Cognitive impairment in asymptomatic carotid artery stenosis is associated with abnormal segments in the Circle of Willis.

OBJECTIVE: Our group has previously demonstrated that patients with asymptomatic carotid artery stenosis (ACAS) demonstrate cognitive impairment. One proposed mechanism for cognitive impairment in patients with ACAS is cerebral hypoperfusion due to flow-restriction. We tested whether the combination of a high-grade carotid stenosis and inadequate cross-collateralization in the Circle of Willis (CoW) resulted in worsened cognitive impairment. METHODS: Twenty-four patients with high-grade (≥70% diameter-reducing) ACAS underwent carotid duplex ultrasound, cognitive assessment, and 3D time-of-flight magnetic resonance angiography. The cognitive battery consisted of nine neuropsychological tests assessing four cognitive domains: learning and recall, attention and working memory, motor and processing speed, and executive function. Raw cognitive scores were converted into standardized T-scores. A structured interpretation of the magnetic resonance angiography images was performed with each segment of the CoW categorized as being either normal or abnormal. Abnormal segments of the CoW were defined as segments characterized as narrowed or occluded due to congenital aplasia or hypoplasia, or acquired atherosclerotic stenosis or occlusion. Linear regression was used to estimate the association between the number of abnormal segments in the CoW, and individual cognitive domain scores. Significance was set to P < .05. RESULTS: The mean age of the patients was 66.1 ± 9.6 years, and 79.2% (n = 19) were male. A significant negative association was found between the number of abnormal segments in the CoW and cognitive scores in the learning and recall (ß = -6.5; P = .01), and attention and working memory (ß = -7.0; P = .02) domains. There was a trend suggesting a negative association in the motor and processing speed (ß = -2.4; P = .35) and executive function (ß = -4.5; P = .06) domains that did not reach significance. CONCLUSIONS: In patients with high-grade ACAS, the concomitant presence of increasing occlusive disease in the CoW correlates with worse cognitive function. This association was significant in the learning and recall and attention and working memory domains. Although motor and processing speed and executive function also declined numerically with increasing abnormal segments in the CoW, the relationship was not significant. Since flow restriction at a carotid stenosis compounded by inadequate collateral compensation across a diseased CoW worsens cerebral perfusion, our findings support the hypothesis that cerebral hypoperfusion underlies the observed cognitive impairment in patients with ACAS.

Clinical risk prediction using language models: benefits and considerations.

OBJECTIVE: The use of electronic health records (EHRs) for clinical risk prediction is on the rise. However, in many practical settings, the limited availability of task-specific EHR data can restrict the application of standard machine learning pipelines. In this study, we investigate the potential of leveraging language models (LMs) as a means to incorporate supplementary domain knowledge for improving the performance of various EHR-based risk prediction tasks. METHODS: We propose two novel LM-based methods, namely "LLaMA2-EHR" and "Sent-e-Med." Our focus is on utilizing the textual descriptions within structured EHRs to make risk predictions about future diagnoses. We conduct a comprehensive comparison with previous approaches across various data types and sizes. RESULTS: Experiments across 6 different methods and 3 separate risk prediction tasks reveal that employing LMs to represent structured EHRs, such as diagnostic histories, results in significant performance improvements when evaluated using standard metrics such as area under the receiver operating characteristic (ROC) curve and precision-recall (PR) curve. Additionally, they offer benefits such as few-shot learning, the ability to handle previously unseen medical concepts, and adaptability to various medical vocabularies. However, it is noteworthy that outcomes may exhibit sensitivity to a specific prompt. CONCLUSION: LMs encompass extensive embedded knowledge, making them valuable for the analysis of EHRs in the context of risk prediction. Nevertheless, it is important to exercise caution in their application, as ongoing safety concerns related to LMs persist and require continuous consideration.

A Sonomyography-Based Muscle Computer Interface for Individuals With Spinal Cord Injury.

Impairment of hand functions in individuals with spinal cord injury (SCI) severely disrupts activities of daily living. Recent advances have enabled rehabilitation assisted by robotic devices to augment the residual function of the muscles. Traditionally, electromyography-based muscle activity sensing interfaces have been utilized to sense volitional motor intent to drive robotic assistive devices. However, the dexterity and fidelity of control that can be achieved with electromyography-based control have been limited due to inherent limitations in signal quality. We have developed and tested a muscle-computer interface (MCI) utilizing sonomyography to provide control of a virtual cursor for individuals with motor-incomplete spinal cord injury. We demonstrate that individuals with SCI successfully gained control of a virtual cursor by utilizing contractions of muscles of the wrist joint. The sonomyography-based interface enabled control of the cursor at multiple graded levels demonstrating the ability to achieve accurate and stable endpoint control. Our sonomyography-based muscle-computer interface can enable dexterous control of upper-extremity assistive devices for individuals with motor-incomplete SCI.

Negative Urgency Linked to Craving and Substance Use Among Adults on Buprenorphine or Methadone.

Despite the effectiveness of medication-assisted treatment (MAT), adults receiving MAT experience opioid cravings and engage in non-opioid illicit substance use that increases the risk of relapse and overdose. The current study examines whether negative urgency, defined as the tendency to act impulsively in response to intense negative emotion, is a risk factor for opioid cravings and non-opioid illicit substance use. Fifty-eight adults (predominately White cis-gender females) receiving MAT (with buprenorphine or methadone) were recruited from online substance use forums and asked to complete self-report questionnaires on negative urgency (UPPS-P Impulsive Behavior Scale), past 3-month opioid cravings (ASSIST-Alcohol, Smoking, and Substance Involvement Screening Test), and non-opioid illicit substance use (e.g., amphetamines, cocaine, benzodiazepines). Results revealed that negative urgency was associated with past 3-month opioid cravings, as well as past month illicit stimulant use (not benzodiazepine use). These results may indicate that individuals high in negative urgency would benefit from receiving extra intervention during MAT.

A Comparison of Approaches for Segmenting the Reaching and Targeting Motion Primitives in Functional Upper Extremity Reaching Tasks.

There is growing interest in the kinematic analysis of human functional upper extremity movement (FUEM) for applications such as health monitoring and rehabilitation. Deconstructing functional movements into activities, actions, and primitives is a necessary procedure for many of these kinematic analyses. Advances in machine learning have led to progress in human activity and action recognition. However, their utility for analyzing the FUEM primitives of reaching and targeting during reach-to-grasp and reach-to-point tasks remains limited. Domain experts use a variety of methods for segmenting the reaching and targeting motion primitives, such as kinematic thresholds, with no consensus on what methods are best to use. Additionally, current studies are small enough that segmentation results can be manually inspected for correctness. As interest in FUEM kinematic analysis expands, such as in the clinic, the amount of data needing segmentation will likely exceed the capacity of existing segmentation workflows used in research laboratories, requiring new methods and workflows for making segmentation less cumbersome. This paper investigates five reaching and targeting motion primitive segmentation methods in two different domains (haptics simulation and real world) and how to evaluate these methods. This work finds that most of the segmentation methods evaluated perform reasonably well given current limitations in our ability to evaluate segmentation results. Furthermore, we propose a method to automatically identify potentially incorrect segmentation results for further review by the human evaluator. Clinical impact: This work supports efforts to automate aspects of processing upper extremity kinematic data used to evaluate reaching and grasping, which will be necessary for more widespread usage in clinical settings.

Clinical, Safety and Engineering Perspectives on Wearable Ultrasound Technology: A Review.

Wearable ultrasound has the potential to become a disruptive technology enabling new applications not only in traditional clinical settings, but also in settings where ultrasound is not currently used. Understanding the basic engineering principles and limitations of wearable ultrasound is critical for clinicians, scientists, and engineers to advance potential applications and translate the technology from bench to bedside. Wearable ultrasound devices, especially monitoring devices, have the potential to apply acoustic energy to the body for far longer durations than conventional diagnostic ultrasound systems. Thus, bioeffects associated with prolonged acoustic exposure as well as skin health need to be carefully considered for wearable ultrasound devices. This paper reviews emerging clinical applications, safety considerations, and future engineering and clinical research directions for wearable ultrasound technology.

A model for personalized diagnostics for non-specific low back pain: the role of the myofascial unit.

Low back pain (LBP) is the leading cause of disability worldwide. Most LBP is non-specific or idiopathic, which is defined as symptoms of unknown origin without a clear specific cause or pathology. Current guidelines for clinical evaluation are based on ruling out underlying serious medical conditions, but not on addressing underlying potential contributors to pain. Although efforts have been made to identify subgroups within this population based on response to treatment, a comprehensive framework to guide assessment is still lacking. In this paper, we propose a model for a personalized mechanism-based assessment based on the available evidence that seeks to identify the underlying pathologies that may initiate and perpetuate central sensitization associated with chronic non-specific low back pain (nsLBP). We propose that central sensitization can have downstream effects on the "myofascial unit", defined as an integrated anatomical and functional structure that includes muscle fibers, fascia (including endomysium, perimysium and epimysium) and its associated innervations (free nerve endings, muscle spindles), lymphatics, and blood vessels. The tissue-level abnormalities can be perpetuated through a vicious cycle of neurogenic inflammation, impaired fascial gliding, and interstitial inflammatory stasis that manifest as the clinical findings for nsLBP. We postulate that our proposed model offers biological plausibility for the complex spectrum of clinical findings, including tissue-level abnormalities, biomechanical dysfunction and postural asymmetry, ecological and psychosocial factors, associated with nsLBP. The model suggests a multi-domain evaluation that is personalized, feasible and helps rule out specific causes for back pain guiding clinically relevant management. It may also provide a roadmap for future research to elucidate mechanisms underlying this ubiquitous and complex problem.

Evidence for an association of serum microanalytes and myofascial pain syndrome.

BACKGROUND: Myofascial Pain Syndrome (MPS) is a common pain disorder. Diagnostic criteria include physical findings which are often unreliable or not universally accepted. A precise biosignature may improve diagnosis and treatment effectiveness. The purpose of this study was to assess whether microanalytic assays significantly correlate with characteristic clinical findings in people with MPS. METHODS: This descriptive, prospective study included 38 participants (25 women) with greater than 3 months of myofascial pain in the upper trapezius. Assessments were performed at a university laboratory. The main outcome measures were the Beighton Index, shoulder range of motion, strength asymmetries and microanalytes: DHEA, Kynurenine, VEGF, interleukins (IL-1b, IL-2, IL-4, IL-5, IL-7, IL-8, IL-13), growth factors (IGF-1, IGF2, G-CSF, GM-CSF), MCP-1, MIP-1b, BDNF, Dopamine, Noradrenaline, NPY, and Acetylcholine. Mann-Whitney test and Spearman's multivariate correlation were applied for all variables. The Spearman's analysis results were used to generate a standard correlation matrix and heat map matrix. RESULTS: Mean age of participants was 32 years (20-61). Eight (21%) had widespread pain (Widespread Pain Index ≥ 7). Thirteen (34%) had MPS for 1-3 years, 14 (37%) 3-10 years, and 11 (29%) for > 10 years. The following showed strong correlations: IL1b,2,4,5,7,8; GM-CSF and IL 2,4,5,7; between DHEA and BDNF and between BDNF and Kynurenine, NPY and acetylcholine. The heat map analysis demonstrated strong correlations between the Beighton Index and IL 5,7, GM-CSF, DHEA. Asymmetries of shoulder and cervical spine motion and strength associated with select microanalytes. CONCLUSION: Cytokine levels significantly correlate with selected clinical assessments. This indirectly suggests possible biological relevance for understanding MPS. Correlations among some cytokine clusters; and DHEA, BDNF kynurenine, NPY, and acetylcholine may act together in MPS. These findings should be further investigated for confirmation that link these microanalytes with select clinical findings in people with MPS.

Using principles of motor control to analyze performance of human machine interfaces.

There have been significant advances in biosignal extraction techniques to drive external biomechatronic devices or to use as inputs to sophisticated human machine interfaces. The control signals are typically derived from biological signals such as myoelectric measurements made either from the surface of the skin or subcutaneously. Other biosignal sensing modalities are emerging. With improvements in sensing modalities and control algorithms, it is becoming possible to robustly control the target position of an end-effector. It remains largely unknown to what extent these improvements can lead to naturalistic human-like movement. In this paper, we sought to answer this question. We utilized a sensing paradigm called sonomyography based on continuous ultrasound imaging of forearm muscles. Unlike myoelectric control strategies which measure electrical activation and use the extracted signals to determine the velocity of an end-effector; sonomyography measures muscle deformation directly with ultrasound and uses the extracted signals to proportionally control the position of an end-effector. Previously, we showed that users were able to accurately and precisely perform a virtual target acquisition task using sonomyography. In this work, we investigate the time course of the control trajectories derived from sonomyography. We show that the time course of the sonomyography-derived trajectories that users take to reach virtual targets reflect the trajectories shown to be typical for kinematic characteristics observed in biological limbs. Specifically, during a target acquisition task, the velocity profiles followed a minimum jerk trajectory shown for point-to-point arm reaching movements, with similar time to target. In addition, the trajectories based on ultrasound imaging result in a systematic delay and scaling of peak movement velocity as the movement distance increased. We believe this is the first evaluation of similarities in control policies in coordinated movements in jointed limbs, and those based on position control signals extracted at the individual muscle level. These results have strong implications for the future development of control paradigms for assistive technologies.

Using Principles of Motor Control to Analyze Performance of Human Machine Interfaces.

There have been significant advances in biosignal extraction techniques to drive external biomechatronic devices or to use as inputs to sophisticated human machine interfaces. The control signals are typically derived from biological signals such as myoelectric measurements made either from the surface of the skin or subcutaneously. Other biosignal sensing modalities are emerging. With improvements in sensing modalities and control algorithms, it is becoming possible to robustly control the target position of a end effector. It remains largely unknown to what extent these improvements can lead to naturalistic human-like movement. In this paper, we sought to answer this question. We utilized a sensing paradigm called sonomyography based on continuous ultrasound imaging of forearm muscles. Unlike myoelectric control strategies which measure electrical activation and use the extracted signals to determine the velocity of an end-effector; sonomyography measures muscle deformation directly with ultrasound and uses the extracted signals to proportionally control the position of an end-effector. Previously, we showed that users were able to accurately and precisely perform a virtual target acquisition task using sonomyography. In this work, we investigate the time course of the control trajectories derived from sonomyography. We show that the time course of the sonomyography-derived trajectories that users take to reach virtual targets reflect the trajectories shown to be typical for kinematic characteristics observed in biological limbs. Specifically, during a target acquisition task, the velocity profiles followed a minimum jerk trajectory shown for point-to-point arm reaching movements, with similar time to target. In addition, the trajectories based on ultrasound imaging result in a systematic delay and scaling of peak movement velocity as the movement distance increased. We believe this is the first evaluation of similarities in control policies in coordinated movements in jointed limbs, and those based on position control signals extracted at the individual muscle level. These results have strong implications for the future development of control paradigms for assistive technologies.

Relationships between surrogate measures of mechanical and psychophysiological load, patellar tendon adaptations, and neuromuscular performance in NCAA division I men's volleyball athletes.

Introduction: Patellar tendon adaptations occur in response to mechanical load. Appropriate loading is necessary to elicit positive adaptations with increased risk of injury and decreased performance likely if loading exceeds the capacity of the tendon. The aim of the current study was to examine intra-individual associations between workloads and patellar tendon properties and neuromuscular performance in collegiate volleyball athletes. Methods: National Collegiate Athletics Association Division I men's volleyball athletes (n = 16, age: 20.33 ± 1.15 years, height: 193.50 ± 6.50 cm, body mass: 84.32 ± 7.99 kg, bodyfat%: 13.18 ± 4.72%) competing across 9 weeks of in-season competition participated. Daily measurements of external workloads (i.e., jump count) and internal workloads [i.e., session rating of perceived exertion (sRPE)] were recorded. Weekly measurements included neuromuscular performance assessments (i.e., countermovement jump, drop jump), and ultrasound images of the patellar tendon to evaluate structural adaptations. Repeated measures correlations (r-rm) assessed intra-individual associations among performance and patellar tendon metrics. Results: Workload measures exhibited significant negative small to moderate (r-rm =-0.26-0.31) associations with neuromuscular performance, negative (r-rm = -0.21-0.30), and positive (r-rm = 0.20-0.32) small to moderate associations with patellar tendon properties. Discussion: Monitoring change in tendon composition and performance adaptations alongside workloads may inform evidence-based frameworks toward managing and reducing the risk of the development of patellar tendinopathy in collegiate men's volleyball athletes.

Exploring county-level spatio-temporal patterns in opioid overdose related emergency department visits.

Opioid overdoses within the United States continue to rise and have been negatively impacting the social and economic status of the country. In order to effectively allocate resources and identify policy solutions to reduce the number of overdoses, it is important to understand the geographical differences in opioid overdose rates and their causes. In this study, we utilized data on emergency department opioid overdose (EDOOD) visits to explore the county-level spatio-temporal distribution of opioid overdose rates within the state of Virginia and their association with aggregate socio-ecological factors. The analyses were performed using a combination of techniques including Moran's I and multilevel modeling. Using data from 2016-2021, we found that Virginia counties had notable differences in their EDOOD visit rates with significant neighborhood-level associations: many counties in the southwestern region were consistently identified as the hotspots (areas with a higher concentration of EDOOD visits) whereas many counties in the northern region were consistently identified as the coldspots (areas with a lower concentration of EDOOD visits). In most Virginia counties, EDOOD visit rates declined from 2017 to 2018. In more recent years (since 2019), the visit rates showed an increasing trend. The multilevel modeling revealed that the change in clinical care factors (i.e., access to care and quality of care) and socio-economic factors (i.e., levels of education, employment, income, family and social support, and community safety) were significantly associated with the change in the EDOOD visit rates. The findings from this study have the potential to assist policymakers in proper resource planning thereby improving health outcomes.

Sonomyography shows feasibility as a tool to quantify joint movement at the muscle level.

Several methods have been used to quantify human movement at different levels, from coordinated multi joint movements to those taking place at the single muscle level. These methods are developed either in order to allow us to interact with computers and machines, or to use such technologies for aiding rehabilitation among those with mobility impairments or movement disorders. Human machine interfaces typically rely on some existing human movement ability and measure it using motion tracking or inertial measurement units, while the rehabilitation applications may require us to measure human motor intent. Surface or implanted electrodes, electromyography, electroencephalography, and brain computer interfaces are beneficial in this regard, but have their own shortcomings. We have previously shown feasibility of using ultrasound imaging (Sonomyography) to infer human motor intent and allow users to control external biomechatronic devices such as prosthetics. Here, we asked users to freely move their hand in three different movement patterns, measuring their actual joint angles and passively computing their Sonomyographic output signal. We found a high correlation between these two signals, demonstrating that the Sonomyography signal is not only user-controlled and stable, but it is closely linked with the user's actual movement level. These results could help design wearable rehabilitation or human computer interaction devices based on Sonomyography to decode human motor intent.

First Demonstration of Functional Task Performance Using a Sonomyographic Prosthesis: A Case Study.

Ultrasound-based sensing of muscle deformation, known as sonomyography, has shown promise for accurately classifying the intended hand grasps of individuals with upper limb loss in offline settings. Building upon this previous work, we present the first demonstration of real-time prosthetic hand control using sonomyography to perform functional tasks. An individual with congenital bilateral limb absence was fitted with sockets containing a low-profile ultrasound transducer placed over forearm muscle tissue in the residual limbs. A classifier was trained using linear discriminant analysis to recognize ultrasound images of muscle contractions for three discrete hand configurations (rest, tripod grasp, index finger point) under a variety of arm positions designed to cover the reachable workspace. A prosthetic hand mounted to the socket was then controlled using this classifier. Using this real-time sonomyographic control, the participant was able to complete three functional tasks that required selecting different hand grasps in order to grasp and move one-inch wooden blocks over a broad range of arm positions. Additionally, these tests were successfully repeated without retraining the classifier across 3 hours of prosthesis use and following simulated donning and doffing of the socket. This study supports the feasibility of using sonomyography to control upper limb prostheses in real-world applications.

Classification Performance and Feature Space Characteristics in Individuals With Upper Limb Loss Using Sonomyography.

Objective: Sonomyography, or ultrasound-based sensing of muscle deformation, is an emerging modality for upper limb prosthesis control. Although prior studies have shown that individuals with upper limb loss can achieve successful motion classification with sonomyography, it is important to better understand the time-course over which proficiency develops. In this study, we characterized user performance during their initial and subsequent exposures to sonomyography. Method: Ultrasound images corresponding to a series of hand gestures were collected from individuals with transradial limb loss under three scenarios: during their initial exposure to sonomyography (Experiment 1), during a subsequent exposure to sonomyography where they were provided biofeedback as part of a training protocol (Experiment 2), and during testing sessions held on different days (Experiment 3). User performance was characterized by offline classification accuracy, as well as metrics describing the consistency and separability of the sonomyography signal patterns in feature space. Results: Classification accuracy was high during initial exposure to sonomyography (96.2 ± 5.9%) and did not systematically change with the provision of biofeedback or on different days. Despite this stable classification performance, some of the feature space metrics changed. Conclusions: User performance was strong upon their initial exposure to sonomyography and did not improve with subsequent exposure. Clinical Impact: Prosthetists may be able to quickly assess if a patient will be successful with sonomyography without submitting them to an extensive training protocol, leading to earlier socket fabrication and delivery.

Lack of association between cognitive impairment and systemic inflammation in asymptomatic carotid stenosis.

BACKGROUND: Asymptomatic carotid atherosclerotic stenosis (ACAS) is associated with cognitive impairment. Systemic inflammation occurs in patients with systemic atherosclerosis and is also associated with cognitive impairment. The goal of this study was to determine if cognitive impairment in patients with ACAS is the result of systemic inflammation. METHODS: A cross-sectional analysis of 104 patients (63 patients with ACAS, 41 controls) with cognitive function and inflammatory biomarker assessments was performed. Venous blood was assayed for proinflammatory biomarkers (IL-1ß, IL-6, IL-6R, IL-8, IL-17, tumor necrosis factor-α, matrix metalloproteinase [MMP]-1, MMP-2, MMP-7, MMP-9, vascular cell adhesion molecule, and high-sensitivity C-reactive protein). The patients also underwent comprehensive cognitive testing to compute five domain-specific cognitive scores per patient. We first assessed the associations between carotid stenosis and cognitive function, and between carotid stenosis and systemic inflammation in separate regression models. We then determined whether cognitive impairments persisted in patients with carotid stenosis after accounting for inflammation by adjusting for inflammatory biomarker levels in a combined model. RESULTS: Patients with ACAS and control patients differed in age, race, coronary artery disease prevalence, and education. Stenosis patients had worse cognitive scores in two domains: learning and memory (P = .05) and motor and processing speed (P = .002). Despite adjusting for inflammatory biomarker levels, patients with ACAS still demonstrated deficits in the domains of learning and memory and motor and processing speed. CONCLUSIONS: Although systemic atherosclerosis-induced inflammation is a well-recognized cause for cognitive impairment, our data suggest that it is not the primary underlying mechanism behind cognitive impairments seen in ACAS. Cognitive impairments in learning and memory and motor and processing speed seen in patients with ACAS persist after adjusting for systemic inflammation. Thus, alternative mechanisms should be explored to account for the observed functional impairments.

Computed tomography angiographic biomarkers help identify vulnerable carotid artery plaque.

OBJECTIVE: The current risk assessment for patients with carotid atherosclerosis relies primarily on measuring the degree of stenosis. More reliable risk stratification could improve patient selection for targeted treatment. We have developed and validated a model to predict for major adverse neurologic events (MANE; stroke, transient ischemic attack, amaurosis fugax) that incorporates a combination of plaque morphology, patient demographics, and patient clinical information. METHODS: We enrolled 221 patients with asymptomatic carotid stenosis of any severity who had undergone computed tomography angiography at baseline and ≥6 months later. The images were analyzed for carotid plaque morphology (plaque geometry and tissue composition). The data were partitioned into training and validation cohorts. Of the 221 patients, 190 had complete records available and were included in the present analysis. The training cohort was used to develop the best model for predicting MANE, incorporating the patient and plaque features. First, single-variable correlation and unsupervised clustering were performed. Next, several multivariable models were implemented for the response variable of MANE. The best model was selected by optimizing the area under the receiver operating characteristic curve (AUC) and Cohen's kappa statistic. The model was validated using the sequestered data to demonstrate generalizability. RESULTS: A total of 62 patients had experienced a MANE during follow-up. Unsupervised clustering of the patient and plaque features identified single-variable predictors of MANE. Multivariable predictive modeling showed that a combination of the plaque features at baseline (matrix, intraplaque hemorrhage [IPH], wall thickness, plaque burden) with the clinical features (age, body mass index, lipid levels) best predicted for MANE (AUC, 0.79), In contrast, the percent diameter stenosis performed the worst (AUC, 0.55). The strongest single variable for discriminating between patients with and without MANE was IPH, and the most predictive model was produced when IPH was considered with wall remodeling. The selected model also performed well for the validation dataset (AUC, 0.64) and maintained superiority compared with percent diameter stenosis (AUC, 0.49). CONCLUSIONS: A composite of plaque geometry, plaque tissue composition, patient demographics, and clinical information predicted for MANE better than did the traditionally used degree of stenosis alone for those with carotid atherosclerosis. Implementing this predictive model in the clinical setting could help identify patients at high risk of MANE.

Toward a wearable monitor of local muscle fatigue during electrical muscle stimulation using tissue Doppler imaging.

Electrical muscle stimulation (EMS) is widely used in rehabilitation and athletic training to generate involuntary muscle contractions. However, EMS leads to rapid muscle fatigue, limiting the force a muscle can produce during prolonged use. Currently available methods to monitor localized muscle fatigue and recovery are generally not compatible with EMS. The purpose of this study was to examine whether Doppler ultrasound imaging can assess changes in stimulated muscle twitches that are related to muscle fatigue from electrical stimulation. We stimulated five isometric muscle twitches in the medial and lateral gastrocnemius of 13 healthy subjects before and after a fatiguing EMS protocol. Tissue Doppler imaging of the medial gastrocnemius recorded muscle tissue velocities during each twitch. Features of the average muscle tissue velocity waveforms changed immediately after the fatiguing stimulation protocol (peak velocity: -38%, p = .022; time-to-zero velocity: +8%, p = .050). As the fatigued muscle recovered, the features of the average tissue velocity waveforms showed a return towards their baseline values similar to that of the normalized ankle torque. We also found that features of the average tissue velocity waveform could significantly predict the ankle twitch torque for each participant (R2 = 0.255-0.849, p < .001). Our results provide evidence that Doppler ultrasound imaging can detect changes in muscle tissue during isometric muscle twitch that are related to muscle fatigue, fatigue recovery, and the generated joint torque. Tissue Doppler imaging may be a feasible method to monitor localized muscle fatigue during EMS in a wearable device.

Revascularization for asymptomatic carotid artery stenosis improves balance and mobility.

OBJECTIVE: Balance and mobility function worsen with age, more so for those with underlying chronic diseases. We recently found that asymptomatic carotid artery stenosis (ACAS) restricts blood flow to the brain and might also contribute to balance and mobility impairment. In the present study, we tested the hypothesis that ACAS is a modifiable risk factor for balance and mobility impairment. Our goal was to assess the effect of restoring blood flow to the brain by carotid revascularization on the balance and mobility of patients with high-grade ACAS (≥70% diameter-reducing stenosis). METHODS: Twenty adults (age, 67.0 ± 9.4 years) undergoing carotid endarterectomy for high-grade stenosis were enrolled. Balance and mobility assessments were performed before and 6 weeks after revascularization. These included the Short Physical Performance Battery, the Berg Balance Scale, the Four Square Step Test, the Dynamic Gait Index (DGI), the Timed Up and Go test, gait speed, the Mini-Balance Evaluation Systems Test (Mini-BESTest), and the Walking While Talking complex test. RESULTS: Consistent with our previous findings, patients demonstrated reduced scores on the Short Physical Performance Battery, Berg Balance Scale, DGI, and Timed Up and Go test and in gait speed. Depending on the outcome measure, 25% to 90% of the patients had scored in the impaired range at baseline. After surgery, significant improvements were observed in the outcome measures that combined walking with dynamic movements, including the DGI (P = .02) and Mini-BESTest (P = .002). The proportion of patients with Mini-BESTest scores indicating a high fall risk had decreased significantly from 90% (n = 18) at baseline to 40% (n = 8) after surgery (P = .02). We used Pearson's correlations to examine the relationship between balance and mobility before surgery and the change after surgery. Patients with lower baseline DGI and Mini-BESTest scores demonstrated the most improvement after surgery (r = -0.59, P = .006; and r = -0.70, P = .001, respectively). CONCLUSIONS: Carotid revascularization improved patients' balance and mobility, especially for measures that combine walking and dynamic movements. The greatest improvements were observed for the patients who had been most impaired at baseline.