Classification of Cirrhotic Patients with or without Minimal Hepatic Encephalopathy and Healthy Subjects Using Resting-State Attention-Related Network Analysis

Abstract

BackgroundAttention deficit is an early and key characteristic of minimal hepatic encephalopathy (MHE) and has been used as indicator for MHE detection. The aim of this study is to classify the cirrhotic patients with or without MHE (NMHE) and healthy controls (HC) using the resting-state attention-related brain network analysis.Methods and FindingsResting-state fMRI was administrated to 20 MHE patients, 21 NMHE patients, and 17 HCs. Three attention-related networks, including dorsal attention network (DAN), ventral attention network (VAN), and default mode network (DMN), were obtained by independent component analysis. One-way analysis of covariance was performed to determine the regions of interest (ROIs) showing significant functional connectivity (FC) change. With FC strength of ROIs as indicators, Linear Discriminant Analysis (LDA) was conducted to differentiate MHE from HC or NMHE. Across three groups, significant FC differences were found within DAN (left superior/inferior parietal lobule and right inferior parietal lobule), VAN (right superior parietal lobule), and DMN (bilateral posterior cingulate gyrus and precuneus, and left inferior parietal lobule). With FC strength of ROIs from three networks as indicators, LDA yielded 94.6% classification accuracy between MHE and HC (100% sensitivity and 88.2% specificity) and 85.4% classification accuracy between MHE and NMHE (90.0% sensitivity and 81.0% specificity).ConclusionsOur results suggest that the resting-state attention-related brain network analysis can be useful in classification of subjects with MHE, NMHE, and HC and may provide a new insight into MHE detection.

Reduced resting state connectivity and gray matter volume correlate with cognitive impairment in minimal hepatic encephalopathy

“…We also observed a significant decrease in rs-FC in MHE patients compared to controls in DAN, which agree with previous studies [15, 17]. DAN is responsible for the orientation of endogenous attention and associated with the deterioration of selective attention and is involved in the change in voluntary attention [34, 35].…”

“…Changes in DMN have already been documented in MHE in previous studies [15–17], which show a progressive increase in DMN deterioration with the progression of cognitive impairment (negative correlations between sc-FC in some of the regions of DMN and the execution of some PHES subtests). Our results are in agreement with these studies, showing a reduction in rs-FC of DMN in patients without MHE compared to controls and a greater reduction of rs-FC in patients with MHE, as well as good correlations with the execution of the cognitive tasks.…”

Dysfunctional resting-state connectivities of brain regions with structural deficits in drug-naive first-episode schizophrenia adolescents

“…The DMN is a well-known intrinsic brain network at rest, including regions such as SPG, PHG, ITG, MTG, ANG, and IPL. The activities of these brain regions in the DMN increase spontaneously during resting state but decrease synchronously during task performance (Chen et al, 2014;Honea et al, 2005). It has been suggested that the DMN is involved in attention to internal emotional states (Raichle and Snyder, 2007), self-referential processing (Gusnard et al, 2001), and stimulus-independent thought (monitoring the internal thoughts) (Mason et al, 2007).…”

Disrupted resting-state attentional networks in T2DM patients

“…The ventral attention network (VAN) consists of the right lateralized temporal parietal junction (TPJ) and the ventral frontal cortex (VFC) and is involved in bottom-up processing of attentional re-orientation. Altered connectivity in the DAN and VAN have been demonstrated in different brain disorders with cognitive impairment, including Alzheimer’s disease (AD) and hepatic encephalopathy 16 17 .…”