Combining arterial-spin labeling with functional magnetic resonance imaging measurement for characterizing patients with minimal hepatic encephalopathy

Quantitative Assessment of Deep Gray Matter Susceptibility and Correlation With Cognition in Patients With Liver Cirrhosis

BACKGROUND AND OBJECTIVES

Accumulation of metals quantified by quantitative susceptibility mapping (QSM) in deep gray matter (DGM) and their impact on cognition have not been studied in patients with liver cirrhosis. This study aims to use QSM to investigate the association between DGM susceptibility and cognition in cirrhotic patients.

METHODS

Thirty cirrhotic patients and 30 age-, gender-, and education-matched controls were imaged using a multiecho gradient-echo sequence for QSM analysis in a 3T scanner. The susceptibility values were determined for the caudate nucleus (CN), putamen (PU), globus pallidus (GP), thalamus (TH), red nucleus (RN), substantia nigra (SN), and dentate nucleus (DN). All subjects underwent number connection test A (NCT-A), digit substitution test (DST), and Montreal Cognitive Assessment (MoCA). Comparisons between the two groups and the correlation between the susceptibility values and neuropsychological scores were analyzed.

RESULTS

The susceptibility values of bilateral CN, TH, and RN were significantly lower in cirrhotic patients. Cirrhotic patients exhibited significantly prolonged NCT-A time and decreased DST and MoCA scores. The NCT-A, DST, MoCA, and sub-domain scores were correlated with susceptibility values of RN, DN, SN, and CN, respectively. The susceptibility value of the left RN was a predictor variable for the DST, MoCA, and visuospatial-executive scores; those of the right CN and left RN were predictor variables for the naming score, and that of the left SN was an independent predictor variable for the language score.

CONCLUSIONS

Altered susceptibility values of DGM measured by QSM are potential quantitative indicators of cognitive impairment in cirrhotic patients.

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

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.

Whole brain atlas-based diffusion kurtosis imaging parameters for evaluation of minimal hepatic encephalopathy

BACKGROUND AND PURPOSES

Minimal hepatic encephalopathy (MHE) has no recognizable clinical symptoms, but patients have cognitive and psychomotor deficits. Hyperammonemia along with neuroinflammation lead to microstructural changes in cerebral parenchyma. Changes at conventional imaging are detected usually at the overt clinical stage, but microstructural alterations by advanced magnetic resonance imaging techniques can be detected at an early stage.

MATERIALS AND METHODS

Whole brain diffusion kurtosis imaging (DKI) data acquired at 3T was analyzed to investigate microstructural parenchymal changes in 15 patients with MHE and compared with 15 age- and sex-matched controls. DKI parametric maps, namely kurtosis fractional anisotropy (kFA), mean kurtosis (MK), axial kurtosis (AK) and radial kurtosis (RK), were evaluated at 64 white matter (WM) and gray matter (GM) regions of interest (ROIs) in the whole brain and correlated with the psychometric hepatic encephalopathy score (PHES).

RESULTS

The MHE group showed a decrease in kFA and AK across the whole brain, whereas MK and RK decreased in WM ROIs but increased in several cortical and deep GM ROIs. These alterations were consistent with brain regions involved in cognitive function. Significant moderate to strong correlations (-0.52 to -0.66; 0.56) between RK, MK and kFA kurtosis metrics and PHES were observed.

CONCLUSION

DKI parameters show extensive microstructural brain abnormalities in MHE with minor correlation between the severity of tissue damage and psychometric scores.

Decreased Mean Kurtosis in the Putamen is a Diagnostic Feature of Minimal Hepatic Encephalopathy in Patients with Cirrhosis

Objective To prevent the development of overt hepatic encephalopathy, the early intervention for minimal hepatic encephalopathy (MHE) based on an accurate diagnosis is essential. This study investigated whether or not magnetic resonance diffusion kurtosis imaging (DKI) and diffusion tensor imaging (DTI) could detect brain microstructure abnormalities in MHE. The aim was to confirm whether or not brain microstructure abnormalities detected by magnetic resonance (MR) imaging could be used for the diagnosis of MHE. Methods Thirty-two subjects were prospectively examined with a 3-T MR scanner. Tract-based spatial statistics and region of interest analyses of diffusion imaging were performed to compare the mean kurtosis (MK), fractional anisotropy (FA), and mean diffusivity (MD) values between patients with and without minimal hepatic encephalopathy. The diagnostic performance for the detection of MHE was assessed with a receiver operating characteristic analysis. Results Ten subjects were diagnosed with MHE by neuropsychological testing. After the exclusion of unsuitable subjects, we analyzed 9 subjects with MHE and 14 without MHE. The patients with MHE had a reduced MK in the widespread white matter. We also found significant decreases in the MK in the caudate nucleus, putamen, globus pallidus, and/or thalamus in the subjects with MHE. The MK in the putamen showed the best diagnostic performance for differentiating the subjects with MHE from those without MHE (cut-off value, 0.74; sensitivity, 0.89; specificity, 0.86). Conclusion DKI detects changes in the cerebral white matter and basal ganglia regions of patients with MHE more sensitively than DTI. The MK values in the putamen can be a useful marker for diagnosing MHE from cirrhotic patients without MHE.

Recent advances in hepatic encephalopathy

Hepatic encephalopathy describes the array of neurological alterations that occur during acute liver failure or chronic liver injury. While key players in the pathogenesis of hepatic encephalopathy, such as increases in brain ammonia, alterations in neurosteroid levels, and neuroinflammation, have been identified, there is still a paucity in our knowledge of the precise pathogenic mechanism. This review gives a brief overview of our understanding of the pathogenesis of hepatic encephalopathy and then summarizes the significant recent advances made in clinical and basic research contributing to our understanding, diagnosis, and possible treatment of hepatic encephalopathy. A literature search using the PubMed database was conducted in May 2017 using "hepatic encephalopathy" as a keyword, and selected manuscripts were limited to those research articles published since May 2014. While the authors acknowledge that many significant advances have been made in the understanding of hepatic encephalopathy prior to May 2014, we have limited the scope of this review to the previous three years only.