Advertisement

Does embryo categorization by existing artificial intelligence, morphokinetic or morphological embryo selection models correlate with blastocyst euploidy rates?

Published:September 30, 2022DOI:https://doi.org/10.1016/j.rbmo.2022.09.010

      Abstract

      Research question

      Does embryo categorization by existing artificial intelligence (AI), morphokinetic or morphological embryo selection models correlate with blastocyst euploidy?

      Design

      A total of 834 patients (mean maternal age 40.5 ± 3.4 years) who underwent preimplantation genetic testing for aneuploidies (PGT-A) on a total of 3573 tested blastocysts were included in this retrospective study. The cycles were stratified into five maternal age groups according to the Society for Assisted Reproductive Technology age groups (<35, 35–37, 38–40, 41–42 and >42 years). The main outcome of this study was the correlation of euploidy rates in stratified maternal age groups and an automated AI model (iDAScore® v1.0), a morphokinetic embryo selection model (KIDScore Day 5 ver 3, KS-D5) and a traditional morphological grading model (Gardner criteria), respectively.

      Results

      Euploidy rates were significantly correlated with iDAScore (P = 0.0035 to <0.001) in all age groups, and expect for the youngest age group, with KS-D5 and Gardner criteria (all P < 0.0001). Additionally, multivariate logistic regression analysis showed that for all models, higher scores were significantly correlated with euploidy (all P < 0.0001).

      Conclusion

      These results show that existing blastocyst scoring models correlate with ploidy status. However, as these models were developed to indicate implantation potential, they cannot accurately diagnose if an embryo is euploid or aneuploid. Instead, they may be used to support the decision of how many and which blastocysts to biopsy, thus potentially reducing patient costs.

      Keywords

      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to Reproductive BioMedicine Online
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Bamford T.
        • Barrie A.
        • Montgomery S.
        • Dhillon-Smith R.
        • Campbell A.
        • Easter C.
        • Coomarasamy A.
        Morphological and morphokinetic associations with aneuploidy: a systematic review and meta-analysis.
        Hum. Reprod. Update. 2022; 28: 656-686
        • Berntsen J.
        • Rimestad J.
        • Lassen J.T.
        • Tran D.
        • Kragh M.F.
        Robust and generalizable embryo selection based on artificial intelligence and time-lapse image sequences.
        PLoS One. 2022; 17e0262661
        • Bhatt S.J.
        • Marchetto N.M.
        • Roy J.
        • Morelli S.S.
        • McGovern P.G.
        Pregnancy outcomes following in vitro fertilization frozen embryo transfer (IVF-FET) with or without preimplantation genetic testing for aneuploidy (PGT-A) in women with recurrent pregnancy loss (RPL): a SART-CORS study.
        Hum. Reprod. 2021; 36: 2339-2344
        • Bori L.
        • Dominguez F.
        • Fernandez E.I.
        • Del Gallego R.
        • Alegre L.
        • Hickman C.
        • Quiñonero A.
        • Nogueira M.F.G.
        • Rocha J.C.
        • Meseguer M.
        An artificial intelligence model based on the proteomic profile of euploid embryos and blastocyst morphology: a preliminary study.
        Reprod. Biomed. Online. 2021; 42: 340-350
        • Bormann C.L.
        • Kanakasabapathy M.K.
        • Thirumalaraju P.
        • Gupta R.
        • Pooniwala R.
        • Kandula H.
        • Hariton E.
        • Souter I.
        • Dimitriadis I.
        • Ramirez L.B.
        • Curchoe C.L.
        • Swain J.
        • Boehnlein L.M.
        • Shafiee H.
        Performance of a deep learning based neural network in the selection of human blastocysts for implantation.
        Elife. 2020; 9: e55301
        • 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: 140-146
        • Capalbo A.
        • Rienzi L.
        • Cimadomo D.
        • Maggiulli R.
        • Elliott T.
        • Wright G.
        • Nagy Z.P.
        • Ubaldi F.M.
        Correlation between standard blastocyst morphology, euploidy and implantation: an observational study in two centers involving 956 screened blastocysts.
        Hum. Reprod. 2014; 29: 1173-1181
        • Chavez-Badiola A.
        • Flores-Saiffe-Farias A.
        • Mendizabal-Ruiz G.
        • Drakeley A.J.
        • Cohen J.
        Embryo Ranking Intelligent Classification Algorithm (ERICA): artificial intelligence clinical assistant predicting embryo ploidy and implantation.
        Reprod. Biomed. Online. 2020; 41: 585-593
        • De Gheselle S.
        • Jacques C.
        • Chambost J.
        • Blank C.
        • Declerck K.
        • De Croo I.
        • Hickman C.
        • Tilleman K.
        Machine learning for prediction of euploidy in human embryos: in search of the best-performing model and predictive features.
        Fertil. Steril. 2022; 117: 738-746
        • Dimitriadis I.
        • Zaninovic N.
        • Badiola A.C.
        • Bormann C.L.
        Artificial intelligence in the embryology laboratory: a review.
        Reprod. Biomed. Online. 2022; 44: 435-448
        • ESHRE Working Group on Time-Lapse Technology
        • Apter S.
        • Ebner T.
        • Freour T.
        • Guns Y.
        • Kovacic B.
        • Le Clef N.
        • Marques M.
        • Meseguer M.
        • Montjean D.
        • Sfontouris I.
        • Sturmey R.
        • Coticchio G.
        Good practice recommendations for the use of time-lapse technology.
        Hum. Reprod. Open. 2020; 2020: 1-26
        • Gardner D.K.
        • Schoolcraft W.B.
        In-vitro culture of human blastocysts.
        in: Jansen R. Mortimer D. Towards Reproductive Certainty: Fertility and Genetics Beyond. Parthenon Press, Carnforth1999: 378-388
        • Gardner D.K.
        • Lane M.
        • Stevens J.
        • Schlenker T.
        • Schoolcraft W.B.
        Blastocyst score affects implantation and pregnancy outcome: towards a single blastocyst transfer.
        Fertil. Steril. 2000; 73: 1155-1158
        • Hill M.J.
        • Richter K.S.
        • Heitmann R.J.
        • Graham J.R.
        • Tucker M.J.
        • DeCherney A.H.
        • Browne P.E.
        • Levens E.D.
        Trophectoderm grade predicts outcomes of single-blastocyst transfers.
        Fertil. Steril. 2013; 99 (1283–1289.e1)
        • Huang B.
        • Tan W.
        • Li Z.
        • Jin L.
        An artificial intelligence model (euploid prediction algorithm) can predict embryo ploidy status based on time-lapse data.
        Reprod. Biol. Endocrinol. 2021; 19: 185
        • Karakida S.
        • Ezoe K.
        • Fukuda J.
        • Yabuuchi A.
        • Kobayashi T.
        • Kato K.
        Effects of gonadotropin administration on clinical outcomes in clomiphene citrate-based minimal stimulation cycle IVF..
        Reprod. Med. Bio. 2020; 19: 128-134
        • Kato K.
        • Kuroda T.
        • Yamadera-Egawa R.
        • Ezoe K.
        • Aoyama N.
        • Usami A.
        • Miki T.
        • Yamamoto T.
        • Takeshita T.
        Preimplantation genetic testing for aneuploidy for recurrent pregnancy loss and recurrent implantation failure in minimal ovarian stimulation cycle for women aged 35–42 years: live birth rate, developmental follow-up of children, and embryo ranking.
        Reprod. Sci. Sep. 2022; 9 (Online ahead of print)https://doi.org/10.1007/s43032-022-01073-z
        • Kato K.
        • Takehara Y.
        • Segawa T.
        • Kawachiya S.
        • Okuno T.
        • Kobayashi T.
        • Bodri D.
        • Kato O.
        Minimal ovarian stimulation combined with elective single embryo transfer policy: age-specific results of a large, single-center, Japanese cohort.
        Reprod. Biol. Endocrinol. 2012; 10: 35
        • Kato K.
        • Ueno S.
        • Berntsen J.
        • Ito M.
        • Shimazaki K.
        • Uchiyama K.
        • Okimura T.
        Comparing prediction of ongoing pregnancy and live birth outcomes in patients with advanced and younger maternal age patients using KIDScore day 5: a large-cohort retrospective study with single vitrified-warmed blastocyst transfer.
        Reprod. Biol. Endocrinol. 2021; 19: 98
        • Lee C.I.
        • Su Y.R.
        • Chen C.H.
        • Chang T.A.
        • Kuo E.E.
        • Zheng W.L.
        • Hsieh W.T.
        • Huang C.C.
        • Lee M.S.
        • Liu M.
        End-to-end deep learning for recognition of ploidy status using time-lapse videos.
        J. Assist. Reprod. Genet. 2021; 38: 1655-1663
        • Maggiulli R.
        • Giancani A.
        • Cimadomo D.
        • Ubaldi F.M.
        • Rienzi L.
        Human blastocyst biopsy and vitrification.
        J. Vis. Exp. 2019; July 26https://doi.org/10.3791/59625
        • 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 (1481–1489.e10)
        • Minasi M.G.
        • Colasante A.
        • Riccio T.
        • Ruberti A.
        • Casciani V.
        • Scarselli F.
        • Spinella F.
        • Fiorentino F.
        • Varricchio M.T.
        • Greco E.
        Correlation between aneuploidy, standard morphology evaluation and morphokinetic development in 1730 biopsied blastocysts: a consecutive case series study.
        Hum. Reprod. 2016; 31: 2245-2254
        • Munné S.
        • Alikani M.
        • Tomkin G.
        • Grifo J.
        • Cohen J.
        Embryo morphology, developmental rates, and maternal age are correlated with chromosome abnormalities.
        Fertil. Steril. 1995; 64: 382-391
        • Okimura T.
        • Kuwayama M.
        • Segawa T.
        • Takehara Y.
        • Kato K.
        • Kato O.
        Relations between the timing of transfer, expansion size and implantation rates in frozen thawed single blastocyst transfer.
        Fertil. Steril. 2009; 92: S246
        • Pribenszky C.
        • Nilselid A.M.
        • 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: 511-520
        • Reignier A.
        • Lammers J.
        • Barriere P.
        • Freour T.
        Can time-lapse parameters predict embryo ploidy? A systematic review.
        Reprod. Biomed. Online. 2018; 36: 380-387
        • Rubio C.
        • Bellver J.
        • Rodrigo L.
        • Castillon G.
        • Guillen A.
        • Vidal C.
        • Giles J.
        • Ferrando M.
        • Cabanillas S.
        • Remohi J.
        • Pellicer A.
        • Simon C.
        In vitro fertilization with preimplantation genetic diagnosis for aneuploidies in advanced maternal age: a randomized, controlled study.
        Fertil. Steril. 2017; 107: 1122-1129
        • Sato T.
        • Sugiura-Ogasawara M.
        • Ozawa F.
        • Yamamoto T.
        • Kato T.
        • Kurahashi H.
        • Irahara M.
        Preimplantation genetic testing for aneuploidy: a comparison of live birth rates in patients with recurrent pregnancy loss due to embryonic aneuploidy or recurrent implantation failure.
        Hum. Reprod. 2019; 34: 2340-2348
        • Simopoulou M.
        • Sfakianoudis K.
        • Maziotis E.
        • Tsioulou P.
        • Grigoriadis S.
        • Rapani A.
        • Giannelou P.
        • Asimakopoulou M.
        • Kokkali G.
        • Pantou A.
        • Nikolettos K.
        • Vlahos N.
        • Pantos K.
        PGT-A: who and when? Alpha systematic review and network meta-analysis of RCTs.
        J. Assist. Reprod. Genet. 2021; 38: 1939-1957
        • Tran D.
        • Cooke S.
        • Illingworth P.J.
        • Gardner D.K.
        Deep learning as a predictive tool for fetal heart pregnancy following time-lapse incubation and blastocyst transfer.
        Hum. Reprod. 2019; 34: 1011-1018
        • Ueno S.
        • Berntsen J.
        • Ito M.
        • Uchiyama K.
        • Okimura T.
        • Yabuuchi A.
        • Kato K.
        Pregnancy prediction performance of an annotation-free embryo scoring system on the basis of deep learning after single vitrified-warmed blastocyst transfer: a single-center large cohort retrospective study.
        Fertil. Steril. 2021; 116: 1172-1180
        • Ueno S.
        • Uchiyama K.
        • Kuroda T.
        • Okimura T.
        • Yabuuchi A.
        • Kobayashi T.
        • Kato K.
        Establishment of day 7 blastocyst freezing criteria using blastocyst diameter for single vitrified-warmed blastocyst transfer from live birth outcomes: a single-center, large cohort, retrospectively matched study.
        J. Assist. Reprod. Genet. 2020; 37: 2327-2335
        • Xiong S.
        • Liu J.X.
        • Liu D.Y.
        • Zhu J.H.
        • Hao X.W.
        • Wu L.H.
        • Gao Y.
        • Li J.Y.
        • Huang G.N.
        Prolonged interval time between blastocyst biopsy and vitrification compromised the outcomes in preimplantation genetic testing.
        Zygote. 2021; 29: 276-281
        • Zaninovic N.
        • Irani M.
        • Meseguer M.
        Assessment of embryo morphology and developmental dynamics by time-lapse microscopy: is there a relation to implantation and ploidy?.
        Fertil. Steril. 2017; 108: 722-729

      Biography

      Dr Keiichi Kato, MD, PhD, is General Director at the Kato Ladies Clinic in Tokyo, Japan. Dr Kato earned his MD and PhD from the University of Kanazawa. His main research interests are natural cycle and minimal stimulation IVF to deliver safe, effective and patient-friendly ART.
      Key message
      The iDAScore, KIDScore Day 5 and Gardner criteria for blastocyst assessment are significantly correlated with euploidy. However, prediction of ploidy status is not an accurate diagnosis, and so for diagnostic purposes embryo biopsy should be prioritized.