O-249 METAPHOR: METabolic imaging through AI-powered Phasor-based Hyperspectral analysis and Organelle recognition for the classification of human blastocysts
Authors: Ojosnegros S , Parra A , Massafret O , Burgos-Artizzu X , Ferrer-Vaquer A , Ares M , Denkova D , Parriego M , Solé M , Boada M , Seriola A 
Published: July 2024

Study question

Can we classify human blastocysts non-invasively using hyperspectral imaging?

Summary answer

HS imaging can significantly enhance our classification of human embryos and reveal numerous cellular features present in the embryo invisible to brightfield imaging.

What is known already

Non-invasive measurement of metabolism is a safe and powerful tool to reliably predict oocyte and embryo quality. We have previously shown that our METAPHOR technology, based on HS imaging coupled to artificial intelligence, was able to separate mouse oocyte categories according to maternal age with an average AUC of 96.2% and predict blastocyst formation (AUC 82.2%). Moreover, it was able to classify mouse embryos deprived from different nutrients with an average AUC of 93.7% showing clear superiority to grading provided by experienced embryologists (51%).

Study design, size, duration

A total of 74 human embryos donated for research at the blastocyst stage have been imaged to date. Embryos were warmed and imaged according to our established protocol and survival was statistically indistinguishable from control embryos.

Participants/materials, setting, methods

Embryos are imaged using multiphoton illumination near the infra-red. The HS detection covered the simultaneous measurement of the whole visible spectrum. Embryos are then allowed to implant in our proprietary 3D ex vivo platform. Implantation is monitored up until day 9 before immunostaining is performed to quantify presence and prevalence of lineage and implantation markers.

Main results and the role of chance

After imaging, embryos were placed on the 3D ex vivo implantation platform and let implant. Successful implantation (75.41%) was scored by observation of the characteristic deformation of collagen fibers within the matrix and staining for relevant cell lineages (OCT4, pMLC2). Interestingly, we observed that embryos with a higher trophectoderm (TE) grading tended to implant with a higher efficiency and penetrate deeper into the matrix than embryos with lower grading.

HS images have unveiled a profound cellular diversity within embryos, elucidating distinctions between the Inner Cell Mass (ICM) and TE, as well as revealing different metabolic states defined by NADH dominance, FAD dominance, protoporphyrin levels, and apoptosis. HS raw images are processed using our HS-phasor approach which allows quick computing by converting the multidimensional HS data into comprehensive visual representation of bidimensional histograms and phasor plots.

In summary, our analysis pipeline encompasses the algorithms to detect and segment the embryos, the computation of histogram and phasor-plot, and the classifier. AI allows us to classify embryos in distinct spectral spaces based on their metabolic features, paving the way to the establishment of a new grading system based on HS imaging.

Limitations, reasons for caution

The cohort size is still limited, and ongoing experiments will increase the dataset needed for more accurate prediction of embryo implantation. The implantation platform is an in vitro test that will require future clinical validation.

Wider implications of the findings

The safety and speed of METAPHOR warrants its incorporation at the IVF clinic, adding an additional layer of information to the current embryo selection methods. Moreover, the non-invasive measurement of the metabolic function opens new alleys of research such as the effect of media and culture supplements on embryo culture.

Trial registration number

Not applicable