Non-invasive diagnosis strategy of hepatocellular carcinoma in low-risk population.

Abstract

AIMS:

With prevalence of hepatocellular carcinoma (HCC) in low-risk population (LRP), establishing a non-invasive diagnostic strategy becomes increasingly urgent to spare unnecessary biopsies in this population. The purposes of this study were to find characterisics of HCC and to establish a proper non-invasive method to diagnose HCC in LRP.

METHODS:

A total of 681 patients in LRP (defined as the population without cirrhosis, chronic HBV infection or HCC history) were collected from 2 institutions. The images of computed tomography (CT) and magnetic resonance imaging (MRI) were manually analysed. We divided the patients into the training cohort (n = 324) and the internal validating cohort (n = 139) by admission time in the first institution. The cohort in the second institution was viewed as the external validation (n = 218). A multivariate logistic regression model incorporating both imaging and clinical independent risk predictors was developed. C-statistics was used to evaluate the diagnostic performance.

RESULTS:

Besides the major imaging features of HCC (non-rim enhancement, washout and enhancing capsule), tumor necrosis or severe ischemia (TNSI) on imaging and two clinical characteristics (gender and alpha fetoprotein) were also independently associated with HCC diagnosis (all P < 0.01). A clinical model (including 3 major features, TNSI, gender and AFP) was built to diagnose HCC and achieved good diagnostic performance (area under curve values were 0.954 in the training cohort, 0.931 in the internal validation cohort and 0.902 in the external cohort).

CONCLUSIONS:

The clinical model in this study developed a satisfied non-invasive diagnostic performance for HCC in LRP.

• Authors: Zonglin Xie, Zhenpeng Peng, Yujian Zou, Han Xiao, Bin Li, Qian Zhou, Shuling Chen, Lixia Xu, Jingxian Shen, Yunxian Mo, Sui Peng, Ming Kuang, Jianting Long, Shi-Ting Feng
• Journal: BMC cancer (BMC Cancer) Vol. 22 Issue 1 Pg. 709 (Jun 28 2022) ISSN: 1471-2407 [Electronic] England
• PMID: 35761201 (Publication Type: Journal Article)
• Copyright: © 2022. The Author(s).

Chemical References

• Contrast Media

Topics

• Carcinoma, Hepatocellular (diagnostic imaging, pathology)
• Contrast Media
• Humans
• Liver Cirrhosis (pathology)
• Liver Neoplasms (diagnostic imaging, pathology)
• Magnetic Resonance Imaging (methods)
• Retrospective Studies
• Sensitivity and Specificity
• Tomography, X-Ray Computed (methods)