Beyond appearance: Can morphologically low-grade euploid blastocysts yield successful pregnancies?

Purpose: The primary objective of this investigation is to evaluate how morphological quality affects the pregnancy outcomes in euploid embryos determined by preimplantation genetic testing for aneuploidies (PGT-A). Concurrently, as a secondary objective, we aim to identify which specific aspects of morphological evaluation exert the most significant impact on these outcomes. Methods: A retrospective analysis of 451 single euploid embryo transfer cycles at our clinic was conducted. Embryos were evaluated based on the degree of blastocyst expansion, inner cell mass (ICM), trophectoderm (TE) morphology, and the day of blastocyst vitrification. Outcomes between morphologically low-grade and high-grade embryos were compared. Additionally, the study analyzed which morphological factors most influenced pregnancy outcomes. Results: Pregnancy outcomes were significantly lower in morphologically low-grade blastocysts compared to high-grade ones. Among the morphological evaluations, the ICM assessment was significantly associated with the live birth rate. Conclusion: Our study indicates that the morphological quality of euploid embryos, particularly the evaluation of the ICM, plays a crucial role in IVF-ET success.

Development of an AI-based support system for controlled ovarian stimulation.

Purpose: Controlled ovarian stimulation (COS) is vital for IVF. We have developed an AI system to support the implementation of COS protocols in our clinical group. Methods: We developed two models as AI algorithms of the AI system. One was the oocyte retrieval decision model, to determine the timing of oocyte retrieval, and the other was the prescription inference model, to provide a prescription similar to that of an expert physician. Data was obtained from IVF treatment records from the In Vitro Fertilization (IVF) management system at the Asada Ladies Clinic, and these models were trained with this data. Results: The oocyte retrieval decision model achieved superior sensitivity and specificity with 0.964 area under the curve (AUC). The prescription inference model achieved an AUC value of 0.948. Four models, namely the hCG prediction model, the hMG prediction model, the Cetrorelix prediction model, and the Estradiol prediction model included in the prescription inference model, achieved AUC values of 0.914, 0.937, 0.966, and 0.976, respectively. Conclusion: The AI algorithm achieved high accuracy and was confirmed to be useful. The AI system has now been implemented as a COS tool in our clinical group for self-funded treatments.

Gonadotropin levels at the start of ovarian stimulation predict normal fertilization after hCG re-trigger in GnRH antagonist cycles.

PURPOSE: To assess the appropriateness of human chorionic gonadotropin (hCG) re-trigger in poor responders to gonadotropin-releasing hormone agonist (GnRHa) trigger in controlled ovarian stimulation (COS) cycles. METHODS: The 2251 cycles in 2251 patients triggered with GnRHa for oocyte stimulation, with or without requiring hCG re-trigger between 2013 and 2018, were retrospectively analyzed to compare gonadotropin levels at the start of COS and the rate of normal fertilization between the re-trigger and non-re-trigger group. Furthermore, patients in the re-trigger group were stratified by the rate of normal fertilization (good: ≥60% or poor: <60%) to compare patient demographics, hormone profiles, and clinical outcome between the subgroups. RESULTS: In the re-trigger group, FSH and LH levels at the start of COS were significantly lower in the good fertilization group than in the poor fertilization group (P < .01). Receiver operating characteristic curves identified cutoff values of the FSH and LH levels of 1.30 and 0.35 mIU/mL, respectively, for predicting ≥60% normal fertilization. CONCLUSION: Gonadotropin levels at the start of COS are predictors of response to GnRHa trigger and hCG re-trigger necessity, and may serve as indicators to help clinicians appropriately choose hCG re-trigger rather than abandoning the cycles or continuing the first oocyte aspiration attempt.

Digital clock drawing test reflects visuospatial ability of older drivers.

Objectives: To keep older drivers safe, it is necessary to assess their fitness to drive. We developed a touch screen-based digital Clock Drawing Test (dCDT) and examined the relationship between the dCDT scores and on-road driving performance of older drivers in a community-setting. Methods: One hundred and forty-one community-dwelling older drivers (range; 64-88 years old) who participated in this study were included in the analysis. Participants completed the dCDT, the Mini-Mental State Examination-Japanese (MMSE-J), and an on-road driving assessment. We examined the relationship between dCDT scores using the method by Rouleau et al. (maximum 10 points) and the on-road driving performance based on a driving assessment system originally developed by Nagoya University. Results: Multiple regression analyses showed that errors in the driving test were associated with dCDT score for the items "confirmation," "turning left" and "maintains driving lane position". Discussion: This study confirmed the relationship between the dCDT score and driving errors, such as confirmation, turning left and maintaining driving lane position. The increase in these errors indicates a decline in visuospatial ability while driving. The dCDT score may reflect older drivers' visuospatial abilities while driving.

Search for morphological indicators that predict implantation by principal component analysis using images of blastocyst.

Background: Although the current evaluation of human blastocysts is based on the Gardner criteria, there may be other notable parameters. The purpose of our study was to clarify whether the morphology of blastocysts has notable indicators other than the Gardner criteria. Methods: To find such indicators, we compared blastocysts that showed elevated human chorionic gonadotropin (hCG) levels after transplantation (hCG-positive group; n = 129) and those that did not (hCG-negative group; n = 105) using principal component analysis of pixel brightness of the images. Results: The comparison revealed that the hCG-positive group had grainy morphology and the hCG-negative group had non-grainy morphology. Classification of the blastocysts by this indicator did not make a difference in Gardner score. Interestingly, all embryos with ≥20% fragmentation were non-grainy. The visual classification based on this analysis was significantly more accurate than the prediction of implantation using the Gardner score ≥3BB. As graininess can be used in combination with the Gardner score, this indicator will enhance current reproductive technologies.