A Narrative Review on the Sperm Selection Methods in Assisted Reproductive Technology: Out with the New, the Old Is Better?

Male infertility, accounting for nearly half of infertility cases worldwide, has spurred significant research into its causes, diagnosis, and treatment strategies. Genetic abnormalities, social causes, environmental exposures, lifestyle, and further health conditions are key contributors. Essential to improving the outcomes of ART is, among other things, the selection of high-quality sperm, which requires methods that assess sperm motility, morphology, DNA integrity, and oxidative stress levels. Traditional techniques such as semen analysis, swim-up, and density gradient centrifugation (DGC) are still widely used, but there is ongoing discussion regarding the limitations in detecting DNA damage and oxidative stress. Advanced methods like magnetic-activated cell sorting (MACS) and microfluidic sorting have emerged as more precise tools for selecting sperm with better genetic integrity, although they face challenges in terms of their standardization, cost, and clinical adoption. Emerging technologies such as artificial intelligence (AI) and Raman spectroscopy offer the potential for more automated, accurate sperm selection, minimizing human error and variability. However, the integration of these methods into clinical practice requires further validation through large-scale studies, including assessments of their long-term safety and cost-effectiveness. Future research should focus on refining sperm selection techniques, tailoring them to personalized infertility approaches, and addressing the gaps in the evidence to improve ART outcomes and patient care.