Effect of Patient Compliance With Treatment Recommendations on Clinical Outcomes in Chronic mTBI: A TEAM-TBI Study.

INTRODUCTION: Treatment approaches for mild traumatic brain injury (mTBI) have evolved to focus on active and targeted therapies, but the effect of compliance with therapy has not been investigated. The purpose of this study was to examine the role of patient compliance with prescribed therapies on clinical outcomes following mTBI. MATERIALS AND METHODS: Participants were aged 18-60 years with chronic (ie, 6+ months) mTBI symptoms who were previously recalcitrant (n = 66). Participants were diagnosed with a vestibular disorder and were prescribed vestibular and exertion therapies. Participants were instructed to continue the exercise regimen during the 6-month treatment phase at home. Participant compliance was evaluated by clinicians at patients' follow up visit as: (1) high, (2) moderate, or (3) low compliance based on patient report and clinician interview. High-compliance was compared to a combined low- and moderate-compliance group on the outcomes using a 2 (group) × 2 (time) analysis of variance. RESULTS: 39 of the 66 (59%) participants with vestibular disorder returned for a 6-month evaluation and were included in the analyses. Of these 39 participants, 16 (41%) were high-compliance (36.7 ± 10.9 years, 18.8% female), 17 (44%) were moderate-compliance (32.5 ± 5.5 years, 23.5% female), and 6 (15%) were low-compliance (32.7 ± 3.3 years, 0% female). CONCLUSION: High compliance significantly reduced total Vestibular/Ocular Motor Screening scores compared to low/middle compliance (P = .005). Post-Concussion Symptom Scale was reduced by 48% and dizziness symptoms reduced by 31% in the high-compliance cohort. High compliance with prescribed exertion/vestibular rehabilitation therapies enhanced clinical outcomes for previously recalcitrant patients with chronic mTBI-related vestibular disorders.

Deep Learning Estimation of Multi-Tissue Constrained Spherical Deconvolution with Limited Single Shell DW-MRI.

Diffusion-weighted magnetic resonance imaging (DW-MRI) is the only non-invasive approach for estimation of intra-voxel tissue microarchitecture and reconstruction of in vivo neural pathways for the human brain. With improvement in accelerated MRI acquisition technologies, DW-MRI protocols that make use of multiple levels of diffusion sensitization have gained popularity. A well-known advanced method for reconstruction of white matter microstructure that uses multi-shell data is multi-tissue constrained spherical deconvolution (MT-CSD). MT-CSD substantially improves the resolution of intra-voxel structure over the traditional single shell version, constrained spherical deconvolution (CSD). Herein, we explore the possibility of using deep learning on single shell data (using the b=1000 s/mm2 from the Human Connectome Project (HCP)) to estimate the information content captured by 8th order MT-CSD using the full three shell data (b=1000, 2000, and 3000 s/mm2 from HCP). Briefly, we examine two network architectures: 1.) Sequential network of fully connected dense layers with a residual block in the middle (ResDNN), 2.) Patch based convolutional neural network with a residual block (ResCNN). For both networks an additional output block for estimation of voxel fraction was used with a modified loss function. Each approach was compared against the baseline of using MT-CSD on all data on 15 subjects from the HCP divided into 5 training, 2 validation, and 8 testing subjects with a total of 6.7 million voxels. The fiber orientation distribution function (fODF) can be recovered with high correlation (0.77 vs 0.74 and 0.65) and low root mean squared error ResCNN:0.0124, ResDNN:0.0168 and sCSD:0.0323 as compared to the ground truth of MT-CST, which was derived from the multi-shell DW-MRI acquisitions. The mean squared error between the MT-CSD estimates for white matter tissue fraction and for the predictions are ResCNN:0.0249 vs ResDNN:0.0264. We illustrate the applicability of high definition fiber tractography on a single testing subject with arcuate and corpus callosum Tractography. In summary, the proposed approach provides a promising framework to estimate MT-CSD with limited single shell data. Source code and models have been made publicly available.

Impact of Multi-Disciplinary Care and Clinical Coach Coordinators on Participant Satisfaction and Retention in TBI Clinical Trials: A TEAM-TBI Study.

BACKGROUND: Targeted Evaluation Action and Monitoring of Traumatic Brain Injury (TEAM-TBI) is a monitored, multiple interventional research identifying clinical profiles and assigns individualized, evidence-based treatment program. The objective of the current study was to assess overall participant satisfaction of the multi-disciplinary care team and approach. METHODS: Between 2014 and 2017, 90 participants completed the 4-day TEAM-TBI clinical intake evaluation resulting in individualized treatment recommendations followed by a six-month intervention phase follow-up. Inclusion criteria were: age 18-60, history of chronic TBI (>6 months post-injury) with refractory clinical sequelae at screening (Post-Concussion Symptom Scale [PCSS] score >30). RESULTS: A total of 85/90 (94%) participants completed the survey at baseline focusing on intake evaluation and approach; 90% of eligible participants also completed the follow-up time-point. Hundred percent of participants had a mean score of >4 across all questions at the initial time point." CONCLUSIONS: The multi-disciplinary care approach and individualized treatment plans of the TEAM-TBI study yielded high participant retention and satisfaction scores. The Clinical Coach component of the trial was one of the highest rated aspects of the program and was associated with participant motivation and high retention rates.

Neural Correlates of Three Neurocognitive Intervention Strategies: A Preliminary Step Towards Personalized Treatment for Psychological Disorders.

Brain-based behavioral interventions targeting specific neurocognitive mechanisms show initial promise in the treatment of emotional disorders, but personalization of such approaches will be facilitated if brain targets are empirically established. As a preliminary step, we conducted a proof-of-concept study to test whether particular emotion regulatory neural circuitry can be differentially targeted by specific neurocognitive tasks, and whether these tasks effectively inhibit amygdala activity. Eleven healthy individuals underwent an idiographic sadness and guilt induction. Brain response was measured via fMRI during 4 subsequent emotion regulation conditions: fixation, cognitive reappraisal (selected to target the ventrolateral prefrontal cortex), working memory practice (selected to target the dorsolateral prefrontal cortex), and visual distraction (Tetris; selected to target occipital cortex). In whole-brain comparisons to fixation, hypotheses were upheld. Reappraisal uniquely activated left ventrolateral prefrontal cortex, working memory practice uniquely activated left dorsolateral prefrontal cortex, and Tetris uniquely activated bilateral occipitoparietal cortex, activations that were largely robust at the single-subject level. All tasks inhibited amygdala activity relative to fixation. Data support examining whether repeated exposure to these tasks in psychiatric patients affects neural abnormalities implicated in emotional disorders. Ideally, psychiatric treatment will be accelerated by matching specific treatments to patients with specific neural profiles.