PREIMPLANTATION EMBRYO DIAGNOSIS-FROM INVASIVE TROPHOBLAST BIOPSY TO ANALYSIS OF CELL-FREE DNA IN CULTURE MEDIUM
DOI:
https://doi.org/10.31435/ijitss.2(50).2026.5771Keywords:
IVF, Embryo Selection, PGT, Non-invasive PGT, Cell-free DNAAbstract
Background: Infertility is a global socio-demographic crisis, affecting approximately 17.5% of the population. Although in vitro fertilization is the therapeutic gold standard, the phenotype-genotype dichotomy reveals that morphologically ideal embryos often harbor genetic abnormalities, leading to implantation failure and miscarriages.
Objective: This review examines the transition from invasive methods to non-invasive preimplantation genetic testing (niPGT), evaluating cell-free DNA (cfDNA) analysis in culture media, integrated with artificial intelligence (AI), and time-lapse imaging. This synergy aims to optimize embryo selection and improve clinical outcomes in assisted reproductive medicine.
Methods: A comprehensive review of literature from PubMed and Google Scholar was conducted. The analysis focused on the mechanisms of cfDNA release, concordance rates between niPGT and trophectoderm biopsy, and the implementation of deep learning algorithms in morphokinetic assessment.
Results: NiPGT offers significant potential for providing a comprehensive genetic profile of the embryo, potentially eliminating mosaicism limitations inherent in traditional biopsies. Current results indicate concordance rates of 65-90% compared to invasive PGT. The integration of AI databases and Vision Transformer models enhances diagnostic accuracy by correlating molecular data with dynamic developmental patterns. However, challenges such as maternal DNA contamination and the lack of global standardization remain key barriers to widespread implementation.
Conclusion: NiPGT marks a new era in personalized reproductive medicine, prioritizing embryo safety and biological integrity. While currently a selection-support tool rather than a full replacement for invasive methods, its synergy with AI offers a safer, more effective path toward the gold standard- the birth of a single healthy child.
References
World Health Organization. (2023, April 4). 1 in 6 people globally affected by infertility. https://www.who.int/news/item/04-04-2023-1-in-6-people-globally-affected-by-infertility
Huang, J., Liao, Y., Yu, M., Zhu, J., Yang, Z., Wu, H., & Zhao, Y. (2025). Global, regional, and national burden of infertility, 1990–2021: Systematic analysis of the Global Burden of Disease Study 2021. Journal of Assisted Reproduction and Genetics, 42(3), 1025–1028. https://doi.org/10.1007/s10815-025-03429-1
Ubaldi, F. M., Cimadomo, D., Vaiarelli, A., Fabozzi, G., Venturella, R., Maggiulli, R., Mazzilli, R., Ferrero, S., Palagiano, A., & Rienzi, L. (2019). Advanced maternal age in IVF: Still a challenge? The present and the future of its treatment. Frontiers in Endocrinology, 10, Article 94. https://doi.org/10.3389/fendo.2019.00094
Shen, D., Yang, S., Qi, C., & Yang, H. (2025). Global, regional, and national prevalence and disability-adjusted life-years for female infertility: Results from a Global Burden of Disease Study, 1990–2019. Gynecologic and Obstetric Investigation, 90(4), 279–295. https://doi.org/10.1159/000542408
Minhas, S., Bettocchi, C., Boeri, L., Capogrosso, P., Carvalho, J., Cilesiz, N. C., Cocci, A., Corona, G., Dimitropoulos, K., Gül, M., Hatzichristodoulou, G., Jones, T. H., Kadioglu, A., Martínez Salamanca, J. I., Milenkovic, U., Modgil, V., Russo, G. I., Serefoglu, E. C., Tharakan, T., ... EAU Working Group on Male Sexual and Reproductive Health. (2021). European Association of Urology guidelines on male sexual and reproductive health: 2021 update on male infertility. European Urology, 80(5), 603–620. https://doi.org/10.1016/j.eururo.2021.08.014
Kiani, Z., Fakari, F. R., Hakimzadeh, A., Hajian, S., Fakari, F. R., & Nasiri, M. (2023). Prevalence of depression in infertile men: A systematic review and meta-analysis. BMC Public Health, 23(1), Article 1972. https://doi.org/10.1186/s12889-023-16865-4
Nixon, B., Schjenken, J. E., Burke, N. D., Skerrett-Byrne, D. A., Hart, H. M., De Iuliis, G. N., Martin, J. H., Lord, T., & Bromfield, E. G. (2023). New horizons in human sperm selection for assisted reproduction. Frontiers in Endocrinology, 14, Article 1145533. https://doi.org/10.3389/fendo.2023.1145533
European IVF Monitoring Consortium (EIM) for the European Society of Human Reproduction and Embryology (ESHRE), Smeenk, J., Wyns, C., De Geyter, C., Kupka, M. S., Bergh, C., Cuevas Saiz, I., De Neubourg, D., Rezabek, K., Tandler-Schneider, A., Rugescu, I., & Goossens, V. (2025). ART in Europe, 2020: Results generated from European registries by ESHRE. Human Reproduction, 40(11), 2038–2055. https://doi.org/10.1093/humrep/deaf179
Munné, S., Kaplan, B., Frattarelli, J. L., Child, T., Nakhuda, G., Shamma, F. N., Silverberg, K., Kalista, T., Handyside, A. H., Katz-Jaffe, M., Wells, D., Gordon, T., Stock-Myer, S., Willman, S., & STAR Study Group. (2019). Preimplantation genetic testing for aneuploidy versus morphology as selection criteria for single frozen-thawed embryo transfer in good-prognosis patients: A multicenter randomized clinical trial. Fertility and Sterility, 112(6), 1071–1079.e7. https://doi.org/10.1016/j.fertnstert.2019.07.1346
Leaver, M., & Wells, D. (2020). Non-invasive preimplantation genetic testing (niPGT): The next revolution in reproductive genetics? Human Reproduction Update, 26(1), 16–42. https://doi.org/10.1093/humupd/dmz033
Glatstein, I., Chavez-Badiola, A., & Curchoe, C. L. (2023). New frontiers in embryo selection. Journal of Assisted Reproduction and Genetics, 40(2), 223–234. https://doi.org/10.1007/s10815-022-02708-5
Lacconi, V., Massimiani, M., Carriero, I., Bianco, C., Ticconi, C., Pavone, V., Alteri, A., Muzii, L., Rago, R., Pisaturo, V., & Campagnolo, L. (2024). When the embryo meets the endometrium: Identifying the features required for successful embryo implantation. International Journal of Molecular Sciences, 25(5), Article 2834. https://doi.org/10.3390/ijms25052834
Shear, M. A., Vaughan, D. A., Modest, A. M., Seidler, E. A., Leung, A. Q., Hacker, M. R., Sakkas, D., & Penzias, A. S. (2020). Blasts from the past: Is morphology useful in PGT-A tested and untested frozen embryo transfers? Reproductive BioMedicine Online, 41(6), 981–989. https://doi.org/10.1016/j.rbmo.2020.07.014
Lundin, K., & Park, H. (2020). Time-lapse technology for embryo culture and selection. Upsala Journal of Medical Sciences, 125(2), 77–84. https://doi.org/10.1080/03009734.2020.1728444
Dimitriadis, I., Zaninovic, N., Badiola, A. C., & Bormann, C. L. (2022). Artificial intelligence in the embryology laboratory: A review. Reproductive BioMedicine Online, 44(3), 435–448. https://doi.org/10.1016/j.rbmo.2021.11.003
Beebeejaun, Y., Nicolaides, K. H., Mania, A., Sarris, I., & Sunkara, S. K. (2024). Preimplantation genetic testing for aneuploidy (PGT-A) in in-vitro fertilisation (IVF) treatment: Study protocol for pilot phase of a randomised controlled trial. Journal of Clinical Medicine, 13(20), Article 6192. https://doi.org/10.3390/jcm13206192
Kim, J. W., Lee, S. Y., Hur, C. Y., Lim, J. H., & Park, C. K. (2024). Clinical outcomes of preimplantation genetic testing for aneuploidy in high-risk patients: A retrospective cohort study. Clinical and Experimental Reproductive Medicine, 51(1), 75–84. https://doi.org/10.5653/cerm.2023.06394
De Rycke, M., & Berckmoes, V. (2020). Preimplantation genetic testing for monogenic disorders. Genes, 11(8), Article 871. https://doi.org/10.3390/genes11080871
Zhang, S., Gao, Y., Wang, X., Li, Q., Tan, J., Liang, B., Gao, M., Wu, J., Ling, X., Liu, J., Teng, X., Li, H., Sun, Y., Huang, W., Tong, X., Lei, C., Li, H., Wang, J., Li, S., Xu, X., ... Chen, Z. J. (2025). Preimplantation genetic testing for structural rearrangements by genome-wide SNP genotyping and haplotype analysis: A prospective multicenter clinical study. EBioMedicine, 111, Article 105514. https://doi.org/10.1016/j.ebiom.2024.105514
Cimadomo, D., Capalbo, A., Ubaldi, F. M., Scarica, C., Palagiano, A., Canipari, R., & Rienzi, L. (2016). The impact of biopsy on human embryo developmental potential during preimplantation genetic diagnosis. BioMed Research International, 2016, Article 7193075. https://doi.org/10.1155/2016/7193075
Heber, M. F., & Ptak, G. E. (2021). The effects of assisted reproduction technologies on metabolic health and disease. Biology of Reproduction, 104(4), 734–744. https://doi.org/10.1093/biolre/ioaa224
Zhang, Y. X., Chen, J. J., Nabu, S., Yeung, Q. S. Y., Li, Y., Tan, J. H., Suksalak, W., Chanchamroen, S., Quangkananurug, W., Wong, P. S., Chung, J. P. W., & Choy, K. W. (2020). The pregnancy outcome of mosaic embryo transfer: A prospective multicenter study and meta-analysis. Genes, 11(9), Article 973. https://doi.org/10.3390/genes11090973
Navarro-Sánchez, L., García-Pascual, C., Rubio, C., & Simón, C. (2022). Non-invasive preimplantation genetic testing for aneuploidies: An update. Reproductive BioMedicine Online, 44(5), 817–828. https://doi.org/10.1016/j.rbmo.2022.01.012
Vera-Rodriguez, M., Diez-Juan, A., Jimenez-Almazan, J., Martinez, S., Navarro, R., Peinado, V., Mercader, A., Meseguer, M., Blesa, D., Moreno, I., Valbuena, D., Rubio, C., & Simon, C. (2018). Origin and composition of cell-free DNA in spent medium from human embryo culture during preimplantation development. Human Reproduction, 33(4), 745–756. https://doi.org/10.1093/humrep/dey028
Chow, J. F. C., Lam, K. K. W., Cheng, H. H. Y., Yeung, W. S. B., Ng, E. H. Y., & Yeung, Q. S. Y. (2024). Optimizing non-invasive preimplantation genetic testing: Investigating culture conditions, sample collection, and IVF treatment for improved non-invasive PGT-A results. Journal of Assisted Reproduction and Genetics, 41(2), 465–472. https://doi.org/10.1007/s10815-023-03015-3
Pan, H. A., Tang, Y. A., Huang, I. N., Wang, C. Y., Chien, C. W., & Sun, H. S. (2025). Optimizing non-invasive PGT-A: A multi-factorial approach for enhanced accuracy and seamless integration into clinical IVF. Reproductive Medicine and Biology, 24(1), Article e12688. https://doi.org/10.1002/rmb2.12688
Tomic, M., Vrtacnik Bokal, E., & Stimpfel, M. (2022). Non-invasive preimplantation genetic testing for aneuploidy and the mystery of genetic material: A review article. International Journal of Molecular Sciences, 23(7), Article 3568. https://doi.org/10.3390/ijms23073568
Voros, C., Darlas, M., Athanasiou, D., Athanasiou, A., Athanasiou, A., Bananis, K., Papadimas, G., Tsimpoukelis, C., Gkirgkinoudis, A., Sapantzoglou, I., Papapanagiotou, I., Vaitsis, D., Koulakmanidis, A. M., Topalis, V., Thomakos, N., Theodora, M., Antsaklis, P., Chatzinikolaou, F., Dahl, H. A., ... Loutradis, D. (2025). Evaluation of the effectiveness and accuracy of non-invasive preimplantation genetic testing (niPGT) compared to invasive embryo biopsy. Biomedicines, 13(8), Article 2010. https://doi.org/10.3390/biomedicines13082010
Yeung, Q. S. Y., Zhang, Y. X., Chung, J. P. W., Lui, W. T., Kwok, Y. K. Y., Gui, B., Kong, G. W. S., Cao, Y., Li, T. C., & Choy, K. W. (2019). A prospective study of non-invasive preimplantation genetic testing for aneuploidies (NiPGT-A) using next-generation sequencing (NGS) on spent culture media (SCM). Journal of Assisted Reproduction and Genetics, 36(8), 1609–1621. https://doi.org/10.1007/s10815-019-01517-7
Iwasa, T., Yamamoto, Y., Noguchi, H., Sato, T., Tanaka, M., Suzuki, K., ... Nakamura, H. (2025). Validation of non-invasive preimplantation genetic testing for aneuploidies (niPGT-A) in a Japanese population: Experience from seven clinics. Journal of Assisted Reproduction and Genetics, 42(10), 3479–3491. https://doi.org/10.1007/s10815-025-03670-8
Orvieto, R., Shimon, C., Rienstein, S., Jonish-Grossman, A., Shani, H., & Aizer, A. (2020). Do human embryos have the ability of self-correction? Reproductive Biology and Endocrinology, 18(1), Article 98. https://doi.org/10.1186/s12958-020-00650-8
Sathyanarayana, S. H., Spracklin, S. B., Deharvengt, S. J., Green, D. C., Instasi, M. D., Gallagher, T. L., Shah, P. S., & Tsongalis, G. J. (2025). Standardized workflow and analytical validation of cell-free DNA extraction for liquid biopsy using a magnetic bead-based cartridge system. Cells, 14(14), Article 1062. https://doi.org/10.3390/cells14141062
Tsai, N. C., Chang, Y. C., Su, Y. R., Lin, Y. C., Weng, P. L., Cheng, Y. H., Li, Y. L., & Lan, K. C. (2022). Validation of non-invasive preimplantation genetic screening using a routine IVF laboratory workflow. Biomedicines, 10(6), Article 1386. https://doi.org/10.3390/biomedicines10061386
Moustakli, E., Zikopoulos, A., Skentou, C., Bouba, I., Dafopoulos, K., & Georgiou, I. (2024). Evolution of minimally invasive and non-invasive preimplantation genetic testing: An overview. Journal of Clinical Medicine, 13(8), Article 2160. https://doi.org/10.3390/jcm13082160
Diakiw, S. M., Hall, J. M. M., VerMilyea, M., Lim, A. Y. X., Quangkananurug, W., Chanchamroen, S., Bankowski, B., Stones, R., Storr, A., Miller, A., Adaniya, G., van Tol, R., Hanson, R., Aizpurua, J., Giardini, L., Johnston, A., Van Nguyen, T., Dakka, M. A., Perugini, D., & Perugini, M. (2022). An artificial intelligence model correlated with morphological and genetic features of blastocyst quality improves ranking of viable embryos. Reproductive BioMedicine Online, 45(6), 1105–1117. https://doi.org/10.1016/j.rbmo.2022.07.018
Moysis, L., Iliadis, L. A., Vergos, G., Sotiroudis, S. P., Boursianis, A. D., Papatheodorou, A., Kokkinidis, K.-I. D., Abdul Matin, M., Sarigiannidis, P., Siniosoglou, I., Argyriou, V., & Goudos, S. K. (2025). Artificial intelligence-empowered embryo selection for IVF applications: A methodological review. Machine Learning and Knowledge Extraction, 7(2), Article 56. https://doi.org/10.3390/make7020056
AlSaad, R., Abusarhan, L., Odeh, N., Abd-Alrazaq, A., Choucair, F., Zegour, R., Ahmed, A., Aziz, S., & Sheikh, J. (2025). Deep learning applications for human embryo assessment using time-lapse imaging: Scoping review. Frontiers in Reproductive Health, 7, Article 1549642. https://doi.org/10.3389/frph.2025.1549642
Luong, T. M., & Le, N. Q. K. (2024). Artificial intelligence in time-lapse system: Advances, applications, and future perspectives in reproductive medicine. Journal of Assisted Reproduction and Genetics, 41(2), 239–252. https://doi.org/10.1007/s10815-023-02973-y
Avidiansyah, M. F., Handayani, N., Aprilliana, T., Afadlal, S., Boediono, A., Polim, A. A., Sirait, B., Suheimi, I., Aditya, M. F., & Sini, I. (2025). Advanced embryo ploidy classification using vision transformers: Integration of sequential time-lapse imaging and undersampling techniques: A retrospective study. Journal of Human Reproductive Sciences, 18(4), 208–217. https://doi.org/10.4103/jhrs.jhrs_111_25
Onthuam, K., Charnpinyo, N., Suthicharoenpanich, K., Engphaiboon, S., Siricharoen, P., Chaichaowarat, R., & Suebthawinkul, C. (2025). Combined input deep learning pipeline for embryo selection for in vitro fertilization using light microscopic images and additional features. Journal of Imaging, 11(1), Article 13. https://doi.org/10.3390/jimaging11010013
Gianaroli, L., Magli, M. C., Gambardella, L., Giusti, A., Grugnetti, C., & Corani, G. (2013). Objective way to support embryo transfer: A probabilistic decision. Human Reproduction, 28(5), 1210–1220. https://doi.org/10.1093/humrep/det030
Gombos, K., Gálik, B., Kalács, K. I., Gödöny, K., Várnagy, Á., Alpár, D., Bódis, J., Gyenesei, A., & Kovács, G. L. (2021). NGS-based application for routine non-invasive pre-implantation genetic assessment in IVF. International Journal of Molecular Sciences, 22(5), Article 2443. https://doi.org/10.3390/ijms22052443
Bellassai, N., Biricik, A., Surdo, M., Bianchi, V., D’Agata, R., Breveglieri, G., Gambari, R., Spinella, F., & Spoto, G. (2025). Non-invasive preimplantation genetic testing: Cell-free DNA detection in embryo culture media using a plasmonic biosensor. Analytical Chemistry, 97(35), 19241–19248. https://doi.org/10.1021/acs.analchem.5c03164
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Copyright (c) 2026 Ewa Bełc, Rafał Borecki, Klaudia Jurkowska, Martyna Stanik, Joanna Górak, Eleonora Y. Mahoney, Agata Reliszka, Aleksandra Stadnik, Adrianna Kępa, Elżbieta Trzyna

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