For many people who are struggling to conceive, in-vitro fertilization (IVF) can offer a life-changing solution. But the average success rate for IVF is only about 30 percent. Investigators from Brigham and Women’s Hospital and Massachusetts General Hospital are developing an artificial intelligence system with the goal of improving IVF success by helping embryologists objectively select embryos most likely to result in a healthy birth. Using thousands of embryo image examples and deep-learning artificial intelligence (AI), the team developed a system that was able to differentiate and identify embryos with the highest potential for success significantly better than 15 experienced embryologists from five different fertility centers across the United States. Results of their study are published in eLife.
A major challenge in the field is deciding on the embryos that need to be transferred during IVF. This AI system has tremendous potential to improve clinical decision making and access to care.
Currently, the tools available to embryologists are limited and expensive, and most embryologists must rely on their observational skills and expertise. The researchers are developing an assistive tool that can evaluate images captured using microscopes traditionally available at fertility centers.
The team trained the AI system using images of embryos captured at 113 hours post-insemination. Among 742 embryos, the AI system was 90 percent accurate in choosing the most high-quality embryos. The investigators further assessed the AI system’s ability to distinguish among high-quality embryos with the normal number of human chromosomes and compared the system’s performance to that of trained embryologists. The system performed with an accuracy of approximately 75 percent while the embryologists performed with an average accuracy of 67 percent.
The authors note that in its current stage, this system is intended to act only as an assistive tool for embryologists to make judgments during embryo selection.
News Source: Eurekalert
