Quantitative Ultrasound Image Analysis Helps in the Differentiation of Hepatocellular Carcinoma (HCC) From Borderline Lesions and Predicting the Histologic Grade of HCC and Microvascular Invasion

Analysis of Sonazoid contrast-enhanced ultrasound for predicting the risk of microvascular invasion in hepatocellular carcinoma: a prospective multicenter study

OBJECTIVES

The aim of this study was to evaluate the potential of Sonazoid contrast-enhanced ultrasound (SNZ-CEUS) as an imaging biomarker for preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC).

METHODS

From August 2020 to March 2021, we conducted a prospective multicenter study on the clinical application of Sonazoid in liver tumor; a MVI prediction model was developed and validated by integrating clinical and imaging variables. Multivariate logistic regression analysis was used to establish the MVI prediction model; three models were developed: a clinical model, a SNZ-CEUS model, and a combined model and conduct external validation. We conducted subgroup analysis to investigate the performance of the SNZ-CEUS model in non-invasive prediction of MVI.

RESULTS

Overall, 211 patients were evaluated. All patients were split into derivation (n = 170) and external validation (n = 41) cohorts. Patients who had MVI accounted for 89 of 211 (42.2%) patients. Multivariate analysis revealed that tumor size (> 49.2 mm), pathology differentiation, arterial phase heterogeneous enhancement pattern, non-single nodular gross morphology, washout time (< 90 s), and gray value ratio (≤ 0.50) were significantly associated with MVI. Combining these factors, the area under the receiver operating characteristic (AUROC) of the combined model in the derivation and external validation cohorts was 0.859 (95% confidence interval (CI): 0.803-0.914) and 0.812 (95% CI: 0.691-0.915), respectively. In subgroup analysis, the AUROC of the SNZ-CEUS model in diameter  ≤ 30 mm and ˃ 30 mm cohorts were 0.819 (95% CI: 0.698-0.941) and 0.747 (95% CI: 0.670-0.824).

CONCLUSIONS

Our model predicted the risk of MVI in HCC patients with high accuracy preoperatively.

CLINICAL RELEVANCE STATEMENT

Sonazoid, a novel second-generation ultrasound contrast agent, can accumulate in the endothelial network and form a unique Kupffer phase in liver imaging. The preoperative non-invasive prediction model based on Sonazoid for MVI is helpful for clinicians to make individualized treatment decisions.

KEY POINTS

• This is the first prospective multicenter study to analyze the possibility of SNZ-CEUS preoperatively predicting MVI. • The model established by combining SNZ-CEUS image features and clinical features has high predictive performance in both derivation cohort and external validation cohort. • The findings can help clinicians predict MVI in HCC patients before surgery and provide a basis for optimizing surgical management and monitoring strategies for HCC patients.

Clinical and imaging features preoperative evaluation of histological grade and microvascular infiltration of hepatocellular carcinoma

Background

To predict the histological grade and microvascular invasion (MVI) in patients with HCC.

Methods

A retrospective analysis was conducted on 175 patients who underwent MRI enhancement scanning (from September 2016.9 to October 2020). They were divided into MVI positive, MVI negative, Grade-high and Grade-low groups.

Results

The AFP of 175 HCC patients distributed in MVI positive and negative groups, Grade-low and Grade-high groups were statistically significant (P = 0.002 and 0.03, respectively). Multiple HCC lesions were more common in MVI positive and Grade-high groups. Correspondingly, more single lesions were found in MVI negative and Grade-low groups (P = 0.005 and 0.019, respectively). Capsule on MRI was more common in MVI negative and Grade-high groups, and the difference was statistically significant (P = 0.02 and 0.011, respectively). There were statistical differences in the distribution of three MRI signs: artistic rim enhancement, artistic peripheral enhancement, and tumor margin between MVI positive and MVI negative groups (P = 0.001, < 0.001, and < 0.001, respectively). Tumor hypointensity on HBP was significantly different between MVI positive and negative groups (P < 0.001).

Conclusions

Our research shows that preoperative enhanced imaging can be used to predict MVI and tumor differentiation grade of HCC. The prognosis of MVI-negative group was better than that of MVI-positive group.

Dynamic Contrast-Enhanced Ultrasonography with Sonazoid for Diagnosis of Microvascular Invasion in Hepatocellular Carcinoma

The aim of the present study was to investigate the imaging features observed in pre-operative Sonazoid contrast-enhanced ultrasound (SZ-CEUS) and the correlations with the presence of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients. In this single-center retrospective study, 31 patients with surgically and histopathologically confirmed HCC lesions were included. Patients were classified according to the presence of MVI into the MVI-positive group (n = 15) and MVI-negative group (n = 16). The CEUS examinations were performed within 2 or 3 d before surgery. Features, including tumor necrosis and ultrasound contrast agent (UCA) distribution characteristics in the arterial phase (AP), tumor types (single nodular [SN] or non-single nodular [non-SN]) in the post-vascular phase (PVP), wash-in time, wash-in slope, time to peak (TTP) and peak intensity (PI), were assessed. Univariate analysis revealed statistically significant differences between the two groups with respect to tumor necrosis (p = 0.002), inhomogeneous distribution of contrast agent in the AP (p = 0.001) and non-SN type in the PVP (p < 0.001). There was no significant difference in the quantitative parameters. Multivariate analysis revealed that non-SN type in the PVP was a significant independent risk factor for MVI of HCC (odds ratio = 30.51, 95% confidence interval [CI]: 2.335-398.731, p = 0.009). The area under the receiver operating characteristic (ROC) curve (AUC), sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were 0.873, 93.3%, 81.3%, 82.4% and 92.9%, respectively. Thus, SZ-CEUS can provide useful information for the diagnosis of MVI in HCC.