Using artificial intelligence to determine embryos with the best chance of producing successful pregnancies through in-vitro fertilisation (IVF) would increase the procedure’s rate of success, according to a study.
The research, presented today at the 33rd Annual Meeting of the European Society of Reproduction and Embryology (ESHRE) in Geneva, found that using AI to standardise the selection of ‘good quality’ embryos would make viable embryo selection more accurate and so increase the chances of a successful pregnancy.
A popular choice for couples with fertility problems, IVF involves removing eggs from the woman’s ovaries, fertilising them with sperm to produce embryos and then implanting the most viable back into the womb, where they – all being well – will develop as normal into a healthy baby.
As part of this, embryologists determine which embryos are most viable for implantation, however despite this selection process, between 30 and 60% fail to implant successfully. Part of the reason for this is patient age, but there is also the fact that different embryologists will make different calls about whether an embryo is viable.
“The issue is that morphological grading by humans leads to wide inter and intra-operator variation,” said investigator Professor José Celso Rocha, from São Paulo State University, Brazil. In other words, embryologists’ assessment of an embryo’s shape and development results in significantly different conclusions depending on who is doing the assessing. And it is this variation that Rocha believes AI can help with.
“To classify images automatically will increase the predictive value of our embryo assessment,” he said. “By increasing objectivity and repeatability in embryo assessment, we can improve the accuracy of diagnosing embryo viability. Clinics can use this information as ‘artificial intelligence’ to customise treatment strategies and better predict a patient’s chance of pregnancy.”
The study which is the focus of this argument involved bovine embryos, with 482 seven-day-old embryos used to ‘train’ the AI system to recognise viable embryos from non-viable ones. The system assessed the embryos against 36 variables to determine viability, resulting in an accuracy of 76% – an improvement on conventional methods – and increased general consistency.
Now the research has moved onto human embryos, and although it is in the early stages of development, it is hoped that it will produce a highly repeatable system that will make future embryo classification far more consistent.
However, while AI might be poised to take over a part of the IVF process, it is human expertise that it will draw from.
“The artificial intelligence system must be based on learning from a human being,” said Rocha. “That is, the experienced embryologists who set the standards of assessment to train the system.”