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- W2616136281 abstract "Abstract Sports‐related concussions lead to persistent anomalies of the brain structure and function that interact with the effects of normal ageing. Although post‐mortem investigations have proposed a bio‐signature of remote concussions, there is still no clear in vivo signature. In the current study, we characterized white matter integrity in retired athletes with a history of remote concussions by conducting a full‐brain, diffusion‐based connectivity analysis. Next, we combined MRI diffusion markers with MR spectroscopic, MRI volumetric, neurobehavioral and genetic markers to identify a multidimensional in vivo signature of remote concussions. Machine learning classifiers trained to detect remote concussions using this signature achieved detection accuracies up to 90% (sensitivity: 93%, specificity: 87%). These automated classifiers identified white matter integrity as the hallmark of remote concussions and could provide, following further validation, a preliminary unbiased detection tool to help medical and legal experts rule out concussion history in patients presenting or complaining about late‐life abnormal cognitive decline." @default.
- W2616136281 created "2017-05-26" @default.
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- W2616136281 creator A5087237906 @default.
- W2616136281 date "2017-05-16" @default.
- W2616136281 modified "2023-10-09" @default.
- W2616136281 title "Defining a multimodal signature of remote sports concussions" @default.
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- W2616136281 doi "https://doi.org/10.1111/ejn.13583" @default.
- W2616136281 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/28512863" @default.
- W2616136281 hasPublicationYear "2017" @default.
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