P-149 Time is over: time-lapse technology to set time cut-offs defining embryo developmental incompetence
Authors: Bartolacci A , Coticchio G , Cimadomo V , Trio S , Borini A , Ubaldi F M , Rienzi L , Cimadomo D 
Published: June 2023

Abstract

Study question
Can time-lapse technology (TLT) discriminate developmentally incompetent embryos through time cut-offs of fertilization and cleavage stages?

Summary answer
TLT identifies developmentally incompetent embryos with high precision, through cut-offs of tPNa, tPNf, t2, t4 and t8. No clinically-applicable cut-offs were found for blastocyst euploidy.

What is known already
TLT is instrumental for continued and undisturbed observation of embryo development. This has produced morphokinetic algorithms aimed at selecting embryos able to generate a viable pregnancy. Such efforts have had limited success. Regardless, the potential of this technology for improving multiple aspects of the IVF process remains considerable. Specifically, TLT could be harnessed to discriminate developmentally incompetent embryos: i.e., those unable to develop to the blastocyst stage or affected by full-chromosome meiotic aneuploidies. If developed, this application would prevent the non-productive use of such embryos, improving laboratory and clinical efficiency and reducing costs derived from unproductive embryo transfer and cryopreservation.

Study design, size, duration
The training dataset involved embryos of PGT-A cycles cultured in Embryoscope with single- media (836 euploid blastocysts, 1179 aneuploid and 1874 arrested embryos; 2013-2020). Selection criteria were ejaculated sperm, fresh own eggs, trophectoderm biopsy, and comprehensive-chromosome-testing to diagnose non-mosaic aneuploidies. Out-of-sample (30% of training), internal (299 euploid blastocysts, 490 aneuploid and 680 arrested embryos; 2021- 2022) and external (97 euploid, 110 aneuploid, 603 untested blastocysts and 514 arrested embryos, 2018 to early-2022) validations were conducted.

Participants/materials, setting, methods
A training dataset (70%) was used to define thresholds. Several models were generated by fitting outcomes to each timing (tPNa-t8) and maternal age. ROC-curves pinpointed in-sample classification values associated with 95%, 99% and 99.99% true-positive-rate for predicting incompetence. These values were integrated with upper limits of maternal age ranges (&lt;35, 35-37, 38-40,41-42 and  &gt; 42 years) in logit functions to identify time cut-offs, whose accuracy was tested on the validation datasets through confusion matrices.

Main results and the role of chance
For developmental (in)competence, the best performing (i) tPNa cut-offs were 27.8hpi (error-rate: 0/743), 32.6hpi (error-rate: 0/934), 26.8hpi (error-rate: 0/1178), 22.9hpi (error-rate: 1/654,0.1%), and 17.2hpi (error-rate: 4/423,0.9%) in the &lt;35, 35-37, 38-40, 41-42 and  &gt; 42 years groups; (ii) tPNf cut-offs were 36.7hpi (error-rate: 0/738), 47.9hpi (error-rate: 0/921), 45.6hpi (error-rate: 1/1156,0.1%), 44.1hpi (error-rate: 0/647), and 41.8hpi (error-rate: 0/417) in the &lt;35, 35-37, 38-40, 41-42 and  &gt; 42 years groups; (iii) t2 cut-offs were 50.9hpi (error-rate: 0/724), 49hpi (error-rate: 0/915), 47.1hpi (error-rate:0/1146), 45.8hpi (error-rate: 0/636), and 43.9hpi (error-rate: 0/416) in the &lt;35, 35-37, 38-40, 41-42 and  &gt; 42 years groups; (iv) t4 cut-offs were 66.9hpi (error-rate: 0/683), 80.7hpi (error-rate: 0/838), 77.1hpi (error-rate:0/1063), 74.7hpi (error-rate: 0/590), and 71.2hpi (error-rate: 0/389) in the &lt;35, 35-37, 38-40, 41-42 and  &gt; 42 years groups; (v) t8 cut-offs were 118.1hpi (error-rate: 0/619), 110.6hpi (error-rate: 0/772), 140hpi (error-rate: 0/969), 135hpi (error-rate: 0/533), and 127.5hpi (error-rate: 0/355) in the &lt;35, 35-37, 38-40, 41-42 and  &gt; 42 years groups.
tPNf and t2 showed a significant association with chromosomal (in)competence, also when adjusted for maternal age. Nevertheless, relevant cut-offs were not clinically applicable.

Limitations, reasons for caution
Study limits are its retrospective design and datasets unbalanced towards advanced maternal age cases. The potential effects of abnormal cleavage patterns were not assessed. Larger sample size and external validations in other clinical settings are warranted.

Wider implications of the findings
If confirmed by independent studies, this approach could significantly impact on the efficiency of ART reducing the workload (extended culture, cryopreservation, and transfer) associated with embryos that ultimately are developmentally incompetent and should not be considered for treatment. Pending validation, these data might be applied also in static settings.

Trial registration number
N.A.