Corticospinal Tract Lesion Load Originating From Both Ventral Premotor and Primary Motor Cortices Are Associated With Post-stroke Motor Severity

2021 ◽  
pp. 154596832110684
Author(s):  
Kaori L. Ito ◽  
Bokkyu Kim ◽  
Jingchun Liu ◽  
Surjo R. Soekadar ◽  
Carolee Winstein ◽  
...  
Keyword(s):  
Retrospective Study ◽  
Primary Motor Cortex ◽  
Corticospinal Tract ◽  
Motor Impairment ◽  
Higher Order ◽  
Lesion Load ◽  
Post Stroke ◽  
Stroke Lesion ◽  
Motor Outcomes ◽  
Probabilistic Map

Lesion load of the corticospinal tract (CST-LL), a measure of overlap between a stroke lesion and the CST, is one of the strongest predictors of motor outcomes following stroke. CST-LL is typically calculated by using a probabilistic map of the CST originating from the primary motor cortex (M1). However, higher order motor areas also have projections that contribute to the CST and motor control. In this retrospective study, we examined whether evaluating CST-LL from additional motor origins is more strongly associated with post-stroke motor severity than using CST-LL originating from M1 only. We found that lesion load to both the ventral premotor (PMv) cortex and M1 were more strongly related to stroke motor severity indexed by Fugl-Meyer Assessment cut-off scores than CST-LL of M1 alone, suggesting that higher order motor regions add clinical relevance to motor impairment.

Abstract 2856: Lesion load of Corticospinal Tract and Initial Motor Impairment in the Acute Stroke Phase Predict Motor Impairment 3 Months Post-Stroke

Stroke ◽  
2012 ◽  
Vol 43 (suppl_1) ◽  
Author(s):  
Wuwei Feng ◽  
Jing Wang ◽  
Evgeny Sidorov ◽  
Christine Holmstedt ◽  
Christopher Doughty ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Acute Stroke ◽  
Corticospinal Tract ◽  
Motor Impairment ◽  
Lesion Size ◽  
Sectional Area ◽  
Lesion Load ◽  
Cross Sectional ◽  
Post Stroke ◽  
Days Of Therapy

Background: We use lesion-mapping techniques in combination with diffusion tensor imaging to quantitatively test the hypothesis that motor impairment 3 months post- stroke is inversely related to the lesion load of the corticospinal tract (CST) in the acute stroke phase. Methods: We prospectively followed up a cohort of 32 patients who presented with their first-ever acute ischemic stroke with various degree of motor deficit , had a MRI during the hospitalization, and had follow-up motor assessments using the Fugl-Meyer Upper Extremity Scale (FM-UE) at 3 months (+/- 2 weeks) after stroke. We calculated a CST-lesion load for each patient by overlaying the patient’s lesion map from diffusion weighted image with a probabilistic DTI tract constructed from 12 age-matched healthy subjects . Both raw and weighted (which accounts for the narrowing of the CST as it descends from the motor cortex to the posterior limb of the internal capsule) were calculated; weighted lesion-loads were calculated by multiplying the lesion-tract overlap on each slice by the ratio of the maximum cross-sectional area of the tract to the cross-sectional area of the tract on that particular slice). A multiple regression is fit to assess the predicted value of CST lesion load (raw or weighted), along with other variables such age, gender, lesion size, initial impairment, days of therapy known to have an possible effect on motor outcome. Results: CST-lesion load and initial motor impairment are found to be significant predictors of upper extremity motor impairment at 3 months post-stroke. Age, gender, lesion size or days of therapy does not have predictive value in our cohort study. The adjusted R² is 0.63 with initial impairment and raw lesion load in the regression model, and is 0.66 with initial impairment and weighted lesion load. Conclusions: Our data shows the degree of motor impairment at 3 months after a first-ever ischemic stroke can be predicted by the overlap of the lesion with the canonical CST derived from age-matched healthy control subjects and the initial motor impairment measured in the acute phase.

scholarly journals Premotor dorsal white matter integrity for the prediction of upper limb motor impairment after stroke

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Leonardo Boccuni ◽  
Sarah Meyer ◽  
Nicholas D’cruz ◽  
Simon S. Kessner ◽  
Lucio Marinelli ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Upper Extremity ◽  
Upper Limb ◽  
Primary Motor Cortex ◽  
Corticospinal Tract ◽  
Demographic Data ◽  
Motor Impairment ◽  
Lesion Load ◽  
Neuroimaging Data ◽  
Multivariable Regression

AbstractCorticospinal tract integrity after stroke has been widely investigated through the evaluation of fibres descending from the primary motor cortex. However, about half of the corticospinal tract is composed by sub-pathways descending from premotor and parietal areas, to which damage may play a more specific role in motor impairment and recovery, particularly post-stroke. Therefore, the main aim of this study was to investigate lesion load within corticospinal tract sub-pathways as predictors of upper limb motor impairment after stroke. Motor impairment (Fugl-Meyer Upper Extremity score) was evaluated in 27 participants at one week and six months after stroke, together with other clinical and demographic data. Neuroimaging data were obtained within the first week after stroke. Univariate regression analysis indicated that among all neural correlates, lesion load within premotor fibres explained the most variance in motor impairment at six months (R2 = 0.44, p < 0.001). Multivariable regression analysis resulted in three independent, significant variables explaining motor impairment at six months; Fugl-Meyer Upper Extremity score at one week, premotor dorsal fibre lesion load at one week, and age below or above 70 years (total R2 = 0.81; p < 0.001). Early examination of premotor dorsal fibre integrity may be a promising biomarker of upper limb motor impairment after stroke.

scholarly journals Interhemispheric Pathways Are Important for Motor Outcome in Individuals with Chronic and Severe Upper Limb Impairment Post Stroke

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Kathryn S. Hayward ◽  
Jason L. Neva ◽  
Cameron S. Mang ◽  
Sue Peters ◽  
Katie P. Wadden ◽  
...  
Keyword(s):  
Corpus Callosum ◽  
Upper Limb ◽  
Motor Impairment ◽  
Post Stroke ◽  
Significant Difference ◽  
Motor Outcome ◽  
Wolf Motor Function Test ◽  
Severe Group ◽  
And Function ◽  
Motor Outcomes

Background. Severity of arm impairment alone does not explain motor outcomes in people with severe impairment post stroke.Objective. Define the contribution of brain biomarkers to upper limb motor outcomes in people with severe arm impairment post stroke.Methods. Paretic arm impairment (Fugl-Meyer upper limb, FM-UL) and function (Wolf Motor Function Test rate, WMFT-rate) were measured in 15 individuals with severe (FM-UL ≤ 30/66) and 14 with mild–moderate (FM-UL > 40/66) impairment. Transcranial magnetic stimulation and diffusion weight imaging indexed structure and function of the corticospinal tract and corpus callosum. Separate models of the relationship between possible biomarkers and motor outcomes at a single chronic (≥6 months) time point post stroke were performed.Results. Age (ΔR20.365,p=0.017) and ipsilesional-transcallosal inhibition (ΔR20.182,p=0.048) explained a 54.7% (p=0.009) variance in paretic WMFT-rate. Prefrontal corpus callous fractional anisotropy (PF-CC FA) alone explained 49.3% (p=0.007) variance in FM-UL outcome. The same models did not explain significant variance in mild–moderate stroke. In the severe group, k-means cluster analysis of PF-CC FA distinguished two subgroups, separated by a clinically meaningful and significant difference in motor impairment (p=0.049) and function (p=0.006) outcomes.Conclusion. Corpus callosum function and structure were identified as possible biomarkers of motor outcome in people with chronic and severe arm impairment.

scholarly journals Corticospinal tract lesion load: An imaging biomarker for stroke motor outcomes

2015 ◽  
Vol 78 (6) ◽  
pp. 860-870 ◽  
Author(s):  
Wuwei Feng ◽  
Jasmine Wang ◽  
Pratik Y. Chhatbar ◽  
Christopher Doughty ◽  
Douglas Landsittel ◽  
...  
Keyword(s):  
Corticospinal Tract ◽  
Imaging Biomarker ◽  
Lesion Load ◽  
Motor Outcomes

scholarly journals Determining Corticospinal Tract Injury from Stroke Using Computed Tomography

2020 ◽  
Vol 47 (6) ◽  
pp. 775-784
Author(s):  
Timothy K. Lam ◽  
Daniel K. Cheung ◽  
Seth A. Climans ◽  
Sandra E. Black ◽  
Fuqiang Gao ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Corticospinal Tract ◽  
Imaging Modality ◽  
Motor Impairment ◽  
Demographic Variables ◽  
Acute Stage ◽  
Ct Scans ◽  
Motor Deficits ◽  
Acute Stroke Care ◽  
Stroke Lesion

ABSTRACT:Introduction:Damage to the corticospinal tract (CST) from stroke leads to motor deficits. The damage can be quantified as the amount of overlap between the stroke lesion and CST (CST Injury). Previous literature has shown that the degree of motor deficits post-stroke is related to the amount of CST Injury. These studies delineate the stroke lesion from structural T1-weighted magnetic resonance imaging (MRI) scans, often acquired for research. In Canada, computed tomography (CT) is the most common imaging modality used in routine acute stroke care. In this proof-of-principle study, we determine whether CST Injury, using lesions delineated from CT scans, significantly explains the variability in motor impairment in individuals with stroke.Methods:Thirty-seven participants with stroke were included in this study. These individuals had a CT scan within the acute stage (7 days) of their stroke and underwent motor assessments. Brain images from CT scans were registered to MRI space. We performed a stepwise regression analysis to determine the contribution of CST injury and demographic variables in explaining motor impairment variability.Results:Using clinically available CT scans, we found modest evidence that CST Injury explains variability in motor impairment (R2adj = 0.12, p = 0.02). None of the participant demographic variables entered the model.Conclusion:We show for the first time a relationship between CST Injury and motor impairment using CT scans. Further work is required to evaluate the utility of data derived from clinical CT scans as a biomarker of stroke motor recovery.

Abstract 87: Neuroimaging, Not Clinical Assessment Predicts Post-Stroke Motor Outcome in Severely Impaired Stroke Patients

Stroke ◽  
2013 ◽  
Vol 44 (suppl_1) ◽  
Author(s):  
Wuwei Feng ◽  
Jing Wang ◽  
Christopher Doughty ◽  
Christine Holmstedt ◽  
Gottfried Schlaug
Keyword(s):  
Clinical Assessment ◽  
Predictive Value ◽  
Motor Impairment ◽  
Stroke Patients ◽  
Lesion Load ◽  
Post Stroke ◽  
Motor Outcome ◽  
Severe Motor ◽  
Stroke Group ◽  
Severe Motor Impairment

Background: Initial motor impairment by clinical assessment and neuroimaging measures of corticospinal tract injury have been shown to predict 3-month motor outcome in mild-to-moderately impaired stroke patients. Clinical assessment alone is good to predict outcome of more severely impaired patients. This study aims to compare clinical assessment with neuroimaging in severely impaired patients. Methods: This study followed 27 first-ever ischemic stroke patients who presented with severe motor impairment at baseline( between 2- 5 days after stroke) which is defined as Upper Extremity Fugl-Meyer (UE-FM) Scale was <=5. Patients will be assessed at 3 months (90 ±14 days) again with UE_FM. A weighted CST lesion load (wCST-LL) was calculated by overlaying each patient’s lesion map on MRI with a probabilistic CST constructed from healthy subjects. A regression analysis was applied to assess the predictive value of wCST-LL and initial motor impairment. Results: Initial motor impairment has no predictive value (p=0.25, R 2 =0.05) while wCST-LL has a strong prediction (p=0.002, R 2 =0.31) for post-stroke motor outcome in this severely impaired stroke group. If wCST is more than 7 cc, no patient recovers more than 20 on UE_FM at 3 months. Conclusion: Compared with clinical assessment, a neuroimaging measure of CST injury excels in post-stroke motor outcome prediction in a severely impaired subgroup.

scholarly journals Motor cortex activation in hemiparetic stroke patients

Stroke ◽  
2001 ◽  
Vol 32 (suppl_1) ◽  
pp. 334-334
Author(s):  
Steven C Cramer ◽  
Keith C Stegbauer ◽  
Angela Mark ◽  
Robert Price ◽  
Kristin Barquist ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Primary Motor Cortex ◽  
Corticospinal Tract ◽  
Supplementary Motor Area ◽  
Index Finger ◽  
Motor Area ◽  
Finger Movement ◽  
Post Stroke ◽  
Paretic Limb ◽  
Hemiparetic Stroke

100 Little is known about the function of surviving motor cortex after hemiparetic stroke. Though the corticospinal tract may be damaged, function may persist via intact intracortical connections. We probed motor cortex function using paradigms unrelated to genesis of paretic limb movement. Seven patients with chronic post-stroke hemiparesis, including total hand plegia, were studied with functional MRI (fMRI). Brain activation was achieved by alternating between rest and one of several stimuli. For the plegic hand, stimuli were passive index finger movement, or viewing active movements; for the non-plegic hand, active or passive index finger movement. Brain activation maps (p<.001) were generated, after which anatomical landmarks were used to identify regions of interest within non-infarcted tissue. Tasks were rehearsed before fMRI, during which surface EMG leads were placed on 5 muscles in each arm. Patients were median 5 months post-stroke, median age 66 years. Median NIH stroke scale score was 9; Rankin, 3; and arm motor Fugl-Meyer score, 18 (normal=66); Motor Activity Log confirmed no plegic hand use. Studies with excess head movement were excluded, including all plegic hand tasks for 1 patient. Plegic hand tasks (10 studies across 6 patients) activated the stroke hemisphere in all patients, including primary motor cortex (5 patients), primary sensory cortex (5 patients), premotor cortex (4 patients), and supplementary motor area (3 patients). Non-stroke hemisphere was also activated, particularly primary motor cortex (5 patients). In a few instances, EMG disclosed paretic arm muscle activity, but this had no relationship to fMRI activation. Non-plegic hand tasks (9 studies across 7 patients) activated the stroke hemisphere ipsilaterally, including supplementary motor area in all 7 patients, and primary motor cortex in 6 patients. In patients with post-stroke hemiparesis, passive stimulation activates surviving motor cortex regions within the stroke-affected hemisphere. After corticospinal tract damage, motor cortex can still be activated during tasks unrelated to paretic limb movement. The results may suggest therapeutic avenues for improving motor function after stroke.

scholarly journals Lesion Load of the Corticospinal Tract Predicts Motor Impairment in Chronic Stroke

Stroke ◽  
2010 ◽  
Vol 41 (5) ◽  
pp. 910-915 ◽  
Author(s):  
Lin L. Zhu ◽  
Robert Lindenberg ◽  
Michael P. Alexander ◽  
Gottfried Schlaug
Keyword(s):  
Corticospinal Tract ◽  
Motor Impairment ◽  
Chronic Stroke ◽  
Lesion Load

scholarly journals Effect of opposing needling on motor cortex excitability in healthy participants and in patients with post-stroke hemiplegia: study protocol for a single-blind, randomised controlled trial

Trials ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Mindong Xu ◽  
Yinyu Zi ◽  
Jianlu Wu ◽  
Nenggui Xu ◽  
Liming Lu ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Primary Motor Cortex ◽  
Motor Evoked Potentials ◽  
Controlled Trial ◽  
Secondary Outcome ◽  
Post Stroke ◽  
Motor Cortex Excitability ◽  
Opposing Needling ◽  
Single Blind ◽  
Healthy Participants

Abstract Background Opposing needling has an obvious curative effect in the treatment of post-stroke hemiplegia; however, the mechanism of the opposing needling in the treatment of post-stroke hemiplegia is still not clear. The purpose of this study is to investigate the effect of opposing needling on the excitability of primary motor cortex (M1) of healthy participants and patients with post-stroke hemiplegia, which may provide insight into the mechanisms of opposing needling in treating post-stroke hemiplegia. Methods This will be a single-blind, randomised, sham-controlled trial in which 80 healthy participants and 40 patients with post-stroke hemiplegia will be recruited. Healthy participants will be randomised 1:1:1:1 to the 2-Hz, 50-Hz, 100-Hz, and sham electroacupuncture groups. Patients with post-stroke hemiplegia will be randomised 1:1 to the opposing needling or conventional treatment groups. The M1 will be located in all groups by using neuroimaging-based navigation. The stimulator coil of transcranial magnetic stimulation (TMS) will be moved over the left and right M1 in order to identify the TMS hotspot, followed by a recording of resting motor thresholds (RMTs) and motor-evoked potentials (MEPs) of the thenar muscles induced by TMS before and after the intervention. The primary outcome measure will be the percent change in the RMTs of the thenar muscles at baseline and after the intervention. The secondary outcome measures will be the amplitude (μV) and latency (ms) of the MEPs of the thenar muscles at baseline and after the intervention. Discussion The aim of this trial is to explore the effect of opposing needling on the excitability of M1 of healthy participants and patients with post-stroke hemiplegia. Trial registration Chinese Clinical Trial Registry ChiCTR1900028138. Registered on 13 December 2019.

scholarly journals Effect of post-stroke spasticity on voluntary movement of the upper limb

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Hadar Lackritz ◽  
Yisrael Parmet ◽  
Silvi Frenkel-Toledo ◽  
Melanie C. Baniña ◽  
Nachum Soroker ◽  
...  
Keyword(s):  
Upper Limb ◽  
Target Location ◽  
Distance Measure ◽  
Movement Time ◽  
Motor Impairment ◽  
Reach To Grasp ◽  
Motion Patterns ◽  
Post Stroke ◽  
The Impact ◽  
Elbow Motion

Abstract Background Hemiparesis following stroke is often accompanied by spasticity. Spasticity is one factor among the multiple components of the upper motor neuron syndrome that contributes to movement impairment. However, the specific contribution of spasticity is difficult to isolate and quantify. We propose a new method of quantification and evaluation of the impact of spasticity on the quality of movement following stroke. Methods Spasticity was assessed using the Tonic Stretch Reflex Threshold (TSRT). TSRT was analyzed in relation to stochastic models of motion to quantify the deviation of the hemiparetic upper limb motion from the normal motion patterns during a reaching task. Specifically, we assessed the impact of spasticity in the elbow flexors on reaching motion patterns using two distinct measures of the ‘distance’ between pathological and normal movement, (a) the bidirectional Kullback–Liebler divergence (BKLD) and (b) Hellinger’s distance (HD). These measures differ in their sensitivity to different confounding variables. Motor impairment was assessed clinically by the Fugl-Meyer assessment scale for the upper extremity (FMA-UE). Forty-two first-event stroke patients in the subacute phase and 13 healthy controls of similar age participated in the study. Elbow motion was analyzed in the context of repeated reach-to-grasp movements towards four differently located targets. Log-BKLD and HD along with movement time, final elbow extension angle, mean elbow velocity, peak elbow velocity, and the number of velocity peaks of the elbow motion were computed. Results Upper limb kinematics in patients with lower FMA-UE scores (greater impairment) showed greater deviation from normality when the distance between impaired and normal elbow motion was analyzed either with the BKLD or HD measures. The severity of spasticity, reflected by the TSRT, was related to the distance between impaired and normal elbow motion analyzed with either distance measure. Mean elbow velocity differed between targets, however HD was not sensitive to target location. This may point at effects of spasticity on motion quality that go beyond effects on velocity. Conclusions The two methods for analyzing pathological movement post-stroke provide new options for studying the relationship between spasticity and movement quality under different spatiotemporal constraints.

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