Scientists predict which embryos are most likely to succeed in IVF treatments

One of the reasons so many couples using in vitro fertilization wind up with twins – and even triplets – is that they choose to transfer multiple embryos into the womb to insure at least one of them will develop into a baby. But carrying multiples can be risky for mother and babies. If only there were a way to reliably predict which embryos are most likely to grow, perhaps couples would be more willing to follow the government’s recommendations and transfer only one or two embryos at a time.

Enter Renee Reijo Pera, who studies the genetics of human embryonic development at Stanford University. She and her colleagues at Stanford and the University of Minnesota thawed 100 frozen IVF embryos that were 12 to 18 hours old and watched them develop over the next five or six days. Fewer than half of them made it all the way to the blastocyst stage. So the scientists looked for patterns that set those successful embryos apart from the others.

The researchers were able to identify three things that characterized the successful embryos:

1. The last step in the process that splits the first cell into two takes no longer than 33 minutes.
2. The lag between the end of the first cell division and the start of the second lasts between 7.8 and 14.3 hours.
3. The lag between the second and third cell division is no longer than 5.8 hours.

These three factors could predict which embryos progressed to the blastocyst stage – and which didn’t – in most cases. The method correctly identified 93% of the embryos that became blastocysts and 94% of the embryos that didn’t make it. It was also reliable for fresh, never-frozen embryos.

Watching embryos grow in dishes isn’t very appealing, so the researchers then investigated whether machines could do the job for them. (After all, the embryos’ movements were already being recorded by time-lapse microscopes.) The automated embryo-watchers were just as good, they reported.

The results were published online Sunday in the journal Nature Biotechnology.

-- Karen Kaplan/Los Angeles Times