National Institutes of Health (NIH)-funded researchers have developed a new technique for processing MRI scans that provides a detailed view of the placenta during pregnancy.

This method enables the automatic detection of placental compartments and the oxygen levels in each region. It also allows malformations in blood vessels (placental lesions) to be determined.

Support for the study, which developed the new analysis technique for MRI scans that are regularly collected in healthcare facilities and hospitals, was provided by the NIH Human Placenta Project led by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD).

The new machine learning technique automatically processes MRI data to visualise separate placental compartments, including placental vessels, placental tissue and the intervillous space.

It can characterise the oxygen levels in these discrete compartments, unlike existing MRI analysis processes, which can only measure placental oxygen as an average across the complete organ.

The researchers’ team also used the region-specific measurements in a study to analyse differences between 22 healthy pregnancy participants and five participants who developed complications in their pregnancy.

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The new technique can serve as a quantitative method for evaluating placental health during pregnancy.

It may also be used as a tool by healthcare providers in pregnancy patient care, mainly for those who are at risk of complications during pregnancy.

NIH stated that better identification and prevention of pregnancy complications, such as fetal growth disorders, preeclampsia and preterm birth, is possible through early monitoring of the placenta.

Last September, the NIH announced that the iLet bionic pancreas device had been found to help type 1 diabetes patients better maintain their blood glucose (sugar) levels in a multicentre clinical trial.