ABSTRACT
Concussions represent a particular challenge for clinicians as no objective tests are available that can be used in diagnosis. In most neurological disorders, neuroimaging plays an important role in the assessment and management process. However, the current application of neuroimaging methods in the diagnosis of a concussion is limited to excluding more severe forms of injury. Recent advances in neuroimaging have shown atypical findings in persons with concussion suggesting that emerging methods may function in future concussion diagnosis protocols. This chapter provides an overview of emerging methods in concussion neuroimaging, specifically structural imaging, functional imaging, and metabolomics. A discussion is also provided regarding advanced computational methods including graph theory and machine learning, and how these methods may be used to inform clinical diagnosis. This chapter provides an overview of current research on concussion neuroimaging methods that potentially can be used in the future to make important concussion management decisions, including return-to-play.
