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

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          Abstract

          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.

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          Most cited references47

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          The Istanbul consensus workshop on embryo assessment: proceedings of an expert meeting.

          Many variations in oocyte and embryo grading make inter-laboratory comparisons extremely difficult. This paper reports the proceedings of an international consensus meeting on oocyte and embryo morphology assessment. Background presentations about current practice were given. The expert panel developed a set of consensus points to define the minimum criteria for oocyte and embryo morphology assessment. It is expected that the definition of common terminology and standardization of laboratory practice related to embryo morphology assessment will result in more effective comparisons of treatment outcomes. This document is intended to be referenced as a global consensus to allow standardized reporting of the minimum data set required for the accurate description of embryo development.
            • Record: found
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            • Article: not found

            Non-invasive imaging of human embryos before embryonic genome activation predicts development to the blastocyst stage.

            We report studies of preimplantation human embryo development that correlate time-lapse image analysis and gene expression profiling. By examining a large set of zygotes from in vitro fertilization (IVF), we find that success in progression to the blastocyst stage can be predicted with >93% sensitivity and specificity by measuring three dynamic, noninvasive imaging parameters by day 2 after fertilization, before embryonic genome activation (EGA). These parameters can be reliably monitored by automated image analysis, confirming that successful development follows a set of carefully orchestrated and predictable events. Moreover, we show that imaging phenotypes reflect molecular programs of the embryo and of individual blastomeres. Single-cell gene expression analysis reveals that blastomeres develop cell autonomously, with some cells advancing to EGA and others arresting. These studies indicate that success and failure in human embryo development is largely determined before EGA. Our methods and algorithms may provide an approach for early diagnosis of embryo potential in assisted reproduction.
              • Record: found
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              Trophectoderm morphology: an important parameter for predicting live birth after single blastocyst transfer.

              In order to select the best blastocyst for transfer, in humans, three morphological parameters have routinely been used, i.e. degree of blastocoele expansion and appearance of both the trophectoderm (TE) and the inner cell mass (ICM). Although it has been shown that blastocysts with highest scores for all three parameters achieve highest implantation rates, their independent ability to predict pregnancy outcome remains unclear. This study is a retrospective analysis of 1117 fresh day 5 single blastocyst transfers and their live birth outcome related to each morphological parameter. All three parameters had a significant effect on live birth however, once adjusted for known significant confounders, it was shown that TE was the only statistically significant independent predictor of live birth outcome. This study has shown, for the first time, the predictive strength of TE grade over ICM for selecting the best blastocyst for embryo replacement. It may be that, even though ICM is important, a strong TE layer is essential at this stage of embryo development, allowing successful hatching and implantation.

                Author and article information

                Journal
                Hum Reprod
                Hum. Reprod
                humrep
                humrep
                Human Reproduction (Oxford, England)
                Oxford University Press
                0268-1161
                1460-2350
                October 2016
                17 September 2016
                17 September 2016
                : 31
                : 10
                : 2231-2244
                Affiliations
                [1 ]Bjørn Molt Petersen BMP Analytics, Vilhelm Becks Vej 20, 8260 Viby J, Denmark
                [2 ]Vitrolife A/S, Jens Juuls Vej 20, 8260 Viby J, Denmark
                [3 ]ilabcomm GmbH, Eisenachstr. 34, 53757 St. Augustin, Germany
                [4 ]School of BioSciences, University of Melbourne , Parkville, Melbourne, Victoria 3010, Australia
                Author notes
                [* ]Correspondence address. Bjørn Molt Petersen BMP Analytics, Vilhelm Becks Vej 20, 8260 Viby J, Denmark. Tel: +45-40897913; E-mail: bjornmolt@ 123456gmail.com
                Article
                dew188
                10.1093/humrep/dew188
                5027927
                27609980
                a9d8401c-581c-48d6-b26d-ababa8b2fb45
                © The Author 2016. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 11 January 2016
                : 23 June 2016
                : 29 June 2016
                Page count
                Pages: 14
                Funding
                Funded by: Vitrolife A/S;
                Funded by: Vitrolife AB;
                Categories
                Original Articles
                Embryology

                Human biology
                time-lapse,algorithm,decision support tool,prediction model,morphokinetic,implantation,embryo selection,blastocyst

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