Researchers at UNC Demonstrate Technique to Reduce MRI Noise

A team at the University of North Carolina at Chapel Hill has developed a new method to significantly reduce the noise associated with functional magnetic resonance imaging (fMRI). This advancement, originating from the lab of Dr. Yen-Yu Ian Shih, aims to enhance the fMRI experience for patients while opening new avenues for brain research.

Functional MRI is a crucial tool in neuroscience, providing insights into brain activity. However, the scans can produce noise levels comparable to a jackhammer, ranging from 120 to 138 decibels, which can be distressing for patients and research subjects. Addressing this issue, Dr. Shih, a professor of neurology and associate director at the UNC Biomedical Research Imaging Center, along with his colleagues, has introduced a pioneering technique named SORDINO, which drastically reduces the acoustic noise produced during fMRI scans.

The SORDINO method, an acronym for Steady-state On-the-Ramp Detection of INduction-decay with Oversampling, provides instructions for MRI scanners to collect brain measurements, such as blood flow and oxygen levels, and translate them into clearer images. Initially applied to small animal models, this technique holds promise for enhancing human MRI and neuroimaging research.

"SORDINO is something we now use regularly in our lab for a variety of neuroscience research projects," said Dr. Shih, the senior author of the study. "It has really simplified our day-to-day fMRI experiments. We hope SORDINO will help other researchers overcome some of the technical barriers that have long complicated fMRI studies and eventually bring similar advances to human MRI."

Researchers noted several advantages of the SORDINO method over conventional fMRI techniques. In comparative studies using mouse models, SORDINO significantly reduced noise and electromagnetic interference. It also decreased stress-related hormone levels, all while delivering images with minimized distortion. These improvements enabled the study of complex behaviors, such as voluntary skilled movements and social interactions between two subjects scanned concurrently. The technique was awarded a U.S. patent in 2024.