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New brain imaging technique allows for a closer look at MS

More detailed scans could lead to better diagnosis and treatments
February 7, 2014

Dr. Yunyan Zhang is a Hotchkiss Brain Institute researcher working on quantitative techniques to increase the diagnostic and therapeutic power of MRI imaging in multiple sclerosis. Photo by Bruce Perrault

The conventional T2-weighted MRI (A) and texture map (B) of two sample MS lesions (box and arrow). As shown in the blow-up of the boxed lesion, there are layers of texture heterogeneity that taper toward the surrounding normal appearing white matter (red and black) in the calculated texture map, but in the conventional MRI, the lesion shows simply a focus of hyperintensity, no detailed information. The color bar represents levels of texture heterogeneity from black (the lowest) to red, green, blue, aqua, purple, yellow, and white (the highest).

Multiple sclerosis (MS) is an unpredictable and debilitating neurodegenerative disease that affects an estimated 100,000 Canadians. Typically, Magnetic Resonance Imaging (MRI) is used to confirm diagnosis, but current techniques are limited in their ability to detect subtle differences in tissue damage.

Recent research out of the University of Calgary’s Hotchkiss Brain Institute (HBI) aims to enhance the diagnostic and therapeutic power of MRI with a new technique that is sensitive to very small changes in patterns within the MRI images of MS patients.

In a study published in the journal Annals of Neurology, the HBI’s Dr. Yunyan Zhang and colleagues developed a mathematical algorithm that they used to analyze MRI images from MS subjects. They found that by applying this algorithm, they could look at a parameter called MRI texture heterogeneity and clearly see patterns and changes in tissue samples.

Algorithm brings changes in tissue texture to light

“An MRI image has a texture that you can’t normally see with your eyes,” explains Zhang, who is a Research Assistant Professor in the Departments of Clinical Neurosciences and Radiology. “This computer algorithm calculates how the image elements are organized. It allows us to see changes in the texture pattern that correspond to areas of damage and it clearly shows boundaries between damaged and normal tissue.”

When looking at the MRI image of an MS patient that has been analyzed with Zhang’s algorithm, the image shows the amount of coarse texture or fine texture that is present. Zhang found that areas with the most coarse texture or heterogeneity corresponded with the greatest amount of damage. When compared to a traditional MRI image, Zhang’s texture map reveals much greater detail, making it a very powerful tool for assessing and diagnosing disease.

Technique works on existing scans

As an added advantage, this technique can be applied to existing MRI images. “This is particularly relevant, because it means we can use data obtained from existing scans in order to better visualize tissue damage,” says Zhang. “Physicians can do what they need to do in order to treat the patient and we can gain a wealth of additional information without the time or cost associated with performing another scan.” 

The potential applications for this technology are far-reaching. Zhang hopes her algorithm will one day prove beneficial for assessing the efficacy of treatment, or for testing new drugs. “If we can compare a scan from a patient prior to treatment with a new scan during treatment, the algorithm will give us a clear picture of the actual extent and location of repair.”

Analysis method could prove useful in assessing other brain diseases and injuries

In addition, Zhang believes this technique could also be applied in cases of other neurodegenerative diseases such as Alzheimer’s disease and even in concussion or other brain injury. 

“This study has confirmed that our technique is a sensitive tool,” says Zhang. “Now we know that tissue heterogeneity corresponds with damage and we can work on increasing the accuracy of the algorithm and exploring other potential applications for it.”

It’s a quick, non-invasive technique that Zhang hopes could one day become standard in the diagnosis and treatment of MS and other neurodegenerative disorders.

This study was funded by the Natural Sciences and Engineering Research Council of Canada (NSERC), MS Society of Canada, Alberta endMS Network, and the HBI MS Program. Collaborators include Drs. V. Wee Yong and Luanne Metz, co-directors of the HBI MS Program, and partners at the University of British Columbia.

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