In trying to explain their neutral results the authors examined the (commercially available) algorithm model used and noted that ‘patient and treatment characteristics’ may influence model performance, although subgroup analyses in this trial found no preferential results dependent on the included variables. And that, they suggest, may yet emerge from new developments in automatic systems and deep learning models. Thus, they add, their results question the rationale on spending resources on such time-lapse models ‘unless there is a gain in workflow and efficiency’. Nevertheless, even with reduced numbers the authors report that results did not indicate that any significant difference would have been found even with all intended patients. Only around one half of the planned total were finally randomised, mainly because of clinic closures and other restrictions from the Covid pandemic.
#TIME LAPSE TOOL COST FULL#
Thus, with a somewhat neutral view of the value of time lapse in the improvement of outcome in ART, they pin their hopes on artificial intelligence technologies ‘to interpret the full scope of images and identify key features that have been missed or not quantified in current models’.ĭespite the notable patient numbers in the trial, there was a shortfall in recruitment. Thus, say the authors, ‘the findings of our study, alongside many others, demonstrate the limitations of morphology and morphokinetic markers to fully reflect the reproductive potential of developing embryos’. Results showed that the primary endpoint of ongoing pregnancy rate for the time-lapse group was 47.4% and 48.1% for the control group. Now, one substantial piece of evidence has been added to the time-lapse equation in publication of a large RCT from ten Nordic IVF centres involving 776 patients - all of whom had at least two good quality blastocysts available at randomisation.(1) Thereafter, two randomised groups proceeded to single blastocyst transfer, the one selected according to morphology alone and the other according to findings from a commercially available time-lapse model. In explaining its reasoning, the HFEA notes ‘there is conflicting evidence from randomised controlled trials (RCTs) to show that it is effective at improving the chances of having a baby for most fertility patients’. ESHRE, however, in its forthcoming guideline on the use of add-ons in ART will still include time-lapse (as a ‘selective’ add-on), while the HFEA’s traffic-light rating of add-ons gives it a cautionary amber light.
Although the assessment of embryo quality from time-lapse monitoring is recognised as an ‘add-on’ in IVF, its use in many laboratories – especially in Europe – has become routine over the past decade.
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