PERSoN4: A Multiparametric Ultrasound Model to Improve CEUS LI-RADS for HCC.

[BACKGROUND AND AIM] Dynamic Contrast-Enhanced Ultrasound (D-CEUS) could be a valuable tool in the non-invasive diagnosis of HCC with atypical vascular imaging features.

[METHODS] Between January 2021 and November 2023, consecutive patients with chronic liver disease and liver nodules candidate for liver biopsy were enrolled in this cohort study. CEUS was perfomed in all patients before biopsy and categorized according to CEUS Liver Imaging Reporting and Data System (LI-RADS). Clips were examined by VueBox® software. Clinical and ultrasound parameters were compared among the different histological entities, analyzed with univariable analysis, and incorporated into a logistic regression model for HCC diagnosis. The diagnostic accuracy of the identified model was evaluated by Receiver Operating Characteristic (ROC) curve and relative Area Under the Curve (AUC). The model was then tested on a validation cohort made of consecutive patients from two centers.

[RESULTS] A total of 88 patients (57 HCC, 17 intrahepatic cholangiocarcinoma, 11 liver metastases and 3 benign lesions) were enrolled. Statistically significant differences between HCC and non-HCC patients in the training cohort were incorporated in an optimal logistic regression model that included the following predictive variables: sex, number of nodules ≥4, peripheral rim-like hyperenhancement and Peak Enhancement ratio. The model displayed high accuracy (AUC 0.91) for diagnosis of HCC. In the validation cohort, the model showed a sensitivity of 48.8% and a specificity of 100.0%, with a PPV of 100.0%, maintaining a fair diagnostic accuracy (AUC of 0.74).

[CONCLUSIONS] PERSoN4 could improve the performance of CEUS LI-RADS criteria, possibly leading to a non-invasive diagnosis of HCC in nearly 50% of patients currently referred for liver biopsy. This model requires further external validation prior entering the clinical practice.

[IMPACT AND IMPLICATIONS] Accurate non-invasive diagnosis of HCC remains challenging in patients with atypical vascular patterns on CEUS, providing the scientific rationale for developing a multiparametric D-CEUS-based risk model that integrates quantitative perfusion analysis with clinical and imaging features. Our findings suggest that the PERSoN4 model can meaningfully enhance the diagnostic performance of CEUS LI-RADS, particularly by identifying a subset of patients in whom HCC can be diagnosed with very high specificity and PPV, which is highly relevant for hepatologists, radiologists, and multidisciplinary tumor boards managing indeterminate nodules. This approach could reduce the need for liver biopsy in nearly half of currently eligible patients, streamlining diagnostic pathways and potentially lowering procedure-related risks and costs. However, given the moderate sensitivity and the limited sample size, further large-scale external validation is essential before widespread clinical implementation.