratories. |
| Endometrial Receptivity | Chronic endometritis—inflammation of the uterine lining interferes with implantation. Asherman’s syndrome–presence of scar tissue in the uterine lining. Insufficient uterine blood flow | Endometrial biopsy to detect inflammation or infections that can then be treated prior to embryo transfer. Promote endometrial lining thickness with hormone replacement therapy. Endometrial receptivity assays to determine optimal timing for embryo transfer. |
| Hormone Balance | An unbalanced hormonal milieux can interfere with the endometrial lining. | Monitoring of hormone levels (estradiol, progesterone) throughout the cycle. Supplementation with progesterone to promote endometrial lining growth or other hormones (thyroid stimulation hormone) as needed. |
| Immunological Factors | Immune response to a foreign object (ie: embryo) results in hindered embryo development and implantation. | Immunological testing to identify this issue Treat with immunoglobulins or corticosteroids to regulate an immune response |
| Lifestyle and General Health | Body Mass Index (BMI)—overweight and underweight conditions may impair implantation. Smoking, Alcohol, Drugs—affects gamete, embryo and endometrial quality. | Promote a healthy lifestyle for patients trying to conceive naturally or with assisted conception. Stress management (ie: mindfulness stress reduction). |
| Technique (Most to Least Important) | When It Should Be Used | Advantages | Limitations | Criteria |
|---|---|---|---|---|
| Blastocyst Morphology/Morphokinetics | Whenever possible | -May be supplemented with AI analysis in the near future -Currently supported using non-invasive time-lapse imaging -Widely available/cost effective | -Grading may be subjective -No genetic assessment | -Garnder grading system (Good) -Day5/6 Blastulation |
| PGT-A/SR | Whenever possible, it should be more heavily considered for patients with advanced maternal age or recurrent implantation failure | -Help identify embryo- specific genetic abnormalities -Reduces implantation failure/miscarriage risks | -Invasive Biopsy -Can be expensive -Less effective for mosaic embryos | -Normal Result(s) on Day 5-6 trophectoderm biopsy |
| Ni-PGT | Whenever possible, especially in cases where biopsy has raised risks | -Non-invasive, Reduces risk of embryo damage -Complements morphological assessment | -Less accurate than traditional PGT, lower DNA quality -New, limited clinical adoption | -Normal Result(s) of spent media analysis |
| Pronuclear Morphology/ Morphokinetics | Whenever possible | -Currently supported using non-invasive time-lapse imaging -May help determine cleavage potential | -Predictive Value is limited, implantation potential may change through development | -Z-score system -High cell numbers -6-8 blastomeres |
| PGT-M/P | In patients who are known to either have or carry genes for genetic disorders | -Helps identify embryos impacted by hereditary disease | -Time consuming/expensive -Some ethical concerns regarding PGT-P testing | -Normal Result(s) on Day 5-6 trophectoderm biopsy |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Amin, N.; Kteily, K.; Deniz, S.; Faghih, M.; Karnis, M.F.; Amin, S.; Neal, M.S. The ART of Embryo Selection: A Review of Methods to Rank the Most Competent Embryo(s) for Transfer to Optimize IVF Success. Biomedicines 2025, 13, 2766. https://doi.org/10.3390/biomedicines13112766
Amin N, Kteily K, Deniz S, Faghih M, Karnis MF, Amin S, Neal MS. The ART of Embryo Selection: A Review of Methods to Rank the Most Competent Embryo(s) for Transfer to Optimize IVF Success. Biomedicines. 2025; 13(11):2766. https://doi.org/10.3390/biomedicines13112766
Chicago/Turabian StyleAmin, Naiya, Karen Kteily, Stacy Deniz, Mehrnoosh Faghih, Megan F. Karnis, Shilpa Amin, and Michael S. Neal. 2025. "The ART of Embryo Selection: A Review of Methods to Rank the Most Competent Embryo(s) for Transfer to Optimize IVF Success" Biomedicines 13, no. 11: 2766. https://doi.org/10.3390/biomedicines13112766
APA StyleAmin, N., Kteily, K., Deniz, S., Faghih, M., Karnis, M. F., Amin, S., & Neal, M. S. (2025). The ART of Embryo Selection: A Review of Methods to Rank the Most Competent Embryo(s) for Transfer to Optimize IVF Success. Biomedicines, 13(11), 2766. https://doi.org/10.3390/biomedicines13112766

