Monoexponential and Biexponential Fitting of Diffusional Magnetic Resonance Imaging Signal Analysis for Prediction of Liver Fibrosis Severity:

Magnetic Resonance imaging analysis of liver fibrosis and inflammation: overwhelming gray zones restrict clinical use

Magnetic resonance (MR) identification and grading of subjects with liver fibrosis and inflammation represents a clinical challenge. MR elastography plays a well-defined role in fibrosis estimation, but its use is not widely available in clinical settings. Given that liver MR is becoming the reference standard for fat and iron quantitation, there is a need to clarify whether there is any role for MR imaging in the concomitant evaluation of fibrosis and inflammation in this setting. This review summarizes the diagnostic estimations of different MR imaging parameters obtained from conventional non-contrast-enhanced multiple b values diffusion-weighted acquisitions, variable flip angles T1 relaxation maps and STIR images. Although some derived parameters have shown a significant correlation to histological scores, a small magnitude of effect with wide overlap across severity grades is the rule. Contrary to fat and iron quantification, the low precision and reproducibility of MR imaging metrics limits its clinical relevance in fibrosis and inflammation assessment. In a sequential clinical approach combining different methodologies, MR imaging has no applicability for ruling-out and low accuracy for ruling-in advanced fibrosis. Thereby, MR elastography remains as the only image method with high diagnostic accuracy for the detection of advanced fibrosis. Until date, inflammation remains in a gray zone where biopsy cannot be replaced, and further investigations are needed. The present review offers an in-depth discuss of the MR imaging diagnostic performance for the evaluation of liver fibrosis and inflammation, highlighting the need for scientific improvements.

Multiparametric MR mapping in clinical decision-making for diffuse liver disease

Accurate diagnosis, monitoring and treatment decisions in patients with chronic liver disease currently rely on biopsy as the diagnostic gold standard, and this has constrained early detection and management of diseases that are both varied and can be concurrent. Recent developments in multiparametric magnetic resonance imaging (mpMRI) suggest real potential to bridge the diagnostic gap between non-specific blood-based biomarkers and invasive and variable histological diagnosis. This has implications for the clinical care and treatment pathway in a number of chronic liver diseases, such as haemochromatosis, steatohepatitis and autoimmune or viral hepatitis. Here we review the relevant MRI techniques in clinical use and their limitations and describe recent potential applications in various liver diseases. We exemplify case studies that highlight how these techniques can improve clinical practice. These techniques could allow clinicians to increase their arsenals available to utilise on patients and direct appropriate treatments.

Value of intravoxel incoherent motion in detecting and staging liver fibrosis: A meta-analysis

BACKGROUND

Liver fibrosis (LF) is a common pathological feature of all chronic liver diseases. With the accumulation of extracellular matrix in the fibrotic liver, true molecular water diffusion and perfusion-related diffusion are restricted. Intravoxel incoherent motion (IVIM) can capture the information on tissue diffusivity and microcapillary perfusion separately and reflect the fibrotic severity with diffusion coefficients.

AIM

To investigate the diagnostic performance of IVIM in detecting and staging LF with histology as a reference standard.

METHODS

A comprehensive literature search was conducted to identify studies on the diagnostic accuracy of IVIM for assessment of histologically proven LF. The stages of LF were classified as F0 (no fibrosis), F1 (portal fibrosis without septa), F2 (periportal fibrosis with few septa), F3 (septal fibrosis), and F4 (cirrhosis) according to histopathological findings. Data were extracted to calculate the pooled sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratio, as well as the area under the summary receiver operating characteristic curve (AUC) in each group.

RESULTS

A total of 12 studies with 923 subjects were included in this meta-analysis with 5 studies (n = 465) for LF ≥ F1, 9 studies (n = 757) for LF ≥ F2, 4 studies (n = 413) for LF ≥ F3, and 6 studies (n = 562) for LF = F4. The pooled sensitivity and specificity were estimated to be 0.78 (95% confidence interval: 0.73-0.82) and 0.81 (0.74-0.86) for LF ≥ F1 detection with IVIM; 0.82 (0.79-0.86) and 0.80 (0.75-0.84) for staging F2 fibrosis; 0.85 (0.79-0.90) and 0.83 (0.77-0.87) for staging F3 fibrosis, and 0.90 (0.84-0.94) and 0.75 (0.70-0.79) for detecting F4 cirrhosis, respectively. The AUCs for LF ≥ F1, F2, F3, F4 detection were 0.862 (0.811-0.914), 0.883 (0.856-0.909), 0.886 (0.865-0.907), and 0.899 (0.866-0.932), respectively. Moderate to substantial heterogeneity was observed with inconsistency index (I²) ranging from 0% to 77.9%. No publication bias was detected.

CONCLUSION

IVIM is a noninvasive tool with good diagnostic performance in detecting and staging LF. Optimized and standardized IVIM protocols are needed to further improve its diagnostic accuracy in clinical practice.