The added value of color parameter imaging for the evaluation of focal liver lesions with "homogenous hyperenhancement and no wash out" on contrast enhanced ultrasound

Objective: The purpose of this study was to investigate the added value of color parameter imaging (CPI) in the differential diagnosis of focal liver lesions (FLLs) with "homogeneous hyperenhancement but not wash out" on contrast-enhanced ultrasound (CEUS). Methods: A total of 101 patients with 108 FLLs were enrolled in this study. All the FLLs received US and CEUS examinations. The stored CEUS clips of target lesions were postprocessed with CPI analysis by radiologists. The receiver operator characteristic (ROC) curve was used to evaluate the added value of CPI. The McNamara test was used to compare the diagnostic sensitivity, specificity, and accuracy between CEUS and CPI patterns. Univariate and multivariate logistic regression analyses were used to develop a CPI nomogram. The C index and calibration curve were used to evaluate the predictive ability of the nomogram. The intraclass correlation coefficient was used to test the reproducibility and reliability of CPI. Decision curve analysis (DCA) was used to evaluate the added value of applying CPI. Results; The following CPI features were more frequently observed in malignant FLLs: eccentric perfusion (malignant: 70.0% vs. benign: 29.2%, p < 0.001), feeding artery (51.7% vs. 4.2%, p < 0.001), mosaic (63.3% vs. 6.3%, p < 0.001), red ingredients >1/3 (90.0% vs. 14.6%, p < 0.001). In addition, centripetal (43.8% vs. 18.3%, p = 0.004), peripheral nodular (54.2% vs. 1.7%, p < 0.001), subcapsular vessel (12.5% vs. 0.0%, p = 0.004), spoke-wheel vessels (25.0% vs. 5.0%, p = 0.003), branched vessels (22.9% vs. 5.0%, p = 0.006), blue and pink ingredients >2/3 (85.4% vs. 10.0%, p < 0.001) were more observed in benign FLLs. A nomogram incorporating peripheral nodular, spoke-wheel vessels, and red ingredients >1/3 was constructed. The model had satisfactory discrimination (AUC = 0.937), and the optimal diagnostic threshold value was 0.740 (0.983, 0.850). By the DCA, the model offered a net benefit over the treat-all-patients scheme or the treat-none scheme at a threshold probability 5%-93%. Conclusion: Using CPI can detect and render subtle information of the main features of FLLs on CEUS; it is conducive to the radiologist for imaging interpretation, and a combining read of the CEUS and CPI of the FLLs with features of "homogenous hyperenhancement and no washout" can improve significantly the diagnostic performance of CEUS for FLLs.