Can the Contrast-Enhanced Ultrasound Washout Rate Be Used to Predict Microvascular Invasion in Hepatocellular Carcinoma?

OBJECTIVE: To investigate the clinical value of dynamic contrast enhanced ultrasound (D-CEUS) in predicting the microvascular invasion (MVI) of hepatocellular carcinoma (HCC). PATIENTS AND METHODS: In this retrospective study, 16 patients with surgery and histopathologically proved HCC lesions were included. Patients were classified according to the presence of MVI: MVI positive group (n = 6) and MVI negative group (n = 10). Contrast enhanced ultrasound (CEUS) examinations were performed within a week before surgery. Dynamic analysis was performed by VueBox ® software (Bracco, Italy). Three regions of interests (ROIs) were set in the center of HCC lesions, at the margin of HCC lesions and in the surrounding liver parenchyma accordingly. Time intensity curves (TICs) were generated and quantitative perfusion parameters including WiR (wash-in rate), WoR (wash-out rate), WiAUC (wash-in area under the curve), WoAUC (wash-out area under the curve) and WiPi (wash-in perfusion index) were obtained and analyzed. RESULTS: All of HCC lesions showed arterial hyperenhancement (100 %) and at the late phase as hypoenhancement (75 %) in CEUS. Among all CEUS quantitative parameters, the WiAUC and WoAUC were higher in MVI positive group than in MVI negative group in the center HCC lesions (P < 0.05), WiAUC, WoAUC and WiPI were higher in MVI positive group than in MVI negative group at the margin of HCC lesions. WiR and WoR were significant higher in MVI positive group. CONCLUSIONS: D-CEUS with quantitative perfusion analysis has potential clinical value in predicting the existence of MVI in HCC lesions.

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Preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma based on kupffer phase radiomic features of sonazoid contrast-enhanced ultrasound (SCEUS): A prospective study

Clinical Hemorheology and Microcirculation ◽

10.3233/ch-211363 ◽

2022 ◽

pp. 1-11

Author(s):

Yi Dong ◽

Dan Zuo ◽

Yi-Jie Qiu ◽

Jia-Ying Cao ◽

Han-Zhang Wang ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Receiver Operating Characteristic ◽

Operating Characteristic ◽

Microvascular Invasion ◽

Ultrasound Images ◽

Contrast Enhanced Ultrasound ◽

Model Based ◽

Preoperative Prediction ◽

Contrast Enhanced ◽

Receiver Operating

OBJECTIVES: To establish and evaluate a machine learning radiomics model based on grayscale and Sonazoid contrast enhanced ultrasound images for the preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients. METHODS: 100 cases of histopathological confirmed HCC lesions were prospectively included. Regions of interest were segmented on both grayscale and Kupffer phase of Sonazoid contrast enhanced (CEUS) images. Radiomic features were extracted from tumor region and region containing 5 mm of peritumoral liver tissues. Maximum relevance minimum redundancy (MRMR) and Least Absolute Shrinkage and Selection Operator (LASSO) were used for feature selection and Support Vector Machine (SVM) classifier was trained for radiomic signature calculation. Radiomic signatures were incorporated with clinical variables using univariate-multivariate logistic regression for the final prediction of MVI. Receiver operating characteristic curves, calibration curves and decision curve analysis were used to evaluate model’s predictive performance of MVI. RESULTS: Age were the only clinical variable significantly associated with MVI. Radiomic signature derived from Kupffer phase images of peritumoral liver tissues (kupfferPT) displayed a significantly better performance with an area under the receiver operating characteristic curve (AUROC) of 0.800 (95% confidence interval: 0.667, 0.834), the final prediction model using Age and kupfferPT achieved an AUROC of 0.804 (95% CI: 0.723, 0.878), accuracy of 75.0%, sensitivity of 87.5% and specificity of 69.1%. CONCLUSIONS: Radiomic model based on Kupffer phase ultrasound images of tissue adjacent to HCC lesions showed an observable better predictive value compared to grayscale images and has potential value to facilitate preoperative identification of HCC patients at higher risk of MVI.

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Preoperative Prediction of Microvascular Invasion in Patients With Hepatocellular Carcinoma Based on Radiomics Nomogram Using Contrast-Enhanced Ultrasound

Frontiers in Oncology ◽

10.3389/fonc.2021.709339 ◽

2021 ◽

Vol 11 ◽

Author(s):

Di Zhang ◽

Qi Wei ◽

Ge-Ge Wu ◽

Xian-Ya Zhang ◽

Wen-Wu Lu ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Tumor Size ◽

Multivariate Logistic Regression Analysis ◽

Microvascular Invasion ◽

Validation Dataset ◽

Contrast Enhanced Ultrasound ◽

Clinical Model ◽

Portal Venous Phase ◽

Preoperative Prediction ◽

Contrast Enhanced

PurposeThis study aimed to develop a radiomics nomogram based on contrast-enhanced ultrasound (CEUS) for preoperatively assessing microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients.MethodsA retrospective dataset of 313 HCC patients who underwent CEUS between September 20, 2016 and March 20, 2020 was enrolled in our study. The study population was randomly grouped as a primary dataset of 192 patients and a validation dataset of 121 patients. Radiomics features were extracted from the B-mode (BM), artery phase (AP), portal venous phase (PVP), and delay phase (DP) images of preoperatively acquired CEUS of each patient. After feature selection, the BM, AP, PVP, and DP radiomics scores (Rad-score) were constructed from the primary dataset. The four radiomics scores and clinical factors were used for multivariate logistic regression analysis, and a radiomics nomogram was then developed. We also built a preoperative clinical prediction model for comparison. The performance of the radiomics nomogram was evaluated via calibration, discrimination, and clinical usefulness.ResultsMultivariate analysis indicated that the PVP and DP Rad-score, tumor size, and AFP (alpha-fetoprotein) level were independent risk predictors associated with MVI. The radiomics nomogram incorporating these four predictors revealed a superior discrimination to the clinical model (based on tumor size and AFP level) in the primary dataset (AUC: 0.849 vs. 0.690; p < 0.001) and validation dataset (AUC: 0.788 vs. 0.661; p = 0.008), with a good calibration. Decision curve analysis also confirmed that the radiomics nomogram was clinically useful. Furthermore, the significant improvement of net reclassification index (NRI) and integrated discriminatory improvement (IDI) implied that the PVP and DP radiomics signatures may be very useful biomarkers for MVI prediction in HCC.ConclusionThe CEUS-based radiomics nomogram showed a favorable predictive value for the preoperative identification of MVI in HCC patients and could guide a more appropriate surgical planning.

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Predictive Value of Contrast-enhanced Ultrasound for Early Recurrence of Single Lesion Hepatocellular Carcinoma After Curative Resection

Ultrasonic Imaging ◽

10.1177/0161734618815231 ◽

2018 ◽

Vol 41 (1) ◽

pp. 49-58 ◽

Cited By ~ 1

Author(s):

Qin Xiachuan ◽

Zhou xiang ◽

Liu xuebing ◽

Luo yan

Keyword(s):

Risk Factors ◽

Hepatocellular Carcinoma ◽

Early Recurrence ◽

Maximum Diameter ◽

Washout Rate ◽

Feeding Artery ◽

Contrast Enhanced Ultrasound ◽

Contrast Enhanced ◽

The Us ◽

Single Lesion

This retrospective study aimed to use preoperative and contrast-enhanced ultrasound (CEUS) factors to assess and reveal risk factors of early recurrence (ER) in patients with hepatocellular carcinoma (HCC). We enrolled 141 patients with primary HCC who had undergone surgical resection. The assessment of the CEUS scan includes (a) the maximum diameter of the lesion, (b) the tumor echogenicity of gray-scale ultrasound (US), (c) the morphology of the tumor, (d) the margin of the tumor, (e) the peripheral hypoechoic halo, (f) tumor necrosis, (g) nutritional arteries shown by tumors, (h) ultrasonography for diagnosis of cirrhosis, and (i) the timer on the US screen displayed the time elapsed from the saline flush and was used to determine time to washout. According to the degree of the phase, the washout rate is divided into four grades, namely, levels 1 to 4. ER is defined as the time between resection and recurrence within 12 months after surgery. Risk factors for ER HCC were analyzed. Predictors of ER on a univariate logistic regression analysis in CEUS are size, washout rate, morphology, center necrosis, and feeding artery appearing in the tumor. Multivariate analysis results indicated that feeding artery, microvascular invasion (MVI), and washout rate were independent risk factors for ER. The relative high risk of ER for washout rate 1, 2, 3, and 4 were 29.3%, 43.2%, 53.1%, and 71.4%, respectively. The appropriateness of hepatectomy in the treatment of single lesion HCC should be carefully considered when the washout rate was 4.

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A Nomogram Based on Combining Clinical Features and Contrast Enhanced Ultrasound LI-RADS Improves Prediction of Microvascular Invasion in Hepatocellular Carcinoma

Frontiers in Oncology ◽

10.3389/fonc.2021.699290 ◽

2021 ◽

Vol 11 ◽

Author(s):

Hang Zhou ◽

Jiawei Sun ◽

Tao Jiang ◽

Jiaqi Wu ◽

Qunying Li ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Predictive Model ◽

Clinical Features ◽

Diagnostic Performance ◽

Clinical Information ◽

Microvascular Invasion ◽

Liver Imaging ◽

Contrast Enhanced Ultrasound ◽

Training Cohort ◽

Contrast Enhanced

PurposesTo establish a predictive model incorporating clinical features and contrast enhanced ultrasound liver imaging and reporting and data system (CEUS LI-RADS) for estimation of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients.MethodsIn the retrospective study, 127 HCC patients from two hospitals were allocated as training cohort (n=98) and test cohorts (n=29) based on cutoff time-point, June 2020. Multivariate regression analysis was performed to identify independent indicators for developing predictive nomogram models. The area under receiver operating characteristic (AUC) curve was also determined to establish the diagnostic performance of different predictive models. Corresponding sensitivities and specificities of different models at the cutoff nomogram value were compared.ResultsIn the training cohort, clinical information (larger tumor size, higher AFP level) and CEUS LR-M were significantly correlated with the presence of MVI (all p<0.05). By incorporating clinical information and CEUS LR-M, the predictive model (LR-M+Clin) achieved a desirable diagnostic performance (AUC=0.80 and 0.84) in both cohorts at nomogram cutoff score value of 89. The sensitivity of LR-M+Clin when predicting MVI in HCC patients was higher than that of the clinical model alone (86.7% vs. 46.7%, p=0.027), while specificities were 78.6% and 85.7% (p=0.06), respectively, in the test cohort. In addition, LR-M+Clin exhibited similar AUC and specificity, but a significantly higher sensitivity (86.7%) than those of LR-M alone and LR-5(No)+Clin (both sensitivities=73.3%, both p=0.048).ConclusionThe predictive model incorporating CEUS LR-M and clinical features was able to predict the MVI status of HCC and is a potential reliable preoperative tool for informing treatment.

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Efficacy of Contrast-Enhanced Ultrasound Washout Rate in Predicting Hepatocellular Carcinoma Differentiation

Ultrasound in Medicine & Biology ◽

10.1016/j.ultrasmedbio.2015.01.026 ◽

2015 ◽

Vol 41 (6) ◽

pp. 1553-1560 ◽

Cited By ~ 12

Author(s):

Yan Feng ◽

Xia-Chuan Qin ◽

Yan Luo ◽

Yong-Zhong Li ◽

Xiang Zhou

Keyword(s):

Hepatocellular Carcinoma ◽

Washout Rate ◽

Contrast Enhanced Ultrasound ◽

Contrast Enhanced

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Study on correlation between two-dimensional ultrasound, contrast-enhanced ultrasound and microvascular invasion in hepatocellular carcinoma

Clinical Hemorheology and Microcirculation ◽

10.3233/ch-211190 ◽

2021 ◽

pp. 1-10

Author(s):

Peihua Wang ◽

Fang Nie ◽

Tiantian Dong ◽

Guojuan Wang ◽

Lan Wang ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Tumor Location ◽

Microvascular Invasion ◽

Initial Time ◽

Arterial Phase ◽

Two Dimensional ◽

Contrast Enhanced Ultrasound ◽

Enhancement Pattern ◽

Time To Peak ◽

Contrast Enhanced

OBJECTIVE: To explore the correlation between two-dimensional ultrasound (2D-US), contrast-enhanced ultrasound (CEUS) and microvascular invasion (MVI) in hepatocellular carcinoma (HCC). METHODS: In this retrospective study, 56 patients with surgically pathologically confirmed HCC lesions were included. Patients were classified according to the presence of MVI: MVI positive group (n = 17) and MVI negative group (n = 39). 2D-US and CEUS examinations were performed within two weeks before surgery. The 2D-US and CEUS features were analyzed for correlation with MVI. Statistically significant parameters of ultrasound characteristic were scored, and the results of the scores were analyzed by ROC curve. RESULTS: There were statistically significant differences in tumor shape, boundary, capsule, CEUS portal phase and delayed phase enhancement pattern, time to wash out, and tumor margin after enhancement (P < 0.05), while there were no statistically significant differences in tumor location and size, CEUS arterial phase enhancement pattern, initial time, time to peak, and peritumor enhancement (P > 0.05). When diagnosing the presence of MVI in HCC patients with cut-off value of the score combined 2D-US and CEUS features≥3, the maximum Jorden index was 0.58, and its diagnostic sensitivity and specificity were 94.10%and 64.1%, respectively, meaning that the total score≥3 was highly suspicious of the presence of MVI. CONCLUSIONS: 2D-US and CEUS are feasible methods for preoperative prediction of MVI in HCC, and can provide some theoretical basis for individualized clinical treatment.

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