BELA's novel approach does not rely on embryologists' subjective assessments, providing a more objective measure. If proven effective in clinical trials, BELA could be widely adopted in embryology clinics to enhance the IVF process.
"This is a fully automated and more objective approach compared to prior approaches, and the larger amount of image data it uses can generate greater predictive power," said Dr. Iman Hajirasouliha, associate professor at Weill Cornell Medicine and a senior author of the study.
The AI model behind BELA analyzes nine time-lapse images of an embryo under a microscope approximately five days after fertilization. This data is combined with maternal age to predict chromosomal normalcy. Developed with data from nearly 2,000 embryos tested for chromosomal status, the system was found to offer more accurate predictions compared to previous versions when tested on both internal and external datasets.
The research team is preparing to conduct a randomized, controlled clinical trial to further evaluate BELA's predictive accuracy.
"BELA and AI models like it could expand the availability of IVF to areas that don't have access to high-end IVF technology and PGT testing, improving equity in IVF care across the world," said Dr. Nikica Zaninovic, associate professor and director of the Embryology Laboratory at Weill Cornell Medicine.
Additionally, the researchers believe that BELA's capabilities could be extended beyond ploidy prediction to assess general embryo quality and predict developmental stages, making it a versatile tool for embryology clinics.
Research Report:Automatic ploidy prediction and quality assessment of human blastocysts using time-lapse imaging
Related Links
Englander Institute for Precision Medicine
All about the robots on Earth and beyond!
| Subscribe Free To Our Daily Newsletters |
| Subscribe Free To Our Daily Newsletters |
