Identifying Minimal Hepatic Encephalopathy: A New Perspective from Magnetic Resonance Imaging.

Autor: Wang Y; Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha, China., Yang L; Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha, China., Shang Y; Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha, China., Huang Y; Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha, China., Ju C; Department of Radiology, The Second Affiliated Hospital of Xinjiang Medical University, Urumqi, China., Zheng H; Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China., Zhao W; Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha, China.; Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.; Clinical Research Center for Medical Imaging in Hunan Province, Changsha, China., Liu J; Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha, China.; Clinical Research Center for Medical Imaging in Hunan Province, Changsha, China.; Department of Radiology Quality Control Center in Hunan Province, Changsha, China.
Jazyk: angličtina
Zdroj: Journal of magnetic resonance imaging : JMRI [J Magn Reson Imaging] 2025 Jan; Vol. 61 (1), pp. 11-24. Date of Electronic Publication: 2023 Dec 27.
DOI: 10.1002/jmri.29179
Abstrakt: Type C hepatic encephalopathy (HE) is a condition characterized by brain dysfunction caused by liver insufficiency and/or portal-systemic blood shunting, which manifests as a broad spectrum of neurological or psychiatric abnormalities, ranging from minimal HE (MHE), detectable only by neuropsychological or neurophysiological assessment, to coma. Though MHE is the subclinical phase of HE, it is highly prevalent in cirrhotic patients and strongly associated with poor quality of life, high risk of overt HE, and mortality. It is, therefore, critical to identify MHE at the earliest and timely intervene, thereby minimizing the subsequent complications and costs. However, proper and sensitive diagnosis of MHE is hampered by its unnoticeable symptoms and the absence of standard diagnostic criteria. A variety of neuropsychological or neurophysiological tests have been performed to diagnose MHE. However, these tests are nonspecific and susceptible to multiple factors (eg, aging, education), thereby limiting their application in clinical practice. Thus, developing an objective, effective, and noninvasive method is imperative to help detect MHE. Magnetic resonance imaging (MRI), a noninvasive technique which can produce many objective biomarkers by different imaging sequences (eg, Magnetic resonance spectroscopy, DWI, rs-MRI, and arterial spin labeling), has recently shown the ability to screen MHE from NHE (non-HE) patients accurately. As advanced MRI techniques continue to emerge, more minor changes in the brain could be captured, providing new means for early diagnosis and quantitative assessment of MHE. In addition, the advancement of artificial intelligence in medical imaging also presents the potential to mine more effective diagnostic biomarkers and further improves the predictive efficiency of MHE. Taken together, advanced MRI techniques may provide a new perspective for us to identify MHE in the future. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.
(© 2023 International Society for Magnetic Resonance in Medicine.)
Databáze: MEDLINE
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