From left to right: Samuel Ojosnegros, Anna Seriola and Albert Parra. Copyright © Institute for Bioengineering of Catalonia (IBEC)
A new technique developed at the Institute for Bioengineering for Catalonia (IBEC) makes it possible to classify the quality of embryos faster and twice as accurately as expert embryologists. The technology, called METAPHOR, uses imaging and artificial intelligence to analyse the metabolism of embryos and oocytes. This technique promises to drastically reduce the time and treatment cycles needed to achieve pregnancy through in vitro fertilisation, minimising the emotional and financial burden on patients.
The revolutionary method, called METAPHOR, generates 3D images that reveal the colours present in the embryo in a completely non-invasive way. Certain naturally fluorescent compounds in the embryo’s metabolism are also key to processes such as cellular respiration or nutrient consumption, making METAPHOR a reliable way to monitor the embryo’s health.
“This new technology will help to increase the probability of success in assisted reproduction processes, reducing the so-called ‘time to pregnancy’ and the economic and psychological burden on patients,” says Samuel Ojosnegros, principal investigator at IBEC and coordinator of the HYLIGHT project.
The paper, published in the prestigious journal PNAS, describes how, in studies with mice, they were able to double the success rate in selecting viable embryos compared to embryologists using traditional microscopy. In addition to embryo analysis, the method is highly accurate in analysing oocyte metabolism, allowing the most suitable oocytes to be selected for in vitro fertilisation. To do this, they compared oocytes from young and older females, as age is known to be crucial for oocyte viability. The METAPHOR system discriminated between young and non-young oocytes with 96% accuracy and was able to predict which would develop into viable embryos with over 80% accuracy, an unprecedented figure in the field.
Read the full story on IBEC‘s website.
Published paper:
Albert Parra, Denitza Denkova, Xavier P. Burgos-Artizzu, Ester Aroca, Marc Casals, Irene Oliver-Vila, Miguel Ares, Anna Ferrer-Vaquer, Enric Mestres, Mònica Acacio, Nuno Costa-Borges, Elena Rebollo, Hsiao Ju Chiang, Scott E. Fraser, Francesco Cutrale, Anna Seriola, and Samuel Ojosnegros. METAPHOR: Metabolic Evaluation through Phasor-based Hyperspectral Imaging and Object Recognition for Mammalian Blastocysts and Oocytes. PNAS (2024).
DOI: https://doi.org/10.1073/pnas.2315043121
More information about the HYLIGHT project is available here.
