Classification of Neoadjuvant Therapy Response in Patients With Colorectal Liver Metastases Using Contrast-Enhanced Ultrasound-With Histological Pathology as the Gold Standard.

OBJECTIVE: To evaluate the response to neoadjuvant therapy in patients with colorectal liver metastases (CRLMs) using ultrasound(US) and contrast-enhanced ultrasound(CEUS), with correction to the tumor regression grade (TRG) of pathological results. METHODS: This study included patients with resectable CRLMs admitted from February to December 2022. After at least 4 cycles neoadjuvant therapy, all the patients received US and CEUS examinations within two weeks before hepatectomy. CEUS clips were postprocessed with color parameter imaging (CPI) and microflow imaging (MFI) analysis. Logistic regression analyses were used to develop an evaluation Nomogram. Ultrasound-based model was constructed to discriminate between the response (TRG1/2/3) and nonresponse (TRG4/5) groups at the lesion level. The model's predictive ability was evaluated using the C index and calibration curve, with decision curve analysis assessing the Nomogram's added value. RESULTS: The study analyzed 105 CRLM lesions (the lesion with the highest diameter analyzed for each patient), with 43.8% showing a response to therapy. Univariate analysis identified calcification on US (p = 0.039), CEUS enhancement degree (p < 0.001), CEUS enhancement pattern (p<0.001), CEUS washout type (p < 0.001), CEUS necrosis (p < 0.001), CPI feeding artery (p = 0.003) and MFI pattern (p < 0.001) were significantly associated with TRG. The multivariate analysis showed CEUS enhancement pattern (p = 0.026), CEUS washout type (p = 0.018) and CEUS necrosis (p = 0.005) were independently associated with the neoadjuvant therapy response. A Nomogram with the three independent predictors was developed, with an AUC of 0.898. CONCLUSION: The ultrasound-based model provided accurate evaluation of pathological tumor response to preoperative chemotherapy in patients with CRLM, and may help to decide the individualized treatment strategy.

Multimode Ultrasound Model for Predicting the Early Treatment Response of Anti-VEGF Agents Plus Anti-PD-1 Antibody in Patients with Unresectable Hepatocellular Carcinoma.

OBJECTIVE: The purpose of the study described was to establish prediction models to initially screen the beneficiary patients with unresectable hepatocellular carcinoma (HCC) in the treatment of anti-vascular endothelial growth factor (VEGF) agents plus anti-programmed cell death-1 (PD-1) antibody. METHODS: A total of 62 patients were enrolled in this study. All patients underwent ultrasound (US), color ddoppler flowing imaging (CDFI), contrast-enhanced ultrasound (CEUS) and laboratory examinations within 2 wk before the treatment. Tumor response was assessed according to mRECIST criteria. Univariate and multivariate analyses were used to select the independent predictors. US + CDFI, CEUS and FULL models were established. Three models were displayed by nomography. Receiver operating characteristic (ROC) and calibration curves were drawn to evaluate the predictive ability of models. Decision curve analysis (DCA) was used to assess the clinical utility of models. RESULTS: On univariate and multivariate analysis, the US boundary (p = 0.037), halo (p = 0.002) and CDFI (p = 0.024) were included in the US + CDFI model. CEUS boundary (p = 0.001) and washout time (p < 0.001) were included in the CEUS model. The number of lesions (p = 0.104), halo on US (p = 0.014), CDFI (p = 0.057) and washout time on CEUS (p = 0.015) were incorporated into the FULL model. The C indices of the US + CDFI, CEUS and FULL models were 0.918, 0.920 and 0.973. CEUS and FULL models yielded a good net benefit for almost all threshold probabilities. CONCLUSION: Nomograms based on US, CDFI, CEUS and clinical characteristics could help to non-invasively predict the response to treatment with anti-PD-1 antibodies plus anti-VEGF agents.

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.

Computer-Aided Color Parameter Imaging of Contrast-Enhanced Ultrasound Evaluates Hepatocellular Carcinoma Hemodynamic Features and Predicts Radiofrequency Ablation Outcome.

Computer-aided color parameter imaging (CPI) is a novel technique for contrast-enhanced ultrasound (CEUS) that can highlight hemodynamic features of focal lesions. The purpose of the study was to investigate the role of CPI in evaluation of hepatocellular carcinoma (HCC) hemodynamic features and prognosis after radiofrequency ablation (RFA). One hundred twenty-one patients with HCC underwent CEUS with CPI analysis before RFA. Eighty-nine patients had pathologically proven well- to moderately differentiated HCC (WM-HCC), and 32 patients had poorly differentiated or undifferentiated HCC (PU-HCC). Perfusion features of CEUS and contrast-enhanced computed tomography/magnetic resonance imaging were compared with CPI parameters for WM-HCC and PU-HCC. The results indicated that 67.4% of WM-HCC had a centrifugal perfusion CPI pattern, whereas 84.4% of PU-HCC tumors had a centripetal pattern (p < 0.001, odds ratio = 11.2). The specificity, sensitivity and accuracy of the CPI perfusion pattern regarding HCC pathological grade were higher than those with routine CEUS (84.4% vs. 9.4%, p < 0.001; 67.4% vs. 3.4%, p < 0.001; 71.9% vs. 5.0%, p < 0.001). Moreover, multivariable analysis revealed that the CPI perfusion pattern was an independent risk factor for progression-free survival post-RFA (centripetal group: 28.3 ± 4.1 mo vs. centrifugal group: 45.8 ± 4.4 mo, p = 0.002). A novel CPI technique for CEUS could non-invasively provide valuable hemodynamic information and predict prognosis for HCC patients treated by RFA.