The Microstructural Status of the Corpus Callosum Is Associated with the Degree of Motor Function and Neurological Deficit in Stroke Patients

<div><p>Human neuroimaging studies and animal models have suggested that white matter damage from ischemic stroke leads to the functional and structural reorganization of perilesional and remote brain regions. However, the quantitative relationship between the transcallosal tract integrity and clinical motor performance score after stroke remains unexplored. The current study employed a tract-based spatial statistics (TBSS) analysis on diffusion tensor imaging (DTI) to investigate the relationship between white matter diffusivity changes and the clinical scores in stroke patients. Probabilistic fiber tracking was also used to identify structural connectivity patterns in the patients. Thirteen ischemic stroke patients and fifteen healthy control subjects participated in this study. TBSS analyses showed that the corpus callosum (CC) and bilateral corticospinal tracts (CST) in the stroke patients exhibited significantly decreased fractional anisotropy and increased axial and radial diffusivity compared with those of the controls. Correlation analyses revealed that the motor and neurological deficit scores in the stroke patients were associated with the value of diffusivity indices in the CC. Compared with the healthy control group, probabilistic fiber tracking analyses revealed that significant changes in the inter-hemispheric fiber connections between the left and right motor cortex in the stroke patients were primarily located in the genu and body of the CC, left anterior thalamic radiation and inferior fronto-occipital fasciculus, bilateral CST, anterior/superior corona radiate, cingulum and superior longitudinal fasciculus, strongly suggesting that ischemic induces inter-hemispheric network disturbances and disrupts the white matter fibers connecting motor regions. In conclusion, the results of the present study show that DTI-derived measures in the CC can be used to predict the severity of motor skill and neurological deficit in stroke patients. Changes in structural connectivity pattern tracking between the left and right motor areas, particularly in the body of the CC, might reflect functional reorganization and behavioral deficit.</p></div

DTI-TBSS analysis showed significant areas in the stroke compared with those in the controls.

<p>White matter structures showing a significant FA decrease and an AD and RD increase in different brain regions in the stroke group (p_FWE < 0.05 corrected for multiple comparisons). Statistical images were overlapped onto the mean of the skeleton (green) and the MNI152 template (gray-scale) for visualization. L, left; FA, fractional anisotropy; AD, axial diffusivity; RD, radial diffusivity.</p

TBSS correlation analyses between FA and Fugl-Meyer Motor Assessment in patients.

<p>The FA values were positively correlated with the FMA scores (A), whereas the AD and RD values were negatively correlated with the FMA scores (B and C). DTI indices in the CC (black circle) showing consistent correlation with the FMA scores in stroke patients. The mean DTI indices from the cluster located in the CC, and the indices correlated with the FMA were extracted. Spearman correlation analyses were used and scatter plots were drawn to demonstrate associations between the mean DTI-indices and the FMA scores (rightmost pictures). The line represents the direction of the association and does not indicate a line of regression. L, left.</p

Demographic and imaging data.

<p>Abbreviations: BG, basal ganglia; CN, caudate nucleus; CS, centrum semiovale; F, female; FMA, Fugl-Meyer Motor Assessment scale; L, left; M, male; NDS, Neurological Deficit Scores; R, right; TH, thalamus.</p><p>Demographic and imaging data.</p

Scatter plot of correlation analysis.

<p>A significant negative correlation between Fugl-Meyer Motor Assessment (FMA) and China Neurological Deficit Scores (NDS) was observed in stroke patients (r = -0.871, p < 0.001).</p

Statistical comparison of the individual probabilistic maps between groups.

<p>The statistical comparison demonstrated that the tracts connecting left and right motor regions were different between the groups. Compared with the healthy control group, a lower streamline density was detected in the patient group (read to yellow). The observed differences between the two groups were primarily located in the genu and body of the CC, left anterior thalamic radiation and inferior fronto-occipital fasciculus, bilateral CST, anterior/superior corona radiata, cingulum and superior longitudinal fasciculus (SLF). L, left.</p

Abnormal regional homogeneity (ReHo) changes between groups.

<p>Compared with healthy controls, decreased ReHo in the insula, the rostral anterior cingulate cortex (rACC), the supplementary motor area (SMA) and the cuneus were shown similarly in the whole migraine patients without aura (MWoA) group (Figure 2.a), SDS (+) group (Figure 2.b) and SDS (−) group (Figure 2.c) (p < 0.05, FWE corrected), which was indicate by a cool color. It is noteworthy that the caudate showed increased ReHo in the SDS (−) group compared with healthy controls (at the bottom of Figure 2.c shown in a warm color), and compared with the SDS (+) group (at the bottom of Figure 2.d in a cool color) (p < 0.05, FWE corrected). As indicated by the straight lines with the arrow, the average ReHo values of the caudate in Figure 2.c was significantly positively correlated with duration of migraine in the SDS (−) group separately. (SDS (+) group: migraine patients without aura with high depressive symptoms, self-rating depression scale (SDS) scores > 49; SDS (−) group: migraine patients without aura with low depressive symptoms, SDS scores ≤ 49.)</p

Studies included in the ALE meta-analyses.

<p>CS = cutaneous stimulation, CUR = current, EA = electro-acupuncture, ERRM = even reinforcing and reducing method, L = left, MA = manual acupuncture, NAP = non-acupuncture point, R = right.</p

Results from the ALE meta-analyses.

<p>Meta-analyses were performed to evaluate brain response to acupuncture across studies, and contrast verum and sham acupuncture. (A) Brain response to verum acupuncture demonstrated activation in sensorimotor and affective/salience processing brain regions and deactivation in the amygdala and DMN brain regions. (B) Differences in brain response for verum and sham acupuncture from direct contrast showed significance in somatosensory areas, limbic regions, visual processing regions and cerebellum. (C) Brain response to verum and sham acupuncture individually demonstrated activation in sensorimotor and affective/salience processing brain regions and deactivation in the amygdala and DMN brain regions associated with verum acupuncture; while sham acupuncture produced activation in somatosensory regions, affective/salience processing regions, cerebellum and deactivation in limbic regions. (D) Differences in brain response between verum and sham acupuncture from subtraction analysis showed more activation in the sensorimotor affective/cognitive processing brain regions and more deactivation in the amygdala/hippocampal formation for verum acupuncture. For subfigures A–C, p<0.05, cluster level FDR corrected, color bar showed ALE value; for subfigure D, p<0.05, cluster level uncorrected, color bar showed Z value. Amyg: amygdala; Ce: cerebellum; dlPFC: dorsolateral prefrontal cortex; FG: fusiform gyrus; H: hippocampal formation; IN: insula; MCC: middle cingulate cortex; Nac: nucleus accumbens; paraHG: parahippocampal gyrus; PCC: posterior cingulate cortex; preCG: precentral gyrus; pre-SMA: pre-supplementary motor area; SI: primary somatosensory cortex; SII: secondary somatosensory cortex; sgACC: subgenual anterior cingulate cortex; SMG: supramarginal gyrus; Th: thalamus; vmPFC: ventromedial prefrontal cortex.</p

Map of brain response to 18 different acupuncture points.

<p>Red: activation; Blue: deactivation; Yellow: overlap.</p