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Objective: Carotid bifurcation geometry has been believed to be a risk factor for the initiation of atherosclerosis because of its influence on hemodynamics. However, the relationships between carotid bifurcation geometry and plaque vulnerability are not fully understood. This study aimed to determine the association between carotid bifurcation geometry and plaque vulnerability using magnetic resonance vessel wall imaging. Approach and Results: A total of 501 carotid arteries with nonstenotic atherosclerosis were included from the cross-sectional, multicenter CARE II study (Chinese Atherosclerosis Risk Evaluation). Four standardized carotid bifurcation geometric parameters (bifurcation angle, internal carotid artery planarity, luminal expansion FlareA, and tortuosity Tort2D) were derived from time-of-flight magnetic resonance angiography. Presence of vulnerable plaque, which was characterized by intraplaque hemorrhage, large lipid-rich necrotic core, or disrupted luminal surface, was determined based on multicontrast carotid magnetic resonance vessel wall images. Vulnerable plaques (N=43) were found to occur at more distal locations (ie, near the level of flow divider) than stable plaques (N=458). Multivariable logistic regression showed that the luminal expansion FlareA (odds ratio, 0.45 [95% CI, 0.25–0.81]; P =0.008) was associated with plaque vulnerability after adjustment for age, sex, maximum wall thickness, plaque location, and other geometric parameters. Conclusions: Smaller luminal expansion at carotid bifurcation is associated with vulnerable plaque. The finding needs to be verified with longitudinal studies and the underlying mechanism should be further explored with hemodynamics measurement in the future.

Objective: Patients with cirrhosis often exhibit cognitive deficits, particularly executive dysfunction, which is considered a predictor of overt hepatic encephalopathy (OHE). We examined brain intrinsic networks associated with executive function to investigate the neural basis of this cognitive deficiency in cirrhosis. Methods:Resting-state functional MRI data were acquired from 20 cirrhotic patients and 18 healthy controls. Seed-based correlation analysis was used to identify the three well-known networks associated with executive function, including executive control (ECN), default mode (DMN), and salience (SN) networks. Functional connectivity (FC) within each network was compared between groups and correlated with patient executive performance (assessed by the Stroop task).results: Patients showed decreased FC between the ECN seed (right dorsolateral prefrontal cortex) and several regions (including right middle/inferior frontal gyrus, left inferior frontal gyrus, bilateral inferior/superior parietal lobules, bilateral middle/inferior temporal gyrus, and right medial frontal gyrus), between the DMN seed [posterior cingulate cortex (PCC)] and several regions (including bilateral medial frontal gyrus, bilateral anterior cingulate cortex, bilateral superior frontal gyrus, bilateral precuneus/PCC, left supramarginal gyrus, and left middle temporal gyrus), and between the SN seed (right anterior insula) and right supramarginal gyrus. FC strength in the ECN and SN was negatively correlated with patient performance during the Stroop task.conclusion: Disrupted functional integration in the core brain cognitive networks, which is reflected by reductions in FC, occurs before OHE bouts and may play an important role in the neural mechanism of executive dysfunction associated with cirrhosis.

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Minimal hepatic encephalopathy (MHE) is characterized by diffuse abnormalities in cerebral structure, such as reduced cortical thickness and altered brain parenchymal volume. This study tested the potential of gray matter (GM) volumetry to differentiate between cirrhotic patients with and without MHE using a support vector machine (SVM) learning method. High-resolution, T1-weighted magnetic resonance images were acquired from 24 cirrhotic patients with MHE and 29 cirrhotic patients without MHE (NHE). Voxel-based morphometry was conducted to evaluate the GM volume (GMV) for each subject. An SVM classifier was employed to explore the ability of the GMV measurement to diagnose MHE, and the leave-one-out cross-validation method was used to assess classification accuracy. The SVM algorithm based on GM volumetry achieved a classification accuracy of 83.02%, with a sensitivity of 83.33% and a specificity of 82.76%. The majority of the most discriminative GMVs were located in the bilateral frontal lobe, bilateral lentiform nucleus, bilateral thalamus, bilateral sensorimotor areas, bilateral visual regions, bilateral temporal lobe, bilateral cerebellum, left inferior parietal lobe, and right precuneus/posterior cingulate gyrus. Our results suggest that SVM analysis based on GM volumetry has the potential to help diagnose MHE in cirrhotic patients.In summary, we successfully differentiated between cirrhotic patients with and without MHE using gray matter volumetry and an SVM classification system. The brain regions with the highest discriminant power included both cortical and subcortical structures. Therefore, our findings suggest that regional changes in GMV can be employed as a biomarker to detect MHE in cirrhotic patients.