ArticleFrontiers in neuroscience2023
Changes in dynamic and static brain fluctuation distinguish minimal hepatic encephalopathy and cirrhosis patients and predict the severity of liver damage.
Article in Frontiers in neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 7 citations in OpenAlex.
- Short-term postoperative neurocognitive safety and recovery profiles of remimazolam tosilate combined with flumazenil vs. propofol in cirrhotic patients undergoing endoscopic variceal treatment: a randomized controlled trial.Frontiers in medicine · 2026Article
- Social Drivers of Health and Cognition in Cirrhosis: A Scoping Review.Clinical nursing research · 2025Article
- Machine learning techniques in hepatic encephalopathy: a scoping review.BMC medical informatics and decision making · 2025Article
- Spontaneous neural activity changes in minimal hepatic encephalopathy before and 1 month after liver transplantation.Frontiers in human neuroscience · 2025Article
- Quantitative susceptibility mapping reveals brain iron accumulation in minimal hepatic encephalopathy: associations with neurocognitive changes.Metabolic brain disease · 2024Article
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6 authors at 4 institutions in 1 country.
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Abstract
Purpose: Minimal hepatic encephalopathy (MHE) is characterized by mild neuropsychological and neurophysiological alterations that are not detectable by routine clinical examination. Abnormal brain activity (in terms of the amplitude of low-frequency fluctuation (ALFF) has been observed in MHE patients. However, little is known concerning temporal dynamics of intrinsic brain activity. The present study aimed to investigate the abnormal dynamics of brain activity (dynamic ALFF; dALFF) and static measures [static ALFF; (sALFF)] in MHE patients and to strive for a reliable imaging neuromarkers for distinguishing MHE patients from cirrhosis patients. In addition, the present study also investigated whether intrinsic brain activity predicted the severity of liver damage. Methods: Thirty-four cirrhosis patients with MHE, 28 cirrhosis patients without MHE, and 33 age-, sex-, and education-matched healthy controls (HCs) underwent resting-state magnetic resonance imaging (rs-fMRI). dALFF was estimated by combining the ALFF method with the sliding-window method, in which temporal variability was quantized over the whole-scan timepoints and then compared among the three groups. Additionally, dALFF, sALFF and both two features were utilized as classification features in a support vector machine (SVM) to distinguish MHE patients from cirrhosis patients. The severity of liver damage was reflected by the Child-Pugh score. dALFF, sALFF and both two features were used to predict Child-Pugh scores in MHE patients using a general linear model. Results: Compared with HCs, MHE patients showed significantly increased dALFF in the left inferior occipital gyrus, right middle occipital gyrus, and right insula; increased dALFF was also observed in the right posterior lobe of the cerebellum (CPL) and right thalamus. Compared with HCs, noMHE patients exhibited decreased dALFF in the right precuneus. In contrast, compared with noMHE patients, MHE patients showed increased dALFF in the right precuneus, right superior frontal gyrus, and right superior occipital gyrus. Furthermore, the increased dALFF values in the left precuneus were positively associated with poor digit-symbol test (DST) scores (r = 0.356, Conclusion: These findings suggest that combining dALFF and sALFF features is a useful neuromarkers for distinguishing MHE patients from cirrhosis patients and highlights the important role of dALFF feature in predicting the severity of liver damage in MHE.
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