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Differentiation of regenerative nodule, dysplastic nodule, and small hepatocellular carcinoma in cirrhotic patients: a contrast-enhanced ultrasound–based multivariable model analysis

  • Hepatobiliary-Pancreas
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Abstract

Objective

To develop a contrast-enhanced ultrasound (CEUS)–based model for differentiating cirrhotic liver lesions and for active surveillance of hepatocellular carcinoma (HCC).

Methods

Patients with focal liver lesions (FLLs) with biopsy/resection-proven pathology and pre-procedure CEUS were enrolled from our institution between January 2011 and November 2014. Univariable and multivariable regression models were constructed using qualitative CEUS features and/or contrast arrival time ratio (CATR). The optimism-adjusted Harrell’s generalized concordance index (CH) was used to quantify the discriminatory ability of each CEUS feature and model.

Results

A total of 149 patients (113 men and 36 women) with 162 FLLs were enrolled with mean age 53.4 ± 12.7 years. A 0.1-unit reduction in CATR was associated with a 68% increase in the odds of having a higher nodule ranking (RN < DN < small HCC) (OR, 0.32; 95% CI, 0.20–0.50, p < .001). Arterial phase hypoenhancement and isoenhancement were inversely associated with a higher nodule ranking compared to hyperenhancement. Late-phase isoenhancement was associated with lower odds of a higher nodule ranking. The CEUS + CATR model (CH 0.92, 0.89–0.95) provided greater discriminatory ability when compared to the CATR model (ΔCH 0.09, 0.04–0.13, p < .001) and the CEUS model (ΔCH 0.03, 0.01–0.05, p = .02).

Conclusions

Our results provide preliminary evidence that multivariable regression model constructed using both qualitative CEUS features and CATR provides the greatest discriminatory ability to differentiate RN, DN, and small HCC in patients with cirrhosis, and might allow for active surveillance of the progression of cirrhotic liver lesions.

Key Points

• Proportional odds logistic regression models based on qualitative CEUS features and/or CAT R can be used for differentiating cirrhotic liver lesions and for active surveillance of HCC.

• The reduction of CAT R (RN < DN < small HCC) was strongly associated with high-risk cirrhotic liver nodules.

• Inclusion of CAT R in the CEUS prediction model significantly improved its performance for cirrhotic liver lesions risk-stratification.

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Abbreviations

APHE:

Arterial phase hyperenhancement

ΔCH :

Difference in optimism-adjusted Harrell’s generalized concordance index

CAT:

Contrast arrival time

CATL :

CAT in lesion

CATN :

CAT in non-lesion liver parenchyma

CATR :

Ratio of CAT in lesion and non-lesion liver parenchyma

CEUS LI-RADS:

Contrast-Enhanced Ultrasound Liver Imaging Reporting and Data System

CH :

Optimism-adjusted Harrell’s generalized concordance index

CI:

Confidence interval

CUS:

Conventional ultrasound

DN:

Dysplastic nodule

EFSUMB:

European Federation of Societies for Ultrasound in Medicine and Biology

FLL:

Focal liver lesion

HE:

Hematoxylin and eosin

IMAX:

Maximum intensity within the analysis regions of interest

OR:

Odds ratio

RN:

Regenerative nodule

TTP:

Time to peak

WFUMB:

World Federation for Ultrasound in Medicine and Biology

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Funding

The authors state that this work has not received any funding.

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Authors and Affiliations

  1. Department of Medical Ultrasonics, The First Affiliated Hospital, Sun Yat-sen University, 58 Zhongshan Road 2, Guangzhou, 510080, China

    Yu Duan, Xiaoyan Xie, Ming Kuang & Manxia Lin

  2. Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA, 02114, USA

    Yu Duan, Qian Li & Anthony E. Samir

  3. Institute for Technology Assessment, Massachusetts General Hospital, Harvard Medical School, 101 Merrimac Street, Suite 1010, Boston, MA, 02114, USA

    Nathaniel Mercaldo

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  1. Yu Duan
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  6. Ming Kuang
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Correspondence to Manxia Lin.

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Duan, Y., Xie, X., Li, Q. et al. Differentiation of regenerative nodule, dysplastic nodule, and small hepatocellular carcinoma in cirrhotic patients: a contrast-enhanced ultrasound–based multivariable model analysis. Eur Radiol 30, 4741–4751 (2020). https://doi.org/10.1007/s00330-020-06834-5

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