Hepatocellular carcinoma: radiomics nomogram on gadoxetic acid-enhanced MR imaging for early postoperative recurrence prediction

Cancer Imaging

Zheng Ye¹  Yi Wei¹  Bin Song¹  Jie Chen¹  Zhen Zhang¹  Hanyu Jiang¹  Likun Cao¹  Xin Li²  Ling Ma² 

[1] 0000 0004 1770 1022, grid.412901.f, Department of Radiology, West China Hospital of Sichuan University, No.37 Guo Xue Xiang, 610041, Chengdu, China;GE Healthcare China, Beijing, China;

关键词: Gadoxetic acid-enhanced MRI;    Hepatocellular carcinoma;    Recurrence;    Radiomics;    Nomogram;   

DOI  :  10.1186/s40644-019-0209-5

来源: publisher

【 摘 要 】

BackgroundThis study was performed to prospectively develop and validate a radiomics nomogram for predicting postoperative early recurrence (≤1 year) of hepatocellular carcinoma (HCC) using whole-lesion radiomics features on preoperative gadoxetic acid-enhanced magnetic resonance (MR) images.MethodsIn total, 155 patients (training cohort: n = 108; validation cohort: n = 47) with surgically confirmed HCC were enrolled in this IRB-approved prospective study. Three-dimensional whole-lesion regions of interest were manually delineated along the tumour margins on multi-sequence MR images. Radiomics features were generated and selected to build a radiomics score using the least absolute shrinkage and selection operator (LASSO) method. Clinical characteristics and qualitative imaging features were identified by two independent radiologists and combined to establish a clinical-radiological nomogram. A radiomics nomogram comprising the radiomics score and clinical-radiological risk factors was constructed based on multivariable logistic regression analysis. Diagnostic performance and clinical usefulness were measured by receiver operation characteristic (ROC) and decision curves.ResultsIn total, 14 radiomics features were selected to construct the radiomics score. For the clinical-radiological nomogram, the alpha-fetoprotein (AFP) level, gross vascular invasion and non-smooth tumour margin were included. The radiomics nomogram integrating the radiomics score with clinical-radiological risk factors showed better discriminative performance (AUC = 0.844, 95%CI, 0.769 to 0.919) than the clinical-radiological nomogram (AUC = 0.796, 95%CI, 0.712 to 0.881; P = 0.045), with increased clinical usefulness confirmed using a decision curve analysis.ConclusionsIncorporating multiple predictive factors, the radiomics nomogram demonstrated great potential in the preoperative prediction of early HCC recurrence after surgery.

【 授权许可】

CC BY