assessment of li-rads efficacy in the classification of hepatocellular carcinoma and benign liver nodules using dce-mri features and adc mri

The liver imaging reporting and data system (li-rads) is a widely utilized tool for classifying liver lesions, particularly in patients at risk for hepatocellular carcinoma (hcc). this study aims to assess the efficacy of li-rads in distinguishing between hcc and benign liver nodules by leveraging dynamic contrast-enhanced magnetic resonance imaging (dce-mri) features and apparent diffusion coefficient (adc) values derived from mri. between october 2023 and march 2024, 43 patients with suspected hcc underwent mri evaluation, including dce-mri and dwi sequences. the diagnostic performance of various mri sequences was analyzed, focusing on their ability to differentiate hcc from benign lesions. 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 to analyze the collected data. the study findings reveal that the dce-mri arterial phase demonstrated perfect diagnostic accuracy with an area under the curve (auc) of 1.00, achieving 100% sensitivity and specificity. t2-weighted imaging also exhibited diagnostic solid performance, with an auc of 0.801, while adc values from dwi sequences showed limited efficacy in differentiating hcc from benign lesions (auc=0.512). these findings indicate that dce-mri significantly enhances the accuracy of li-rads in classifying hcc versus benign liver nodules. this study highlights the importance of incorporating advanced imaging features into li-rads to improve the diagnostic precision of liver lesion evaluation in clinical practice.