Dynamic Contrast Enhanced-MRI and Apparent Diffusion Coefficient Quantitation for Differentiate Hepatocellular Carcinoma from Hepatocellular Adenoma.

BACKGROUND: Due to their overlapping radiological characteristics, hepatic lesions, such as hepatocellular carcinoma (HCC) and hepatocellular adenoma (HCA), present a substantial diagnostic challenge. Accurate differentiation between HCC and HCA is essential for the best clinical treatment and therapeutic decision-making. This study aims to assess the potential role of DCE-MRI and Apparent Diffusion Coefficient (ADC) quantitation in the diagnosis of hepatocellular carcinoma (HCC) from hepatocellular adenoma (HCA). METHODS: 103 patients (56 HCC, 47 HCA) with histopathologically proven hepatocellular lesions were the subjects of a cross-sectional investigation. A standardized imaging technique was used for DCE-MRI on all patients. Diffusion-weighted imaging (DWI) provided the ADC values. The diagnostic efficacy of DCE-MRI and ADC in differentiation was evaluated using statistical analyses, such as t-tests and receiver operating characteristic (ROC) curve analysis. SPSS VER 16 was used for the analysis of the collected data. RESULTS: A total of 103 patients (female: male= 52:51, 57.14±3.09 years) were included in the study. The study revealed significant differences in DCE-MRI parameters and ADC values between HCC and HCA lesions. ADC value was significantly lower in HCC than in HCA (p < 0.001). The area under the curve (AUC) was 0.78 (95% CI: 0.69-0.87) for ADC, 0.84 (95% CI: 0.76-0.91) for Ktrans, and 0.72 (95% CI: 0.62-0.82) for Ve. Sensitivity and specificity for ADC were 76.59% and 71.42%, respectively. Also, PPV and NPV of ADC were 69.23% and 78.43%, respectively. Sensitivity and specificity for Ktrans were 82.14% and 76.59%, respectively. Also, PPV and NPV of Ktrans were 80.7% and 78.26%, respectively. CONCLUSION: In conclusion, DCE-MRI-derived parameters, along with ADC values, exhibit promise as non-invasive tools for differentiating HCC from HCA.

Evidence Supporting Diagnostic Value of Liver Imaging Reporting and Data System for CT- and MR Imaging-based Diagnosis of Hepatocellular Carcinoma: A Systematic Review and Meta-analysis.

Background: Based on the Liver Imaging Data and Reporting System (LI-RADS) guidelines, Hepatocellular Carcinoma (HCC) can be diagnosed using imaging criteria in patients at risk of HCC. Objective: This study aimed to assess the diagnostic value of LI-RADS in high-risk patients with HCC. Material and Methods: This systematic review is conducted on international databases, including Google Scholar, Web of Science, PubMed, Embase, PROQUEST, and Cochrane Library, with appropriate keywords. Using the binomial distribution formula, the variance of each study was calculated, and all the data were analyzed using STATA version 16. The pooled sensitivity and specificity were determined using a random-effects meta-analysis approach. Also, we used the chi-squared test and I2 index to calculate heterogeneity among studies, and Funnel plots and Egger tests were used for evaluating publication bias. Results: The pooled sensitivity was estimated at 0.80 (95% CI 0.76-0.84). According to different types of Liver Imaging Reporting and Data Systems (LI-RADS), the highest pooled sensitivity was in version 2018 (0.83 (95% CI 0.79-0.87) (I2: 80.6%, P of chi 2 test for heterogeneity <0.001 and T2: 0.001). The pooled specificity was estimated as 0.89 (95% CI 0.87-0.92). According to different types of LI-RADS, the highest pooled specificity was in version 2014 (93.0 (95% CI 89.0-96.0) (I2: 81.7%, P of chi 2 test for heterogeneity <0.001 and T2: 0.001). Conclusion: LI-RADS can assist radiologists in achieving the required sensitivity and specificity in high-risk patients suspected to have HCC. Therefore, this strategy can serve as an appropriate tool for identifying HCC.