An artificial intelligence model correlated with morphological and genetic features of blastocyst quality improves ranking of viable embryos.

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.

Droplet-based digital PCR for non-invasive prenatal genetic diagnosis of α and ß-thalassemia.

Non-invasive prenatal diagnosis (NIPD) of isolated cell-free DNA from maternal plasma has been applied to detect monogenic diseases in the fetus. Droplet digital PCR (ddPCR) is a sensitive and quantitative technique for NIPD. In the present study, the development and evaluation of ddPCR-based assays for common α and ß-thalassemia variants amongst the Asian population was described; specifically, Southeast Asian (SEA) deletion, HbE, and 41/42 (-CTTT). SEA is caused by deletion of a 20 kb region surrounding the α-globin gene, whilst HbE and 41/42 (-CTTT) are caused by point mutations on the ß-globin gene. Cell-free DNA samples from 46 singleton pregnant women who were carriers of these mutations were isolated and quantified using ddPCR with specially designed probes for each target allele. Allelic copy number calculation and likelihood ratio tests were used to classify fetal genotypes. Classification performances were evaluated against ground truth fetal genotypes obtained from conventional amniocentesis. Copy number variation analysis of SEA deletion accurately classified fetal genotypes in 20 out of 22 cases with an area under the receiver operating characteristic curve of 0.98 for detecting Hb Bart's hydrops fetalis. For HbE cases, 10 out of 16 samples were correctly classified, and three were inconclusive. For 41/42 (-CTTT) cases, 2 out of 8 were correctly classified, and four were inconclusive. The correct genotype was not rejected in any inconclusive case and may be resolved with additional ddPCR experiments. These results indicate that ddPCR-based analysis of maternal plasma can become an accurate and effective NIPD for SEA deletion α-(0) thalassemia. Although the performance of ddPCR on HbE and 41/42 (-CTTT) mutations were not sufficient for clinical application, these results may serve as a foundation for future works in this field.

The Pregnancy Outcome of Mosaic Embryo Transfer: A Prospective Multicenter Study and Meta-Analysis.

Chromosomal mosaicism is at high occurrence in early developmental-stage embryos, but much lower in those at prenatal stage. Recent studies provided evidence on the viability of mosaic embryos by reporting pregnancy outcomes. Expanded research is warranted to evaluate its clinical significance. This is a multi-center prospective cohort study on 137 mosaic, 476 euploid and 835 non-preimplantation genetic testing (non-PGT) embryos from three in vitro fertilization (IVF) providers of three countries in Asia, applying the same preimplantation genetic testing for aneuploidies (PGT-A) reporting criteria. Mosaic embryo transfers (METs) resulted in a significantly lower clinical pregnancy rate (40.1% versus 59.0% versus 48.4%), lower ongoing/live birth rate (27.1% versus 47.0% versus 35.1%) and higher miscarriage rate (33.3% versus 20.5% versus 27.4%) than euploid and non-PGT transfers, respectively. Pregnancy losses after METs were different between embryos carrying numerical and segmental chromosomal abnormalities (p = 0.04). Our meta-analysis concluded that METs gave rise to pregnancies but were associated with a reduced ongoing/live birth rate and a higher miscarriage rate. All 37 MET live births were confirmed viable, among which 8 completed prenatal genetic testing with normal results. Longitudinal investigation on one MET pregnancy evidenced the aneuploidy depletion hypothesis. This is the first multi-center prospective study reporting a full MET pregnancy outcome with complementary information from prenatal genetic testing as compared to euploid and non-PGT cohorts.

Detection and quantitation of chromosomal mosaicism in human blastocysts using copy number variation sequencing.

OBJECTIVE: Currently, our understanding of the nature and reproductive potential of blastocysts associated with trophectoderm (TE) lineage chromosomal mosaicism is limited. The objective of this study was to first validate copy number variation sequencing (CNV-Seq) for measuring the level of mosaicism and second, examine the nature and level of mosaicism in TE biopsies of patient's blastocysts. METHOD: TE biopy samples were analysed by array comparative genomic hybridization (CGH) and CNV-Seq to discriminate between euploid, aneuploid and mosaic blastocysts. RESULTS: Using artificial models of TE mosaicism for five different chromosomes, CNV-Seq accurately and reproducibly quantitated mosaicism at levels of 50% and 20%. In a comparative 24-chromosome study of 49 blastocysts by array CGH and CNV-Seq, 43 blastocysts (87.8%) had a concordant diagnosis and 6 blastocysts (12.2%) were discordant. The discordance was attributed to low to medium levels of chromosomal mosaicism (30-70%) not detected by array CGH. In an expanded study of 399 blastocysts using CNV-Seq as the sole diagnostic method, the proportion of diploid-aneuploid mosaics (34, 8.5%) was significantly higher than aneuploid mosaics (18, 4.5%) (p < 0.02). CONCLUSION: Mosaicism is a significant chromosomal abnormality associated with the TE lineage of human blastocysts that can be reliably and accurately detected by CNV-Seq.