Traumatic brain injury (TBI) is common, affecting more than 1.7
million Americans each year.1
Survivors of TBI may be left with subsequent cognitive, emotional, and
behavioral changes that result in persistent disability and psychosocial/neuropsychiatric
impairment. Advanced MRI approaches,
including resting-state blood oxygen level dependent (BOLD) functional MRI (fMRI)
are further expanding our ability to understand normal brain organization and
the neurobiological basis of TBI. Of
particular interest in the clinical domain is the apparent ability of resting-state
fMRI to identify between-group differences in patients with head injury,
even when conventional imaging fails to detect brain abnormalities, suggesting that MRI measures
of functional connectivity may serve as future biomarkers of TBI.
One of the most commonly studied resting-state fMRI networks
associated with TBI is the default mode network (DMN), a neuronal system that
includes regions in medial parietal, lateral parietal, medial prefrontal, medial
temporal and lateral temporal cortices.2 Resting-state functional connectivity has
been shown to be significantly decreased between regions of the DMN across the
severity spectrum of TBI3-10, and has been associated with DTI evidence
of white matter damage within the DMN.11 In particular, patients
with TBI-associated disorders of consciousness have demonstrated decreases in
brain regions associated with the DMN.12 Furthermore, connectivity between the DMN posterior
cingulate cortex and medial prefrontal cortex has been shown to predict
emergence from coma.5 Several
studies have demonstrated alterations in task-induced DMN deactivation, with
attenuated or loss of normal anti-correlation between the DMN and other
networks across a range of TBI, from those with impaired consciousness13-14
to those with post-concussive sequelae.15-17 On the milder continuum of "subconcussive" TBI,
several studies of sports-related head impact exposure have demonstrated
abnormalities of DMN inter-network connectivity even in the absence of
clinically diagnosed concussion18-19, which were related to
abnormalities of cognitive performance.19 Recent studies have begun to investigate networks
beyond the DMN, exploring post-TBI phenotypes of brain functional connectivity
and outcomes following injury within the frontoparietal, salience, auditory,
sensorimotor and visual networks.12, 20
To date, resting-state fMRI has been utilized primarily for
research, demonstrating statistical differences between TBI and non-TBI groups.
The ability to interpret resting-state fMRI data from a single patient with TBI does not
presently exist in routine clinical practice. Several challenges for translating resting-state
fMRI into clinical tools for TBI include: 1) lack of large-scale age-stratified
fMRI data acquired from TBI and non-TBI subjects using standardized protocols
developed with consensus by clinical and research communities, 2) insufficient
data regarding patterns of injury that are predictive of clinical and
neuropsychological deficits, and 3) lack of sufficient data regarding standard
approaches to account for technical differences between clinical scanners that
may introduce artifactual false-positives or -negatives into an individual
patient assessment.21-22 Machine
learning classification paradigms applied to TBI-associated resting-state fMRI
features may be one approach to more rapid translation of advanced MRI
techniques into clinical practice.22
References
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