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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.
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Bełc et al. (2026) studied this question.
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