More than a third of stroke patients experience aphasia, a disorder that interferes with patients’ ability to speak, listen, read, and/or write. In some patients, symptoms resolve, but in others the effects on quality of life are devastating. Currently, physicians cannot reliably predict which patients will recover or which therapies will help them to do so.
A new collaborative initiative by MUSC, the University of South Carolina, Johns Hopkins University, and the University of California Irvine is attempting to change that. They comprise the Center for the Study of Aphasia Recovery, which was launched in 2016 by Julius Fridriksson, Ph.D., of the University of South Carolina with $11.1 million in funding (over five years) from the National Institutes of Health.
The center aims to lay the foundation for individualized aphasia care, in which patients will receive the most appropriate treatment to address their specific stroke signature. Together, the four research sites will be able to recruit hundreds of patients with aphasia for the study. “Once finished, this is going to be the largest study of aphasia recovery in the past couple of decades,” said Fridriksson.
A long-time collaborator of Fridriksson, MUSC Health neurologist Leonardo Bonilha, M.D., Ph.D., one of the principal investigators of the MUSC research site, is exploring whether disruptions to white matter connectivity after stroke affect language abilities. White matter fiber tracts are the insulated wires that connect one area of the brain to others. Currently, structural MRI is used after stroke to assess lesions in the cortical tissue — the brain’s grey matter. However, the extent of cortical damage often does not correlate with the severity of language deficits.
In the June 22, 2016 Journal of Neuroscience, Bonilha and his MUSC and USC collaborators reported findings suggesting that imaging all of the brain’s connections (i.e., the connectome) in addition to imaging only the areas of cortical damage can help determine which patients will have language deficits, how severe those deficits will be, and how much potential there will be for recovery. This information could then be used to direct rehabilitative therapy to improve outcomes.