Abstract
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.
Highlights
Hepatocellular carcinoma (HCC) has become the second most common cancer and ranks as the sixth most common cause of cancer-related death worldwide [1]
Development of predictive nomograms In total, 1 clinical characteristic (AFP level), 6 qualitative imaging features and the radiomics score were identified by univariate analysis
[95%CI, 0.488 to 9.974], P < 0.001), gross vascular invasion (OR, 3.356 [95%CI, 1.308 to 9.023], P = 0.013) and a non-smooth tumour margin (OR, 2.735 [95%CI, 1.104 to 6.989], P = 0.031) significantly predicted early recurrence (Table 2)
Summary
Hepatocellular carcinoma (HCC) has become the second most common cancer and ranks as the sixth most common cause of cancer-related death worldwide [1]. Studies on magnetic resonance (MR) imaging, with the hepatocyte specific contrast agent gadoxetic acid (formerly known as Gd-EOB-DTPA, Bayer Healthcare, Germany), have reported several qualitative imaging features, such as peritumoural parenchymal enhancement, satellite nodules and non-smooth tumour margin, to be non-invasive predictors of early recurrence in HCC [10,11,12]. These criteria for preoperative imaging prediction of early recurrence in HCC have not yet been widely recognized. This 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
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