Yu Duan1,2, Xiaoyan Xie1, Qian Li2, Nathaniel Mercaldo3, Anthony E Samir2, Ming Kuang1, Manxia Lin4. 1. Department of Medical Ultrasonics, The First Affiliated Hospital, Sun Yat-sen University, 58 Zhongshan Road 2, Guangzhou, 510080, China. 2. Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA, 02114, USA. 3. Institute for Technology Assessment, Massachusetts General Hospital, Harvard Medical School, 101 Merrimac Street, Suite 1010, Boston, MA, 02114, USA. 4. Department of Medical Ultrasonics, The First Affiliated Hospital, Sun Yat-sen University, 58 Zhongshan Road 2, Guangzhou, 510080, China. linmxia@mail.sysu.edu.cn.
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 CATR can be used for differentiating cirrhotic liver lesions and for active surveillance of HCC. • The reduction of CATR (RN < DN < small HCC) was strongly associated with high-risk cirrhotic liver nodules. • Inclusion of CATR in the CEUS prediction model significantly improved its performance for cirrhotic liver lesions risk-stratification.
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 CATR can be used for differentiating cirrhotic liver lesions and for active surveillance of HCC. • The reduction of CATR (RN < DN < small HCC) was strongly associated with high-risk cirrhotic liver nodules. • Inclusion of CATR in the CEUS prediction model significantly improved its performance for cirrhotic liver lesions risk-stratification.