Prospective study comparing hepatic steatosis assessment by magnetic resonance imaging and four ultrasound methods in 105 successive patients

Comparison of ultrasound to MR and histological methods for liver fat quantification

PURPOSE

This prospective pilot study aims to evaluate the capabilities of novel quantitative ultrasound (QUS) methods based on attenuation (Att.PLUS) and sound speed (SSp.PLUS) for detecting liver fat.

PATIENTS AND METHODS

The study included 56 individuals with biopsy-proven steatosis (percutaneous liver biopsy) ranging from 0 % to 90 % of hepatocytes containing intracellular lipid vacuoles. Histopathology was considered reference standard. Abdominal QUS examinations were conducted using Att.PLUS and SSp.PLUS techniques on the Aixplorer MACH 30 system. Comparative assessments were made using the results of liver biopsy and magnetic resonance spectroscopy (MRS) together with magnetic resonance imaging proton density fat fraction (MRI-PDFF). MR examinations were performed on the Siemens VIDA 3 T system.

RESULTS

ROC analysis was conducted for two groups: (a) patients without steatosis (S0) versus those with steatosis (S1 + S2 + S3) yielded AUC values of 0.79 for Att.PLUS and 0.78 for SSp.PLUS, in contrast to an AUC > 0.95 for MRS and MRI-PDFF; and (b) patients without or with mild steatosis (S0 + S1) versus those with severe steatosis (S2 + S3), yielded AUC values of 0.93 for Att.PLUS and 0.89 for SSp.PLUS, in contrast to an AUC > 0.99 for MRS and MRI-PDFF. However, MR methods were superior in detecting liver fat content in obese patients and post-liver transplantation individuals.

CONCLUSION

Both QUS parameters (Att.PLUS and SSp.PLUS) appear equivalent at differentiating S0 vs. (S1 + S2 + S3) patients, but the Att.PLUS parameter may be more effective at identifying advanced steatosis (S2 + S3). MR techniques outperformed QUS methods, making them more suitable for clinical studies.

WFUMB Guidelines/Guidance on Liver Multiparametric Ultrasound. Part 2: Guidance on Liver Fat Quantification

The World Federation for Ultrasound in Medicine and Biology (WFUMB) has promoted the development of this document on multiparametric ultrasound. Part 2 is a guidance on the use of the available tools for the quantification of liver fat content with ultrasound. These are attenuation coefficient, backscatter coefficient, and speed of sound. All of them use the raw data of the ultrasound beam to estimate liver fat content. This guidance has the aim of helping the reader in understanding how they work and interpret the results. Confounding factors are discussed and a standardized protocol for measurement acquisition is suggested to mitigate them. The recommendations were based on published studies and experts' opinion but were not formally graded because the body of evidence remained low at the time of drafting this document.

Early and accurate diagnosis of steatotic liver by artificial intelligence (AI)-supported ultrasonography

OBJECTIVES

Steatotic liver disease is the most frequent chronic liver disease worldwide. Ultrasonography (US) is commonly employed for the assessment and diagnosis. Few information is available on the possible use of artificial intelligence (AI) to ameliorate the diagnostic accuracy of ultrasonography.

MATERIALS AND METHODS

An AI-based algorithm was developed using a dataset of US images. We prospectively enrolled 134 patients for algorithm validation. Patients underwent abdominal US and Proton Density Fat Fraction MRI scans (MRI-PDFF), assumed as reference technique. The hepatorenal index was manually calculated (HRIM) by 4 operators. An automatic hepatorenal index (HRIA) was obtained by the algorithm. The accuracy of HRIA to discriminate steatosis grades was evaluated by ROC analysis using MRI-PDFF cut-offs.

RESULTS

Overweight was 40 % of subjects (BMI 26.4 kg/cm2). The median HRIA was 1.11 (IQR 0.32) and the average of 4 manually calculated HRIM was 1.08 (IQR 0.26), with a 15 % inter-operator variability. Both HRIA (R = 0.79, P < 0.0001) and HRIM (R = 0.69, P < 0.0001) significantly correlated with liver fat percentage (MRI-PDFF). According to MRI-PDFF, 32 % of enrolled subjects had steatosis. Discrimination capacity by AUC between patient with steatosis and patient without steatosis was better for HRIA than HRIM (AUC: 0.87 vs. 0.82, respectively). ROC analysis showed an AUC = 0.98 for HRIA with 1.64 cut-off in distinguishing between mild and moderate/severe groups.

CONCLUSIONS

The use of AI improves accuracy and speed of ultrasonography in the diagnosis of liver steatosis. Further studies should evaluate the routine use of this technique in the management of liver steatosis at high cardio-metabolic risk.

Association between non-alcoholic fatty liver disease and the risk of pulmonary nodules in patients with intestinal polyps

Background

Associations between metabolic risk factors and lung cancer remain elusive, and evidence on the linkage between non-alcoholic fatty liver disease (NAFLD) and pulmonary nodules is limited. This study sought to examine the independent association between NAFLD and the risk of pulmonary nodules.

Methods

Cross-sectional analyses of 1,119 patients with intestinal polyps hospitalized at the Department of Gastroenterology, Minhang District Central Hospital of Shanghai, China, were conducted. NAFLD was diagnosed based on hepatic ultrasonography or computed tomography (CT) findings of hepatic steatosis, with exclusion criteria ensuring patients had no history of significant alcohol consumption, viral infections, or hepatic autoimmune diseases. The currently accepted definition of a pulmonary nodule is a solid or sub-solid shadow ≤3 cm in diameter that appears as a solid or semi-solid pattern on a chest CT scan (our specific treatment is pulmonary nodule size: 5 mm to 3 cm). Adjusted 95% confidence intervals (CIs) and odds ratios (ORs) for NAFLD and the clinical features connected with pulmonary nodule risk were determined using a multivariable logistic regression analysis.

Results

Among the 979 intestinal polyp patients, the prevalence rates of NAFLD and pulmonary nodules were 25.9% and 32.8%, respectively. Patients with pulmonary nodules exhibited higher rates of NAFLD (31.5% vs. 23.3%, P=0.006) and obesity (41.4% vs. 32.5%, P=0.006) compared to those without pulmonary nodules. After removing all the possible confounding variables, the adjusted ORs for NAFLD, an older age, smoking, and obesity were 1.370 (95% CI: 1.006-1.867, P=0.04), 1.022 (95% CI: 1.010-1.033), 1.599 (95% CI: 1.033-2.475), and 1.410 (95% CI: 1.057-1.880), respectively (all P values <0.05). NAFLD showed a significant association with an increased risk of pulmonary nodules.

Conclusions

NAFLD was independently linked to an increased incidence of pulmonary nodules in intestinal polyp patients, which emphasizes the importance of screening and managing these conditions in lung cancer prevention.