Mathematical Model Improves Brain Diagnoses
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| Courtesy of Ysangkok |
The ability to obtain accurate measurement of different brain tissues from MRI scan imagery is a step closer as new technology develops. Associate Professor Alan Liew from Griffith University’s School of Information, Communication Technology, has been working on computational algorithms which are important in the clinical diagnosis of brain conditions such as Alzheimer’s and Parkinson’s Disease.
Using this mathematical model, an MRI scanner can be used to accurately segment and measure different tissue classes. The data can then be used by a clinician as a diagnostic tool to compare the brain tissue of healthy patients.
“These computations will allow the accurate quantitative measurement of tissue volume, such as the brain’s grey matter, which is important for memory and other cognitive processes and is relevant to conditions including Alzheimer’s,” Associate Professor Liew said.
Currently, there is no way for a clinician to accurately obtain this information from an MRI scanning device.
“By using these algorithms, the clinician will be able to obtain quantitative measurements that can help both predict and monitor the rate of potential disease progression in designated increments.”
The research continues Associate Professor Liew’s development work which began in 2003 and was the focus of a 2010 $150,000 ARC Discovery Grant.
Although the technique has not yet been perfected and is undergoing further refinement, Associate Professor Liew said the ability for clinicians to use the technology in hospitals as a diagnostic tool is potentially only a few years away.
“Medical practitioners will not only have the opportunity to be able to plan patient treatment in advance for conditions such as Alzheimer’s and Parkinson’s, but there will also be other applications for the technology such as in the study of sleep disorders,” he said.
Preliminary research into this area also has shown that the computational modelling can be used to study MRI scans which can ascertain the brain tissue differences present in people with sleep disorders.
“Without the ability to obtain accurate measurements of the brain tissues by using these algorithms, again this type of comparison would not be possible,” Associate Professor Liew said.
