Cortical signature of patients with HBV-related cirrhosis without overt hepatic encephalopathy: a morphometric analysis

Brain Gray Matter Alterations in Hepatic Encephalopathy: A Voxel-Based Meta-Analysis of Whole-Brain Studies

Background

Previous studies on voxel-based morphometry (VBM) have found that there were gray matter alterations in patients with hepatic encephalopathy (HE). However, the reported results were inconsistent and lack a quantitative review. Therefore, this study aims for a quantitative meta-analysis of VBM analysis on patients with HE.

Methods

The studies in our meta-analysis were collected from Pubmed, Web of Science, and Embase, which were published from January 1947 to October 2021. The seed-based d mapping (SDM) method was applied to quantitatively estimate the regional gray matter abnormalities in patients with HE. A meta-regression analysis was applied to evaluate the relationship between plasma ammonia and gray matter alteration.

Results

There were nine studies, with sixteen datasets consisting of 333 participants with HE and 429 healthy controls. The pooled and subgroup meta-analyses showed an increase in gray matter volume (GMV) in the bilateral thalamus and the calcarine fissure but a decrease in the GMV in the bilateral insula, the basal ganglia, the anterior cingulate gyrus, and the cerebellum. The meta-regression showed that plasma ammonia was positively associated with the GMV in the left thalamus but was negatively associated with the GMV in the cerebellum and the bilateral striatum.

Conclusion

Gray matter volume in patients with HE largely varied and could be affected by plasma ammonia. The findings of this study could help us to better understand the pathophysiology of cognitive dysfunction in patients with HE.

Chemotherapy-induced brain changes in breast cancer survivors: evaluation with multimodality magnetic resonance imaging

Chemotherapy related cognitive impairments are common in breast cancer patients undergoing chemotherapy. These cognitive dysfunctions are mainly attributable to chemotherapy related brain structural and functional alterations. Multimodality magnetic resonance imaging (MRI) can reveal brain gray matter volume loss, white matter microstructural disruption, reduced gray matter density, impaired cerebral blood flow and brain structural and functional connection networks at both local and global levels. This review outlines the potential applications of multimodality MR imaging techniques in chemotherapy induced cognitive deficit in breast cancer survivors and provides future research perspective in this field.

Reduced Cortical Complexity in Cirrhotic Patients with Minimal Hepatic Encephalopathy

Purpose

Gray matter volume loss, regional cortical thinning, and local gyrification index alteration have been documented in minimal hepatic encephalopathy (MHE). Fractal dimension (FD), another morphological parameter, has been widely used to describe structural complexity alterations in neurological or psychiatric disease. Here, we conducted the first study to investigate FD alterations in MHE.

Methods and Materials

We performed high-resolution structural magnetic resonance imaging on cirrhotic patients with MHE (n = 20) and healthy controls (n = 21). We evaluated their cognitive performance using the psychometric hepatic encephalopathy score (PHES). The regional FD value was calculated by Computational Anatomy Toolbox (CAT12) and compared between groups. We further estimated the association between patients' cognitive performance and FD values.

Results

MHE patients presented significantly decreased FD values in the left precuneus, left supramarginal gyrus, right caudal anterior cingulate cortex, right isthmus cingulate cortex, right insula, bilateral pericalcarine cortex, and bilateral paracentral cortex compared to normal controls. In addition, the FD values in the right isthmus cingulate cortex and right insula were shown to be positively correlated with patients' cognitive performance.

Conclusion

Aberrant cortical complexity is an additional characteristic of MHE, and FD analysis may provide novel insight into the neurobiological basis of cognitive dysfunction in MHE.

Identification of patients with and without minimal hepatic encephalopathy based on gray matter volumetry using a support vector machine learning algorithm

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.

Altered cognitive control network is related to psychometric and biochemical profiles in covert hepatic encephalopathy

The cognitive control network (CCN) is a network responsible for multiple executive functions, which are impaired in covert hepatic encephalopathy (CHE). We aimed to use functional connectivity (FC) magnetic resonance imaging to test the hypothesis that CHE manifested with disconnection within the CCN, which is associated with impaired neuropsychiatric and biochemical profiles. CHE was detected with abnormally low psychometric hepatic encephalopathy scores (PHES) (total cut-off score <−4). Two seeds in the dorsal anterior cingulate cortex (dACC) and the dorsolateral prefrontal cortex (DLPFC) were used to calculate the FC map within the CCN. Pearson correlation analysis was performed between the CCN and psychometric, biochemical profiles including ammonia, Interleukin (IL)-6, and tumor necrosis factor (TNF)-α. Eighteen CHE, 36 non-HE (NHE) cirrhotic patients and 36 controls were studied. Significant differences in FC were noted among groups, which revealed CHE patients had a lower FC in the bilateral lateral occipital cortex (seed in the bilateral dACC) and in the right lateral occipital and precuneus cortices (seed in the left DLPFC) (P < 0.05, corrected) compared with NHE. Progressively decreased FC in the left precentral gyrus within the CCN was noted from control, NHE to CHE. PHES positively and biochemistry negatively correlated with FC in the CCN. In conclusion, CHE patients showed aberrant FC within the CCN which is correlated with both cognitive dysfunction and biochemical profiles. Ammonia and pro-inflammatory cytokines may contribute to the occurrence of aberrant connectivity. Impaired FC within the CCN may serve as a complementary biomarker for CHE.

Microstructural brain abnormalities correlate with neurocognitive dysfunction in minimal hepatic encephalopathy: a diffusion kurtosis imaging study

PURPOSE

To investigate the diffusion kurtosis imaging (DKI) in early minimal hepatic encephalopathy (MHE) diagnosis and evaluate the correlations between changes in DKI metrics and cognitive performance.

METHODS

We enrolled 116 cirrhosis patients, divided into non-HE (n = 61) and MHE (n = 55), and 46 normal controls (NCs). All patients underwent cognitive testing before magnetic resonance imaging. DKI metrics were calculated through whole-brain voxel-based analysis (VBA) and differences between the groups were assessed. Pearson correlation between the DKI metrics and cognitive performance was analysed. The receiver operating characteristic (ROC) curve was used to analyse the diagnostic efficiency of DKI metrics for MHE.

RESULTS

MHE patients had significantly altered DKI metrics in a wide range of regions; lower fractional anisotropy (FA) and higher mean diffusivity (MD) are mainly located in the corpus callosum, left temporal white matter (WM), and right medial frontal WM. Furthermore, significantly altered kurtosis metrics included lower mean kurtosis (MK) in the corpus callosum and left thalamus, lower radial kurtosis (RK) in the corpus callosum, and lower axial kurtosis (AK) in the right anterior thalamic radiation. Alterations in axial diffusivity (AD), radial diffusivity (RD), and MD were closely correlated with cognitive scores. The ROC curves indicated AD in the forceps minor had the highest predictive performance for MHE in the cirrhosis patients (area under curve = 0.801, sensitivity = 77.05%, specificity = 74.55%).

CONCLUSIONS

Altered DKI metrics indicate brain microstructure abnormalities in MHE patients, some of which may be used as neuroimaging markers for early MHE diagnosis.

Multimodal MR imaging in hepatic encephalopathy: state of the art

Hepatic encephalopathy (HE) is a neurological or neuropsychological complication due to liver failure or portosystemic shunting. The clinical manifestation is highly variable, which can exhibit mild cognitive or motor impairment initially, or gradually progress to a coma, even death, without treatment. Neuroimaging plays a critical role in uncovering the neural mechanism of HE. In particular, multimodality MR imaging is able to assess both structural and functional derangements of the brain with HE in focal or neural network perspectives. In recent years, there has been rapid development in novel MR technologies and applications to investigate the pathophysiological mechanism of HE. Therefore, it is necessary to update the latest MR findings regarding HE by use of multimodality MRI to refine and deepen our understanding of the neural traits in HE. Herein, this review highlights the latest MR imaging findings in HE to refresh our understanding of MRI application in HE.