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Nomogram Development and Validation to Predict Hepatocellular Carcinoma Tumor Behavior by Preoperative Gadoxetic Acid-Enhanced MRI

37 Pages Posted: 10 May 2019

See all articles by Shuling Chen

Shuling Chen

Sun Yat-Sen University (SYSU) - Department of Medical Ultrasonics

Mimi Tang

Sun Yat-Sen University (SYSU) - Department of Gastroenterology and Hepatology

Qian Zhou

Sun Yat-Sen University (SYSU) - First Affiliated Hospital

Mengqi Huang

Sun Yat-Sen University (SYSU) - First Affiliated Hospital

Kaiyu Sun

Sun Yat-Sen University (SYSU) - First Affiliated Hospital

Tingfan Wu

GE HealthCare China

Xin Li

GE HealthCare China

Bing Liao

Sun Yat-Sen University (SYSU) - Department of Pathology

Lili Chen

Sun Yat-Sen University (SYSU) - First Affiliated Hospital

Junbin Liao

Sun Yat-Sen University (SYSU) - Department of Liver Surgery

Sui Peng

Sun Yat-Sen University (SYSU), First Affiliated Hospital, Clinical Trial Unit; Sun Yat-Sen University (SYSU) - Department of Gastroenterology and Hepatology

Ming Kuang

Sun Yat-Sen University (SYSU) - Division of Interventional Ultrasound; Sun Yat-Sen University (SYSU) - Division of Interventional Ultrasound

Shi-Ting Feng

Sun Yat-Sen University (SYSU) - Department of Radiology

More...

Abstract

Background: Pretreatment evaluation of tumor biology and microenvironment of hepatocellular carcinoma (HCC) are important to predict prognosis and plan treatment. We aimed to develop nomograms based on Gd-EOB-DTPA-enhanced magnetic resonance imaging (MRI) to predict microvascular invasion (MVI), tumor differentiation, and immunoscore.

Methods: This retrospective study included 273 patients with HCC who underwent preoperative Gd-EOB-DTPA-enhanced MRI. Patients were assigned to two groups: training (N = 191) and validation (N = 82). Univariable and multivariable logistic regression analyses were performed to investigate clinical variables and MRI features' associations with MVI, tumor differentiation and immunoscore. Nomograms were developed based on features associated with these histopathological features in the same training cohort, then validated, and evaluated.

Findings: Predictors of MVI included tumor size (P = 0.002), rim enhancement (P = 0.017), percent reduction in T1 images (T1D%; P = 0.043), and standard deviation of apparent diffusion coefficient (P = 0.028), while capsule (P = 0.007), mean relaxation time on the hepatocellular phase (T1E; P < 0.001), and alpha-fetoprotein levels (P = 0.003) predicted tumor differentiation. Predictors of immunoscore included the radiologic score (P = 0.001) constructed by tumor number, intratumoral vessel, margin, capsule, rim enhancement, T1D%, relaxation time on plain scan (T1P) and T1E, and serum alpha-fetoprotein (P = 0.027) and alanine aminotransferase levels (P = 0.028). Three nomograms achieved high C-index in predicting MVI (0.754, 0.746), tumor differentiation (0.758, 0.699) and immunoscore (0.737, 0.726) in the training and validation cohorts, respectively.   Interpretation:MRI-based nomograms effectively predict tumor behaviors in HCC and may assist clinicians in prognosis prediction.

Funding: This work was funded by the National Natural Science Foundation of China (No. 81771908, 81571750, 81801703), the National Science Fund for Distinguished Young Scholars (No. 81825013) and the Guangdong Natural Science Foundation of Guangdong Province (No. 2018A030310282).

Declaration of Interest: The authors declare that they have no competing interests.

Ethical Approval: The Institutional Ethic Review Board has approved our study, and informed consent was waived due to the retrospective nature of the study.

Keywords: gadoxetic acid; microvascular invasion; tumor differentiation; immunoscore; tumor microenvironment

Suggested Citation

Chen, Shuling and Tang, Mimi and Zhou, Qian and Huang, Mengqi and Sun, Kaiyu and Wu, Tingfan and Li, Xin and Liao, Bing and Chen, Lili and Liao, Junbin and Peng, Sui and Kuang, Ming and Feng, Shi-Ting, Nomogram Development and Validation to Predict Hepatocellular Carcinoma Tumor Behavior by Preoperative Gadoxetic Acid-Enhanced MRI (April 5, 2019). Available at SSRN: https://ssrn.com/abstract=3384867 or http://dx.doi.org/10.2139/ssrn.3384867

Shuling Chen

Sun Yat-Sen University (SYSU) - Department of Medical Ultrasonics ( email )

China

Mimi Tang

Sun Yat-Sen University (SYSU) - Department of Gastroenterology and Hepatology

135, Xingang Xi Road
Guangdong, Guangdong 510275
China

Qian Zhou

Sun Yat-Sen University (SYSU) - First Affiliated Hospital

Guangzhou
China

Mengqi Huang

Sun Yat-Sen University (SYSU) - First Affiliated Hospital ( email )

Guangzhou
China

Kaiyu Sun

Sun Yat-Sen University (SYSU) - First Affiliated Hospital

Guangzhou
China

Tingfan Wu

GE HealthCare China

China

Xin Li

GE HealthCare China

China

Bing Liao

Sun Yat-Sen University (SYSU) - Department of Pathology

Guangzhou, Guangdong
China

Lili Chen

Sun Yat-Sen University (SYSU) - First Affiliated Hospital

Guangzhou
China

Junbin Liao

Sun Yat-Sen University (SYSU) - Department of Liver Surgery

China

Sui Peng

Sun Yat-Sen University (SYSU), First Affiliated Hospital, Clinical Trial Unit ( email )

China

Sun Yat-Sen University (SYSU) - Department of Gastroenterology and Hepatology

135, Xingang Xi Road
Guangdong, Guangdong 510275
China

Ming Kuang

Sun Yat-Sen University (SYSU) - Division of Interventional Ultrasound ( email )

China

Sun Yat-Sen University (SYSU) - Division of Interventional Ultrasound ( email )

China

Shi-Ting Feng (Contact Author)

Sun Yat-Sen University (SYSU) - Department of Radiology ( email )

135, Xingang Xi Road
Guangzhou, Guangdong 510275
China

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