Faculty Bibliography

BACKGROUND:The initial limited supply of COVID-19 vaccine in the U.S. presented significant allocation, distribution, and delivery challenges. Information that can assist health officials, hospital administrators and other decision makers with readily identifying who and where to target vaccine resources and efforts can improve public health response. OBJECTIVE:The objective of this project was to develop a publicly available geographical information system (GIS) web mapping tool that would assist North Carolina health officials readily identify high-risk, high priority population groups and facilities in the immunization decision making process. METHODS:Publicly available data were used to identify 14 key health and socio-demographic variables and 5 differing themes (social and economic status; minority status and language; housing situation; at risk population; and health status). Vaccine priority population index (VPI) scores were created by calculating a percentile rank for each variable over each N.C. Census tract. All Census tracts (N = 2,195) values were ranked from lowest to highest (0.0 to 1.0) with a non-zero population and mapped using ArcGIS. RESULTS:The VPI tool was made publicly available (https://enchealth.org/) during the pandemic to readily assist with identifying high risk population priority areas in N.C. for the planning, distribution, and delivery of COVID-19 vaccine. DISCUSSION/CONCLUSIONS:While health officials may have benefitted by using the VPI tool during the pandemic, a more formal evaluation process is needed to fully assess its usefulness, functionality, and limitations. CONCLUSION/CONCLUSIONS:When considering COVID-19 immunization efforts, the VPI tool can serve as an added component in the decision-making process.

Introduction: Quantifying upper extremity (UE) motor impairment after stroke is impractical, limiting our ability to tailor rehabilitation training in real time. The current gold-standard measure of impairment, the Fugl-Meyer Assessment (FMA), is time-consuming and requires a trained assessor. The FMA furthermore does not assess functional motions in real-world contexts, which is exactly where we aim our rehabilitation interventions. Here, we took initial steps to develop an approach to automatically quantify UE motor impairment during functional task performance.
Method(s): We studied 51 chronic stroke patients (28F:23M; 57.7 (21.3-84.3) years old; 28L:23R paretic; FMA 43.1 (8-65)).We recorded upper body motion with 9 inertial measurement units (IMUs) while patients performed the FMA and a functional task (moving an object on a horizontal 8-target array). We trained a long short-term memory (LSTM) deep learning model to estimate FMA scores from the recorded motion (training set n=40; test set n=11; 4 LSTM layers with between-layer batch normalization; IMU data windows of 4s with slide of 1s). LSTM-generated impairment scores were computed from FMA motions or from functional motions. To ascertain the accuracy of the approach, we calculated the root mean square error (RMSE) and the Spearman correlation coefficient (rho) between the LSTM scores and the FMA scores from a trained expert. We also examined whether the performance of particular classes of functional primitives (i.e. reach, transport, or reposition) would be sufficient to accurately estimate impairment.
Result(s): Using motions from the FMA performance, our approach estimated FMA scores within 1.1 points of a trained assessor. Using motions from the functional task performance, our approach estimated FMA scores within 1.6 points. Correlation values between the FMA scores and LSTM scores were rho = 0.98 for FMA motions and rho = 0.96 for functional motions. Among the three functional primitives, reaches were the most informative for estimating the impairment scores (RMSE: 1.9 points), followed by transports (RMSE: 2.1 points), and repositions (RMSE: 2.8 points).
Discussion(s): We present a new approach that uses sensor-based motion capture and deep learning to automatically estimate UE motor impairment. This approach has high accuracy and shows high concurrent validity with the FMA, even when it assesses unrelated functional motions. Thus, it may be possible to directly measure impairment from performance of real-world functional tasks, which the FMA does not offer. Estimating impairment during stroke rehabilitation would enable clinicians to tailor treatment strategy in real time.

The objective is to quantitatively assess surgical outcomes in epilepsy patients who underwent scanning at 7T MRI whose lesions were undetectable at conventional field strengths (1.5T/3T). 16 patients who underwent an initial 1.5T/3T scan that was marked as non-lesional by a neuroradiologist and were candidates for epilepsy surgery were scanned at 7T. The 7T findings were evaluated by an expert neuroradiologist blinded to the suspected seizure onset zone (sSOZ). The relation of the neuroradiologist's findings compared with the sSOZ was classified as non-definite (no 7T lesion or lesion of no epileptogenic significance, or lesion of epileptogenic potential which localizes to the patient's sSOZ but is not the definitive cause), or definite (7T lesion of epileptogenic potential that highly localizes to the sSOZ and is confirmed through surgical intervention).. Each patient underwent neurosurgical intervention and postoperative Engel outcomes were obtained through retrospective chart review by an epileptologist. Of the 16 patients, 7 had imaging findings of definite epileptogenic potential at 7T while 9 had non-definite imaging findings. 15 out of 16 patients had Engel I, II, or III outcomes indicating worthwhile improvement. Patients with definite lesion status achieved Engel I surgical outcomes at higher rates (57.1%) than patients with non-definite lesion status (33.3%). Patients with normal clinical diagnostic scans at lower field strengths who have definite radiological findings on 7T corresponding to the sSOZ may experience worthwhile improvement from surgical intervention.

Background: Fatigue is among the most frequent and disabling symptoms in RMS patients.
Objective(s): To measure multiple sclerosis (MS) fatigue and its impact on daily life in a real-world population using a survey including the relapsing MS (RMS)-specific Fatigue Symptoms and Impacts Questionnaire-Relapsing Multiple Sclerosis (FSIQ-RMS).
Method(s): This is an ongoing noninterventional prospective study of RMS patients recruited across the USA via an online survey. Participants completed questionnaires including disease history, disease status, sleep, social and emotional functioning, and the FSIQ-RMS, administered daily for 7 days. The FSIQ-RMS measures self-reported fatigue, and scores range from 0-100 (higher score = greater severity). The impact of fatigue on several aspects of patient's life was rated from 0 (no impact) to 10 (very high impact).
Result(s): A total of 300 RMS participants completed the 7-day assessment: mean age: 43.0 yrs; 88% women; mean diagnosis age: 32 yrs. Fatigue was reported as the symptom with the greatest impact on daily functioning. Participants with lower disability rated fatigue as the most impactful symptom on daily life. Fatigue was rated as severe, with a mean score: 57.3 for the FSIQ-RMS symptom domain; 3 impact sub-domain scores were 42.3, 43.4 and 50.1 (physical, cognitive/emotional, and coping). Fatigue severity did not vary among patients receiving high efficacy disease modifying therapy (DMT) vs other DMTs (44% [n=111] vs 56% [n=143], with score of 57.8?}17.6 vs 55.9?}19.8). Impact of ability to perform daily activities was rated as the highest (6.9/10) in terms of impact on patient's life. Because of MS, 44% of participants did not work. Among those who were working currently (48%), the impact of fatigue on professional life was rated as 4.5/10. Nearly half of the participants (49% of 300) discussed fatigue at each visit with their neurologists and 35% discussed at most visits, with 'impact of fatigue on quality of life' being the most discussed topic (65% of 289). Participants used different approaches to manage their fatigue including avoided heat exposure (77%), took breaks (65%), managed their energy (59%), took non-medicinal products (58%); however, only 6% (of 293) were totally satisfied with these strategies.
Conclusion(s): In this survey including the novel RMS specific FSIQ-RMS, fatigue occurred in most MS participants and adversely influenced patient's daily functioning and life. Fatigue remains a major concern for those with MS

Undiagnosed concussions increase the risk of additional concussion and persistent symptoms from concussion. Because there are no reliable objective markers of concussion, self-reporting of subjective and non-visible symptoms are critical to ensuring proper concussion management. For this reason, educational interventions target concussion reporting, but the majority of studies have examined the efficacy of single educational interventions or compared interventions to one another. This randomized crossover study sought to identify whether there was benefit to administering multiple concussion education programs in tandem, back to back. The study randomized 313 male high school football players to first receive CrashCourse concussion education (CC) or Centers for Disease Control and Prevention video concussion education (CDC) followed by crossover with the other education. Athlete concussion-reporting intention, attitudes, subjective norms, perceived behavioral control, and enjoyment of education were assessed at baseline and after each intervention. There were statistically significant improvements across all measures, both after single intervention and crossover (all p < 0.001). Secondary analyses examining differences between education found that athletes reported higher enjoyment of concussion education immediately after participating in CC, as compared to CDC (p < 0.001). These findings demonstrate an additive benefit to implementing CC and CDC education in tandem, without decrement in enjoyment of concussion education after experiencing dual educations; in fact, enjoyment of concussion education improved after receiving education programs back to back. These educational programs appear to complement one another, and the results support the use of multi-modal concussion education to differentially target and maximize concussion reporting.

The WU-Minn Human Connectome Project (HCP) is a publicly-available dataset containing state-of-art structural, functional, and diffusion-MRI for over a thousand healthy subjects. While the planned scope of the HCP included an anatomical connectome, resting-state functional-MRI forms the bulk of the HCP's current connectomic output. We address this by presenting a full-cortex connectome derived from probabilistic diffusion tractography and organized into the HCP-MMP1.0 atlas. Probabilistic methods and large sample sizes are preferable for whole-connectome mapping as they increase the fidelity of traced low-probability connections. We find that overall, connection strengths are lognormally distributed and decay exponentially with tract length, that connectivity reasonably matches macaque histological tracing in homologous areas, that contralateral homologs and left-lateralized language areas are hyperconnected, and that hierarchical similarity influences connectivity. We compare the diffusion-MRI connectome to existing resting-state fMRI and cortico-cortico evoked potential connectivity matrices and find that it is more similar to the latter. This work helps fulfill the promise of the HCP and will make possible comparisons between the underlying structural connectome and functional connectomes of various modalities, brain states, and clinical conditions.Significance Statement The tracts between cortical parcels can be estimated from diffusion MRI, but most studies concentrate on only the largest connections. Here we present an atlas, the largest and most detailed of its kind, showing connections among all cortical parcels. Connectivity is relatively enhanced between frontotemporal language areas and homologous contralateral locations. We find that connectivity decays with fiber tract distance more slowly than predicted by brain volume and that structural and stimulation-derived connectivity are more similar to each other than to resting-state functional MRI correlations. The connectome presented is publicly available and organized into a commonly used scheme for defining brain areas in order to enable ready comparison to other brain imaging datasets of various modalities.