Diffusion-weighted MRI for the assessment of liver fibrosis: principles and applications

Apparent diffusion coefficient and its standard deviation from diffusion-weighted imaging in preoperative predicting liver invasion by T3-staged resectable gallbladder carcinoma

AIM

To evaluate apparent diffusion coefficient (ADC) and its standard deviation (SDADC) in preoperative predicting liver invasion by T3-staged gallbladder carcinoma (GBC).

MATERIALS AND METHODS

Forty-one consecutive patients with T3-staged resectable GBC were included and divided into two sets with (n=27) and without (n=14) liver invasion. All patients underwent DWI at b-values of 0, 20, 50, 80, 100, 200, 400, 600, 800, and 1,000 s/mm2 with a 3 T magnetic resonance imaging scanner before surgery. ADC and SDADC of tumour-adjacent and tumour-distant liver tissues were measured on DWI, and were compared by Mann-Whitney U-tests. If there was a significant difference in any derived parameter, the area under the receiver operating characteristic curve (AUC) was used to assess performance of this parameter to predict liver invasion.

RESULTS

DWI could differentiate between patients with and without liver invasion when b = 0, 1,000 s/mm2 (AUCs of ADC and SDADC were 0.697 and 0.714, respectively). In patients with liver invasion, mean ADC and SDADC of tumour-adjacent liver tissue were lower than of tumour-distant liver tissue when b = 0, 800 s/mm2, and = 0, 1,000 s/mm2 (all p-values <0.05). To differentiate tumour-adjacent from tumour-distant liver tissues in patients with liver invasion, AUCs of ADC were 0.687 (b = 0, 800 s/mm2) and 0.680 (b = 0, 1,000 s/mm2), and AUCs of SDADC were 0.673 (b = 0, 800 s/mm2) and 0.731 (b = 0, 1,000 s/mm2).

CONCLUSIONS

DWI could have potential value in preoperative predicting liver invasion by T3-staged GBC.

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.

Determination of Non-Invasive Biomarkers for the Assessment of Fibrosis, Steatosis and Hepatic Iron Overload by MR Image Analysis. A Pilot Study

The reference diagnostic test of fibrosis, steatosis, and hepatic iron overload is liver biopsy, a clear invasive procedure. The main objective of this work was to propose HSA, or human serum albumin, as a biomarker for the assessment of fibrosis and to study non-invasive biomarkers for the assessment of steatosis and hepatic iron overload by means of an MR image acquisition protocol. It was performed on a set of eight subjects to determine fibrosis, steatosis, and hepatic iron overload with four different MRI sequences. We calibrated longitudinal relaxation times (T1 [ms]) with seven human serum albumin (HSA [%]) phantoms, and we studied the relationship between them as this protein is synthesized by the liver, and its concentration decreases in advanced fibrosis. Steatosis was calculated by means of the fat fraction (FF [%]) between fat and water liver signals in “fat-only images” (the subtraction of in-phase [IP] images and out-of-phase [OOP] images) and in “water-only images” (the addition of IP and OOP images). Liver iron concentration (LIC [µmol/g]) was obtained by the transverse relaxation time (T2* [ms]) using Gandon’s method with multiple echo times (TE) in T2-weighted IP and OOP images. The preliminary results showed that there is an inverse relationship (r = −0.9662) between the T1 relaxation times (ms) and HSA concentrations (%). Steatosis was determined with FF > 6.4% and when the liver signal was greater than the paravertebral muscles signal, and thus, the liver appeared hyperintense in fat-only images. Hepatic iron overload was detected with LIC > 36 µmol/g, and in these cases, the liver signal was smaller than the paravertebral muscles signal, and thus, the liver behaved as hypointense in IP images.

Diffusion-weighted magnetic resonance imaging for the assessment of liver fibrosis in chronic viral hepatitis

Background

Accurate noninvasive methods for the assessment of liver fibrosis are urgently needed. This prospective study evaluated the diagnostic accuracy of diffusion-weighted magnetic resonance imaging (DWI) for the staging of liver fibrosis and proposed a diagnostic algorithm using DWI to identify cirrhosis in patients with chronic viral hepatitis.

Methods

One hundred twenty-one treatment-naïve patients with chronic hepatitis B or C were evaluated with DWI followed by liver biopsy on the same day. Breath-hold single-shot echo-planar DWI was performed to measure the apparent diffusion coefficient (ADC) of the liver and spleen. Normalized liver ADC was calculated as the ratio of liver ADC to spleen ADC.

Results

There was an inverse correlation between fibrosis stage and normalized liver ADC (p<0.05). For the prediction of fibrosis stage ≥2, stage ≥3, and cirrhosis, the area under the receiver-operating curve of normalized liver ADC was 0.603, 0.704, and 0.847, respectively. The normalized liver ADC value ≤1.02×10⁻³ mm²/s had 88% sensitivity, 81% specificity, 25% positive predictive value (PPV), and 99% negative predictive value (NPV) for the diagnosis of cirrhosis. Using a sequential approach with the Fibrosis-4 index followed by DWI, normalized liver ADC ≤1.02×10⁻³ mm²/s in patients with Fibrosis-4 >3.25 yielded an 80% PPV for cirrhosis, and a 100% NPV to exclude cirrhosis in patients with Fibrosis-4 between 1.45 and 3.25. Only 15.7% of patients would require a liver biopsy. This sequential strategy can reduce DWI examinations by 53.7%.

Conclusion

Normalized liver ADC measurement on DWI is an accurate and noninvasive tool for the diagnosis of cirrhosis in patients with chronic viral hepatitis.

Evidence of Tri-Exponential Decay for Liver Intravoxel Incoherent Motion MRI: A Review of Published Results and Limitations

Diffusion weighted imaging (DWI) and intravoxel incoherent motion (IVIM) have been explored to assess liver tumors and diffused liver diseases. IVIM reflects the microscopic translational motions that occur in voxels in magnetic resonance (MR) DWI. In biologic tissues, molecular diffusion of water and microcirculation of blood in the capillary network can be assessed using IVIM DWI. The most commonly applied model to describe the DWI signal is a bi-exponential model, with a slow compartment of diffusion linked to pure molecular diffusion (represented by the coefficient D_slow), and a fast compartment of diffusion, related to microperfusion (represented by the coefficient D_fast). However, high variance in D_fast estimates has been consistently shown in literature for liver IVIM, restricting its application in clinical practice. This variation could be explained by the presence of another very fast compartment of diffusion in the liver. Therefore, a tri-exponential model would be more suitable to describe the DWI signal. This article reviews the published evidence of the existence of this additional very fast diffusion compartment and discusses the performance and limitations of the tri-exponential model for liver IVIM in current clinical settings.

Association between liver diffusion-weighted imaging apparent diffusion coefficient values and other measures of liver disease in pediatric autoimmune liver disease patients

BACKGROUND

Multiple quantitative magnetic resonance imaging (MRI) methods have been described to noninvasively detect and characterize liver fibrosis, including diffusion-weighted imaging (DWI).

PURPOSE

To evaluate associations between liver MRI DWI apparent diffusion coefficient (ADC) values and clinical factors and other quantitative liver MRI metrics in pediatric patients with autoimmune liver disease (AILD).

MATERIALS AND METHODS

Fifty-seven research liver MRI examinations performed from January 2017 to August 2018 for pediatric AILD registry participants were evaluated. Liver DWI ADC values, liver and spleen stiffness (kPa), and iron-corrected T1 (cT1; Perspectum Diagnostics) were measured at four anatomic levels. Participant age, sex, and laboratory data (alanine aminotransferase [ALT], total bilirubin, alkaline phosphatase, gamma-glutamyl transferase [GGT]) were recorded. Spearman's rank-order correlation (rho) and multiple linear regression were used to evaluate the associations between liver ADC values and predictor variables.

RESULTS

Mean (SD) participant age was 14.8 (4.0) years, 45.6% (26/57) were girls. Mean liver DWI ADC value was 1.34 (0.14 × 10^-3) mm²/s. Liver ADC values showed weak to moderate correlations with liver stiffness (r = - 0.42, p = 0.001), spleen stiffness (r = - 0.34; p = 0.015), whole-liver mean cT1 (r = - 0.39; p = 0.007), ALT (r = - 0.50; p = 0.0001), and GGT (r = - 0.48; p = 0.0004). Multiple linear regression showed liver stiffness (p = 0.0009) and sex (p = 0.023) to be independent predictors of liver ADC values.

CONCLUSION

Liver DWI ADC values are significantly associated with liver and spleen stiffnesses, liver cT1, ALT, GGT, and participant sex, with liver stiffness and sex remaining significant at multivariable regression. Liver ADC ultimately may play a role in multi-parametric prediction of chronic liver disease/fibrosis severity.

Putting it all together: established and emerging MRI techniques for detecting and measuring liver fibrosis

Chronic injury to the liver leads to inflammation and hepatocyte necrosis, which when untreated can lead to myofibroblast activation and fibrogenesis with deposition of fibrous tissue. Over time, liver fibrosis can accumulate and lead to cirrhosis and end-stage liver disease with associated portal hypertension and liver failure. Detection and accurate measurement of the severity of liver fibrosis are important for assessing disease severity and progression, directing patient management, and establishing prognosis. Liver biopsy, generally considered the clinical standard of reference for detecting and measuring liver fibrosis, is invasive and has limitations, including sampling error, relatively high cost, and possible complications. For these reasons, liver biopsy is suboptimal for fibrosis screening, longitudinal monitoring, and assessing therapeutic efficacy. A variety of established and emerging qualitative and quantitative noninvasive MRI methods for detecting and staging liver fibrosis might ultimately serve these purposes. In this article, we review multiple MRI methods for detecting and measuring liver fibrosis and discuss the diagnostic performance and specific strengths and limitations of the various techniques.

Quantitative assessment of hepatic fibrosis in chronic hepatitis B and C: T1 mapping on Gd-EOB-DTPA-enhanced liver magnetic resonance imaging

AIM

To assess the accuracy of Look-Locker on gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI) for staging liver fibrosis in chronic hepatitis B/C (CHB/C).

METHODS

We prospectively included 109 patients with CHB or CHC who underwent a 3.0-Tesla MRI examination, including T1-weighted and Look-Locker sequences for T1 mapping. Hepatocyte fractions (HeF) and relaxation time reduction rate (RE) were measured for staging liver fibrosis. A receiver operating characteristic analysis using the area under the receiver operating characteristic curve (AUC) was used to compare the diagnostic performance in predicting liver fibrosis between HeF and RE.

RESULTS

A total of 73 patients had both pathological results and MRI information. The number of patients in each fibrosis stage was evaluated semiquantitatively according to the METAVIR scoring system: F0, n = 23 (31.5%); F1, n = 19 (26.0%); F2, n = 13 (17.8%); F3, n = 6 (8.2%), and F4, n = 12 (16.4%). HeF by EOB enhancement imaging was significantly correlated with fibrosis stage (r = -0.808, P < 0.05). AUC values for diagnosis of any (≥ F1), significant (≥ F2) or advanced (≥ F3) fibrosis, and cirrhosis (F4) using HeF were 0.837 (0.733-0.913), 0.890 (0.795-0.951), 0.957 (0.881-0.990), and 0.957 (0.882-0.991), respectively. HeF measurement was more accurate than use of RE in establishing liver fibrosis staging, suggesting that calculation of HeF is a superior noninvasive liver fibrosis staging method.

CONCLUSION

A T1 mapping-based HeF method is an efficient diagnostic tool for the staging of liver fibrosis.

Staging of rat liver fibrosis using monoexponential, stretched exponential and diffusion kurtosis models with diffusion weighted imaging- magnetic resonance

Early diagnosis of liver fibrosis is important. The objective of this study was to explore the characteristics and to assess the accuracy of monoexponential, stretched exponential models (SEM), and diffusion kurtosis imaging (DKI) with diffusion-weighted imaging (DWI)-magnetic resonance imaging (MRI) in various stages of liver fibrosis in two standard rat models induced by carbon tetrachloride (CCl₄) and biliary duct ligation (BDL). Parameters (ADC, D_app, K_app, DDC, α) were measured with a 3.0T MRI. Liver fibrosis stages (F0–F4) were defined by METAVIR scoring. Parameters (ADC, D_app, DDC) were found to be negatively associated (r: -0.675~-0.789; P<0.05) with advancement of fibrosis stage. The analysis of receiver operating characteristic (ROC) curves illustrated that the areas under the curves (AUC) for ADC, D_app, and DDC were 0.687~0.957, 0.805~0.938 and 0.876~1.000, respectively. The study showed that (ADC, D_app, K_app, DDC, α) from various diffusion models reflected pathological and physiological tissue changes. We conclude that SEM and DKI may provide more accurate information about diffusion, and non-Gaussian diffusion analysis may be a complementary tool for the assessment of liver fibrosis.

Intravoxel Incoherent Motion MR Imaging for Staging of Hepatic Fibrosis

Objectives

To determine the potential of intravoxel incoherent motion (IVIM) MR imaging for staging of hepatic fibrosis (HF).

Methods

We searched PubMed and EMBASE from their inception to 31 July 2015 to select studies reporting IVIM MR imaging and HF staging. We defined F1-2 as non-advanced HF, F3-4 as advanced HF, F0 as normal liver, F1 as very early HF, and F2-4 as significant HF. Then we compared stage F0 with F1, F0-1 with F2-3, and F1-2 with F3-4 using IVIM-derived parameters (pseudo-diffusion coefficient D*, perfusion fraction f, and pure molecular diffusion parameter D). The effect estimate was expressed as a pooled weighted mean difference (WMD) with 95% confidence interval (CI), using the fixed-effects model.

Results

Overall, we included six papers (406 patients) in this study. Significant differences in D* were observed between F0 and F1, F0-1 and F2-3, and F1-2 and F3-4 (WMD 2.46, 95% CI 0.83–4.09, P = 0.006; WMD 13.10, 95% CI 9.53–16.67, P < 0.001; WMD 14.34, 95% CI 10.26–18.42, P < 0.001, respectively). Significant differences in f were also found between F0 and F1, F0-1 and F2-3, and F1-2 and F3-4 (WMD 1.62, 95% CI 0.06–3.18, P = 0.027; WMD 5.63, 95% CI 2.74–8.52, P < 0.001; WMD 3.30, 95% CI 2.10–4.50, P < 0.001, respectively). However, D showed no differences between F0 and F1, F0-1 and F2-3, and F1-2 and F3-4 (WMD 0.05, 95% CI -0.01─0.11, P = 0.105; WMD 0.04, 95% CI -0.01─0.10, P = 0.230; WMD 0.02, 95% CI -0.02─0.06, P = 0.378, respectively).

Conclusions

IVIM MR imaging provides an effective method of staging HF and can distinguish early HF from normal liver, significant HF from normal liver or very early HF, and advanced HF from non-advanced HF.

Technical advancements and protocol optimization of diffusion-weighted imaging (DWI) in liver

An area of rapid advancement in abdominal MRI is diffusion-weighted imaging (DWI). By measuring diffusion properties of water molecules, DWI is capable of non-invasively probing tissue properties and physiology at cellular and macromolecular level. The integration of DWI as part of abdominal MRI exam allows better lesion characterization and therefore more accurate initial diagnosis and treatment monitoring. One of the most technical challenging, but also most useful abdominal DWI applications is in liver and therefore requires special attention and careful optimization. In this article, the latest technical developments of DWI and its liver applications are reviewed with the explanations of the technical principles, recommendations of the imaging parameters, and examples of clinical applications. More advanced DWI techniques, including Intra-Voxel Incoherent Motion (IVIM) diffusion imaging, anomalous diffusion imaging, and Diffusion Kurtosis Imaging (DKI) are discussed.