Data-driven biomarkers better associate with stroke motor outcomes than theory-based biomarkers

Chronic motor impairments are a leading cause of disability after stroke. Previous studies have associated motor outcomes with the degree of damage to predefined structures in the motor system, such as the corticospinal tract. However, such theory-based approaches may not take full advantage of the information contained in clinical imaging data. The present study uses data-driven approaches to model chronic motor outcomes after stroke and compares the accuracy of these associations to previously-identified theory-based biomarkers. Using a cross-validation framework, regression models were trained using lesion masks and motor outcomes data from 789 stroke patients from the Enhancing NeuroImaging Genetics through Meta Analysis (ENIGMA) Stroke Recovery Working Group. Using the explained variance metric to measure the strength of the association between chronic motor outcomes and imaging biomarkers, we compared theory-based biomarkers, like lesion load to known motor tracts, to three data-driven biomarkers: lesion load of lesion-behaviour maps, lesion load of structural networks associated with lesion-behaviour maps, and measures of regional structural disconnection. In general, data-driven biomarkers had stronger associations with chronic motor outcomes accuracy than theory-based biomarkers. Data-driven models of regional structural disconnection performed the best of all models tested (R 2 = 0.210, P < 0.001), performing significantly better than the theory-based biomarkers of lesion load of the corticospinal tract (R 2 = 0.132, P < 0.001) and of multiple descending motor tracts (R 2 = 0.180, P < 0.001). They also performed slightly, but significantly, better than other data-driven biomarkers including lesion load of lesion-behaviour maps (R 2 = 0.200, P < 0.001) and lesion load of structural networks associated with lesion-behaviour maps (R 2 = 0.167, P < 0.001). Ensemble models - combining basic demographic variables like age, sex, and time since stroke - improved the strength of associations for theory-based and data-driven biomarkers. Combining both theory-based and data-driven biomarkers with demographic variables improved predictions, and the best ensemble model achieved R 2 = 0.241, P < 0.001. Overall, these results demonstrate that out-of-sample associations between chronic motor outcomes and data-driven imaging features, particularly when lesion data is represented in terms of structural disconnection, are stronger than associations between chronic motor outcomes and theory-based biomarkers. However, combining both theory-based and data-driven models provides the most robust associations.

The emergence of multiscale connectomics-based approaches in stroke recovery

Stroke is a leading cause of adult disability. Understanding stroke damage and recovery requires deciphering changes in complex brain networks across different spatiotemporal scales. While recent developments in brain readout technologies and progress in complex network modeling have revolutionized current understanding of the effects of stroke on brain networks at a macroscale, reorganization of smaller scale brain networks remains incompletely understood. In this review, we use a conceptual framework of graph theory to define brain networks from nano- to macroscales. Highlighting stroke-related brain connectivity studies at multiple scales, we argue that multiscale connectomics-based approaches may provide new routes to better evaluate brain structural and functional remapping after stroke and during recovery.

Resting state functional connectivity associated with impaired proprioception post-stroke

Deficits in proprioception, the knowledge of limb position and movement in the absence of vision, occur in ~50% of all strokes; however, our lack of knowledge of the neurological mechanisms of these deficits diminishes the effectiveness of rehabilitation and prolongs recovery. We performed resting-state functional magnetic resonance imaging (fMRI) on stroke patients to determine functional brain networks that exhibited changes in connectivity in association with proprioception deficits determined by a Kinarm robotic exoskeleton assessment. Thirty stroke participants were assessed for proprioceptive impairments using a Kinarm robot and underwent resting-state fMRI at 1 month post-stroke. Age-matched healthy control (n = 30) fMRI data were also examined and compared to stroke data in terms of the functional connectivity of brain regions associated with proprioception. Stroke patients exhibited reduced connectivity of the supplementary motor area and the supramarginal gyrus, relative to controls. Functional connectivity of these regions plus primary somatosensory cortex and parietal opercular area was significantly associated with proprioceptive function. The parietal lobe of the lesioned hemisphere is a significant node for proprioception after stroke. Assessment of functional connectivity of this region after stroke may assist with prognostication of recovery. This study also provides potential targets for therapeutic neurostimulation to aid in stroke recovery.

The Evolution of Hand Proprioceptive and Motor Impairments in the Sub-Acute Phase After Stroke

BACKGROUND

Hand proprioception is essential for fine movements and therefore many activities of daily living. Although frequently impaired after stroke, it is unclear how hand proprioception evolves in the sub-acute phase and whether it follows a similar pattern of changes as motor impairments.

OBJECTIVE

This work investigates whether there is a corresponding pattern of changes over time in hand proprioception and motor function as comprehensively quantified by a combination of robotic, clinical, and neurophysiological assessments.

METHODS

Finger proprioception (position sense) and motor function (force, velocity, range of motion) were evaluated using robotic assessments at baseline (<3 months after stroke) and up to 4 weeks later (discharge). Clinical assessments (among others, Box & Block Test [BBT]) as well as Somatosensory/Motor Evoked Potentials (SSEP/MEP) were additionally performed.

RESULTS

Complete datasets from 45 participants post-stroke were obtained. For 42% of all study participants proprioception and motor function had a dissociated pattern of changes (only 1 function considerably improved). This dissociation was either due to the absence of a measurable impairment in 1 modality at baseline, or due to a severe lesion of central somatosensory or motor tracts (absent SSEP/MEP). Better baseline BBT correlated with proprioceptive gains, while proprioceptive impairment at baseline did not correlate with change in BBT.

CONCLUSIONS

Proprioception and motor function frequently followed a dissociated pattern of changes in sub-acute stroke. This highlights the importance of monitoring both functions, which could help to further personalize therapies.

The locations of stroke lesions next to the posterior internal capsule may predict the recovery of the related proprioceptive deficits

Background

Somatosensory deficits after stroke correlate with functional disabilities and impact everyday-life. In particular, the interaction of proprioception and motor dysfunctions affects the recovery. While corticospinal tract (CST) damage is linked to poor motor outcome, much less is known on proprioceptive recovery. Identifying a predictor for such a recovery could help to gain insights in the complex functional recovery processes thereby reshaping rehabilitation strategies.

Methods

50 patients with subacute stroke were tested before and after neurological rehabilitation. Proprioceptive and motor impairments were quantified with three clinical assessments and four hand movement and proprioception measures using a robotic device. Somatosensory evoked potentials (SSEP) to median nerve stimulation and structural imaging data (MRI) were also collected. Voxel-based lesion-symptom mapping (VLSM) along with a region of interest (ROI) analysis were performed for the corticospinal tract (CST) and for cortical areas.

Results

Before rehabilitation, the VLSM revealed lesion correlates for all clinical and three robotic measures. The identified voxels were located in the white matter within or near the CST. These regions associated with proprioception were located posterior compared to those associated with motor performance. After rehabilitation the patients showed an improvement of all clinical and three robotic assessments. Improvement in the box and block test was associated with an area in anterior CST. Poor recovery of proprioception was correlated with a high lesion load in fibers towards primary sensorymotor cortex (S1 and M1 tract). Patients with loss of SSEP showed higher lesion loads in these tracts and somewhat poorer recovery of proprioception. The VSLM analysis for SSEP loss revealed a region within and dorsal of internal capsule next to the posterior part of CST, the posterior part of insula and the rolandic operculum.

Conclusion

Lesions dorsal to internal capsule next to the posterior CST were associated with proprioceptive deficits and may have predictive value. Higher lesion load was correlated with poorer restoration of proprioceptive function. Furthermore, patients with SSEP loss trended towards poor recovery of proprioception, the corresponding lesions were also located in the same location. These findings suggest that structural imaging of the internal capsule and CST could serve as a recovery predictor of proprioceptive function.

Data-driven biomarkers outperform theory-based biomarkers in predicting stroke motor outcomes

Chronic motor impairments are a leading cause of disability after stroke. Previous studies have predicted motor outcomes based on the degree of damage to predefined structures in the motor system, such as the corticospinal tract. However, such theory-based approaches may not take full advantage of the information contained in clinical imaging data. The present study uses data-driven approaches to predict chronic motor outcomes after stroke and compares the accuracy of these predictions to previously-identified theory-based biomarkers. Using a cross-validation framework, regression models were trained using lesion masks and motor outcomes data from 789 stroke patients (293 female/496 male) from the ENIGMA Stroke Recovery Working Group (age 64.9±18.0 years; time since stroke 12.2±0.2 months; normalised motor score 0.7±0.5 (range [0,1]). The out-of-sample prediction accuracy of two theory-based biomarkers was assessed: lesion load of the corticospinal tract, and lesion load of multiple descending motor tracts. These theory-based prediction accuracies were compared to the prediction accuracy from three data-driven biomarkers: lesion load of lesion-behaviour maps, lesion load of structural networks associated with lesion-behaviour maps, and measures of regional structural disconnection. In general, data-driven biomarkers had better prediction accuracy - as measured by higher explained variance in chronic motor outcomes - than theory-based biomarkers. Data-driven models of regional structural disconnection performed the best of all models tested (R2 = 0.210, p < 0.001), performing significantly better than predictions using the theory-based biomarkers of lesion load of the corticospinal tract (R2 = 0.132, p< 0.001) and of multiple descending motor tracts (R2 = 0.180, p < 0.001). They also performed slightly, but significantly, better than other data-driven biomarkers including lesion load of lesion-behaviour maps (R2 =0.200, p < 0.001) and lesion load of structural networks associated with lesion-behaviour maps (R2 =0.167, p < 0.001). Ensemble models - combining basic demographic variables like age, sex, and time since stroke - improved prediction accuracy for theory-based and data-driven biomarkers. Finally, combining both theory-based and data-driven biomarkers with demographic variables improved predictions, and the best ensemble model achieved R2 = 0.241, p < 0.001. Overall, these results demonstrate that models that predict chronic motor outcomes using data-driven features, particularly when lesion data is represented in terms of structural disconnection, perform better than models that predict chronic motor outcomes using theory-based features from the motor system. However, combining both theory-based and data-driven models provides the best predictions.

Enhanced Integrity of White Matter Microstructure in Mind-Body Practitioners: A Whole-Brain Diffusion Tensor Imaging Study

Tai Chi Chuan (TCC) is an increasingly popular multimodal mind-body practice with potential cognitive benefits, yet the neurobiological mechanisms underlying these effects, particularly in relation to brain white matter (WM) microstructure, remain largely unknown. In this study, we used diffusion tensor imaging (DTI) and the attention network test (ANT) to compare 22 TCC practitioners and 18 healthy controls. We found extensive differences in fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) between the two groups. Specifically, TCC practitioners had significantly different diffusion metrics in the corticospinal tract (CST), fornix (FX)/stria terminalis (ST), and cerebral peduncle (CP). We also observed a significant correlation between increased FA values in the right CP and ANT performance in TCC practitioners. Our findings suggest that optimized regional WM microstructure may contribute to the complex information processing associated with TCC practice, providing insights for preventing cognitive decline and treating neurological disorders with cognitive impairment in clinical rehabilitation.

Leveraging Factors of Self-Efficacy and Motivation to Optimize Stroke Recovery

The International Classification of Functioning, Disability and Health framework recognizes that an individual's functioning post-stroke reflects an interaction between their health condition and contextual factors encompassing personal and environmental factors. Personal factors significantly impact rehabilitation outcomes as they determine how an individual evaluates their situation and copes with their condition in daily life. A key personal factor is self-efficacy-an individual's belief in their capacity to achieve certain outcomes. Self-efficacy influences an individual's motivational state to execute behaviors necessary for achieving desired rehabilitation outcomes. Stroke rehabilitation practice and research now acknowledge self-efficacy and motivation as critical elements in post-stroke recovery, and increasing evidence highlights their contributions to motor (re)learning. Given the informative value of neuroimaging-based biomarkers in stroke, elucidating the neurological underpinnings of self-efficacy and motivation may optimize post-stroke recovery. In this review, we examine the role of self-efficacy and motivation in stroke rehabilitation and recovery, identify potential neural substrates underlying these factors from current neuroimaging literature, and discuss how leveraging these factors and their associated neural substrates has the potential to advance the field of stroke rehabilitation.

Dynamic connectivity predicts acute motor impairment and recovery post-stroke

Thorough assessment of cerebral dysfunction after acute lesions is paramount to optimize predicting clinical outcomes. We here built random forest classifier-based prediction models of acute motor impairment and recovery post-stroke. Predictions relied on structural and resting-state fMRI data from 54 stroke patients scanned within the first days of symptom onset. Functional connectivity was estimated via static and dynamic approaches. Motor performance was phenotyped in the acute phase and 6 months later. A model based on the time spent in specific dynamic connectivity configurations achieved the best discrimination between patients with and without motor impairments (out-of-sample area under the curve, 95% confidence interval: 0.67 ± 0.01). In contrast, patients with moderate-to-severe impairments could be differentiated from patients with mild deficits using a model based on the variability of dynamic connectivity (0.83 ± 0.01). Here, the variability of the connectivity between ipsilesional sensorimotor cortex and putamen discriminated the most between patients. Finally, motor recovery was best predicted by the time spent in specific connectivity configurations (0.89 ± 0.01) in combination with the initial impairment. Here, better recovery was linked to a shorter time spent in a functionally integrated configuration. Dynamic connectivity-derived parameters constitute potent predictors of acute impairment and recovery, which, in the future, might inform personalized therapy regimens to promote stroke recovery.

Investigating the neuroanatomy underlying proprioception using a stroke model

Neuroanatomical investigations have associated cortical areas, beyond Primary Somatosensory Cortex (S1), with impaired proprioception. Cortical regions have included temporoparietal (TP) regions (supramarginal gyrus, superior temporal gyrus, Heschl's gyrus) and insula. Previous approaches have struggled to account for concurrent damage across multiple brain regions. Here, we used a targeted lesion analysis approach to examine the impact of specific combinations of cortical and sub-cortical lesions and quantified the prevalence of proprioceptive impairments when different regions are damaged or spared. Seventy-seven individuals with stroke (49 male; 28 female) were identified meeting prespecified lesion criteria based on MRI/CT imaging: 1) TP lesions without S1, 2) TP lesions with S1, 3) isolated S1 lesions, 4) isolated insula lesions, and 5) lesions not impacting these regions (other regions group). Initially, participants meeting these criteria (1-4) were grouped together into right or left lesion groups and compared to each other, and the other regions group (5), on a robotic Arm Position Matching (APM) task and a Kinesthesia (KIN) task. We then examined the behaviour of individuals that met each specific criteria (groups 1-5). Proprioceptive impairments were more prevalent following right hemisphere lesions than left hemisphere lesions. The extent of damage to TP regions correlated with performance on both robotic tasks. Even without concurrent S1 lesions, TP and insular lesions were associated with impairments on the APM and KIN tasks. Finally, lesions not impacting these regions were much less likely to result in impairments. This study highlights the critical importance of TP and insular regions for accurate proprioception. SIGNIFICANCE STATEMENT: This work advances our understanding of the neuroanatomy of human proprioception. We validate the importance of regions, beyond the dorsal column medial lemniscal pathway and S1, for proprioception. Further, we provide additional evidence of the importance of the right hemisphere for human proprioception. Improved knowledge on the neuroanatomy of proprioception is crucial for advancing therapeutic approaches which target individuals with proprioceptive impairments following neurological injury or with neurological disorders.

Effectiveness of Rehabilitation Nursing versus Usual Therapist-Led Treatment in Patients with Acute Ischemic Stroke: A Randomized Non-Inferiority Trial

Purpose

To determine the effectiveness of rehabilitation nursing program interventions in patients with acute ischemic stroke.

Patients and Methods

An assessment-blinded randomized controlled trial was conducted at a tertiary referral hospital in China. Eligible patients were stratified according to their weighted corticospinal tract lesion load and then randomly assigned to an experimental group (n = 121) or a control group (n = 103). The experimental group received rehabilitation nursing from well-trained, qualified nurses (30 minutes per session, two sessions per day for seven consecutive days). The control group received therapist-led rehabilitation with the same timing and frequency. Comparative analysis of the primary outcomes was performed to determine non-inferiority with a predetermined non-inferiority margin. The primary outcomes were the Motor Assessment Scale, Fugl-Meyer Assessment, and the Action Research Arm Test assessed at baseline and after seven days of treatment. The secondary outcomes were the modified Barthel Index, the National Institutes of Health Stroke Scale, and the modified Rankin Scale, evaluated before and after the intervention and at 4 and 12 weeks of follow-up.

Results

Two hundred participants completed the trial. In both groups, all outcomes improved significantly after seven days and at follow-ups. The rehabilitation nursing program was non-inferior to therapist-led treatment with lower 95% confidence limits beyond the margins for primary outcomes (P < 0.001).

Conclusion

Both treatments had comparable effects; however, no definite conclusion could be drawn. Adequately powered studies are required.

Cortical N-acetylaspartate concentrations are impacted in chronic stroke but do not relate to motor impairment: A magnetic resonance spectroscopy study

Magnetic resonance spectroscopy (MRS) measures cerebral metabolite concentrations, which can inform our understanding of the neurobiological processes associated with stroke recovery. Here, we investigated whether metabolite concentrations in primary motor and somatosensory cortices (sensorimotor cortex) are impacted by stroke and relate to upper‐extremity motor impairment in 45 individuals with chronic stroke. Cerebral metabolite estimates were adjusted for cerebrospinal fluid and brain tissue composition in the MRS voxel. Upper‐extremity motor impairment was indexed with the Fugl‐Meyer (FM) scale. N‐acetylaspartate (NAA) concentration was reduced bilaterally in stroke participants with right hemisphere lesions (n = 23), relative to right‐handed healthy older adults (n = 15; p = .006). Within the entire stroke sample (n = 45) NAA and glutamate/glutamine (GLX) were lower in the ipsilesional sensorimotor cortex, relative to the contralesional cortex (NAA: p < .001; GLX: p = .003). Lower ipsilesional NAA was related to greater extent of corticospinal tract (CST) injury, quantified by a weighted CST lesion load (p = .006). Cortical NAA and GLX concentrations did not relate to the severity of chronic upper‐extremity impairment (p > .05), including after a sensitivity analysis imputing missing metabolite data for individuals with large cortical lesions (n = 5). Our results suggest that NAA, a marker of neuronal integrity, is sensitive to stroke‐related cortical damage and may provide mechanistic insights into cellular processes of cortical adaptation to stroke. However, cortical MRS metabolites may have limited clinical utility as prospective biomarkers of upper‐extremity outcomes in chronic stroke.

Lesion Quantification Toolkit: A MATLAB software tool for estimating grey matter damage and white matter disconnections in patients with focal brain lesions

Lesion studies are an important tool for cognitive neuroscientists and neurologists. However, while brain lesion studies have traditionally aimed to localize neurological symptoms to specific anatomical loci, a growing body of evidence indicates that neurological diseases such as stroke are best conceptualized as brain network disorders. While researchers in the fields of neuroscience and neurology are therefore increasingly interested in quantifying the effects of focal brain lesions on the white matter connections that form the brain's structural connectome, few dedicated tools exist to facilitate this endeavor. Here, we present the Lesion Quantification Toolkit, a publicly available MATLAB software package for quantifying the structural impacts of focal brain lesions. The Lesion Quantification Toolkit uses atlas-based approaches to estimate parcel-level grey matter lesion loads and multiple measures of white matter disconnection severity that include tract-level disconnection measures, voxel-wise disconnection maps, and parcel-wise disconnection matrices. The toolkit also estimates lesion-induced increases in the lengths of the shortest structural paths between parcel pairs, which provide information about changes in higher-order structural network topology. We describe in detail each of the different measures produced by the toolkit, discuss their applications and considerations relevant to their use, and perform example analyses using real behavioral data collected from sub-acute stroke patients. We show that analyses performed using the different measures produced by the toolkit produce results that are highly consistent with results that have been reported in the prior literature, and we demonstrate the consistency of results obtained from analyses conducted using the different disconnection measures produced by the toolkit. We anticipate that the Lesion Quantification Toolkit will empower researchers to address research questions that would be difficult or impossible to address using traditional lesion analyses alone, and ultimately, lead to advances in our understanding of how white matter disconnections contribute to the cognitive, behavioral, and physiological consequences of focal brain lesions.

Bringing proportional recovery into proportion: Bayesian modelling of post-stroke motor impairment

Accurate predictions of motor impairment after stroke are of cardinal importance for the patient, clinician, and healthcare system. More than 10 years ago, the proportional recovery rule was introduced by promising that high-fidelity predictions of recovery following stroke were based only on the initially lost motor function, at least for a specific fraction of patients. However, emerging evidence suggests that this recovery rule is subject to various confounds and may apply less universally than previously assumed. Here, we systematically revisited stroke outcome predictions by applying strategies to avoid confounds and fitting hierarchical Bayesian models. We jointly analysed 385 post-stroke trajectories from six separate studies-one of the largest overall datasets of upper limb motor recovery. We addressed confounding ceiling effects by introducing a subset approach and ensured correct model estimation through synthetic data simulations. Subsequently, we used model comparisons to assess the underlying nature of recovery within our empirical recovery data. The first model comparison, relying on the conventional fraction of patients called 'fitters', pointed to a combination of proportional to lost function and constant recovery. 'Proportional to lost' here describes the original notion of proportionality, indicating greater recovery in case of a more severe initial impairment. This combination explained only 32% of the variance in recovery, which is in stark contrast to previous reports of >80%. When instead analysing the complete spectrum of subjects, 'fitters' and 'non-fitters', a combination of proportional to spared function and constant recovery was favoured, implying a more significant improvement in case of more preserved function. Explained variance was at 53%. Therefore, our quantitative findings suggest that motor recovery post-stroke may exhibit some characteristics of proportionality. However, the variance explained was substantially reduced compared to what has previously been reported. This finding motivates future research moving beyond solely behaviour scores to explain stroke recovery and establish robust and discriminating single-subject predictions.

Statistical Considerations for Drawing Conclusions About Recovery

BACKGROUND

Numerous studies have found associations when change scores are regressed onto initial impairments in people with stroke (slopes ≈ 0.7). However, there are important statistical considerations that limit the conclusions we can draw about recovery from these studies.

OBJECTIVE

To provide an accessible checklist of conceptual and analytical issues on longitudinal measures of stroke recovery. Proportional recovery is an illustrative example, but these considerations apply broadly to studies of change over time.

METHODS

Using a pooled data set of n = 373 Fugl-Meyer Assessment upper extremity scores, we ran simulations to illustrate 3 considerations: (1) how change scores can be problematic in this context; (2) how "nil" and nonzero null-hypothesis significance tests can be used; and (3) how scale boundaries can create the illusion of proportionality, whereas other analytical procedures (eg, post hoc classifications) can augment this problem.

RESULTS

Our simulations highlight several limitations of common methods for analyzing recovery. We find that uniform recovery leads to similar group-level statistics (regression slopes) and individual-level classifications (into fitters and nonfitters) that have been claimed as evidence for the proportional recovery rule. New analyses, however, also speak to the complexities in variance about the regression slope.

CONCLUSIONS

Our results highlight that one cannot identify whether proportional recovery is true or not based on commonly used methods. We illustrate how these techniques, measurement tools, and post hoc classifications (eg, nonfitters) can create spurious results. Going forward, the field needs to carefully consider the influence of these factors on how we measure, analyze, and conceptualize recovery.

Infarct site and prognosis in small subcortical infarction: Role of the corticospinal tract and lentiform

OBJECTIVE

To determine the impact of infarct site combinations on prognosis of small subcortical infarction (SSI) by classifying the infarcted perforator area in relation to the anatomical structures that surround and/or involve the corticospinal tract.

METHODS

Consecutive patients with SSI ≤24 h from onset to initial magnetic resonance imaging (MRI) and ≤ 14 days from onset to second MRI were included. Infarct sites were defined as follows: caudate head, lentiform (L), corona radiata (CR), posterior limb and genu of the internal capsule (IC), thalamus, and brainstem with or without involvement of the corticospinal tract. An unfavorable outcome was defined as a modified Rankin Scale score of 2 to 6 at 3 months from onset. Infarct site combinations related to an unfavorable outcome were evaluated.

RESULTS

We screened 1558 consecutive patients with ischemic strokes, including 128 with SSI (99 [77%] male, median age 64 years). Of all, 29 (23%) had unfavorable outcomes. Factors associated with unfavorable outcomes were age (odds ratio (OR) 2.057, 95% confidence interval (CI) 1.230-3.493, p = 0.006), maximum infarct area (OR 1.094, 95% CI 1.030-1.163, p = 0.004), and infarct simultaneously involving the CR, IC, and L (OR 9.403, 95% CI 1.506-58.710, p = 0.016). Patients with simultaneous involvement of the CR, IC, and L were likely to have a higher subscore in the National Institutes of Health Stroke Scale item of arm motor impairment at discharge (OR 2.947, 95% CI 1.098-7.910, p = 0.032).

CONCLUSIONS

Infarcts involving the CR, IC, and L predict unfavorable outcomes in SSI.

Neural correlates of within-session practice effects in mild motor impairment after stroke: a preliminary investigation

While the structural integrity of the corticospinal tract (CST) has been shown to support motor performance after stroke, the neural correlates of within-session practice effects are not known. The purpose of this preliminary investigation was to examine the structural brain correlates of within-session practice effects on a functional motor task completed with the more impaired arm after stroke. Eleven individuals with mild motor impairment (mean age 57.0 ± 9.4 years, mean months post-stroke 37.0 ± 66.1, able to move ≥ 26 blocks on the Box and Blocks Test) due to left hemisphere stroke completed structural MRI and practiced a functional motor task that involved spooning beans from a start cup to three distal targets. Performance on the motor task improved with practice (p = 0.004), although response was variable. Baseline motor performance (Block 1) correlated with integrity of the CST (r = - 0.696) while within-session practice effects (change from Block 1 to Block 3) did not. Instead, practice effects correlated with degree of lesion to the superior longitudinal fasciculus (r = 0.606), a pathway that connects frontal and parietal brain regions previously shown to support motor learning. This difference between white matter tracts associated with baseline motor performance and within-session practice effects may have implications for understanding response to motor practice and the application of brain-focused intervention approaches aimed at improving hand function after stroke.

Assessment of Sex Differences in Recovery of Motor and Sensory Impairments Poststroke

Background. Understanding potential sex differences in stroke recovery is important for prognosis, ensuring appropriate allocation of health care resources, and for stratification in research studies. Previously, functional measures have shown poorer outcomes for females, however, little is known about sex differences that may exist in specific motor and sensory impairments. Objective. The aim of this study was to utilize robotic assessments of motor and sensory impairments to determine if there are sex differences at the impairment level in stroke recovery over the first 6 months poststroke. Methods. We used robotic and clinical assessments of motor and sensory impairments at 1, 6, 12, and 26 weeks poststroke in 108 males and 52 females. Linear mixed models were used to examine the effect of sex on recovery poststroke, controlling for age and lesion volume. Results. In general, we did not find significant sex differences across a range of assessments. The exception to this was a sex × age interaction for the Purdue Pegboard Assessment, where we found that females had better performance than males at younger ages (<62 years), but males had better performance at older ages. Conclusions. While recruitment biases need to be acknowledged when generalizing our results to stroke recovery at-large, our results suggest that sex differences do not exist at the impairment level poststroke.

Vision does not always help stroke survivors compensate for impaired limb position sense

BACKGROUND

Position sense is commonly impaired after stroke. Traditional rehabilitation methods instruct patients to visualize their limbs to compensate for impaired position sense.

OBJECTIVE

Our goal was to evaluate how the use of vision influences impaired position sense.

METHODS

We examined 177 stroke survivors, an average of 12.7 days (+/- 10 days (SD)) post-stroke, and 133 neurologically-intact controls with a robotic assessment of position sense. The robot positioned one limb (affected) and subjects attempted to mirror-match the position using the opposite limb (unaffected). Subjects completed the test without, then with vision of their limbs. We examined three measures of position sense: variability (Var), contraction/expansion (C/E) and systematic shift (Shift). We classified stroke survivors as having full compensation if they performed the robotic task abnormally without vision but corrected performance within the range of normal with vision. Stroke survivors were deemed to have partial compensation if they performed the task outside the range of normal without and with vision, but improved significantly with vision. Those with absent compensation performed the task abnormally in both conditions and did not improve with vision.

RESULTS

Many stroke survivors demonstrated impaired position sense with vision occluded [Var: 116 (66%), C/E: 91 (51%), Shift: 52 (29%)]. Of those stroke survivors with impaired position sense, some exhibited full compensation with vision [Var: 23 (20%), C/E: 42 (46%), Shift: 32 (62%)], others showed partial compensation [Var: 37 (32%), C/E: 8 (9%), Shift: 3 (6%)] and many displayed absent compensation (Var: 56 (48%), C/E: 41 (45%), Shift: 17 (33%)]. Stroke survivors with an affected left arm, visuospatial neglect and/or visual field defects were less likely to compensate for impaired position sense using vision.

CONCLUSIONS

Our results indicate that vision does not help many stroke survivors compensate for impaired position sense, at least within the current paradigm. This contrasts with historical reports that vision helps compensate for proprioceptive loss following neurologic injuries.