Diagnostic comparison of vibration-controlled transient elastography and MRI techniques in overweight and obese patients with NAFLD

Diagnosis and non-invasive assessment of MASLD in type 2 diabetes and obesity

BACKGROUND

Metabolic dysfunction-associated steatotic liver disease (MASLD) is currently the most common chronic liver disease and an important cause of cirrhosis and hepatocellular carcinoma. It is strongly associated with type 2 diabetes and obesity. Because of the huge number of patients at risk of MASLD, it is imperative to use non-invasive tests appropriately.

AIMS

To provide a narrative review on the performance and limitations of non-invasive tests, with a special emphasis on the impact of diabetes and obesity.

METHODS

We searched PubMed and Cochrane databases for articles published from 1990 to August 2023.

RESULTS

Abdominal ultrasonography remains the primary method to diagnose hepatic steatosis, while magnetic resonance imaging proton density fat fraction is currently the gold standard to quantify steatosis. Simple fibrosis scores such as the Fibrosis-4 index are well suited as initial assessment in primary care and non-hepatology settings to rule out advanced fibrosis and future risk of liver-related complications. However, because of its low positive predictive value, an abnormal test should be followed by specific blood (e.g. Enhanced Liver Fibrosis score) or imaging biomarkers (e.g. vibration-controlled transient elastography and magnetic resonance elastography) of fibrosis. Some non-invasive tests of fibrosis appear to be less accurate in patients with diabetes. Obesity also affects the performance of abdominal ultrasonography and transient elastography, whereas magnetic resonance imaging may not be feasible in some patients with severe obesity.

CONCLUSIONS

This article highlights issues surrounding the clinical application of non-invasive tests for MASLD in patients with type 2 diabetes and obesity.

Image-based AI diagnostic performance for fatty liver: a systematic review and meta-analysis

BACKGROUND

The gold standard to diagnose fatty liver is pathology. Recently, image-based artificial intelligence (AI) has been found to have high diagnostic performance. We systematically reviewed studies of image-based AI in the diagnosis of fatty liver.

METHODS

We searched the Cochrane Library, Pubmed, Embase and assessed the quality of included studies by QUADAS-AI. The pooled sensitivity, specificity, negative likelihood ratio (NLR), positive likelihood ratio (PLR), and diagnostic odds ratio (DOR) were calculated using a random effects model. Summary receiver operating characteristic curves (SROC) were generated to identify the diagnostic accuracy of AI models.

RESULTS

15 studies were selected in our meta-analysis. Pooled sensitivity and specificity were 92% (95% CI: 90-93%) and 94% (95% CI: 93-96%), PLR and NLR were 12.67 (95% CI: 7.65-20.98) and 0.09 (95% CI: 0.06-0.13), DOR was 182.36 (95% CI: 94.85-350.61). After subgroup analysis by AI algorithm (conventional machine learning/deep learning), region, reference (US, MRI or pathology), imaging techniques (MRI or US) and transfer learning, the model also demonstrated acceptable diagnostic efficacy.

CONCLUSION

AI has satisfactory performance in the diagnosis of fatty liver by medical imaging. The integration of AI into imaging devices may produce effective diagnostic tools, but more high-quality studies are needed for further evaluation.

[Use of a controlled attenuation parameter for the diagnosis of non-alcoholic fatty liver disease]

AIM

To evaluate the efficacy of vibration-controlled transient elastography (VCTE) with a controlled attenuation parameter (CAP) in a population of patients with non-alcoholic fatty liver disease (NAFLD)and to compare to US and different non-invasive indices.

MATERIALS AND METHODS

Single center NAFLD patients' database of 2021-2023 years was retrospectively analysed. Data of VCTE evaluation with CAP (FibroScan 530® and FibroScan 630 Expert®) as well as liver US examination results and values of HSI, FLI, BAAT and NAFLD-LFS were extracted. AUROCs for all methods used were constructed and sensitivity and specificity analysis was performed.

RESULTS

The data of 1081 patients were available for analysis (385 with steatosis, 274 with NASH, 422 without NAFLD as a control). Ultrasound examination in the diagnosis of liver steatosis compared to VCTE with CAP showed sensitivity and specificity of 94.6 and 63.7%, respectively. Diagnosis of liver steatosis using indices and scales showed sensitivity and specificity of HSI: 97.9 and 60.1% (AUROC 0.90), FLI: 92.5 and 85.3% (AUROC 0.93), BAAT: 76.6 and 73.5% (AUROC 0.82), NAFLD-LFS: 56.7 and 81.8% (AUROC 0.85).

CONCLUSION

The sensitivity of the US of the liver was consistent with previous studies, but the specificity was low. The HSI index had the best indicators of sensitivity and specificity in relation to the diagnosis of liver steatosis. Combination of liver US and HSI can be used in screening of liver steatosis, however, for the complete diagnosis better tools which can simultaneously evaluate liver steatosis and fibrosis should be used.

Repeatability of MRI Biomarkers in Nonalcoholic Fatty Liver Disease: The NIMBLE Consortium

Background There is a need for reliable noninvasive methods for diagnosing and monitoring nonalcoholic fatty liver disease (NAFLD). Thus, the multidisciplinary Non-invasive Biomarkers of Metabolic Liver disease (NIMBLE) consortium was formed to identify and advance the regulatory qualification of NAFLD imaging biomarkers. Purpose To determine the different-day same-scanner repeatability coefficient of liver MRI biomarkers in patients with NAFLD at risk for steatohepatitis. Materials and Methods NIMBLE 1.2 is a prospective, observational, single-center short-term cross-sectional study (October 2021 to June 2022) in adults with NAFLD across a spectrum of low, intermediate, and high likelihood of advanced fibrosis as determined according to the fibrosis based on four factors (FIB-4) index. Participants underwent up to seven MRI examinations across two visits less than or equal to 7 days apart. Standardized imaging protocols were implemented with six MRI scanners from three vendors at both 1.5 T and 3 T, with central analysis of the data performed by an independent reading center (University of California, San Diego). Trained analysts, who were blinded to clinical data, measured the MRI proton density fat fraction (PDFF), liver stiffness at MR elastography (MRE), and visceral adipose tissue (VAT) for each participant. Point estimates and CIs were calculated using χ2 distribution and statistical modeling for pooled repeatability measures. Results A total of 17 participants (mean age, 58 years ± 8.5 [SD]; 10 female) were included, of which seven (41.2%), six (35.3%), and four (23.5%) participants had a low, intermediate, or high likelihood of advanced fibrosis, respectively. The different-day same-scanner mean measurements were 13%-14% for PDFF, 6.6 L for VAT, and 3.15 kPa for two-dimensional MRE stiffness. The different-day same-scanner repeatability coefficients were 0.22 L (95% CI: 0.17, 0.29) for VAT, 0.75 kPa (95% CI: 0.6, 0.99) for MRE stiffness, 1.19% (95% CI: 0.96, 1.61) for MRI PDFF using magnitude reconstruction, 1.56% (95% CI: 1.26, 2.07) for MRI PDFF using complex reconstruction, and 19.7% (95% CI: 15.8, 26.2) for three-dimensional MRE shear modulus. Conclusion This preliminary study suggests that thresholds of 1.2%-1.6%, 0.22 L, and 0.75 kPa for MRI PDFF, VAT, and MRE, respectively, should be used to discern measurement error from real change in patients with NAFLD. ClinicalTrials.gov registration no. NCT05081427 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Kozaka and Matsui in this issue.

Association of Non-Invasive Markers with Significant Fibrosis in Patients with Nonalcoholic Fatty Liver Disease: A Cross-Sectional Study

Purpose

The identification of significant fibrosis is critical for predicting the prognosis of non-alcoholic fatty liver disease (NAFLD). This study aimed to compare the predictive value of chitinase-3-like protein 1 (CHl3L1) and other non-invasive biomarkers, as well as to establish a novel non-invasive diagnostic model for assessing the risk of significant fibrosis in NAFLD.

Patients and Methods

A total of 71 patients with confirmed NAFLD based on liver biopsy were included in this study. Serum CHI3L1 levels and other non-invasive fibrosis assessment measures were determined. The aspartate aminotransferase-to-platelet ratio index (APRI) and Fibrosis-4 Index (FIB-4) were calculated to assess the diagnostic superiority of serum CHI3L1 compared to other non-invasive fibrosis assessment measures. Multivariate logistic regression analysis was conducted to identify relevant variables for constructing a diagnostic model. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic accuracy of each index, including the area under ROC curve (AUC), sensitivity, and specificity. A nomogram was established based on the logistic regression model.

Results

Serum CHI3LI levels were found to be higher in NAFLD patients with significant fibrosis compared to those without significant fibrosis. Multivariate logistic regression analysis revealed that aspartate aminotransferase (AST), type IV collagen (IV-C), CHI3L1, and liver stiffness measurement (LSM) were identified as potential independent risk factors associated with significant fibrosis in patients. The AUC of CHI3L1 for diagnosing significant liver fibrosis was 0.716 (0.596,0.836), with the optimal cut-off point of 125.315. The nomogram incorporating CHI3LI, AST, IV-C, and LSM further improved the potential predictive value, with an AUC for diagnosing significant fibrosis of 0.864 (0.766,0.962). This was superior to IV-C, CHI3L1, LSM, and APRI (all p < 0.05).

Conclusion

The diagnostic model constructed by CHI3L1 combined with the existing non-invasive markers AST, IV-C, and LSM can help assess the risk of significant liver fibrosis in NAFLD.