ABSTRACT
Objective: To determine the effects of sperm deoxyribonucleic acid (DNA) fragmentation at the time of fertilization on in vitro fertilization (IVF) outcomes and genetic diagnosis using next generation sequencing. Design: Prospective double-blinded study. Setting: Private Clinic. Patients: Couples (n = 150). Intervention: In vitro fertilization with preimplantation genetic testing for aneuploidy and sperm DNA fragmentation assay, as in sperm chromatin structure assay the day of retrieval. Main Outcome Measures: Laboratory outcomes are listed in the results section. Statistical analysis was performed using JMP, XYLSTAT, and STATA version 15. Results: The sperm DNA fragmentation index (DFI) in the neat ejaculate did not predict fertilization rate, quality, blastulation, or genetic diagnosis. No statistically significant results were obtained comparing <15% with >15%, <20% with >20%, <30% with >30% except for DFI. No statistically significant differences in oocyte source age or male age were observed. No statistically significant differences comparing <15% with >15%, <20% with >20%, <30% with >30% DFI at the time of standard IVF or intracytoplasmic sperm injection (ICSI) were observed for % euploid, aneuploid, mosaic, blastulation, biopsied, or D5/total biopsied. The DFI of >15% had more good quality D3 embryos than the <15% group, as did the >20% group compared with the <20% group. The ICSI fertilization was significantly higher in all 3 lower percentage groups compared with the higher counterpart. Standard IVF had significantly more blastocysts/fertilized suitable for biopsy and more D5/total number biopsied than ICSI embryos despite no difference in DFI. Conclusions: The DFI at fertilization is correlated with decreased fertilization for ICSI and IVF.
ABSTRACT
RESEARCH QUESTION: Can better methods be developed to evaluate the performance and characteristics of an artificial intelligence model for evaluating the likelihood of clinical pregnancy based on analysis of day-5 blastocyst-stage embryos, such that performance evaluation more closely reflects clinical use in IVF procedures, and correlations with known features of embryo quality are identified? DESIGN: De-identified images were provided retrospectively or collected prospectively by IVF clinics using the artificial intelligence model in clinical practice. A total of 9359 images were provided by 18 IVF clinics across six countries, from 4709 women who underwent IVF between 2011 and 2021. Main outcome measures included clinical pregnancy outcome (fetal heartbeat at first ultrasound scan), embryo morphology score, and/or pre-implantation genetic testing for aneuploidy (PGT-A) results. RESULTS: A positive linear correlation of artificial intelligence scores with pregnancy outcomes was found, and up to a 12.2% reduction in time to pregnancy (TTP) was observed when comparing the artificial intelligence model with standard morphological grading methods using a novel simulated cohort ranking method. Artificial intelligence scores were significantly correlated with known morphological features of embryo quality based on the Gardner score, and with previously unknown morphological features associated with embryo ploidy status, including chromosomal abnormalities indicative of severity when considering embryos for transfer during IVF. CONCLUSION: Improved methods for evaluating artificial intelligence for embryo selection were developed, and advantages of the artificial intelligence model over current grading approaches were highlighted, strongly supporting the use of the artificial intelligence model in a clinical setting.
