Are tri-pronuclear embryos that show two normal-sized pronuclei and additional smaller pronuclei useful for embryo transfer?

Purpose: This study aimed to analyze whether tripronuclear (3PN) zygotes, with two normal-sized PNs and an additional smaller PN (2.1PN), can be used for embryo transfer. Methods: A retrospective embryo cohort study was conducted on 695 patients who underwent intracytoplasmic sperm injection treatment. Blastocyst formation rates were compared between 2.1PN and 2PN zygotes and PGT-A analysis was performed on 15 blastocysts derived from 2.1PN zygotes. Results: Blastocyst formation rates were comparable between 2.1PN (43.8%) and 2PN zygotes (54.8%; p = 0.212). The rates of blastocysts with good morphology derived from 2.1 PN and 2PN zygotes were 18.8% and 25.5%, respectively. No significant differences were detected (p = 0.383). All of the analyzed blastocysts were diploid; however, 13 of these were found to be aneuploid, with a further two being mosaic. Conclusion: Our results suggest that 2.1PN embryos can reach blastocyst stage. These blastocysts were diploid, however, predominantly aneuploid, and therefore could not be used for embryo transfer.

Clinical outcomes of MII oocytes with refractile bodies in patients undergoing ICSI and single frozen embryo transfer.

PURPOSE: This study aimed to analyze whether the presence of refractile bodies (RFs) negatively affects fertilization, embryo development, and/or implantation rates following intracytoplasmic sperm injection (ICSI). METHODS: This retrospective embryo cohort study involved a total of 272 patients undergoing ICSI treatment of blastocyst cryopreservation. RESULTS: In the study, no significant differences were found regarding 2PN formation rates between RF(+) (76.5%) and RF(-) oocytes (77.2%). However, the blastocyst formation rate on Day 5 in RF(+) oocytes was 45.8%, which was significantly lower than that of 52.2% in RF(-) oocytes (aOR 0.74, 95% CI 0.59-0.93, P = .011). Implantation rates were also significantly lower in RF(+) oocytes (24.2%) as compared to RF(-) oocytes (42.2%) (aOR 0.46, 95% CI 0.26-0.78, P = .005). Furthermore, the implantation rate of RF(+) oocytes (28.6%), when high-quality blastocysts were transferred, was significantly lower than that of RF(-) oocytes (46.1%) (aOR 0.50, 95% CI 0.25-0.96, P = .043). CONCLUSION: Our results suggest that oocytes with the presence of RFs have a lower potential for blastocyst development. Even when they develop into high-quality blastocysts, the chances of implantation are reduced.

Feasibility of predicting live birth by combining conventional embryo evaluation with artificial intelligence applied to a blastocyst image in patients classified by age.

PURPOSE: To identify the multivariate logistic regression in a combination (combination method) involving artificial intelligence (AI) classifiers in images of blastocysts along with a conventional embryo evaluation (CEE) to predict the probability of accomplishing a live birth in patients classified by maternal age. METHODS: Retrospectively, a total of 5691 blastocysts were enrolled. Images captured 115 hours or 139 hours if not yet sufficiently large after insemination were classified according to age as follows: <35, 35-37, 38-39, 40-41, and ≥42 years old. The classifiers for each category were created by using convolutional neural networks associated with deep learning. Next, the feasibility of a method combining AI with multivariate logistic model functions by CEE was investigated. RESULTS: The values of the area under the curve (AUC) and the accuracies to predict live birth achieved by the CEE/AI/combination methods were 0.651/0.634/0.655, 0.697/0.688/0.723, 0.771/0.728/0.791, 0.788/0.743/0.806 and 0.820/0.837/0.888, and 0.631/0.647/0.616, 0.687/0.675/0.671, 0.725/0.697/0.732, 0.714/0.776/0.801, and 0.910/0.866/0.784 for age categories of <35, 35-37, 38-39, 40-41, and ≥42 years old, respectively. CONCLUSIONS: Though there were mostly no significant differences regarding the AUC and the sensitivity plus specificity in all age categories, the combination method seemed to be the best.

A higher incidence of smooth endoplasmic reticulum clusters with aromatase inhibitors.

PURPOSE: This study aimed to analyze whether a regimen of aromatase inhibitor (AI) could reduce the occurrence of smooth endoplasmic reticulum clusters (sERCs) in oocytes. METHODS: The AI and the clomiphene citrate (CC) regimens were compared, regarding the sERC (+) rates and the serum estradiol and progesterone levels on the date of hCG administration, and the duration of AI, CC, and hMG administration. RESULTS: The occurrence of sERCs in oocytes from patients treated with AI was significantly higher than that in oocytes from those treated with CC. Both the serum estradiol and progesterone levels were found to be significantly higher in sERC (+) than in sERC (-) cycles. With regard to the CC cycles, no significant differences were detected. The duration of AI and hMG administration was longer for sERC (+) than for sERC (-) cycles. CONCLUSION: As AI did not reduce the occurrence of sERCs, the elevation of estradiol may not be the cause of sERC occurrence but a consequence. Considering the higher levels of progesterone and longer duration of hMG in sERC (+) cycles, the negative effects of premature luteinization, which frequently occur with the AI protocol, should be investigated further.

Feasibility of artificial intelligence for predicting live birth without aneuploidy from a blastocyst image.

PURPOSE: To make the artificial intelligence (AI) classifiers of the image of the blastocyst implanted later in order to predict the probability of achieving live birth. METHODS: A system for using the machine learning approaches, which are logistic regression, naive Bayes, nearest neighbors, random forest, neural network, and support vector machine, of artificial intelligence to predict the probability of live birth from a blastocyst image was developed. Eighty images of blastocysts that led to live births and 80 images of blastocysts that led to aneuploid miscarriages were used to create an AI-based method with 5-fold cross-validation retrospectively for classifying embryos. RESULTS: The logistic regression method showed the best results. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were 0.65, 0.60, 0.70, 0.67, and 0.64, respectively. Area under the curve was 0.65 ± 0.04 (mean ± SE). Estimated probability of belonging to the live birth category was found significantly related to the probability of live birth (P < 0.005). CONCLUSIONS: Classifiers using artificial intelligence applied toward a blastocyst image have a potential to show the probability of live birth being the outcome.

Feasibility of deep learning for predicting live birth from a blastocyst image in patients classified by age.

PURPOSE: To identify artificial intelligence (AI) classifiers in images of blastocysts to predict the probability of achieving a live birth in patients classified by age. Results are compared to those obtained by conventional embryo (CE) evaluation. METHODS: A total of 5691 blastocysts were retrospectively enrolled. Images captured 115 hours after insemination (or 139 hours if not yet large enough) were classified according to maternal age as follows: <35, 35-37, 38-39, 40-41, and ≥42 years. The classifiers for each category and a classifier for all ages were related to convolutional neural networks associated with deep learning. Then, the live birth functions predicted by the AI and the multivariate logistic model functions predicted by CE were tested. The feasibility of the AI was investigated. RESULTS: The accuracies of AI/CE for predicting live birth were 0.64/0.61, 0.71/0.70, 0.78/0.77, 0.81/0.83, 0.88/0.94, and 0.72/0.74 for the age categories <35, 35-37, 38-39, 40-41, and ≥42 years and all ages, respectively. The sum value of the sensitivity and specificity revealed that AI performed better than CE (P = 0.01). CONCLUSIONS: AI classifiers categorized by age can predict the probability of live birth from an image of the blastocyst and produced better results than were achieved using CE.

Potential role of hCG in apoptosis of human luteinized granulosa cells.

The corpus luteum (CL) forms after ovulation and acts as a temporary endocrine gland that produces progesterone (P4), a hormone that is essential for implantation and maintenance of pregnancy in mammals. In pregnant women, human chorionic gonadotropin (hCG) secreted by the conceptus prevents luteolysis. hCG also increases the survival of cultured human luteinized granulosa cells (hLGCs). To clarify the maintenance mechanism of the human CL, we investigated the effects of hCG and P4 receptor antagonists, onapristone (OP) and RU486, on the viability of hLGCs. With the patients' consent, hLGCs were isolated from follicular aspirates for in vitro fertilization. The cells were cultured with hCG (0.1, 1, 10, 100 IU/ml), OP (10, 25, 50, 100 µM), RU486 (100 µM), P4 (1, 10, 25, 50 µM) or some combination of the four for 24 h. Cell viability was significantly increased by hCG (100 IU/ml) and significantly decreased by OP (100 µM) compared with the control. Cells treated with hCG and OP together were significantly less viable than the control and OP-treated cells. The combined treatment also significantly increased CASP3 activity and cleaved CASP3 protein expression. Furthermore, P4 addition reversed the reduction in cell viability caused by the combination of hCG and OP treatment. The overall findings suggest that hCG cooperates with P4 to increase survival of hLGCs and to induce apoptosis when P4 action supported by hCG is attenuated in the human CL.

Improved development of mouse and human embryos using a tilting embryo culture system.

Mammalian embryos experience not only hormonal but also mechanical stimuli, such as shear stress, compression and friction force in the Fallopian tube before nidation. In order to apply mechanical stimuli to embryos in a conventional IVF culture system, the tilting embryo culture system (TECS) was developed. The observed embryo images from the TECS suggest that the velocities and shear stresses of TECS embryos are similar to those experienced in the oviduct. Use of TECS enhanced the development rate to the blastocyst stage and significantly increased the cell number of mouse blastocysts (P<0.05). Although not statistically significant, human thawed embryos showed slight improvement in development to the blastocyst stage following culture in TECS compared with static controls. Rates of blastocyst formation following culture in TECS were significantly improved in low-quality embryos and those embryos cultured under suboptimal conditions (P<0.05). The TECS is proposed as a promising approach to improve embryo development and blastocyst formation by exposing embryos to mechanical stimuli similar to those in the Fallopian tube.

Blastocyst quality scoring based on morphologic grading correlates with cell number.

Blastocyst quality score (BQS), first reported by Rehman et al., is a numerical blastocyst-morphology grading system based on the criteria established by Gardner and Schoolcraft. We demonstrate a positive correlation between the calculated BQS score and cell number by staining thawed human embryos and suggest that BQS can be applied to evaluate culture systems clinically.