Jiancheng Hou1, Arman Kulkarni2, Neelima Tellapragada1, Veena Nair1, Mitch Tyler2,3, Yuri Danilov3, Kurt Kaczmarek3, Beth Meyerand2, and Vivek Prabhakaran1
1Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States, 2Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States, 3Department of Kinesiology, University of Wisconsin-Madison, Madison, WI, United States
Synopsis
The main
conventional approach for treating traumatic brain injury related gait and
balance deficits has been through physical therapy, but few approaches have
focused on brain based rehabilitation efforts that create direct neuroplastic
changes. There remains a need for such an approach. Therefore, the goal of this
study was: 1) to apply Cranial Nerve Non-Invasive NeuroModulation (CN-NINM) via
the tongue in combination with multiple symptom-specific physical therapy exercises
in patients with mild to moderate TBI, and 2) to investigate and quantify gray
matter volume changes prior to and after intervention as well as their
correlation with behavior.
Introduction
The primary conventional
approach for treating traumatic brain injury (TBI) related symptoms of gait and
balance deficits is physical therapy. However, few studies have examined the
efficacy of brain based rehabilitation techniques that harness direct neuroplasticity
changes1.
There remains a need
for such an approach. One pilot TBI study suggested that, in the absence of
identifiable tissue damage, a combination of neurostimulation and
rehabilitation that is both targeted and challenging will induce neuroplastic
changes, reduce symptoms, and begin normalizing function2. These
changes include rehabilitation and re-establishment of movement control, and cognition.
Therefore, the goal of this study was: first, to apply Cranial Nerve
Non-Invasive NeuroModulation (CN-NINM) via the tongue in combination with multiple
symptom-specific physical therapy3 exercises in patients with mild
to moderate TBI, and second, to investigate and quantify gray matter volume
(GMV) changes from pre- to post-intervention and their correlation with
behavior. Methods
9 patients with TBI (at least one year post-injury, mean age =
53.11, SD = 6.60, 3 male and 6 female) were recruited. The CN-NINM intervention
training consisted of twice-daily in-lab training for two-weeks. The
participants also received physical exercise training to develop improved motor
coordination and mobility. Structural MRI scans on a 3T GE scanner were
collected using the FSPGR BRAVO sequence (TR = 8.132 ms, TE = 3.18 ms, TI = 450
ms) over a 256 x 256 matrix and 156 slices (flip angle = 12°, FOV = 25.6 cm,
slice thickness = 1 mm) before the first intervention (‘pre’) and then after the
final (‘post’) intervention session. At the same time, all participants completed
two tasks of Sensory Organization Test (SOT) and Dynamic Gait Index (DGI) before
and after the week of twice-daily interventions. SOT (NeuroCom International,
Clackamas OR, USA) is an objective, automated measure of sensory-motor
integration that evaluates the functional contribution of the somatosensory,
visual, and vestibular components of balance. DGI is a clinician-scored index
of eight facets of gait--normal walking, changing speed while walking, head
turns and up/down tilts while walking, turning and stopping, walking around and
stepping over objects, and traversing stairs4. Preprocessing for GMV
was performed using the Computational Anatomy Toolbox (CAT Version 12;
https://www.nitrc.org/projects/cat/) and SPM (Version 12) with MATLAB R2015a. Bias
field correction was applied to correct for MRI inhomogeneities; noise was
removed and voxel intensities were normalized5; brain tissue was
segmented and normalized into six different tissues classes (gray and white
matters, cerebrospinal fluid, bone, other soft tissues, and air/background)
using the modified unified segmentation approach implemented in SPM6.
Images were transformed nonlinearly to standard stereotaxic space of Montreal
Neurological Institute (MNI) and resliced to 2×2×2 mm using diffeomorphic
registration algorithm (DARTEL)7,8,9 to CAT12’s default template
(IXI555_MNI152)10,11. For GMV analysis, gray matter probability maps
were multiplied by the non-linear component of the Jacobian determinant, and
modulated gray matter probability maps were spatially smoothed with an 8 mm
full-width at half-maximum (FWHM) Gaussian kernel. The paired t-test analysis (pre vs. post interventions) was used for GMV data.
The statistical threshold was set to p
< .05 and cluster size > 212 using the AlphaSim multiple comparison
correction. Pearson r correlations
were used to examine the relation between changes in GMV (post- minus pre-intervention)
and changes in behavioral measures (SOT and DGI). The statistical package SPSS 22.0
was used for all analyses, p <
.05. Results
Paired t-test
results showed significant increase from pre- to post-intervention on both the
SOT and DGI. CN-NINM intervention induced multiple GMV increases within the
temporal, frontal, occipital lobes and cerebellum, as well as some GMV
decreases within the frontal and parietal lobes (Figure 1 and Table 1). Score
differences on both SOT and DGI were negatively correlated to all GMV
differences (Table 2). Discussion
These preliminary results suggest that overall there appears to be an
increase in GMV of regions and possibly increase in functionality of regions
involved in gait/posture/balance (cerebellum, associative areas in associative
temporal-occipital regions) and decrease in GMV and possibly decrease in
functionality of areas that were needed for compensation such as frontoparietal
areas involved in attention/executive function.Conclusions
Overall regions involved
in automatic processing of gait, balance and posture seemed to increase in GMV,
whereas compensatory regions that were needed for effortful processing such as
executive function and attention decreased in GMV. These results indicate
that CN-NINM may be a promising way to treat the symptoms of TBI.Acknowledgements
This work was supported by the National
Institute of Child Health and Human Development (grant number K12HD055894 to
SS), and pilot funding from the UW-Madison Department of Radiology R&D (to
SS) and the UW-Madison Department of Medicine (to SS), by the National Institute of Health (grant numbers
T32GM008692, UL1TR000427, T32EB011434). The content of this paper is solely the
responsibility of the authors and does not necessarily represent the official
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