Helmet Technology, Head Impact Exposure, and Cortical Thinning Following a Season of High School Football.

The purpose of this study was to compare the effects of wearing older, lower-ranked football helmets (LRank) to wearing newer, higher-ranked football helmets (HRank) on pre- to post-season changes in cortical thickness in response to repetitive head impacts and assess whether changes in cortical thickness are associated with head impact exposure for either helmet type. 105 male high-school athletes (NHRank = 52, NLRank = 53) wore accelerometers affixed behind the left mastoid during all practices and games for one regular season of American football to monitor head impact exposure. Pre- and post-season magnetic resonance imaging (MRI) were completed to assess longitudinal changes in cortical thickness. Significant reductions in cortical thickness (i.e., cortical thinning) were observed pre- to post-season for each group, but these longitudinal alterations were not significantly different between the LRank and HRank groups. Further, significant group-by-head impact exposure interactions were observed when predicting changes in cortical thickness. Specifically, a greater frequency of high magnitude head impacts during the football season resulted in greater cortical thinning for the LRank group, but not for the HRank group. These data provide preliminary in vivo evidence that HRank helmets may provide a buffer between the specific effect of high magnitude head impacts on regional thinning by dissipating forces more evenly throughout the cortex. However, future research with larger sample sizes, increased longitudinal measures and additional helmet technologies is warranted to both expand upon and further validate the present study findings.

A Novel Approach to Evaluate Brain Activation for Lower Extremity Motor Control.

BACKGROUND AND PURPOSE: The purpose of this study was to assess the consistency of a novel MR safe lower extremity motor control neuroimaging paradigm to elicit reliable sensorimotor region brain activity. METHODS: Participants completed multiple sets of unilateral leg presses combining ankle, knee, and hip extension and flexion movements against resistance at a pace of 1.2 Hz while lying supine in a 3T MRI scanner. Regions of Interest (ROI) consisted of regions primarily involved in lower extremity motor control (right and left primary motor cortex, primary somatosensory cortex, premotor cortex, secondary somatosensory cortex, basal ganglia, and the cerebellum). RESULTS: The group analysis based on mixed effects paired samples t-test revealed no differences for brain activity between sessions (P > .05). Intraclass correlation coefficients in the sensorimotor regions were good to excellent for average percent signal change (.621 to .918) and Z-score (.697 to .883), with the exception of the left secondary somatosensory cortex percent signal change (.165). CONCLUSIONS: These results indicate that a loaded lower extremity force production and attenuation task that simulates the range of motion of squatting, stepping, and landing from a jump is reliable for longitudinal neuroimaging applications and support the use of this paradigm in further studies examining therapeutic interventions and changes in dynamic lower extremity motor function.

A novel method to generate dynamic boundary conditions for airway CFD by mapping upper airway movement with non-rigid registration of dynamic and static MRI.

Computational fluid dynamics (CFD) simulations of airflow in the human airways have the potential to provide a great deal of information that can aid clinicians in case management and surgical decision making, such as airway resistance, energy expenditure, airflow distribution, heat and moisture transfer, and particle deposition, as well as the change in each of these due to surgical interventions. However, the clinical relevance of CFD simulations has been limited to date, as previous models either did not incorporate neuromuscular motion or any motion at all. Many common airway pathologies, such as obstructive sleep apnea (OSA) and tracheomalacia, involve large movements of the structures surrounding the airway, such as the tongue and soft palate. Airway wall motion may be due to many factors including neuromuscular motion, internal aerodynamic forces, and external forces such as gravity. Therefore, to realistically model these airway diseases, a method is required to derive the airway wall motion, whatever the cause, and apply it as a boundary condition to CFD simulations. This paper presents and validates a novel method of capturing in vivo motion of airway walls from magnetic resonance images with high spatiotemporal resolution, through a novel combination of non-rigid image, surface, and surface-normal-vector registration. Coupled with image-synchronous pneumotachography, this technique provides the necessary boundary conditions for dynamic CFD simulations of breathing, allowing the effect of the airway's complex motion to be calculated for the first time, in both normal subjects and those with conditions such as OSA.