A clinically useful simplified blastocyst grading system.

The aim of this study was to investigate whether a new simplified blastocyst grading system (A: fully expanded, clear inner cell mass, cohesive trophectoderm; B: not yet expanded, clear inner cell mass, cohesive trophectoderm; C: small inner cell mass ± irregular trophectoderm ± excluded/degenerate cells) was clinically useful. All day-5 single embryo transfers between 15 June 2009 and 29 June 2012 were reviewed. Implantation, clinical pregnancy and live birth rates were related to embryo quality. Five embryologists were asked to grade and decide the clinical fate of 80 images of day-5 embryos on two occasions 4-6 weeks apart. Implantation, clinical pregnancy and live birth rates decreased with deteriorating embryo quality. A highly significant (P < 0.01) difference was observed between the groups. Inter-observer agreement was substantial for grade allocation (K = 0.63) and clinical decision-making (K = 0.66). Intra-observer agreement ranged from substantial (K = 0.71) to almost perfect (K = 0.88) for grade allocation, and was almost perfect for clinical fate determination (K ≥ 0.84). This grading system is quick and easy to use, effectively predicts IVF outcome and has levels of agreement similar to, if not better than, those associated with more complex grading systems.

Deep learning versus manual morphology-based embryo selection in IVF: a randomized, double-blind noninferiority trial.

To assess the value of deep learning in selecting the optimal embryo for in vitro fertilization, a multicenter, randomized, double-blind, noninferiority parallel-group trial was conducted across 14 in vitro fertilization clinics in Australia and Europe. Women under 42 years of age with at least two early-stage blastocysts on day 5 were randomized to either the control arm, using standard morphological assessment, or the study arm, employing a deep learning algorithm, intelligent Data Analysis Score (iDAScore), for embryo selection. The primary endpoint was a clinical pregnancy rate with a noninferiority margin of 5%. The trial included 1,066 patients (533 in the iDAScore group and 533 in the morphology group). The iDAScore group exhibited a clinical pregnancy rate of 46.5% (248 of 533 patients), compared to 48.2% (257 of 533 patients) in the morphology arm (risk difference -1.7%; 95% confidence interval -7.7, 4.3; P = 0.62). This study was not able to demonstrate noninferiority of deep learning for clinical pregnancy rate when compared to standard morphology and a predefined prioritization scheme. Australian New Zealand Clinical Trials Registry (ANZCTR) registration: 379161 .

Temporal validation of a simplified blastocyst grading system.

We have recently established the clinical effectiveness and credibility of a simplified blastocyst grading system by demonstrating its prognostic potential and the inter- and intra-observer variability associated with it. To be considered clinically useful, however, the grading system also needs to be accurate (i.e. well calibrated with good discriminative ability). This study prospectively evaluates the performance of the grading system on subsequent patients from the same IVF unit in an attempt to temporally validate the model. All day 5 single embryo transfers between 1st July 2012 and 30th June 2014 were included in the study. The observed implantation, clinical pregnancy and live birth rates according to grade of embryo transferred were compared to the expected rates as predicted by the development data set and the statistical significance of any differences between the two were calculated using the Chi-square test. A total of 435 single embryo transfers were included. For each grade of embryo transferred, there was generally no significant difference between the observed and expected frequencies of implantation, clinical pregnancy and live birth suggesting that the simplified blastocyst grading system is accurate and temporal validation has been satisfactorily demonstrated. It is now necessary to externally validate the grading system to prove generality before further dissemination.