In collaboration with radiologists at the University of Pennsylvania, Moss Rehabilitation Research Institute (MRRI) researchers are applying a new algorithm that improves normalization of MRI images of TBI brains. Preliminary research results using the algorithm suggest that the increased detail and accuracy it affords could greatly enhance the TBI imaging research investigating structure, function, and perhaps treatment effects in this population.

More Detailed, Accurate, Meaningful Images

The Symmetric Diffeomorphic Normalization (SyN) method, created by researchers at the University of Pennsylvania, is a state-of-the-art technique that can “warp” severely injured brains to a healthy brain, while also preserving common “landmarks” found in every brain. Consequently, TBI brains normalized using the SyN method can be compared more easily to control subjects, yielding more detailed, accurate, meaningful images for group analysis and, in turn, stronger study conclusions.

Algorithm facilitates structural and functional neuroimaging research in TBI MRRI

Researchers are employing the SyN algorithm to elucidate two research areas: exploring the structural consequences of TBI through structural MRI, and exploring the neuropsychological functioning impacts of TBI through functional MRI imaging.

The research on structural consequences attempts to delineate the precise brain volume changes in chronic TBI patients. Interim results from this study indicate that the SyN helps provide excellent three-dimensional delineation of brain volume loss. According to Junghoon Kim, PhD, MRRI scientist and Director, Clinical Neuroimaging Laboratory, the current study is the first to volumetrically delineate the entire brain structure of TBI patients. Data from this study may assist in illuminating the relationship between brain structure and patient behavior in the future.

Kim and his collaborators, including John Whyte, MD, PhD, have also had promising results from the functional MRI research on attention functioning in TBI patients. Preliminary results indicate that the SyN algorithm identifies more areas of neuropsychological activation during task completion in TBI patients than other algorithms.

Use of the SyN algorithm is expected to increase the sensitivity of future neuroimaging studies of TBI. For example, researchers could do a pharmacologic intervention study of a psychostimulant in TBI and measure brain activity on and off the drug. Kim and his colleagues believe that with the SyN algorithm, results may be more detailed and accurate enough to detect subtle drug effects.