When applied to brain imaging, the algorithm assists in the detection of subtle abnormalities in instances of drug-resistant focal cortical dysplasia (FCD), which is known to cause epilepsy and is historically difficult to detect. 

Deep learning models can increase reader accuracy while simultaneously decreasing interpretation times when evaluating imaging for intracranial aneurysms.

Authors of the new study suggested that their findings, once further validated in larger cohorts, could provide objective measures to diagnose ADHD and monitor treatment responses in the future. 

Experts involved in the research believe their findings could help to guide providers in making treatment decisions. 

“The value of MRI added to CT in patients such as these should not be presumed."

Better risk stratification can improve clinical decision making and better outcomes, experts involved in the study explained in EJR.

In the largest known study to date on the relationship between moderate alcohol consumption and iron homeostasis, experts suggested that as little as four drinks per week can increase the presence of iron deposits on imaging.

The researchers are now working on developing a qMRI method that can be incorporated into clinical settings, with an anticipated timeline of three to five years.