An AI algorithm can generate synthetic 3-tesla images from MRI data acquired on a portable 64-mT MRI scanner from patients with multiple sclerosis (MS), according to research published April 22 in Radiology.

Called LowGAN, the generative adversarial network (GAN) yielded both qualitative and quantitative improvement for the low-field-strength MRI scans, a team led by first author Alfredo Lucas of the University of Pennsylvania reported. The researchers said that their results serve as preliminary evidence for the feasibility of combining portable MRI with a deep-learning algorithm is feasible for screening, monitoring, and characterizing MS.

“For portable MRI in multiple sclerosis (MS), LowGAN produced 3T-like images, recovered regional brain volumes, and increased white matter lesion conspicuity,” the authors wrote.