P–263 Life Whisperer™, an AI-based algorithm to select non invasively best quality blastocysts for transfer: A multicenter analysis
Authors: Muño. Espert P , Galiana Y , Medrano L , Ballester J , Ortega L , Aizpurua J 
Published: August 2021

Abstract

Study question
Is the AI-based Life Whisperer™ (LW) tool, suitable to evaluate blastocysts quality and predict clinical pregnancy (CP) in couples undergoing ICSI cycles?

Summary answer
LW blastocyst score is comparable to the scores of other classification methods. This AI model showed high sensitivity and a comparable specificity for CP.

What is known already
The morphology grading is the most widely used method for the selection and classification of the embryos in clinical practice.However,this evaluation entails intervariability and intravariability decision among the embryologists.Recently, research has been focused on new embryo selection systems based on computer-assisted evaluation such as time-lapse with complex algorithms that allow the recognition of objective parameters of the embryo morphology.The implementation of these technologies requires substantial investments that are not available for all clinics.LW is a new embryo selection method based on AI,where specific hardware is not needed,as it is based on single blastocyst images taken with a routine microscope.

Study design, size, duration
Between 2017–2020, a total of 513 Day–5 blastocysts, after ICSI, comming from egg donation treatment were included in this retrospective-multicentre study.Day–5 embryos were evaluated with 3 classification methods:Gardner’s blastocyst grade (GB), the computer derived-output Eeva (EV) and LW AI-supported system. The good quality blastocysts were first evaluated using the GB and EV scores and subsequently compared with the LW scores.The sensitivity and specificity of LW was assessed to validate this system as a clinical pregnancy predictor.

Participants/materials, setting, methods
A total of 513 Day–5 blastocysts, from 134 oocyte donation cycles, were evaluated first by GB score: expansion (1–6), inner cell mass and throphoectoderm (A-C).EV analyses the cell division timing P2 (2cells stage duration) and P3 (3cells stage duration) differentiating three categories:High,Medium and Low(VerMilyea et al.,2014).LW scores ranked 1–10 from a single Day–5 blastocyst HR Image performed on inverted microscope,with a threshold &gt;5 for defining a viable blastocyst.T-test and ROC-curves were used for statistical analysis.

Main results and the role of chance
The average of LW score obtained from GB higher blastocyst expansion score (≥4) was 7.48±0.09, while the average of LW score obtained from GB lower blastocyst expansion score (&lt;4) was 4.69±0.3 (P &lt; 0.001). The average of LW score yielded from GB good morphology of Inner Cell Mass and trophoectoderm (AA,AB,BA) was 7.98±0.1 while the average of LW score obtained from GB lower quality blastocyst score (BB,BC,CB,CA,AC) was 6.36±0.156 (P &lt; 0.001).The average of LW score resulted from EV High blastocysts was 7.42±0.17, while the average of this obtained from EV low score was 6.43±0.3 (P = 0.009).A correlation between EV and LW score could be assesed, except for the blastocyst that are considered Medium score from EV.
Therefore, a strong correlation between GB and LW system, as well GB+EV and LW, was found and an equivalent usability of the LW tool could be confirmed.
The analyse of LW score for transferred embryos (N = 156), using ROC curve, showed a high sensitivity (0,928) but a low specificity (0,154) with a threshold of 5. Regarding our data, ROC curve shows that a threshold of 8,46 could enhance the prediction of CPR because in this point the specifity value is higher than 0.5.

Limitations, reasons for caution
The LW score validation compared to GB and EV methodology was carried out on a small number of embryos.Additionally,not all embryos had been transferred at the time of the analysis.Thus to enhance the accuracy of these data and the specificity of the clinical prediction, a higher sample size is needed.
Wider implications of the findings: Blastocyst selection looks equivalent between all systems,but the LW tool is more objective and faster, saving time and costs significantly, without needing substantial hardware investments.
Additionally,the LW-system shows almost the highest sensibility and may also improve the specificity by self-learning feeding the AI-system, thus tailoring predictions to each laboratory unique environment.

Trial registration number
NA