Quantitative evaluation of hepatic fibrosis by fibro Scan and Gd-EOB-DTPA-enhanced T1 mapping magnetic resonance imaging in chronic hepatitis B

Noninvasive diagnosis of liver cirrhosis: qualitative and quantitative imaging biomarkers

A diagnosis of cirrhosis initiates a shift in the management of chronic liver disease and affects the diagnostic workflow and treatment decision of primary liver cancer. Liver biopsy remains the gold standard for cirrhosis diagnosis, but it is invasive and susceptible to sampling bias and observer variability. Various qualitative and quantitative imaging biomarkers based on ultrasound, CT and MRI have been proposed for noninvasive diagnosis of cirrhosis. Qualitative imaging features are easy to apply but have moderate diagnostic sensitivity. Elastography techniques allow quantitative assessment of liver stiffness and are highly accurate for cirrhosis diagnosis. Ultrasound elastography are widely used in clinical practice, while MR elastography has narrower availability. Although not applicable in clinical practice yet, other quantitative imaging features, including liver surface nodularity, linear and volumetric measurement, extracellular volume fraction, liver enhancement on hepatobiliary phase, and parameters derived from diffusion-weighted imaging, can provide additional information of liver morphology, perfusion, and function, thus may increase diagnosis performance. The introduction of radiomics and deep learning has further improved diagnostic accuracy while reducing subjectivity. Several imaging features may also help to assess liver function and outcomes in patients with cirrhosis. In this review, we summarize the qualitative and quantitative imaging biomarkers for noninvasive cirrhosis diagnosis, and the assessment of liver function and outcomes, and discuss the challenges and future directions in this field.

Shear-wave elastography to predict hepatocellular carcinoma after hepatitis C virus eradication: A systematic review and meta-analysis

BACKGROUND

Direct-acting antiviral agents (DAAs) are highly effective treatment for chronic hepatitis C (CHC) with a significant rate of sustained virologic response (SVR). The achievement of SVR is crucial to prevent additional liver damage and slow down fibrosis progression. The assessment of fibrosis degree can be performed with transient elastography, magnetic resonance elastography or shear-wave elastography (SWE). Liver elastography could function as a predictor for hepatocellular carcinoma (HCC) in CHC patients treated with DAAs.

AIM

To explore the predictive value of SWE for HCC development after complete clearance of hepatitis C virus (HCV).

METHODS

A comprehensive literature search of clinical studies was performed to identify the ability of SWE to predict HCC occurrence after HCV clearance. In accordance with the study protocol, a qualitative and quantitative analysis of the evidence was planned.

RESULTS

At baseline and after 12 wk of follow-up, a trend was shown towards greater liver stiffness (LS) in those who go on to develop HCC compared to those who do not [baseline LS standardized mean difference (SMD): 1.15, 95% confidence interval (95%CI): 020-2.50; LS SMD after 12 wk: 0.83, 95%CI: 0.33-1.98]. The absence of a statistically significant difference between the mean LS in those who developed HCC or not may be related to the inability to correct for confounding factors and the absence of raw source data. There was a statistically significant LS SMD at 24 wk of follow-up between patients who developed HCC vs not (0.64; 95%CI: 0.04-1.24).

CONCLUSION

SWE could be a promising tool for prediction of HCC occurrence in patients treated with DAAs. Further studies with larger cohorts and standardized timing of elastographic evaluation are needed to confirm these data.

Conventional and artificial intelligence-based computed tomography and magnetic resonance imaging quantitative techniques for non-invasive liver fibrosis staging

Chronic liver disease (CLD) ultimately develops into liver fibrosis and cirrhosis and is a major public health problem globally. The assessment of liver fibrosis is important for patients with CLD for prognostication, treatment decisions, and surveillance. Liver biopsies are traditionally performed to determine the stage of liver fibrosis. However, the risks of complications and technical limitations restrict their application to screening and sequential monitoring in clinical practice. CT and MRI are essential for evaluating cirrhosis-associated complications in patients with CLD, and several non-invasive methods based on them have been proposed. Artificial intelligence (AI) techniques have also been applied to stage liver fibrosis. This review aimed to explore the values of conventional and AI-based CT and MRI quantitative techniques for non-invasive liver fibrosis staging and summarized their diagnostic performance, advantages, and limitations.

Quantitative liver magnetic resonance imaging: correlation between conventional magnetic resonance imaging, laboratory values, and prognostic indices in Budd-Chiari syndrome

PURPOSE

In Budd-Chiari syndrome (BCS), unevenly distributed parenchymal changes and perfusion abnormalities occur due to hepatic venous outflow obstruction. This study aimed to evaluate the changes in the liver parenchyma in BCS using the quantitative magnetic resonance (MR) techniques of MR elastography, T1 and T2 mapping, and diffusion imaging and correlate the quantitative MR parameters through biochemical results and prognostic indices.

METHODS

Fourteen patients with BCS (seven men and seven women) were examined retrospectively. Liver stiffness (kPa), T1 relaxation times (ms) were achieved using the modified Look-Locker inversion recovery (MOLLI) 3(2)3(2)5 sequence and B1-corrected variable flip angle methods, T2 relaxation times (ms), and apparent diffusion coefficient (ADC) values (mm2/s) were measured using regions of interest placed in the same region in all quantitative methods. Measurements were repeated at the precontrast and postcontrast hepatobiliary phases. The reduction rate (RR; %) and adjusted postcontrast T1 (%) were calculated. The values obtained from different liver parenchyma areas (whole liver, caudate lobe, pathological T2 hyperintense tissue, and relatively preserved normal-appearing tissue) were compared using the Wilcoxon signed-rank test. Spearman's correlation coefficient was used to investigate the correlation between quantitative MR parameters and biochemical parameters/ prognostic scores (Child-Pugh score, Clichy score, and Rotterdam index).

RESULTS

The parenchymal stiffness and precontrast T1 values of the caudate lobe were significantly lower than those of the remainder of the parenchyma, whereas the adjusted postcontrast T1 percentages (MOLLI) were significantly higher (P ≤ 0.027). The parenchymal stiffness value, T1 and T2 values, percentages of RR (MOLLI), and adjusted postcontrast T1 values for the pathological tissue and relatively normal tissue were significantly different (P < 0.028). No significant difference was found in terms of ADC values between any of the distinct regions of the liver. A strong correlation was detected between the Child-Pugh score, Clichy score, and precontrast T1 values obtained through the MOLLI sequence (r = 0.867, P = 0.012, r = 0.821, P = 0.023, respectively). No correlation was found between the whole liver stiffness values and the laboratory parameters, fibrosis markers, prognostic indices, or MR parameters. A significant correlation was identified between creatinine levels and several T1 parameters and the T2 relaxation time (r ≥ 0.661, P ≤ 0.052).

CONCLUSION

Tissue stiffness and T1 relaxation values are high in the areas identified as fibrosis compared with those in the relatively preserved parenchyma. The T1 relaxation time can offer quantitative information for assessing segmental functional changes and prognosis in BCS.ion for assessing segmental functional changes and prognosis in BCS.

Nomogram development and validation to predict Ki-67 expression of hepatocellular carcinoma derived from Gd-EOB-DTPA-enhanced MRI combined with T1 mapping

Objective

As an important biomarker to reflect tumor cell proliferation and tumor aggressiveness, Ki-67 is closely related to the high early recurrence rate and poor prognosis, and pretreatment evaluation of Ki-67 expression possibly provides a more accurate prognosis assessment and more better treatment plan. We aimed to develop a nomogram based on gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI) combined with T1 mapping to predict Ki-67 expression in hepatocellular carcinoma (HCC).

Methods

This two-center study retrospectively enrolled 148 consecutive patients who underwent preoperative Gd-EOB-DTPA-enhanced MRI T1 mapping and surgically confirmed HCC from July 2019 to December 2020. The correlation between quantitative parameters from T1 mapping, ADC, and Ki-67 was explored. Three cohorts were constructed: a training cohort (n = 73) and an internal validation cohort (n = 31) from Shunde Hospital of Southern Medical University, and an external validation cohort (n = 44) from the Sixth Affiliated Hospital, South China University of Technology. The clinical variables and MRI qualitative and quantitative parameters associational with Ki-67 expression were analyzed by univariate and multivariate logistic regression analyses. A nomogram was developed based on these associated with Ki-67 expression in the training cohort and validated in the internal and external validation cohorts.

Results

T1rt-Pre and T1rt-20min were strongly positively correlated with Ki-67 (r = 0.627, r = 0.607, P < 0.001); the apparent diffusion coefficient value was moderately negatively correlated with Ki-67 (r = -0.401, P < 0.001). Predictors of Ki-67 expression included in the nomogram were peritumoral enhancement, peritumoral hypointensity, T1rt-20min, and tumor margin, while arterial phase hyperenhancement (APHE) was not a significant predictor even included in the regression model. The nomograms achieved good concordance indices in predicting Ki-67 expression in the training and two validation cohorts (0.919, 0.925, 0.850), respectively.

Conclusions

T1rt-Pre and T1rt-20min had a strong positive correlation with the Ki-67 expression in HCC, and Gd-EOB-DTPA enhanced MRI combined with T1 mapping-based nomogram effectively predicts high Ki-67 expression in HCC.