Rita Vassena
Co-founder and CEO of Fecundis, a company developing assisted reproduction treatments, and previously scientific director of the Eugin Group
This study by Parra and colleagues provides a very interesting initial validation of the use of hyperspectral microscopy, a method for assessing the level of autofluorescent molecules in living cells, for the determination of viability in oocytes and embryos.
The study is carried out in mice and serves as proof of principle that this technology can indeed correctly differentiate between embryos with different metabolic profiles, a prelude to identifying those most likely to implant and lead to a viable pregnancy. In addition, the authors have convincingly demonstrated that the technology can distinguish which oocyte is likely to develop into an embryo, a feature that could be of great interest if transferred to our species.
Every year, tens of thousands of women save their oocytes for future use; being able to non-invasively know how many of them will eventually become an embryo would provide much-needed advice and peace of mind, as these women could decide, for example, to add more oocytes to their reserve or to stop at the number they already have.
This work was awaited with some expectation in the specialised scientific community; the field of assisted reproduction has been struggling for decades to find a non-invasive method to sort embryos - analysing everything from spent culture medium to time-lapse videos of developing embryos and resorting to the use of artificial intelligence in the process.
Recent attempts to use autofluorescent molecules to sort human embryos based on their ability to result in a viable pregnancy with a related technology called FLIM, while partially successful, did not reach the expected level of clinical utility.
It appears that hyperspectral microscopy, with its ability to read multiple signals simultaneously and interpolate them into a complex metabolic portrait of the embryo, may provide greater analytical granularity and the level of accuracy and sensitivity needed to demonstrate clinical utility.