Noninvasive prediction of HCC with progenitor phenotype based on gadoxetic acid-enhanced MRI.

Autor: Chen J; West China School of Medicine, Sichuan University, Guoxue Xiang, No. 37, Chengdu, 610041, China., Wu Z; Laboratory of Pathology, West China Hospital, Sichuan University, B2 Building, No. 88, South Ke Yuan Road, Chengdu, 610041, China., Xia C; Department of Radiology, West China Hospital, Sichuan University, Guoxue Xiang, No. 37, Chengdu, 610041, China., Jiang H; West China School of Medicine, Sichuan University, Guoxue Xiang, No. 37, Chengdu, 610041, China., Liu X; Department of Radiology, West China Hospital, Sichuan University, Guoxue Xiang, No. 37, Chengdu, 610041, China., Duan T; Department of Radiology, West China Hospital, Sichuan University, Guoxue Xiang, No. 37, Chengdu, 610041, China., Cao L; West China School of Medicine, Sichuan University, Guoxue Xiang, No. 37, Chengdu, 610041, China., Ye Z; West China School of Medicine, Sichuan University, Guoxue Xiang, No. 37, Chengdu, 610041, China., Zhang Z; West China School of Medicine, Sichuan University, Guoxue Xiang, No. 37, Chengdu, 610041, China., Ma L; Application Advanced Team, GE Healthcare, Shanghai, China., Song B; Department of Radiology, West China Hospital, Sichuan University, Guoxue Xiang, No. 37, Chengdu, 610041, China. songlab_radiology@163.com., Shi Y; Laboratory of Pathology, West China Hospital, Sichuan University, B2 Building, No. 88, South Ke Yuan Road, Chengdu, 610041, China. shiyujun@scu.edu.cn.
Jazyk: angličtina
Zdroj: European radiology [Eur Radiol] 2020 Feb; Vol. 30 (2), pp. 1232-1242. Date of Electronic Publication: 2019 Sep 16.
DOI: 10.1007/s00330-019-06414-2
Abstrakt: Objectives: To explore the noninvasive prediction of hepatocellular carcinoma (HCC) with progenitor phenotype based on gadoxetic acid-enhanced magnetic resonance imaging (MRI).
Methods: This retrospective study included 115 surgery-proven HCCs with preoperative gadoxetic acid-enhanced MRI from August 2015 to September 2018. Image features were reviewed. Quantitative image analysis was performed using histogram analysis. HCC with progenitor phenotype was defined as positive for either cytokeratin 19 (CK19) or epithelial cell adhesion molecule (EpCAM) expression. Statistically significant variables for identifying HCCs with progenitor phenotype were determined at multivariate analyses. ROC analyses were used to determined cutoff values and the diagnostic performance of significant variables and combinations. Prediction nomogram was constructed based on multivariate analysis.
Results: At multivariate regression analyses, AFP ≥ 155.25 ng/mL (p < 0.001), skewness on T2WI ≤ 1.10 (p = 0.024), uniformity on pre-T1WI ≤ 0.91 (p = 0.024), irregular tumor margin (p = 0.006), targetoid appearance (p = 0.001), and the absence of mosaic architecture (p = 0.014) were significant predictors of HCCs expressing progenitor cell markers. Combing any three of those significant variables, it provides a diagnostic accuracy of 0.86 (95% CI 0.78-0.92) with sensitivity of 0.97 (95% CI 0.86-1.00), and specificity of 0.74 (95% CI 0.63-0.83). The C-index of the regression coefficient-based nomogram was 0.94 (95% CI 0.91-0.98).
Conclusions: Noninvasive prediction of HCCs with progenitor phenotype can be achieved with high accuracy by integrated interpretation of biochemical and radiological information, representing a handy tool for precise patient management and the prediction of prognosis.
Key Points: • Qualitative image features of irregular tumor margin, targetoid appearance, and the absence of mosaic architecture are significant predictors of hepatocellular carcinoma with progenitor phenotype. • Quantitative analyses using whole-lesion histogram analysis provides additional information for the prediction of hepatocellular carcinoma with progenitor phenotype. • Noninvasive prediction of hepatocellular carcinoma with progenitor phenotype can be achieved with high accuracy by integrated interpretation of clinical information and qualitative and quantitative imaging analyses.
Databáze: MEDLINE
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