Background 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. Methods In 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. Results In 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. Conclusions Incorporating multiple predictive factors, the radiomics nomogram demonstrated great potential in the preoperative prediction of early HCC recurrence after surgery. Electronic supplementary material The online version of this article (10.1186/s40644-019-0209-5) contains supplementary material, which is available to authorized users.

Hepatocellular carcinoma (HCC) is the most common primary liver cancer and a major public health problem worldwide. Hepatocarcinogenesis is a complex multistep process at molecular, cellular, and histologic levels with key alterations that can be revealed by noninvasive imaging modalities. Therefore, imaging techniques play pivotal roles in the detection, characterization, staging, surveillance, and prognosis evaluation of HCC. Currently, ultrasound is the first-line imaging modality for screening and surveillance purposes. While based on conclusive enhancement patterns comprising arterial phase hyperenhancement and portal venous and/or delayed phase wash-out, contrast enhanced dynamic computed tomography and magnetic resonance imaging (MRI) are the diagnostic tools for HCC without requirements for histopathologic confirmation. Functional MRI techniques, including diffusion-weighted imaging, MRI with hepatobiliary contrast agents, perfusion imaging, and magnetic resonance elastography, show promise in providing further important information regarding tumor biological behaviors. In addition, evaluation of tumor imaging characteristics, including nodule size, margin, number, vascular invasion, and growth patterns, allows preoperative prediction of tumor microvascular invasion and patient prognosis. Therefore, the aim of this article is to review the current state-of-the-art and recent advances in the comprehensive noninvasive imaging evaluation of HCC. We also provide the basic key concepts of HCC development and an overview of the current practice guidelines.

Background: The aim of this study was to prospectively evaluate the diagnostic efficacy of diffusion kurtosis imaging (DKI) in predicting microvascular invasion (MVI) and histologic grade of hepatocellular carcinoma (HCC) with comparison to the conventional diffusion-weighted imaging (DWI). Methods: This prospective study was approved by the Institutional Review Board, and written informed consent was obtained from all patients. From September 2015 to January 2017, 74 consecutive HCC patients were enrolled in this study. Preoperative magnetic resonance imaging including DKI protocol was performed, and patients were followed up for at least one year after surgery. Diffusion parameters including the mean corrected apparent diffusion coefficient (MD), mean apparent kurtosis coefficient (MK), and apparent diffusion coefficient (ADC) were calculated. Differences of diffusion parameters among different histopathological groups were compared. For parameters that were significantly different between pathological groups, receiver operating characteristics (ROC) curve analyses were performed to evaluate the diagnostic efficiency for identifying MVI and predicting high-grade HCC. Univariate and multivariate logistic regression analyses were used to evaluate the relative value of clinical and laboratory variables and diffusion parameters as risk factors for early recurrence (≤1 year). Results: Among all the studied diffusion parameters, only MK differed significantly between the MVIpositive and MVI-negative group (0.91±0.10 vs. 0.82±0.09, P<0.001), and showed moderate diagnostic efficacy (AUC =0.77) for identifying MVI. High-grade HCCs showed significantly higher MK values (0.93±0.10 vs. 0.82±0.09, P<0.001), along with MD (1.34±0.18 vs. 1.54±0.22, P<0.001) and ADC values (1.17±0.15 vs. 1.30±0.16, P=0.001) than low-grade HCCs. For differentiating high-grade from low-grade HCCs, MK demonstrated a higher area under the ROC curve (AUC) and significantly higher specificity than MD and ADC (AUC =0.81 vs. 0.76 and 0.74; specificity =82.2% vs. 60.0% and 60.0%, P=0.02). In addition, higher MK (OR =5.700, P=0.002) and Barcelona Clinic Liver Cancer (BCLC) stage C (OR =6.329, P=0.005) were independent risk factors for early HCC recurrence. Conclusions: DKI-derived MK values outperformed conventional ADC values for predicting MVI and histologic grade of HCC, and are associated with increased risk of early tumor recurrence.

ObjectiveTo investigate the value of whole-lesion texture analysis on preoperative gadoxetic acid enhanced magnetic resonance imaging (MRI) for predicting tumor Ki-67 status after curative resection in patients with hepatocellular carcinoma (HCC).MethodsThis study consisted of 89 consecutive patients with surgically confirmed HCC. Texture features were extracted from multiparametric MRI based on whole-lesion regions of interest. The Ki-67 status was immunohistochemical determined and classified into low Ki-67 (labeling index ≤15%) and high Ki-67 (labeling index >15%) groups. Least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression were applied for generating the texture signature, clinical nomogram and combined nomogram. The discrimination power, calibration and clinical usefulness of the three models were evaluated accordingly. Recurrence-free survival (RFS) rates after curative hepatectomy were also compared between groups.ResultsA total of 13 texture features were selected to construct a texture signature for predicting Ki-67 status in HCC patients (C-index: 0.878, 95% confidence interval: 0.791−0.937). After incorporating texture signature to the clinical nomogram which included significant clinical variates (AFP, BCLC-stage, capsule integrity, tumor margin, enhancing capsule), the combined nomogram showed higher discrimination ability (C-index: 0.936vs. 0.795, P<0.001), good calibration (P>0.05 in Hosmer-Lemeshow test) and higher clinical usefulness by decision curve analysis. RFS rate was significantly lower in the high Ki-67 group compared with the low Ki-67 group after curative surgery (63.27%vs. 85.00%, P<0.05). ConclusionsTexture analysis on gadoxetic acid enhanced MRI can serve as a noninvasive approach to preoperatively predict Ki-67 status of HCC after curative resection. The combination of texture signature and clinical factors demonstrated the potential to further improve the prediction performance.

No abstract