Computing Science

Detecting brain development abnormalities in preterm babies

September 11, 2013
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Only July 10, Computing Science associate professor Ghassan Hamarneh was announced a semi-finalist in Johnson & Johnson Innovation’s Cognition Challenge. The challenge invited researchers and entrepreneurs from across Canada to submit solutions addressing problems of learning and memory related to Alzheimer's disease and cognitive disorders. Hamarneh’s project, PrediCog, proposes using diffusion MRI data to predict cognitive and clinical outcomes of preterm babies. The project was recognized as an outstanding submission, in the top four semi-finalists out of 45 total submissions.

Diffusion MRI maps the diffusion process of molecules in biological tissues. Hamarneh’s project proposes creating software that uses diffusion MRI datasets and connectivity patterns to quantify brain connectivity, revealing white matter abnormalities in premature infants. Hamarneh notes that half of all neurological disabilities in children, including Down syndrome, autism spectrum disorders and speech disorders, are related to premature birth. Using neuroimaging tools like diffusion MRI to explore the brain and detect abnormalities in development allows pediatric neuroradiologists to provide better prognosis, intervene earlier, and present families and caregivers with more effective rehabilitation options.

The project is a continuation of Hamarneh’s collaboration with clinical researchers at BC Children’s Hospital and Toronto’s Hospital for Sick Children, where researchers aim to detect brain injury that might occur in infants in the womb or at birth.

Johnson & Johnson Innovation partnered with its affiliate Janssen Research & Development, LLC, as well as the Consulate General of Canada to support the Cognition Challenge program. The collaboration was led by Johnson & Johnson’s California Innovation Center.

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