In-vitro development of embryos derived from vitrified-warmed oocytes is delayed compared with embryos derived from fresh oocytes : a time-lapse sibling oocyte study

Research question: Is there a difference in blastocyst formation between fresh and vitrified-warmed sibling oocytes and can this difference be attributed to changes in embryo morphokinetics? Design: Between February 2016 and December 2017, 472 metaphase II (MI1) oocytes in 67 donor-recipient cycles from 27 different healthy anonymous oocyte donors were allocated for fresh transfer (FSHO) (n = 220) to a synchronous recipient (n = 36) or vitrified (VITO) (n = 252) to be warmed and transferred to another recipient (n = 31). Embryos derived from the FSHO and their sibling VITO were analysed for morphokinetic development using time-lapse imaging, blastocyst formation and clinical outcome. Results: Time-lapse analysis showed an overall delay in cleavage rate from the time of pronuclei disappearance up to the time of blastulation in the VITO compared with their sibling FSHO. Twelve morphokinetic variables were significantly different between the groups. On Day 5 significantly more FSHO embryos developed to blastocyst (expansion 1-6) and reached the full blastocyst stage (expansion 3-6) compared with the VITO embryos [53.2% (84/158) versus 40.0% (64/160); P = 0.0244 and 48.1% (76/158) versus 31.3% (50/160); P = 0.0028, respectively]. The embryo utilization rate was similar in both groups at the time of cryopreservation; 51.3% (FSHO) versus 45.0% (VITO) (P = 0.3124). The pregnancy rate per cycle was 47.2% (17/36) in FSHO patients and 48.4% (15/31) in VITO patients (P = 1). Limitations in this study: non-randomized, small study size and not powered to detect differences in clinical outcomes. Conclusions: Timing of development is altered and blastocyst formation is delayed in embryos derived from vitrified-warmed donor oocytes compared with their fresh sibling counterparts. Although preliminary results suggest that the clinical impact of this delay may be limited, this needs further investigation in larger randomized studies

Efficiency of polarized microscopy as a predictive tool for human oocyte quality

BACKGROUND: Conflicting results have been reported regarding the use of polarized microscopy as a predictive tool for human oocyte quality. METHODS: Oocytes from 121 ICSI cycles were analysed with polarized microscopy. Both qualitative (spindle presence) and quantitative (retardance) data were correlated to the key assisted reproduction technology outcome parameters. Second, polarized microscopy was applied on in vitro matured (IVM) oocytes from germinal vesicle oocytes that matured after 24 or 48 h and from metaphase I oocytes matured after 3 or 24 h. These data were correlated with confocal analysis of spindle-chromosome complex. RESULTS: Spindles were detected in 82% of in vivo matured oocytes and in 64% adjacent to the first polar body (PB). Fertilization rate was higher in oocytes with a visible spindle (P = 0.0002). In patients aged over 35 years, the percentage of a visible spindle and mean spindle retardance was lower than in younger patients (P < 0.03). A higher number of spindles were located adjacent to the first PB in IVM matured oocytes (94%) versus in vivo matured oocytes (P < 0.0001). Confocal imaging revealed that spindle absent IVM metaphase II (MII) oocytes had a higher degree of aberrant spindle and chromosomal configurations versus IVM MII oocytes with a visible spindle (P = 0.002). CONCLUSIONS: Oocytes with absent spindles were associated with lower fertilization rates and advanced female age. Other important outcome parameters (embryo quality, pregnancy rates) were not correlated to spindle nor zona inner layer analysis. Interestingly, confocal imaging showed that polarized microscopy might be used as a qualitative predictive tool of human oocyte quality but no correlation could be demonstrated with quantitative polarized microscopy

Efficiency of assisted oocyte activation as a solution for failed intracytoplasmic sperm injection

Failed fertilization after intracytoplasmic sperm injection (ICSI) can occur due to an oocyte activation defect. In these cases assisted oocyte activation (AOA) may help but efficiency is still unknown. Prior to AOA, the mouse oocyte activation test (MOAT) can be carried out by injecting human spermatozoa into mouse oocytes to evaluate their activating capacity. According to the MOAT activation percentage achieved. patients were classified into three groups: 0-20% (16 patients) 20-85% (seven patients) 85-100% (seven patients). For AOA, CaCl2 was injected together with spermatozoa followed by a double Ca2+ ionophore treatment. The fertilization rates before application of AOA in 50 cycles were 6%. 22% and 14% in. respectively, groups 1, 2 and 3 without any pregnancy. Fertilization and pregnancy rates after AOA in 61 cycles were significantly increased to 75% and 34% for group 1, 73% and 43% for group 2, and 75% and 17% for group 3 (P < 0.0001 and P < 0.004, respectively). Application of AOA results in normal fertilization and pregnancy rates in patients whose spermatozoa show deficient activation. When MOAT reveals no activation deficiency in spermatozoa, AOA still allows for high fertilization and acceptable pregnancy rates. The obstetric and neonatal outcomes after AOA were normal as no malformations were observed

A methodological validation of an easy one-step swim-out semen preparation procedure for selecting DNA fragmentation-free spermatozoa for ICSI

The main purpose of this methodological paper was to describe a recently designed one-step ICSI semen preparation swim-out method (called swim-ICSI) and to compare its efficacy with our conventional two-step swim-out method for the selection of motile spermatozoa for ICSI with minimal DNA damage. In this observational cohort study, 42 fresh ejaculate sperm samples for ICSI were included to compare the new swim-ICSI with the conventional swim-out. In a sub-analysis (n = 20), both in-house designed ICSI preparation methods were compared with a commercial magnetic-activated cell sorting test (MACS (R)). Sperm DNA fragmentation (SDF), using Halosperm (R), was determined at different time points during sperm preparation: on the native sample (a), after density gradient centrifugation (DG) (b), on the motile (A + B) spermatozoa selected with conventional swim-out post-DG (c) and selected with swim-ICSI method post-DG (d). For a subgroup (n = 20), SDF was also calculated after MACS (e). The mean SDF significantly reduced after EACH preparation step and reduced to almost zero in the recovered A + B spermatozoa when the semen prepared with DG was further processed for ICSI (swim-ICSI vs. swim-out, p = .001). In conclusion, the optimised one-step and fine-tuned swim-ICSI technique shows the possibility to select a population of spermatozoa with almost zero SDF to be used in ICSI treatments

High success rate of assisted oocyte activation after a diagnostic mouse oocyte activation test in couples with low or failed fertilization after ICSI

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Machine learning for prediction of euploidy in human embryos : in search of the best-performing model and predictive features

Objective: To assess the best-performing machine learning (ML) model and features to predict euploidy in human embryos. Design: Retrospective cohort analysis. Setting: Department for reproductive medicine in a university hospital. Patient(s): One hundred twenty-eight infertile couples treated between January 2016 and December 2019. Demographic and clinical data and embryonic developmental and morphokinetic data from 539 embryos (45% euploid, 55% aneuploid) were analyzed. Intervention(s): Random forest classifier (RFC), scikit-learn gradient boosting classifier, support vector machine, multivariate logistic regression, and naive Bayes ML models were trained and used in 9 databases containing either 26 morphokinetic features (as absolute [A1] or interim [A2] times or combined [A3]) alone or plus 19 standard development features [B1, B2, and B3] with and without 40 demographic and clinical characteristics [C1, C2, and C3]. Feature selection and model retraining were executed for the bestperforming combination of model and dataset. Main Outcome Measure(s): The main outcome measures were overall accuracy, precision, recall or sensitivity, F1 score (the weighted average of precision and recall), and area under the receiver operating characteristic curve (AUC) of ML models for each dataset. The secondary outcome measure was ranking of feature importance for the best-performing combination of model and dataset. Result(s): The RFC model had the highest accuracy (71%) and AUC (0.75) when trained and used on dataset C1. The precision, recall or sensitivity, F1 score, and AUC were 66%, 86%, 75%, and 0.75, respectively. The accuracy, recall or sensitivity, and F1 score increased to 72%, 88%, and 76%, respectively, after feature selection and retraining. Morphokinetic features had the highest relative predictive weight. Conclusion(s): The RFC model can predict euploidy with an acceptable accuracy (>70%) using a dataset including embryos' morphokinetics and standard embryonic development and subjects' demographic and clinical features. ((C) 2021 by American Society for Reproductive Medicine.) El resumen esta disponible en Espanol al final del articulo