There is growing public concern about neurodegenerative changes (e.g., Chronic Traumatic Encephalopathy) that may occur chronically following clinically apparent and clinically silent (i.e., sub-concussive blows) pediatric mild traumatic brain injury (pmTBI). However, there are currently no biomarkers that clinicians can use to objectively diagnose patients or predict those who may struggle to recover. Non-invasive neuroimaging, electrophysiological and neuromodulation biomarkers have promise for providing evidence of the so-called "invisible wounds" of pmTBI. Our systematic review, however, belies that notion, identifying a relative paucity of high-quality, clinically impactful, diagnostic or prognostic biomarker studies in the sub-acute injury phase (36 studies on unique samples in 28 years), with the majority focusing on adolescent pmTBI. Ultimately, well-powered longitudinal studies with appropriate control groups, as well as standardized and clearly-defined inclusion criteria (time post-injury, injury severity and past history) are needed to truly understand the complex pathophysiology that is hypothesized (i.e., still needs to be determined) to exist during the acute and sub-acute stages of pmTBI and may underlie post-concussive symptoms.

OBJECTIVECervical spondylotic myelopathy (CSM) is a common cause of spinal cord dysfunction. Recently, it has been shown that diffusion tensor imaging (DTI) may be a better biomarker than T2-weighted signal intensity (T2SI) on MRI for CSM. However, there is very little literature on a comparison between the quantitative measurements of DTI and T2SI in the CSM patient population to determine disease severity and recovery.METHODSA prospective analysis of 46 patients with both preoperative DTI and T2-weighted MRI was undertaken. Normalized T2SI (NT2SI), regardless of the presence or absence of T2SI at the level of maximum compression (LMC), was determined by calculating the T2SI at the LMC/T2SI at the level of the foramen magnum. Regression analysis was performed to determine the relationship of fractional anisotropy (FA), a quantitative measure derived from DTI, and NT2SI individually as well their combination with baseline preoperative modified Japanese Orthopaedic Association (mJOA) score and ∆mJOA score at the 3-, 6-, 12-, and 24-month follow-ups. Goodness-of-fit analysis was done using residual diagnostics. In addition, mixed-effects regression analysis was used to evaluate the impact of FA and NT2SI individually. A p value < 0.05 was selected to indicate statistical significance.RESULTSRegression analysis showed a significant positive correlation between FA at the LMC and preoperative mJOA score (p = 0.041) but a significant negative correlation between FA at the LMC and the ΔmJOA score at the 12-month follow-up (p = 0.010). All other relationships between FA at the LMC and the baseline preoperative mJOA score or ∆mJOA score at the 3-, 6-, and 24-month follow-ups were not statistically significant. For NT2SI and the combination of FA and NT2SI, no significant relationships with preoperative mJOA score or ∆mJOA at 3, 6, and 24 months were seen on regression analysis. However, there was a significant correlation of combined FA and NT2SI with ∆mJOA score at the 12-month follow-up. Mixed-effects regression revealed that FA measured at the LMC was the only significant predictor of ΔmJOA score (p = 0.03), whereas NT2SI and time were not. Goodness-of-fit analysis did not show any evidence of lack of fit.CONCLUSIONSIn this large prospective study of CSM patients, FA at LMC appears to be a better biomarker for determining long-term outcomes following surgery in CSM patients than NT2SI or the combination values at LMC.

Functional magnetic resonance imaging (fMRI) studies have demonstrated alterations during task-induced brain activation in spinal cord injury (SCI) patients. The interruption to structural integrity of the spinal cord and the resultant disrupted flow of bidirectional communication between the brain and the spinal cord might contribute to the observed dynamic reorganization (neural plasticity). However, the effect of SCI on brain resting-state connectivity patterns remains unclear. We undertook a prospective resting-state fMRI (rs-fMRI) study to explore changes to cortical activation patterns following SCI. With institutional review board approval, rs-fMRI data was obtained in eleven patients with complete cervical SCI (>2 years post injury) and nine age-matched controls. The data was processed using the Analysis of Functional Neuroimages software. Region of interest (ROI) based analysis was performed to study changes in the sensorimotor network using pre- and post-central gyri as seed regions. Two-sampled t-test was carried out to check for significant differences between the two groups. SCI patients showed decreased functional connectivity in motor and sensory cortical regions when compared to controls. The decrease was noted in ipsilateral, contralateral, and interhemispheric regions for left and right precentral ROIs. Additionally, the left postcentral ROI demonstrated increased connectivity with the thalamus bilaterally in SCI patients. Our results suggest that cortical activation patterns in the sensorimotor network undergo dynamic reorganization following SCI. The presence of these changes in chronic spinal cord injury patients is suggestive of the inherent neural plasticity within the central nervous system.

There has been a recent call for longitudinal imaging studies to better characterize the time course of physiological recovery following sport‐related concussion (SRC) and its relationship with clinical recovery. To address this, we evaluated changes to resting‐state functional connectivity (rs‐FC) of the whole‐brain network following SRC and explored associations between rs‐FC and measures of clinical outcome. High school and collegiate football athletes were enrolled during preseason. Athletes that suffered SRC (N = 62) were assessed across the acute (within 48 hr) and sub‐acute (days 8, 15, and 45) phases. Matched football athletes without concussion served as controls (N = 60) and participated in similar visits. Multi‐band resting‐state fMRI was used to assess whole‐brain rs‐FC at each visit using network‐based statistic and average nodal strength from regions of interest defined using a common whole‐brain parcellation. Concussed athletes had elevated symptoms, psychological distress, and oculomotor, balance, and memory deficits at 48 hr postconcussion relative to controls, with diminished yet significant elevations in symptoms and psychological distress at 8 days. Both rs‐FC analyses showed that concussed athletes had a global increase in connectivity at 8 days postconcussion relative to controls, with no differences at the 48‐hr, 15‐day, or 45‐day visits. Further analysis revealed the group effect at the 8‐day visit was driven by the large minority of concussed athletes still symptomatic at their visit; asymptomatic concussed athletes did not differ from controls. Findings from this large‐scale, prospective study suggest whole‐brain rs‐FC alterations following SRC are delayed in onset but associated with the presence of self‐reported symptoms.

Large-scale network analysis characterizes the brain as a complex network of nodes and edges to evaluate functional connectivity patterns. The utility of graph-based techniques has been demonstrated in an increasing number of resting-state functional MRI (rs-fMRI) studies in the normal and diseased brain. However, to our knowledge, graph theory has not been used to study the reorganization pattern of resting-state brain networks in patients with traumatic complete spinal cord injury (SCI). In the present analysis, we applied a graph-theoretical approach to explore changes to global brain network architecture as a result of SCI. Fifteen subjects with chronic (> 2 years) complete (American Spinal Injury Association [ASIA] A) cervical SCI and 15 neurologically intact controls were scanned using rs-fMRI. The data were preprocessed followed by parcellation of the brain into 116 regions of interest (ROI) or nodes. The average time series was extracted at each node, and correlation analysis was performed between every pair of nodes. A functional connectivity matrix for each subject was then generated. Subsequently, the matrices were averaged across groups, and network changes were evaluated between groups using the network-based statistic (NBS) method. Our results showed decreased connectivity in a subnetwork of the whole brain in SCI compared with control subjects. Upon further examination, increased connectivity was observed in a subnetwork of the sensorimotor cortex and cerebellum network in SCI. In conclusion, our findings emphasize the applicability of NBS to study functional connectivity architecture in diseased brain states. Further, we show reorganization of large-scale resting-state brain networks in traumatic SCI, with potential prognostic and therapeutic implications.