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.

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.

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.

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.

Asymptomatic carotid artery stenosis is associated with cerebral hypoperfusion.

OBJECTIVE: We have shown that almost 50% of patients with asymptomatic carotid stenosis (ACS) will demonstrate cognitive impairment. Recent evidence has suggested that cerebral hypoperfusion is an important cause of cognitive impairment. Carotid stenosis can restrict blood flow to the brain, with consequent cerebral hypoperfusion. In contrast, cross-hemispheric collateral compensation through the Circle of Willis, and cerebrovascular vasodilation can also mitigate the effects of flow restriction. It is, therefore, critical to develop a clinically relevant measure of net brain perfusion in patients with ACS that could help in risk stratification and in determining the appropriate treatment. To determine whether ACS results in cerebral hypoperfusion, we developed a novel approach to quantify interhemispheric cerebral perfusion differences, measured as the time to peak (TTP) and mean transit time (MTT) delays using perfusion-weighted magnetic resonance imaging (PWI) of the whole brain. To evaluate the utility of using clinical duplex ultrasonography (DUS) to infer brain perfusion, we also assessed the relationship between the PWI findings and ultrasound-based peak systolic velocity (PSV). METHODS: Structural and PWI of the brain and magnetic resonance angiography of the carotid arteries were performed in 20 patients with ≥70% ACS. DUS provided the PSV, and magnetic resonance angiography provided plaque geometric measures at the stenosis. Volumetric perfusion maps of the entire brain from PWI were analyzed to obtain the mean interhemispheric differences for the TTP and MTT delays. In addition, the proportion of brain volume that demonstrated a delay in TTP and MTT was also measured. These proportions were measured for increasing severity of perfusion delays (0.5, 1.0, and 2.0 seconds). Finally, perfusion asymmetries on PWI were correlated with the PSV and stenosis features on DUS using Pearson's correlation coefficients. RESULTS: Of the 20 patients, 18 had unilateral stenosis (8 right and 10 left) and 2 had bilateral stenoses. The interhemispheric (left-right) TTP delays measured for the whole brain volume identified impaired perfusion in the hemisphere ipsilateral to the stenosis in 16 of the 18 patients. More than 45% of the patients had had ischemia in at least one half of their brain volume, with a TTP delay >0.5 second. The TTP and MTT delays showed strong correlations with PSV. In contrast, the correlations with the percentage of stenosis were weaker. The correlations for the PSV were strongest with the perfusion deficits (TTP and MTT delays) measured for the whole brain using our proposed algorithm (r = 0.80 and r = 0.74, respectively) rather than when measured on a single magnetic resonance angiography slice as performed in current clinical protocols (r = 0.31 and r = 0.58, respectively). CONCLUSIONS: Interhemispheric TTP and MTT delay measured for the whole brain using PWI has provided a new tool for assessing cerebral perfusion deficits in patients with ACS. Carotid stenosis was associated with a detectable reduction in ipsilateral brain perfusion compared with the opposite hemisphere in >80% of patients. The PSV measured at the carotid stenosis using ultrasonography correlated with TTP and MTT delays and might serve as a clinically useful surrogate to brain hypoperfusion in these patients.

Asymptomatic carotid stenosis is associated with mobility and cognitive dysfunction and heightens falls in older adults.

BACKGROUND: Atherosclerosis of the carotid bifurcation with plaque formation causes asymptomatic carotid artery stenosis (ACAS), which may also be associated with cerebral hypoperfusion. Cerebral hypoperfusion adversely affects multiple aspects of mobility and cognition. This study tests the hypothesis that community-dwelling older adults with a 50% or greater diameter-reducing ACAS will have mobility and cognitive impairments that heighten their risk for falls. METHODS: Eighty community-dwelling adults completed a mobility assessment (Short Physical Performance Battery, Berg Balance Scale, Four Square Step Test, Dynamic Gait Index, Timed Up and Go, and gait speed), self-reported physical function (Activities-Specific Balance Confidence, SF-12 Physical Function Component), and cognitive tests (Mini-Mental State Examination). Falls were recorded for the past 6 months. Standardized carotid ultrasound examination classified participants into no stenosis (<50% diameter reduction) (n = 54), moderate stenosis (50%-69%) (n = 17), and high-grade stenosis (70%-99%) (n = 9) groups. Linear and logistic regression analyses determined the associations between these measures and the degree of stenosis (three groups). RESULTS: Logistic regression analysis showed their degree of stenosis was associated with reductions in mobility (Short Physical Performance Battery [P = .008], Berg Balance Scale [P = .0008], Four Square Step Test [P = .005], DGI [P = .0001], TUG [P = .0004], gait speed [P = .02]), perceived physical function (ABC [P < .0001], SF-12 Physical Function Component [P < .0001]), and cognition (MMSE [P = .003]). Adults with moderate- and high-grade stenosis had a greater incidence of falls compared with those without stenosis (relative risk, 2.86; P = .01). Results remained unchanged after adjustment for age, sex and cardiovascular risk factors. CONCLUSIONS: ACAS is associated with impaired mobility and cognition that are accompanied with increased fall risk. These impairments increased with worsening severity.

Quantitative assessment of carotid plaque morphology (geometry and tissue composition) using computed tomography angiography.

OBJECTIVE: Quantification of carotid plaque morphology (geometry and tissue composition) may help stratify risk for future stroke and assess plaque progression or regression in response to medical risk factor modification. We assessed the feasibility and reliability of morphologic measurements of carotid plaques using computed tomography angiography (CTA) and determined the minimum detectable change in plaque features by this approach. METHODS: CTA images of both carotid arteries in 50 patients were analyzed by two observers using a semiautomatic image analysis program, yielding 93 observations per user (seven arteries were excluded because of prior stenting). One observer repeated the analyses 4 weeks later. Measurements included total plaque volume; percentage stenosis (by diameter and area); and tissue composition for calcium, lipid-rich necrotic core (LRNC), and intraplaque hemorrhage (IPH). Reliability of measurements was assessed by intraclass and interclass correlation and Bland-Altman plots. Dice similarity coefficient (DSC) and modified Hausdorff distance (MHD) assessed reliability of geometric shape measurements. We additionally computed the minimum amount of change in these features detectable by our approach. RESULTS: The cohort was 51% male (mean age, 70.1 years), and 56% had a prior stroke. The mean (± standard deviation) plaque volume was 837.3 ± 431.3 mm3, stenosis diameter was 44.5% ± 25.6%, and stenosis area was 58.1% ± 29.0%. These measurements showed high reliability. Intraclass correlation coefficients for plaque volume, percentage stenosis by diameter, and percentage stenosis by area were 0.96, 0.87, and 0.83, respectively; interclass correlation coefficients were 0.88, 0.84, and 0.78. Intraclass correlations for tissue composition were 0.99, 0.96, and 0.86 (calcium, LRNC, and IPH, respectively), and interclass correlations were 0.99, 0.92, and 0.92. Shape measurements showed high intraobserver (DSC, 0.95 ± 0.04; MHD, 0.16 ± 0.10 mm) and interobserver (DSC, 0.94 ± 0.05; MHD, 0.19 ± 0.12 mm) luminal agreement. This approach can detect a change of at least 3.9% in total plaque volume, 1.2 mm3 in calcium, 4.3 mm3 in LRNC, and 8.6 mm3 in IPH with the same observer repeating measurements and 9.9% in plaque volume, 1.9 mm3 in calcium, 7.9 mm3 in LRNC, and 6.8 mm3 in IPH for two different observers. CONCLUSIONS: Carotid plaque geometry (total volume, diameter stenosis, and area stenosis) and tissue composition (calcium, LRNC, and IPH) are measured reliably from clinical CTA images using a semiautomatic image analysis program. The minimum change in plaque volume detectable is ∼4% if the same observer makes both measurements and ∼10% for different observers. Small changes in plaque composition can also be detected reliably. This approach can facilitate longitudinal studies for identifying high-risk plaque features and for quantifying plaque progression or regression after treatment.

Quantification of Muscle Tissue Properties by Modeling the Statistics of Ultrasound Image Intensities Using a Mixture of Gamma Distributions in Children With and Without Cerebral Palsy.

OBJECTIVES: To investigate whether quantitative ultrasound (US) imaging, based on the envelope statistics of the backscattered US signal, can describe muscle properties in typically developing children and those with cerebral palsy (CP). METHODS: Radiofrequency US data were acquired from the rectus femoris muscle of children with CP (n = 22) and an age-matched cohort without CP (n = 14) at rest and during maximal voluntary isometric contraction. A mixture of gamma distributions was used to model the histogram of the echo intensities within a region of interest in the muscle. RESULTS: Muscle in CP had a heterogeneous echo texture that was significantly different from that in healthy controls (P < .001), with larger deviations from Rayleigh scattering. A mixture of 2 gamma distributions showed an excellent fit to the US intensity, and the shape and rate parameters were significantly different between CP and control groups (P < .05). The rate parameters for both the single gamma distribution and mixture of gamma distributions were significantly higher for contracted muscles compared to resting muscles, but there was no significant interaction between these factors (CP and muscle contraction) for a mixed-model analysis of variance. CONCLUSIONS: Ultrasound tissue characterization indicates a more disorganized architecture and increased echogenicity in muscles in CP, consistent with previously documented increases in fibrous infiltration and connective tissue changes in this population. Our results indicate that quantitative US can be used to objectively differentiate muscle architecture and tissue properties.

Noninvasive characterization of carotid plaque strain.

OBJECTIVE: Current risk stratification of internal carotid artery plaques based on diameter-reducing percentage stenosis may be unreliable because ischemic stroke results from plaque disruption with atheroembolization. Biomechanical forces acting on the plaque may render it vulnerable to rupture. The feasibility of ultrasound-based quantification of plaque displacement and strain induced by hemodynamic forces and their relationship to high-risk plaques have not been determined. We studied the feasibility and reliability of carotid plaque strain measurement from clinical B-mode ultrasound images and the relationship of strain to high-risk plaque morphology. METHODS: We analyzed carotid ultrasound B-mode cine loops obtained in patients with asymptomatic ≥50% stenosis during routine clinical scanning. Optical flow methods were used to quantify plaque motion and shear strain during the cardiac cycle. The magnitude (maximum absolute shear strain rate [MASSR]) and variability (entropy of shear strain rate [ESSR] and variance of shear strain rate [VSSR]) of strain were combined into a composite shear strain index (SSI), which was assessed for interscan repeatability and correlated with plaque echolucency. RESULTS: Nineteen patients (mean age, 70 years) constituting 36 plaques underwent imaging; 37% of patients (n = 7) showed high strain (SSI ≥0.5; MASSR, 2.2; ESSR, 39.7; VSSR, 0.03) in their plaques; the remaining clustered into a low-strain group (SSI <0.5; MASSR, 0.58; ESSR, 21.2; VSSR, 0.002). The area of echolucent morphology was greater in high-strain plaques vs low-strain plaques (28% vs 17%; P = .018). Strain measurements showed low variability on Bland-Altman plots with cluster assignment agreement of 76% on repeated scanning. Two patients developed a stroke during 2 years of follow-up; both demonstrated high SSI (≥0.5) at baseline. CONCLUSIONS: Carotid plaque strain is reliably computed from routine B-mode imaging using clinical ultrasound machines. High plaque strain correlates with known high-risk echolucent morphology. Strain measurement can complement identification of patients at high risk for plaque disruption and stroke.

Semiautomatic quantification of carotid plaque volume with three-dimensional ultrasound imaging.

OBJECTIVE: Vessel wall volume (VWV) assessed by three-dimensional duplex ultrasound (3DUS) imaging provides a more comprehensive measure of plaque burden than conventional two-dimensional measures of diameter stenosis. We previously demonstrated that manual outlining of the arterial lumen-intima boundary and outer wall boundary can be performed reliably on images obtained with a commercially available 3D-DUS transducer. Manual segmentation, however, is time consuming (∼45 minutes), limiting its clinical translation. We have developed a semiautomatic algorithm (manual selection of the carotid bifurcation image with subsequent automatic plaque outlining) to outline carotid plaques on 3DUS data sets. In this study, we investigated the accuracy, reproducibility, reliability, and time taken by this algorithm. METHODS: 3DUS data sets from 30 patients with asymptomatic ≥50% carotid stenosis underwent manual outlining of lumen-intima boundary and outer wall boundary to measure VWV. Two observers implemented a semiautomatic segmentation algorithm. The algorithm's accuracy was compared with manual outlining using the Pearson correlation coefficient. The Dice similarity coefficient (DSC) and modified-Hausdorff distance (MHD) were used to quantify the geometric similarity of the outlines. We also compared results after an intermediate stage of the algorithm vs the complete algorithm. Reproducibility and the least amount of detectable change in plaque volume were computed for each method. Intraobserver and interobserver metrics for each method were computed using the intraclass correlation coefficient (ICC), coefficient of variability (CV), minimum detectable change (MDC), and standard error of measurement (SEM) of the VWV. RESULTS: Plaque volume estimates obtained from the semiautomatic algorithm were accurate compared with manual outlining. The Pearson correlation coefficient was 0.76 (P < .001), and measurements were geometrically similar (DSC, 0.85; MHD, 0.48 mm). The algorithm was more reproducible and reliable and could detect smaller changes in plaque volume on repeat imaging (low interobserver variability: ICC, 0.9; CV, 8.22%; MDC, 5.57%; SEM, 1.45%; DSC, 0.88; MHD, 0.43 mm). Intraobserver variability was even lower (ICC, 0.9; CV, 8%; MDC, 3.62%; SEM, 1.31%; DSC, 0.89; MHD, 0.37 mm). Plaque volume estimates at the intermediate stage of the algorithm matched results from the full algorithm (Pearson correlation coefficient, 0.76; DSC, 0.84; MHD, 0.52 mm). The intermediate approach, however, was less reliable than the full algorithm (interobserver: ICC, 0.81; CV, 11.7%; MDC, 9.58%; SEM, 3.46%; DSC, 0.88; MHD, 0.42 mm; intraobserver: ICC, 0.87; CV, 8.6%; MDC, 4.55%; SEM, 1.64%; DSC, 0.89; MHD, 0.38 mm). The full algorithm required ∼14 minutes to implement. However, a quick (7 minutes) and accurate assessment of VWV can be obtained by running only the intermediate stage of the algorithm, although with a loss in repeatability and reliability. CONCLUSIONS: We present a unique algorithm to perform semiautomatic quantification of carotid plaque volume using 3DUS imaging. It is quick (mean time, 14 minutes), accurate, repeatable, and implementable in a clinical environment and in longitudinal studies tracking plaque progression. It reliably detects plaque volume changes as low as 4% to 6% with 95% confidence.

Asymptomatic carotid stenosis is associated with cognitive impairment.

BACKGROUND: Cerebrovascular risk factors (eg, hypertension, coronary artery disease) and stroke can lead to vascular cognitive impairment. The Asymptomatic Carotid Stenosis and Cognitive Function study evaluated the isolated impact of asymptomatic carotid stenosis (no prior ipsilateral or contralateral stroke or transient ischemic attack) on cognitive function. Cerebrovascular hemodynamic and carotid plaque characteristics were analyzed to elucidate potential mechanisms affecting cognition. METHODS: There were 82 patients with ≥50% asymptomatic carotid stenosis and 62 controls without stenosis but matched for vascular comorbidities who underwent neurologic, National Institutes of Health Stroke Scale, and comprehensive neuropsychological examination. Overall cognitive function and five domain-specific scores were computed. Duplex ultrasound with Doppler waveform and B-mode imaging defined the degree of stenosis, least luminal diameter, plaque area, and plaque gray-scale median. Breath-holding index (BHI) and microembolization were measured using transcranial Doppler. We assessed cognitive differences between stenosis patients and control patients and of stenosis patients with low vs high BHI and correlated cognitive function with microembolic counts and plaque characteristics. RESULTS: Stenosis and control patients did not differ in vascular risk factors, education, estimated intelligence, or depressive symptoms. Stenosis patients had worse composite cognitive scores (P = .02; Cohen's d = 0.43) and domain-specific scores for learning/memory (P = .02; d = 0.42) and motor/processing speed (P = .01; d = 0.65), whereas scores for executive function were numerically lower (P = .08). Approximately 49.4% of all stenosis patients were impaired in at least two cognitive domains. Precisely 50% of stenosis patients demonstrated a reduced BHI. Stenosis patients with reduced BHI performed worse on the overall composite cognitive score (t = -2.1; P = .02; d = 0.53) and tests for learning/memory (t = -2.7; P = .01; d = 0.66). Cognitive function did not correlate with measures of plaque burden (degree of stenosis, least luminal diameter, and plaque area) or with plaque gray-scale median. CONCLUSIONS: Asymptomatic carotid stenosis is associated with cognitive impairment independent of known vascular risk factors for vascular cognitive impairment. Approximately 49.4% of these patients demonstrate impairment in at least two neuropsychological domains. The deficit is driven primarily by reduced motor/processing speed and learning/memory and is mild to moderate in severity. The mechanism for impairment is likely to be hemodynamic as evidenced by reduced cerebrovascular reserve and the likely result of hypoperfusion from a pressure drop across the stenosis in the presence of inadequate collateralization.

Carotid plaque morphometric assessment with three-dimensional ultrasound imaging.

OBJECTIVE: As investigations into nonsurgical treatment for atherosclerosis expand, the measurement of plaque regression and progression has become an important end point to evaluate. Measurements of three-dimensional (3D) plaque volume are more reliable and sensitive to change than are traditional estimates of stenosis severity or cross-sectional area. 3D ultrasound (3D US) imaging may allow monitoring of plaque volume changes but has not been used routinely due to the cumbersome motorized units required to drive transducers. We investigated the variability, reliability, and the least amount of change detectable by 1D plaque measures, as well as 2D and 3D measures of plaque morphometry, that can be applied in a clinical environment. METHODS: 3D US imaging was obtained in 10 patients with carotid stenosis. The lumen and outer wall boundaries were outlined in serial cross-sectional images 1 mm apart. Three observers manually segmented vessel wall volumes (VWVs), and the segmentation was repeated again 4 weeks later. This allowed measurement of interobserver and intraobserver variability of 6 pairs of observations. We measured Bland-Altman statistics, intraclass correlation coefficients, coefficient of variability, and the minimum detectable plaque change for each morphometric measure. RESULTS: The mean VWV of carotid lesions in the study was 1276.8 mm(3) (range, 620.6-1956.3 mm(3)). Bland-Altman plots demonstrated low interobserver and intraobserver variability. The interobserver variability of volume measurements as a function of mean volume was 14.8% and interobserver variability was 8.9%. Reliability was 87% as quantified by the interclass correlation and was 95% by the intraclass correlation. The least detectable change in VWV was 12.9% for interobserver variability and 4.5% for intraobserver variability for the three observers. CONCLUSIONS: Carotid plaque diameter measurements from B-mode images have high variability. Plaque burden, as estimated by VWV, can be measured reliably with a 3D US technique using a clinical scanner. The volumetric change, with 95% confidence, that must be observed to establish that a plaque has undergone growth or regression is ∼12.9% for different observers and 4.5% for the same observer performing the follow-up study.

Novel Use of Ultrasound Elastography to Quantify Muscle Tissue Changes After Dry Needling of Myofascial Trigger Points in Patients With Chronic Myofascial Pain.

OBJECTIVES: To compare a mechanical heterogeneity index derived from ultrasound vibration elastography with physical findings before and after dry-needling treatment of spontaneously painful active myofascial trigger points in the upper trapezius muscle. METHODS: Forty-eight patients with chronic myofascial pain enrolled in a prospective interventional trial of 3 weekly dry-needling treatments for active myofascial trigger points. Trigger points were evaluated at baseline and at treatment completion using palpation, the pressure-pain threshold, and the mechanical heterogeneity index. Thirty patients were reevaluated at 8 weeks. Trigger points that "responded" changed to tissue that was no longer spontaneously painful, with or without the presence of a palpable nodule. Trigger points that "resolved" changed to tissue without a palpable nodule. The mechanical heterogeneity index was defined as the proportion of the upper trapezius muscle that appeared mechanically stiffer on elastography. Statistical significance for comparisons was determined at P < .05. RESULTS: Following 3 dry needle treatments, the mechanical heterogeneity index decreased significantly for the 38 myofascial trigger points (79% of 48) that responded to treatment. Among these, the baseline mechanical heterogeneity index was significantly lower for the 13 trigger points (27% of 38) that resolved, but the decrease after 3 dry needle treatments did not reach significance. The pressure-pain threshold improved significantly for both groups. At 8 weeks, the mechanical heterogeneity index decreased significantly for the 22 trigger points (73% of 30) that responded and for the 10 (45% of 22) that resolved. The pressure-pain threshold improvement was significant for trigger points that responded but did not reach significance for resolved trigger points. CONCLUSIONS: The mechanical heterogeneity index identifies changes in muscle tissue properties that correlate with changes in the myofascial trigger point status after dry needling.

Dynamic ultrasound imaging applications to quantify musculoskeletal function.

Advances in imaging methods have led to new capability to study muscle and tendon motion in vivo. Direct measurements of muscle and tendon kinematics using imaging may lead to improved understanding of musculoskeletal function. This review presents quantitative ultrasound methods for muscle dynamics that can be used to assess in vivo musculoskeletal function when integrated with other conventional biomechanical measurements.

SonoMyoNet: A Convolutional Neural Network for Predicting Isometric Force from Highly Sparse Ultrasound Images.

Ultrasound imaging or sonomyography has been found to be a robust modality for measuring muscle activity due to its ability to image deep-seated muscles directly while providing superior spatiotemporal specificity compared to surface electromyography-based techniques. Quantifying the morphological changes during muscle activity involves computationally expensive approaches for tracking muscle anatomical structures or extracting features from brightness-mode (B-mode) images and amplitude-mode (A-mode) signals. This paper uses an offline regression convolutional neural network (CNN) called SonoMyoNet to estimate continuous isometric force from sparse ultrasound scanlines. SonoMyoNet learns features from a few equispaced scanlines selected from B-mode images and utilizes the learned features to estimate continuous isometric force accurately. The performance of SonoMyoNet was evaluated by varying the number of scanlines to simulate the placement of multiple single-element ultrasound transducers in a wearable system. Results showed that SonoMyoNet could accurately predict isometric force with just four scanlines and is immune to speckle noise and shifts in the scanline location. Thus, the proposed network reduces the computational load involved in feature tracking algorithms and estimates muscle force from the global features of sparse ultrasound images.

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.

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.

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.