A multimodal biomarker for concussion identification, prognosis and management

• Published in: Computers in biology and medicine Vol. 102; pp. 95 - 103
• Main Authors: Jacquin, Arnaud, Kanakia, Saloni, Oberly, Doug, Prichep, Leslie S.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 01.11.2018; Elsevier Limited
• Subjects: Adolescents; Adults; Assessments; Biomarkers; Brain; Brain function index; Children; Classifier algorithms; Classifiers; Cognition; Cognitive ability; Colleges & universities; Community colleges; Concussion; Diagnosis; EEG; Electroencephalography; Electrophysiology of TBI; Enhanced BFI; Genetic algorithms; Head injuries; Injuries; Medical prognosis; Multidimensional methods; Neural networks; Neurocognitive assessments; Overtraining; Physiology; Quantitative brain activity; Recovery; Return to play; Schools; Secondary schools; Sport-related concussion; TBI; Traumatic brain injury; Vestibular system; Young adults; United States > US; Texas; Michigan; Concussion; Enhanced BFI; Classifier algorithms; Neurocognitive assessments; Electrophysiology of TBI; Quantitative brain activity; TBI; Sport-related concussion; Brain function index; Return to play
• ISSN: 0010-4825; 1879-0534
• DOI: 10.1016/j.compbiomed.2018.09.011

Prompt, accurate, objective assessment of concussion is crucial, particularly for children/adolescents and young adults. While there is currently no gold standard for the diagnosis of concussion, the importance of multidimensional/multimodal assessments has recently been emphasized. Concussed subjects (N = 177), matched controls (N = 187) and healthy volunteers (N = 204) represented a convenience sample of male and female subjects between the ages of 13 and 25 years, enrolled at 29 Colleges and 19 High Schools in the US. Subjects were tested at time of injury and at multiple time points during recovery. Assessments included EEG, neurocognitive tests and standard concussion assessment tools. Multimodal classifiers to maximally separate controls from concussed subjects with prolonged recovery (≥14 days) were derived using quantitative EEG, neurocognitive and vestibular measures, informed feature reduction and a Genetic Algorithm methodology for classifier derivation. The methodology protected against overtraining using an internal cross-validation framework. An enhanced multimodal Brain Function Index (eBFI) was derived from the classifier output and mapped to a percentile scale which expressed the index relative to non-injured controls. At time of injury eBFIs were significantly different between controls and concussed subjects with prolonged recovery, showing return to non-concussed levels at return-to-play plus 45 days. For the combined concussed population, and for the short recovery subjects, a more rapid recovery was seen. This multivariate, multimodal, objective index of brain function impairment can potentially be used, along with other tools, to aid in diagnosis, assessment, and tracking of recovery from concussion. •No gold standard exists for the assessment of Sport-Related Concussion (SRC).•An enhanced, objective, multimodal Brain Function Index (eBFI) can help assess SRC.•The eBFI can predict prolonged recovery from SRC.•The eBFI can be used to track brain function recovery to baseline from SRC.