Elevated bilirubin after acute ischemic stroke linked to the stroke severity

Background

Our previous study demonstrated that the level of serum bilirubin after acute ischemic stroke (AIS) was correlated to the severity of stroke, also there has the evidence of hyperbilirubinemia prevalent in AIS. We aimed to identify the exact change of bilirubin in the early phase of AIS, and study if this kind of change linked to the severity of stroke.

Methods

Bilirubin and other biochemical indexes were measured in 608 AIS patients and 188 transient ischemic attack (TIA) patients which set as the control group. National Institutes of Health Stroke Scale (NIHSS) scores were assessed simultaneously with blood collection. First, the level of bilirubin and its distribution were compared between the AIS and control group. According to a cut-off point, we next analyzed the impacted factors of elevated bilirubin including the direct bilirubin (Dbil) and total bilirubin (Tbil), especially the correlation between elevated bilirubin and the severity of stroke. Finally, we compared the difference of concentration and percent of elevated bilirubin among the Oxford Community Stroke Project (OCSP) subtypes.

Results

The level of serum Dbil and Tbil was significantly higher in the AIS group than that in the TIA group. Different distribution was observed between the two groups, which manifested as the percent of low bilirubin level group was lower while high level group was higher in AIS than that in TIA, the p value were 0.043 and 0.078 in Dbil and Tbil, respectively. When the cut-off point of elevated bilirubin was selected as Dbil ≥ 6.84 μmol/L and Tbil ≥ 22.2 μmol/L, we found that both NIHSS score and relative severity of AIS were significantly associated with elevated bilirubin whenever in Dbil or Tbil, so did the OCSP subtypes. This trend was still maintained by multivariable logistic regression analysis adjust for relative influence factors. In regard of OCSP subtypes, the highest level of bilirubin was found in TACI, so did the highest rate of elevated bilirubin.

Conclusion

The serum levels of Dbil and Tbil were increased after AIS, which linked to the severity of stroke.     

Statistical inference of dynamic resting‐state functional connectivity using hierarchical observation modeling

Spontaneous fluctuations of blood‐oxygenation level‐dependent functional magnetic resonance imaging (BOLD fMRI) signals are highly synchronous between brain regions that serve similar functions. This provides a means to investigate functional networks; however, most analysis techniques assume functional connections are constant over time. This may be problematic in the case of neurological disease, where functional connections may be highly variable. Recently, several methods have been proposed to determine moment‐to‐moment changes in the strength of functional connections over an imaging session (so called dynamic connectivity). Here a novel analysis framework based on a hierarchical observation modeling approach was proposed, to permit statistical inference of the presence of dynamic connectivity. A two‐level linear model composed of overlapping sliding windows of fMRI signals, incorporating the fact that overlapping windows are not independent was described. To test this approach, datasets were synthesized whereby functional connectivity was either constant (significant or insignificant) or modulated by an external input. The method successfully determines the statistical significance of a functional connection in phase with the modulation, and it exhibits greater sensitivity and specificity in detecting regions with variable connectivity, when compared with sliding‐window correlation analysis. For real data, this technique possesses greater reproducibility and provides a more discriminative estimate of dynamic connectivity than sliding‐window correlation analysis. Hum Brain Mapp 37:4566–4580, 2016. © 2016 Wiley Periodicals, Inc.     

Predictors of outcome after acute ischemic stroke

The aim of this study was to determine which variables should be the predictors for clinical outcome at discharge and sixth month after acute ischemic stroke. METHODS: Two hundred and sixty-six consecutive patients, each with an acute ischemic cerebrovascular disease, were evaluated within 24 h of symptom onset. We divided our patients into two groups; 1 - Independent (Rankin scale RS < or = 2) and, 2 - Dependent (RS>3) and death. Baseline characteristics, clinical variables, risk factors, infarct subtypes and radiologic parameters were analyzed. RESULTS: Canadian Neurological Scale (CNS) on admission <6.5 [odds ratio (OR) 22] and posterior circulation infarction (OR 4.2) were associated with a poor outcome at discharge from hospital whereas only a CNS score <6.5 (OR 14) was associated with a poor outcome at 6 months. CONCLUSIONS: Severity of neurologic deficit is the most important indicator for clinical outcome in acute ischemic stroke both at short-term and at sixth month, whereas posterior circulation infarction also predicts a poor outcome at discharge.     

Neurological recovery after decompressive craniectomy for massive ischemic stroke

Introduction: Decompressive craniectomy has demonstrated efficacy in reducing morbidity and mortality in critically ill patients with massive hemispheric cerebral infarction. However, little is known about the patterns of functional recovery that exist in patients after decompressive craniectomy, and controversy still exists as to whether craniotomy and infarct resection (“strokectomy”) are appropriate alternatives to decompression alone. We therefore used functional magnetic resonance imaging (f-MRI) to assess the extent and location of functional recovery in patients after decompressive craniectomy for massive ischemic stroke. Methods: f-MRI was obtained in three patients with massive nondominant cerebral infarction who had undergone decompressive craniectomy for severe cerebral edema 13 to 26 months previously. Brain activation was triggered by hand-gripping or foot-movement tasks. Imaging results were combined with periodic clinical follow-up to determine the extent of neurological recovery. Results: Activation of the contralateral hemisphere was seen in the sensorimotor cortex, premotor, and supplementary motor areas. Lesser activation patterns were seen in equivalent regions of the infarcted hemisphere. Peri-infarct activation foci were seen in two of the three patients, but no activation occurred within the area of infarction as defined by the initial stroke seen on diffusion-weighted MRI. All three patients demonstrated some corresponding neurological improvement. Conclusion: After massive hemispheric cerebral infarction requiring decompressive craniectomy, patients may experience functional recovery as a result of activation in both the infarcted and contralateral hemispheres. The evidence of functional recovery in peri-infarct regions suggests that decompression alone may be preferable to strokectomy where the risk of damage to adjacent nonischemic brain may be greater.     

Abnormal dynamic functional connectivity after sleep deprivation from temporal variability perspective

Sleep deprivation (SD) is very common in modern society and regarded as a potential causal mechanism of several clinical disorders. Previous neuroimaging studies have explored the neural mechanisms of SD using magnetic resonance imaging (MRI) from static (comparing two MRI sessions [one after SD and one after resting wakefulness]) and dynamic (using repeated MRI during one night of SD) perspectives. Recent SD researches have focused on the dynamic functional brain organization during the resting‐state scan. Our present study adopted a novel metric (temporal variability), which has been successfully applied to many clinical diseases, to examine the dynamic functional connectivity after SD in 55 normal young subjects. We found that sleep‐deprived subjects showed increased regional‐level temporal variability in large‐scale brain regions, and decreased regional‐level temporal variability in several thalamus subregions. After SD, participants exhibited enhanced intra‐network temporal variability in the default mode network (DMN) and increased inter‐network temporal variability in numerous subnetwork pairs. Furthermore, we found that the inter‐network temporal variability between visual network and DMN was negative related with the slowest 10% respond speed (β = −.42, p = 5.57 × 10⁻⁴) of the psychomotor vigilance test after SD following the stepwise regression analysis. In conclusion, our findings suggested that sleep‐deprived subjects showed abnormal dynamic brain functional configuration, which provides new insights into the neural underpinnings of SD and contributes to our understanding of the pathophysiology of clinical disorders.     

Changes in brain functional network connectivity after stroke简

Studies have shown that functional network connection models can be used to study brain net- work changes in patients with schizophrenia. In this study, we inferred that these models could also be used to explore functional network connectivity changes in stroke patients. We used independent component analysis to find the motor areas of stroke patients, which is a novel way to determine these areas. In this study, we collected functional magnetic resonance imaging datasets from healthy controls and right-handed stroke patients following their first ever stroke. Using independent component analysis, six spatially independent components highly correlat- ed to the experimental paradigm were extracted. Then, the functional network connectivity of both patients and controls was established to observe the differences between them. The results showed that there were 11 connections in the model in the stroke patients, while there were only four connections in the healthy controls. Further analysis found that some damaged connections may be compensated for by new indirect connections or circuits produced after stroke. These connections may have a direct correlation with the degree of stroke rehabilitation. Our findings suggest that functional network connectivity in stroke patients is more complex than that in hea- lthy controls, and that there is a compensation loop in the functional network following stroke. This implies that functional network reorganization plays a very important role in the process of rehabilitation after stroke.     

Altered static and dynamic functional network connectivity in Alzheimer's disease and subcortical ischemic vascular disease: shared and specific brain connectivity abnormalities

Subcortical ischemic vascular disease (SIVD) is a major subtype of vascular dementia with features that overlap clinically with Alzheimer's disease (AD), confounding diagnosis. Neuroimaging is a more specific and biologically based approach for detecting brain changes and thus may help to distinguish these diseases. There is still a lack of knowledge regarding the shared and specific functional brain abnormalities, especially functional connectivity changes in relation to AD and SIVD. In this study, we investigated both static functional network connectivity (sFNC) and dynamic FNC (dFNC) between 54 intrinsic connectivity networks in 19 AD patients, 19 SIVD patients, and 38 age‐matched healthy controls. The results show that both patient groups have increased sFNC between the visual and cerebellar (CB) domains but decreased sFNC between the cognitive‐control and CB domains. SIVD has specifically decreased sFNC within the sensorimotor domain while AD has specifically altered sFNC between the default‐mode and CB domains. In addition, SIVD has more occurrences and a longer dwell time in the weakly connected dFNC states, but with fewer occurrences and a shorter dwell time in the strongly connected dFNC states. AD has both similar and opposite changes in certain dynamic features. More importantly, the dynamic features are found to be associated with cognitive performance. Our findings highlight similar and distinct functional connectivity alterations in AD and SIVD from both static and dynamic perspectives and indicate dFNC to be a more important biomarker for dementia since its progressively altered patterns can better track cognitive impairment in AD and SIVD.     

Periinfarct rewiring supports recovery after primary motor cortex stroke

After stroke restricted to the primary motor cortex (M1), it is uncertain whether network reorganization associated with recovery involves the periinfarct or more remote regions. We studied 16 patients with focal M1 stroke and hand paresis. Motor function and resting-state MRI functional connectivity (FC) were assessed at three time points: acute (<10 days), early subacute (3 weeks), and late subacute (3 months). FC correlates of recovery were investigated at three spatial scales, (i) ipsilesional non-infarcted M1, (ii) core motor network (M1, premotor cortex (PMC), supplementary motor area (SMA), and primary somatosensory cortex), and (iii) extended motor network including all regions structurally connected to the upper limb representation of M1. Hand dexterity was impaired only in the acute phase (P = 0.036). At a small spatial scale, clinical recovery was more frequently associated with connections involving ipsilesional non-infarcted M1 (Odds Ratio = 6.29; P = 0.036). At a larger scale, recovery correlated with increased FC strength in the core network compared to the extended motor network (rho = 0.71;P = 0.006). These results suggest that FC changes associated with motor improvement involve the perilesional M1 and do not extend beyond the core motor network. Core motor regions, and more specifically ipsilesional non-infarcted M1, could hence become primary targets for restorative therapies.     

Early motor network connectivity after stroke: An interplay of general reorganization and state‐specific compensation

Motor recovery after stroke relies on functional reorganization of the motor network, which is commonly assessed via functional magnetic resonance imaging (fMRI)‐based resting‐state functional connectivity (rsFC) or task‐related effective connectivity (trEC). Measures of either connectivity mode have been shown to successfully explain motor impairment post‐stroke, posing the question whether motor impairment is more closely reflected by rsFC or trEC. Moreover, highly similar changes in ipsilesional and interhemispheric motor network connectivity have been reported for both rsFC and trEC after stroke, suggesting that altered rsFC and trEC may capture similar aspects of information integration in the motor network reflecting principle, state‐independent mechanisms of network reorganization rather than state‐specific compensation strategies. To address this question, we conducted the first direct comparison of rsFC and trEC in a sample of early subacute stroke patients (n = 26, included on average 7.3 days post‐stroke). We found that both rsFC and trEC explained motor impairment across patients, stressing the clinical potential of fMRI‐based connectivity. Importantly, intrahemispheric connectivity between ipsilesional M1 and premotor areas depended on the activation state, whereas interhemispheric connectivity between homologs was state‐independent. From a mechanistic perspective, our results may thus arise from two distinct aspects of motor network plasticity: task‐specific compensation within the ipsilesional hemisphere and a more fundamental form of reorganization between hemispheres.     

Screening diagnosis of executive dysfunction after ischemic stroke and the effects of transcranial magnetic stimulation: A prospective functional near-infrared spectroscopy study

Background

Post-ischemic stroke executive impairment (PISEI) is a serious obstacle for patients to returning to their society and is currently difficult to screen early and clinically ineffective.

Aim

The aim of the study was to clarify whether functional near-infrared spectroscopy (fNIRS) can be used as a rapid screening tool for PISEI and to explore the efficacy of transcranial magnetic stimulation (TMS) in PISEI patients and the changes in brain function.

Methods

A single-blind, randomized controlled study design was used to detect hemodynamic differences by fNIIRS in 16 PISEI patients and 16 healthy subjects during the resting state and Stroop task, respectively. After 3 days, all subjects received a single TMS intervention and underwent simultaneous fNIRS testing for the Stroop task before and 3 days after the TMS intervention.

Results

PISEI patients had significantly higher HbO₂ content in the left dorsolateral prefrontal cortex (DLPFC), the right pre-motor cortex (PMC) and the right primary sensorimotor cortex (SM1) during the Stroop task compared to the resting state (F = 141.966, p < 0.001), but significantly lower than healthy subjects (T = −3.413, p = 0.002). After TMS intervention, PISEI patients' time and error number scores on the Stroop test were significantly enhanced, and the functional activity of the above-mentioned brain regions was significantly more active than at baseline, while the strength of their functional connections with each other was markedly increased.

Conclusions

fNIRS helped screen and diagnose PISEI. A single TMS session benefited PISEI patients with effects lasting 3 days, which may be attributed to activation of the left DLPFC, right PMC and right SM1 brain regions.     

An average sliding window correlation method for dynamic functional connectivity

Sliding window correlation (SWC) is utilized in many studies to analyze the temporal characteristics of brain connectivity. However, spurious artifacts have been reported in simulated data using this technique. Several suggestions have been made through the development of the SWC technique. Recently, it has been proposed to utilize a SWC window length of 100 s given that the lowest nominal fMRI frequency is 0.01 Hz. The main pitfall is the loss of temporal resolution due to a large window length. In this work, we propose an average sliding window correlation (ASWC) approach that presents several advantages over the SWC. One advantage is the requirement for a smaller window length. This is important because shorter lengths allow for a more accurate estimation of transient dynamicity of functional connectivity. Another advantage is the behavior of ASWC as a tunable high pass filter. We demonstrate the advantages of ASWC over SWC using simulated signals with configurable functional connectivity dynamics. We present analytical models explaining the behavior of ASWC and SWC for several dynamic connectivity cases. We also include a real data example to demonstrate the application of the new method. In summary, ASWC shows lower artifacts and resolves faster transient connectivity fluctuations, resulting in a lower mean square error than in SWC.     

Transient states of network connectivity are atypical in autism: A dynamic functional connectivity study

There is ample evidence of atypical functional connectivity (FC) in autism spectrum disorders (ASDs). However, transient relationships between neural networks cannot be captured by conventional static FC analyses. Dynamic FC (dFC) approaches have been used to identify repeating, transient connectivity patterns (“states”), revealing spatiotemporal network properties not observable in static FC. Recent studies have found atypical dFC in ASDs, but questions remain about the nature of group differences in transient connectivity, and the degree to which states persist or change over time. This study aimed to: (a) describe and relate static and dynamic FC in typical development and ASDs, (b) describe group differences in transient states and compare them with static FC patterns, and (c) examine temporal stability and flexibility between identified states. Resting‐state functional magnetic resonance imaging (fMRI) data were collected from 62 ASD and 57 typically developing (TD) children and adolescents. Whole‐brain, data‐driven regions of interest were derived from group independent component analysis. Sliding window analysis and k‐means clustering were used to explore dFC and identify transient states. Across all regions, static overconnnectivity and increased variability over time in ASDs predominated. Furthermore, significant patterns of group differences emerged in two transient states that were not observed in the static FC matrix, with group differences in one state primarily involving sensory and motor networks, and in the other involving higher‐order cognition networks. Default mode network segregation was significantly reduced in ASDs in both states. Results highlight that dynamic approaches may reveal more nuanced transient patterns of atypical FC in ASDs.     

Assessment of leptomeningeal collaterals using dynamic CT angiography in patients with acute ischemic stroke

Whole-brain dynamic time-resolved computed tomography angiography (CTA) is a technique developed on the new 320-detector row CT scanner capable of generating time-resolved cerebral angiograms from skull base to vertex. Unlike a conventional cerebral angiogram, this technique visualizes pial arterial filling in all vascular territories, thereby providing additional hemodynamic information. Ours was a retrospective study of consecutive patients with ischemic stroke and M1 middle cerebral artery +/−intracranial internal carotid artery occlusions presenting to our center from June 2010 and undergoing dynamic time-resolved CTA and perfusion CT within 6 hours of symptom onset. Leptomeningeal collateral status was assessed by determining relative prominence of pial arteries in the ischemic region, rate and extent of retrograde flow, and various topographical patterns of pial arterial filling. Twenty-five patients were included in the study. We demonstrate the existence of the following novel properties of leptomeningeal collaterals in humans: (a) posterior (posterior cerebral artery (PCA)–MCA) dominant collateralization, (b) intra-territorial ‘within MCA region'' leptomeningeal collaterals, and (c) significant variability in size, extent, and retrograde filling time in pial arteries. We also describe a simple and reliable collateral grading template that, for the first time on dynamic CTA, incorporates back-filling time as well as size and extent of collateral filling.     

Low-normal free triiodothyronine and high leukocyte levels in relation to stroke severity and poor outcome in acute ischemic stroke with intracranial atherosclerotic stenosis

Background: It is uncertain that the effect of free triiodothyronine (FT3) within normal ranges on initial severity and early functional outcomes in acute ischemic stroke (AIS) patients with Intracranial Atherosclerotic Stenosis (ICAS). The predictive values of white blood cell (WBC) and FT3 are also unclear in symptomatic ICAS (sICAS) patients.

Methods: We consecutively reviewed 848 ischemic stroke patients admitted into Xiangya Hospital within 72?h after symptom onset. sICAS was defined as AIS patient with degree of ICAS ≥50% proved by magnetic resonance angiography, computed tomography angiography or digital subtraction angiography. WBC and FT3 were assessed within 24?h after admission. Neurological severity was evaluated on admission using the National Institutes of Health Stroke Scale (NIHSS). Stroke outcomes were defined by the modified Rankin Scale (mRS) on the 14th day after admission.

Results: Logistic regression analysis showed that hypertension, lower FT3 and higher WBC concentrations independently associated with severe stroke [FT3 (odds ratio(OR)?=?0.543, 95% confidence interval(95% CI): 0.383–0.769); hypertension (OR = 0.436, 95% CI: 0.238–0.800); WBC (OR = 1.17; 95% CI:1.041–1.316]. Besides, lower FT3, higher FT4, higher WBC and higher plasma glucose concentrations independently associated with unfavorable outcomes [FT3 (OR = 0.460; 95% CI: 0.306–0.690); FT4 (OR = 1.151; 95% CI: 1.055–1.255); WBC (OR = 1.178; 95% CI: 1.039–1.334); Plasma glucose (OR = 1.160; 95% CI: 1.002–1.342)].

Conclusions: Lower FT3 levels within normal ranges and higher WBC count are independently associated with the severity and early poor prognosis of sICAS simultaneously, FT3 and WBC count might be important biomarkers for sICAS patients.