Comparison of Acoustic Structure Quantification, Transient Elastography (FibroScan) and Histology in Patients with Chronic Hepatitis B and without Moderate to Severe Hepatic Steatosis

Quantitative Ultrasound Biomarkers to Assess Nonalcoholic Fatty Liver Disease

PURPOSE

To assess diagnostic performance of quantitative ultrasound (QUS) biomarkers in assessing hepatic steatosis.

METHODS

We prospectively recruited 125 participants (mean age 54 years) who underwent liver QUS, magnetic resonance imaging (MRI), and laboratory tests within 30 days in this IRB approved study. Based on MRI-proton density fat fraction (MRI-PDFF) and MRE, we divided 125 participants into normal liver, nonalcoholic fatty liver (NAFL) and liver fibrosis (≥F1) groups. We examined diagnostic performance of ultrasound attenuation coefficient (AC), normalized local variance (NLV), superb microvascular imaging-based vascularity index (SMI-VI), and shear wave velocity (SWV) for determining hepatic steatosis and fibrosis using area under receiver operating characteristic curve (AUC). We also analyzed correlations of QUS biomarkers to MRI using Spearman correlation coefficient.

RESULTS

We observed significant differences in AC, NLV, and SMI-VI among the three groups (22 participants with normal liver, 78 with NAFL, and 25 with liver fibrosis). AUC of AC, NLV, and SMI-VI for determining ≥ mild steatotic livers (MRI-PDFF ≥5%) was 0.95, 0.90, and 0.92, respectively. AUC of SWV for determining ≥ F1 liver fibrosis was 0.93. The correlation of MRI-PDFF was positive to AC (r = 0.91) and negative to NLV (r = -0.74), SMI-VI (r = -0.8) in NAFL group. There was a significant difference in regression slope of AC to MRI-PDFF in livers with and without ≥F1 (0.84 vs 0.91, P = .02).

CONCLUSIONS

QUS biomarkers have high sensitivity and specificity to determine and grade hepatic steatosis and detect liver fibrosis. The effect of liver fibrosis on the performance of QUS biomarkers in quantifying liver fat content warrants further investigation.

Quantitative evaluation of hepatic steatosis using novel ultrasound technology normalized local variance (NLV) and its standard deviation with different ROIs in patients with metabolic-associated fatty liver disease: a pilot study

Purpose

The purpose of this study was to evaluate the diagnostic performance of novel ultrasound technology normalized local variance (NLV) and the standard deviation of NLV (NLV-SD) using different ROIs for hepatic steatosis in patients with metabolic-associated fatty liver disease (MAFLD) and to identify the factors that influence the NLV value and NLV-SD value, using pathology results as the gold standard.

Methods

We prospectively enrolled 34 consecutive patients with suspected MAFLD who underwent percutaneous liver biopsy for evaluation of hepatic steatosis from June 2020 to December 2020. All patients underwent ultrasound and NLV examinations. NLV values and NLV-SD values were measured using different ROIs just before the liver biopsy procedure.

Results

The distribution of hepatic steatosis grade on histopathology was 4/19/6/5 for none (< 5%)/ mild (5–33%)/ moderate (> 33–66%)/ and severe steatosis (> 66%), respectively. The NLV value with 50-mm-diameter ROI and NLV-SD value with 50-mm-diameter ROI showed a significant negative correlation with hepatic steatosis (spearman correlation coefficient: − 0.449, p = 0.008; − 0.471, p = 0.005). The AUROC of NLV (50 mm) for the detection of mild, moderate, and severe hepatic steatosis was 0.875, 0.735, and 0.583, respectively. The AUROC of NLV-SD (50 mm) for the detection of mild, moderate, and severe hepatic steatosis was 0.900, 0.745, and 0.603, respectively. NLV (50 mm) values and NLV-SD (50 mm) values between two readers showed excellent repeatability and the intraclass correlation coefficient (ICC) was 0.930 (p < 0.001) and 0.899 (p < 0.001). Hepatic steatosis was the only determinant factor for NLV value and NLV-SD value (p = 0.012, p = 0.038).

Conclusion

The NLV (50 mm) and NLV-SD (50 mm) provided good diagnostic performance in detecting the varying degrees of hepatic steatosis with great reproducibility. This study showed that the degree of steatosis was the only significant factor affecting the NLV value and NLV-SD value.

Ultrasound Detection of Liver Fibrosis in Individuals with Hepatic Steatosis Using the Homodyned K Distribution

Acoustic structure quantification (ASQ) based on the analysis of ultrasound backscattered statistics has been reported to detect liver fibrosis without significant hepatic steatosis. This study proposed using ultrasound parametric imaging based on the parameter α of the homodyned K (HK) distribution for staging liver fibrosis in patients with significant hepatic steatosis. Raw ultrasound image data were acquired from patients (n = 237) to construct B-mode and HK α parametric images, which were compared with the focal disturbance (FD) ratio obtained from ASQ on the basis of histologic evidence (METAVIR fibrosis score and hepatic steatosis severity). The data were divided into group I (n = 173; normal to mild hepatic steatosis) and group II (n = 64; with moderate to severe hepatic steatosis) for statistical analysis through one-way analysis of variance and receiver operating characteristic (ROC) curve analysis. The results showed that the HK α parameter monotonically decreased as the liver fibrosis stage increased (p < .05); concurrently, the FD ratio increased (p < .05). For group I, the areas under the ROC (AUROCs) obtained using the FD ratio and the α parameter (AUROC_FD and AUROC_α) were, respectively, 0.56 and 0.55, 0.68 and 0.68, 0.64 and 0.64 and 0.62 and 0.62 for diagnosing liver fibrosis ≥F1, ≥F2, ≥F3 and ≥F4. The values of AUROC_FD and AUROC_α for group II were, respectively, 0.88 and 0.91, 0.81 and 0.81, 0.77 and 0.76 and 0.78 and 0.73 for diagnosing liver fibrosis ≥F1, ≥F2, ≥F3 and ≥F4. As opposed to previous studies, ASQ was found to fail in characterizing liver fibrosis in group I; however, it was workable for identifying liver fibrosis in patients with significant hepatic steatosis (group II). Compared with ASQ, HK imaging provided improved diagnostic performance in the early detection of liver fibrosis coexisting with moderate to severe hepatic steatosis. Ultrasound HK imaging is recommended as a strategy to evaluate early fibrosis risk in patients with significant hepatic steatosis.

Ultrasound Backscatter Envelope Statistics Parametric Imaging for Liver Fibrosis Characterization: A Review

Early detection and diagnosis of liver fibrosis is of critical importance. Currently the gold standard for diagnosing liver fibrosis is biopsy. However, liver biopsy is invasive and associated with sampling errors and can lead to complications such as bleeding. Therefore, developing noninvasive imaging techniques for assessing liver fibrosis is of clinical value. Ultrasound has become the first-line tool for the management of chronic liver diseases. However, the commonly used B-mode ultrasound is qualitative and can cause interobserver or intraobserver difference. Ultrasound backscatter envelope statistics parametric imaging is an important group of quantitative ultrasound techniques that have been applied to characterizing different kinds of tissue. However, a state-of-the-art review of ultrasound backscatter envelope statistics parametric imaging for liver fibrosis characterization has not been conducted. In this paper, we focused on the development of ultrasound backscatter envelope statistics parametric imaging techniques for assessing liver fibrosis from 1998 to September 2019. We classified these techniques into six categories: constant false alarm rate, fiber structure extraction technique, acoustic structure quantification, quantile-quantile probability plot, the multi-Rayleigh model, and the Nakagami model. We presented the theoretical background and algorithms for liver fibrosis assessment by ultrasound backscatter envelope statistics parametric imaging. Then, the specific applications of ultrasound backscatter envelope statistics parametric imaging techniques to liver fibrosis evaluation were reviewed and analyzed. Finally, the pros and cons of each technique were discussed, and the future development was suggested.