Validation of cerebral blood flow connectivity as imaging prognostic biomarker on subcortical stroke

Withdrawn: The altered dynamic community structure for adaptive adjustment in stroke patients with multidomain cognitive impairments: A multilayer network analysis

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Neurocognitive correlates of semantic memory navigation in Parkinson's disease

Cognitive studies on Parkinson's disease (PD) reveal abnormal semantic processing. Most research, however, fails to indicate which conceptual properties are most affected and capture patients' neurocognitive profiles. Here, we asked persons with PD, healthy controls, and individuals with behavioral variant frontotemporal dementia (bvFTD, as a disease control group) to read concepts (e.g., 'sun') and list their features (e.g., hot). Responses were analyzed in terms of ten word properties (including concreteness, imageability, and semantic variability), used for group-level comparisons, subject-level classification, and brain-behavior correlations. PD (but not bvFTD) patients produced more concrete and imageable words than controls, both patterns being associated with overall cognitive status. PD and bvFTD patients showed reduced semantic variability, an anomaly which predicted semantic inhibition outcomes. Word-property patterns robustly classified PD (but not bvFTD) patients and correlated with disease-specific hypoconnectivity along the sensorimotor and salience networks. Fine-grained semantic assessments, then, can reveal distinct neurocognitive signatures of PD.

Determining acute ischemic stroke onset time using machine learning and radiomics features of infarct lesions and whole brain

Accurate determination of the onset time in acute ischemic stroke (AIS) patients helps to formulate more beneficial treatment plans and plays a vital role in the recovery of patients. Considering that the whole brain may contain some critical information, we combined the Radiomics features of infarct lesions and whole brain to improve the prediction accuracy. First, the radiomics features of infarct lesions and whole brain were separately calculated using apparent diffusion coefficient (ADC), diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) sequences of AIS patients with clear onset time. Then, the least absolute shrinkage and selection operator (Lasso) was used to select features. Four experimental groups were generated according to combination strategies: Features in infarct lesions (IL), features in whole brain (WB), direct combination of them (IW) and Lasso selection again after direct combination (IWS), which were used to evaluate the predictive performance. The results of ten-fold cross-validation showed that IWS achieved the best AUC of 0.904, which improved by 13.5% compared with IL (0.769), by 18.7% compared with WB (0.717) and 4.2% compared with IW (0.862). In conclusion, combining infarct lesions and whole brain features from multiple sequences can further improve the accuracy of AIS onset time.

Dynamic brain activity states of memory impairment in stroke patients with varying motor outcomes

Introduction

The objective of this study was to characterize the alteration patterns of dynamic spatiotemporal activity in chronic subcortical stroke patients with varying motor outcomes, while investigating the imaging indicators relevant to the assessment of potential cognitive deficits in these patients.

Methods

A total of 136 patients and 88 normal controls were included in the analysis of static and dynamic intrinsic brain activity, determined by amplitude of low-frequency fluctuations.

Results

The findings unveiled that subcortical stroke patients exhibited significantly aberrant temporal dynamics of intrinsic brain activity, involving regions within multiple brain networks. These spatiotemporal patterns were found to be contingent upon the side of the lesion. In addition, these aberrant metrics demonstrated potential in discerning cognitive deficits in stroke patients with memory impairment, with the dynamic indices exerting more influence than the static ones. The observe findings may indicate that subcortical stroke can trigger imbalances in the segregation and integration of spatiotemporal patterns across the entire brain with multi-domain networks, especially in patients with poor motor outcomes.

Conclusion

It suggests that the temporal dynamics indices of intrinsic brain activity could serve as potential imaging indicators for assessing cognitive impairment in patients with chronic subcortical stroke, which may be associated with the motor outcomes.

Intracranial Atherosclerotic Stenosis Is Associated with Cognitive Impairment in Patients with Nondisabling Ischemic Stroke: A pCASL-Based Study

Background: Intracranial atherosclerotic stenosis (ICAS) is a key risk factor for vascular cognitive impairment. Cerebral blood flow (CBF) and the spatial coefficient of variation (sCoV) of CBF images (based on pseudocontinuous arterial spin labeling) are used to explore abnormal cerebral perfusion. We aimed to probe the mechanisms underlying cognitive impairment in patients with nondisabling anterior circulation macrovascular disease. Methods: This study included 47 patients with ICAS or occlusion and 40 controls. All participants underwent global and individual neuropsychology assessments and magnetic resonance imaging scan. The correlations between cognitive function and abnormal perfusion were explored. Results: The CBF in the ipsilateral middle cerebral artery (MCA) territory of the lesion side decreased significantly, while it increased on the contralateral side. CBF value had a significant correlation with the memory function in the right cerebral artery lesion group. The sCoV in both gray matter (GM) and the ipsilateral MCA territory of the lesion increased significantly. The sCoV value based on the GM territory or MCA territory was significantly correlated with global cognitive function, memory function, and executive function in patients with ICAS. Conclusions: The cognitive function of patients with severe ICAS or occlusion in anterior circulation was significantly impaired. sCoV could be a better indicator of cognitive impairment than CBF. Interventions to relieve vascular stenosis or occlusion and delay cognitive impairment or improve cognitive function should be actively considered.

The Combination of Whole-Brain Features and Local-Lesion Features in DSC-PWI May Improve Ischemic Stroke Outcome Prediction

Accurate and reliable outcome predictions can help evaluate the functional recovery of ischemic stroke patients and assist in making treatment plans. Given that recovery factors may be hidden in the whole-brain features, this study aims to validate the role of dynamic radiomics features (DRFs) in the whole brain, DRFs in local ischemic lesions, and their combination in predicting functional outcomes of ischemic stroke patients. First, the DRFs in the whole brain and the DRFs in local lesions of dynamic susceptibility contrast-enhanced perfusion-weighted imaging (DSC-PWI) images are calculated. Second, the least absolute shrinkage and selection operator (Lasso) is used to generate four groups of DRFs, including the outstanding DRFs in the whole brain (Lasso (WB)), the outstanding DRFs in local lesions (Lasso (LL)), the combination of them (combined DRFs), and the outstanding DRFs in the combined DRFs (Lasso (combined)). Then, the performance of the four groups of DRFs is evaluated to predict the functional recovery in three months. As a result, Lasso (combined) in the four groups achieves the best AUC score of 0.971, which improves the score by 8.9% compared with Lasso (WB), and by 3.5% compared with Lasso (WB) and combined DRFs. In conclusion, the outstanding combined DRFs generated from the outstanding DRFs in the whole brain and local lesions can predict functional outcomes in ischemic stroke patients better than the single DRFs in the whole brain or local lesions.

Abnormal functional connectivities patterns of multidomain cognitive impairments in pontine stroke patients

Cognitive dysfunction in patients with infratentorial stroke has been paid little attention. Brainstem stroke may disrupt network connectivity across the whole brain and affect multidomain cognition, but the details of this process remain unclear. The study aimed to investigate the effects of stroke‐induced pontine injury on whole‐brain network connectivity and cognitive function. We included 47 patients with pontine stroke and 56 healthy comparisons (HC), who underwent cognitive tests and functional magnetic resonance imaging (fMRI). Seven meaningful brain networks were identified using independent component analysis (ICA). Patients with pontine stroke had decreased intra‐network functional connectivities (FCs) in the primary perceptual and higher cognitive control networks, including sensorimotor network (SMN), visual network (VIS), default mode network (DMN), and salience network (SAN), as well as decreased inter‐network FCs in the primary perceptual (VIS‐SMN) and higher cognitive control networks (bilateral frontoparietal networks, rFPN‐lFPN). While the FCs between the primary perceptual and higher cognitive control networks (VIS‐DMN, VIS‐rFPN, VIS‐lFPN) were increased. Furthermore, the alterations in these FCs correlated with patients' cognitive measurements. These findings suggested that the infratentorial stroke can induce dysfunctional connectivity in both primary perceptual and higher cognitive control networks at the whole‐brain level, which may be attributable to the neural substrates of multidomain cognitive deficits in these patients.