The clinical need for a method of identification of embryos destined to become a blastocyst in assisted reproductive technology cycles

Development of a generally applicable morphokinetic algorithm capable of predicting the implantation potential of embryos transferred on Day 3

STUDY QUESTION

Can a generally applicable morphokinetic algorithm suitable for Day 3 transfers of time-lapse monitored embryos originating from different culture conditions and fertilization methods be developed for the purpose of supporting the embryologist's decision on which embryo to transfer back to the patient in assisted reproduction?

SUMMARY ANSWER

The algorithm presented here can be used independently of culture conditions and fertilization method and provides predictive power not surpassed by other published algorithms for ranking embryos according to their blastocyst formation potential.

WHAT IS KNOWN ALREADY

Generally applicable algorithms have so far been developed only for predicting blastocyst formation. A number of clinics have reported validated implantation prediction algorithms, which have been developed based on clinic-specific culture conditions and clinical environment. However, a generally applicable embryo evaluation algorithm based on actual implantation outcome has not yet been reported.

STUDY DESIGN, SIZE, DURATION

Retrospective evaluation of data extracted from a database of known implantation data (KID) originating from 3275 embryos transferred on Day 3 conducted in 24 clinics between 2009 and 2014. The data represented different culture conditions (reduced and ambient oxygen with various culture medium strategies) and fertilization methods (IVF, ICSI). The capability to predict blastocyst formation was evaluated on an independent set of morphokinetic data from 11 218 embryos which had been cultured to Day 5.

PARTICIPANTS/MATERIALS, SETTING, METHODS

The algorithm was developed by applying automated recursive partitioning to a large number of annotation types and derived equations, progressing to a five-fold cross-validation test of the complete data set and a validation test of different incubation conditions and fertilization methods. The results were expressed as receiver operating characteristics curves using the area under the curve (AUC) to establish the predictive strength of the algorithm.

MAIN RESULTS AND THE ROLE OF CHANCE

By applying the here developed algorithm (KIDScore), which was based on six annotations (the number of pronuclei equals 2 at the 1-cell stage, time from insemination to pronuclei fading at the 1-cell stage, time from insemination to the 2-cell stage, time from insemination to the 3-cell stage, time from insemination to the 5-cell stage and time from insemination to the 8-cell stage) and ranking the embryos in five groups, the implantation potential of the embryos was predicted with an AUC of 0.650. On Day 3 the KIDScore algorithm was capable of predicting blastocyst development with an AUC of 0.745 and blastocyst quality with an AUC of 0.679. In a comparison of blastocyst prediction including six other published algorithms and KIDScore, only KIDScore and one more algorithm surpassed an algorithm constructed on conventional Alpha/ESHRE consensus timings in terms of predictive power.

LIMITATIONS, REASONS FOR CAUTION

Some morphological assessments were not available and consequently three of the algorithms in the comparison were not used in full and may therefore have been put at a disadvantage. Algorithms based on implantation data from Day 3 embryo transfers require adjustments to be capable of predicting the implantation potential of Day 5 embryo transfers. The current study is restricted by its retrospective nature and absence of live birth information. Prospective Randomized Controlled Trials should be used in future studies to establish the value of time-lapse technology and morphokinetic evaluation.

WIDER IMPLICATIONS OF THE FINDINGS

Algorithms applicable to different culture conditions can be developed if based on large data sets of heterogeneous origin.

STUDY FUNDING/COMPETING INTEREST(S)

This study was funded by Vitrolife A/S, Denmark and Vitrolife AB, Sweden. B.M.P.’s company BMP Analytics is performing consultancy for Vitrolife A/S. M.B. is employed at Vitrolife A/S. M.M.’s company ilabcomm GmbH received honorarium for consultancy from Vitrolife AB. D.K.G. received research support from Vitrolife AB.

A predictive model for blastocyst formation based on morphokinetic parameters in time-lapse monitoring of embryo development

PURPOSE

The aim of the study was to create a predictive model of blastocyst development based on morphokinetic parameters of time-lapse embryoscope monitoring.

METHODS

Time-lapse recordings of 432 embryos (obtained from 77 patients), monitored in Embryoscope, were involved in the study. Patients underwent in vitro fertilization according to standard procedure between June 2012 and April 2013. A retrospective analysis of morphokinetic features, focused on duration of time from the Intracytoplasmic Sperm Injection (ICSI) procedure to consecutive embryo division for 2, 3, 4 and 5 blastomeres, as well as time intervals between each division, was conducted. All embryos were observed for 5 days.

RESULTS

Based on the distribution of analyzed morphokinetic parameters and number of embryos developed to blastocyst, a range denoting the possibility of an embryo reaching blastocyst stage was determined. According to the obtained results, univariate and multivariate logistic regression analyses were performed. Based on the times of division for two and five blastomeres and intervals between the second and third division, a multivariate predictive model was created. The predictive equation was constructed based on the parameters of logistic regression analysis (odds ratios). Statistically significant differences (p < 0.001) in the size of the prediction parameter between the group of embryos developed to blastocyst (the median value: Me = 9.95, and quartiles: Q1 = 7.59, Q3 = 12.30) and embryos that did not develop to the blastocyst stage (Me = 4.66, Q1 = 2.33, Q3 = 8.19) were found. A Receiver Operating Characteristic (ROC) curve was created for the constructed predictive model. The Area Under the Curve was AUC = 0.806 with a 95 % confidence interval (0.747, 0.864). The predictive model constructed in this study has been validated using an independent data set, which indicates that the model is reliable and repeatable.

CONCLUSIONS

Time-lapse imaging presents a new diagnostic tool for parametric evaluation of embryo development, from the oocyte stage, through fertilization, up to the blastocyst stage. The assessment of morphokinetic parameters can help us to provide more accurate information about the reproductive potential of embryos. It allows for early selection of embryos with high reproductive potential and shortens embryo incubation.

Using the Eeva Test™ adjunctively to traditional day 3 morphology is informative for consistent embryo assessment within a panel of embryologists with diverse experience

PURPOSE

Since many transferred, good morphology embryos fail to implant, technologies to identify embryos with high developmental potential would be beneficial. The Eeva™ (Early Embryo Viability Assessment) Test, a prognostic test based on automated detection and analysis of time-lapse imaging information, has been shown to benefit embryo selection specificity for a panel of three highly experienced embryologists (Conaghan et al., 2013). Here we examined if adjunctive use of Eeva Test results following morphological assessment would allow embryologists with diverse clinical backgrounds to consistently improve the selection of embryos with high developmental potential.

METHODS

Prospective, double-blinded multi-center study with 54 patients undergoing blastocyst transfer cycles consented to have embryos imaged using the Eeva System, which automatically measures key cell division timings and categorizes embryos into groups based on developmental potential. Five embryologists of diverse clinical practices, laboratory training, and geographical areas predicted blastocyst formation using day 3 morphology alone and day 3 morphology followed by Eeva Test results. Odds ratio (OR) and diagnostic performance measures were calculated by comparing prediction results to true blastocyst outcomes.

RESULTS

When Eeva Test results were used adjunctively to traditional morphology to help predict blastocyst formation among embryos graded good or fair on day 3, the OR was 2.57 (95 % CI=1.88-3.51). The OR using morphology alone was 1.68 (95 % CI=1.29-2.19). Adjunct use of the Eeva Test reduced the variability in prediction performance across all five embryologists: the variability was reduced from a range of 1.06 (OR=1.14 to 2.20) to a range of 0.45 (OR=2.33 to 2.78).

CONCLUSIONS

The Eeva Test, an automated, time-lapse enabled prognostic test, used adjunctively with morphology, is informative in helping embryologists with various levels of experience select embryos with high developmental potential.

Prevalence, consequence, and significance of reverse cleavage by human embryos viewed with the use of the Embryoscope time-lapse video system

OBJECTIVE

To investigate the prevalence and potential causes of reverse cleavage (RC) by human early-cleavage embryos and its associations with embryonic development and implantation after transfer.

DESIGN

Clinical retrospective cohort study.

SETTING

Private fertility treatment center.

PATIENT(S)

A total of 126 consecutive in vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI) treatment cycles, with 353 IVF and 436 ICSI embryos cultured in the Embryoscope until day 3.

INTERVENTION(S)

None.

MAIN OUTCOME MEASURE(S)

Embryo assessment on day 3, incidence of abnormal division, embryo morphokinetic parameters, and fetal heart beat.

RESULT(S)

RC, referring to either blastomere fusion or failed cytokinesis, occurred up to three times per individual embryo in 27.4% of embryos during the first three cleavage cycles. A higher incidence was associated with GnRH antagonist cycles compared with agonist cycles (odds ratio [OR] 1.683), or with ICSI compared with IVF (OR 1.600). After ICSI, sperm progressive motility was associated with RC (area under the receiver operating characteristic curve: 0.573). Compared with RC-negative embryos, a lower proportion of RC-positive embryos reached 6-cell stage or beyond by day 3 (47.7% vs. 71.7%), and were more likely to have multinucleation at the 4-cell stage (10.1% vs. 5.0%). Embryos showing RC had significantly poorer performance in both conventional grading and morphokinetic parameters, and they implanted less (0/22 vs. 29/131) than those not showing RC.

CONCLUSION(S)

RC significantly compromised embryo development, culminating in poor implantation potential. For each embryo, it can occur on more than one occasion at any stage during the first 3 days of culture. It is associated with factors affecting both oocyte and sperm.

Improving embryo selection using a computer-automated time-lapse image analysis test plus day 3 morphology: results from a prospective multicenter trial

OBJECTIVE

To assess the first computer-automated platform for time-lapse image analysis and blastocyst prediction and to determine how the screening information may assist embryologists in day 3 (D3) embryo selection.

DESIGN

Prospective, multicenter, cohort study.

SETTING

Five IVF clinics in the United States.

PATIENT(S)

One hundred sixty women ≥ 18 years of age undergoing fresh IVF treatment with basal antral follicle count ≥ 8, basal FSH <10 IU/mL, and ≥ 8 normally fertilized oocytes.

INTERVENTION(S)

A noninvasive test combining time-lapse image analysis with the cell-tracking software, Eeva (Early Embryo Viability Assessment), was used to measure early embryo development and generate usable blastocyst predictions by D3.

MAIN OUTCOME MEASURE(S)

Improvement in the ability of experienced embryologists to select which embryos are likely to develop to usable blastocysts using D3 morphology alone, compared with morphology plus Eeva.

RESULT(S)

Experienced embryologists using Eeva in combination with D3 morphology significantly improved their ability to identify embryos that would reach the usable blastocyst stage (specificity for each of three embryologists using morphology vs. morphology plus Eeva: 59.7% vs. 86.3%, 41.9% vs. 84.0%, 79.5% vs. 86.6%). Adjunctive use of morphology plus Eeva improved embryo selection by enabling embryologists to better discriminate which embryos would be unlikely to develop to blastocyst and was particularly beneficial for improving selection among good-morphology embryos. Adjunctive use of morphology plus Eeva also reduced interindividual variability in embryo selection.

CONCLUSION(S)

Previous studies have shown improved implantation rates for blastocyst transfer compared with cleavage-stage transfer. Addition of Eeva to the current embryo grading process may improve the success rates of cleavage-stage ETs.

Biomarkers identified with time-lapse imaging: discovery, validation, and practical application

"Time-lapse markers," which are defined by time-lapse imaging and correlated with clinical outcomes, may provide embryologists with new opportunities for improving embryo selection. This article provides an overview of noninvasive biomarkers defined by time-lapse imaging studies. In addition to comprehensively reviewing the discovery of each time-lapse marker, it focuses on the criteria necessary for their successful integration into clinical practice, including [1] statistical and biological significance, [2] validation through prospective clinical studies, and [3] development of reliable technology to measure and quantify the time-lapse marker. Because manual analysis of time-lapse images is labor intensive and limits the practical use of the image data in the clinic, automated image analysis software platforms may contribute substantially to improvements in embryo selection accuracy. Ultimately, time-lapse markers that are based on a foundation of basic research, validated through prospective clinical studies, and enabled by a reliable quantification technology may improve IVF success rates, encourage broader adoption of single-embryo transfer, and reduce the risks associated with multiple gestation pregnancies.