Neuroimaging of the Injured Pediatric Brain: Methods and New Lessons.
Emily Larson DennisTalin BabikianChristopher C GizaPaul M ThompsonRobert F AsarnowPublished in: The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry (2018)
Traumatic brain injury (TBI) is a significant public health problem in the United States, especially for children and adolescents. Current epidemiological data estimate over 600,000 patients younger than 20 years are treated for TBI in emergency rooms annually. While many patients experience a full recovery, for others there can be long-lasting cognitive, neurological, psychological, and behavioral disruptions. TBI in youth can disrupt ongoing brain development and create added family stress during a formative period. The neuroimaging methods used to assess brain injury improve each year, providing researchers a more detailed characterization of the injury and recovery process. In this review, we cover current imaging methods used to quantify brain disruption post-injury, including structural magnetic resonance imaging (MRI), diffusion MRI, functional MRI, resting state fMRI, and magnetic resonance spectroscopy (MRS), with brief coverage of other methods, including electroencephalography (EEG), single-photon emission computed tomography (SPECT), and positron emission tomography (PET). We include studies focusing on pediatric moderate-severe TBI from 2 months post-injury and beyond. While the morbidity of pediatric TBI is considerable, continuing advances in imaging methods have the potential to identify new treatment targets that can lead to significant improvements in outcome.
Keyphrases
- resting state
- traumatic brain injury
- functional connectivity
- computed tomography
- magnetic resonance imaging
- positron emission tomography
- public health
- brain injury
- contrast enhanced
- newly diagnosed
- end stage renal disease
- severe traumatic brain injury
- ejection fraction
- prognostic factors
- mild traumatic brain injury
- subarachnoid hemorrhage
- white matter
- healthcare
- mental health
- depressive symptoms
- machine learning
- patient reported outcomes
- electronic health record
- high intensity
- big data
- pet imaging
- climate change