A Non-Invasive Nomogram for Preoperative Prediction of Microvascular Invasion Risk in Hepatocellular Carcinoma

BackgroundMicrovascular invasion (MVI) is a significant predictive factor for early recurrence, metastasis, and poor prognosis of hepatocellular carcinoma. The aim of the present study is to identify preoperative factors for predicting MVI, in addition to develop and validate non-invasive nomogram for predicting MVI.MethodsA total of 381 patients with resected HCC were enrolled and divided into a training cohort (n = 267) and a validation cohort (n = 114). Serum VEGF-A level was examined by enzyme-linked immunosorbent assay (ELISA). Risk factors for MVI were assessed based on univariate and multivariate analyses in the training cohort. A nomogram incorporating independent risk predictors was established and validated.ResultThe serum VEGF-A levels in the MVI positive group (n = 198) and MVI negative group (n = 183) were 215.25 ± 105.68 pg/ml and 86.52 ± 62.45 pg/ml, respectively (P <0.05). Serum VEGF-A concentration ≥138.30 pg/ml was an independent risk factor of MVI (OR: 33.088; 95%CI: 12.871–85.057; P <0.001). Higher serum concentrations of AFP and VEGF-A, lower lymphocyte count, peritumoral enhancement, irregular tumor shape, and intratumoral artery were identified as significant predictors for MVI. The nomogram indicated excellent predictive performance with an AUROC of 0.948 (95% CI: 0.923–0.973) and 0.881 (95% CI: 0.820–0.942) in the training and validation cohorts, respectively. The nomogram showed a good model fit and calibration.ConclusionsHigher serum concentrations of AFP and VEGF-A, lower lymphocyte count, peritumoral enhancement, irregular tumor shape, and intratumoral artery are promising markers for MVI prediction in HCC. A reliable non-invasive nomogram which incorporated blood biomarkers and imaging risk factors was established and validated. The nomogram achieved desirable effectiveness in preoperatively predicting MVI in HCC patients.

Pharmacokinetic analysis of different contrast agents on multiphase enhanced MRI for microvascular invasion: preoperative prediction in hepatocellular carcinoma

Background The preoperative diagnosis of microvascular invasion (MVI) for the solitary small hepatocellular carcinoma (sHCC) is crucial for the decision of surgical strategies. Purpose To compare the kinetic parameters and diagnostic effects of two contrast agents for preoperatively predicting MVI of sHCC on multiphase enhanced magnetic resonance imaging (MRI). Material and Methods Two groups of patients with known solitary sHCC underwent an enhanced MRI examination before hepatic resection: Data A (n = 61) patients underwent Gd-EOB-DTPA-enhanced MRI, and Data B (n = 41) patients had a normal contrast agent. The two sets of data were processed in the same way. Arterial peritumoral enhancement measured from multiphase enhanced MRI was analyzed using quantitative kinetic parameters, including initial signal enhancement (SE1), peak signal enhancement (SEpeak), and calculation of the signal enhancement ratio (SER). Results The statistical analysis showed that the average SE1 and SER (Data A) for the MVI-positive group were significantly higher ( P < 0.05) than those in the MVI-negative group. The SER (Data B) and SEpeak showed no significant difference for either group. In Data A, the receiver operating characteristic analysis between the two groups had an area under the curve of 0.74 and 0.71 for SE1 and SER, respectively, which was higher than that of Data B. The different contrast agents had the same enhancement curve trend. Conclusion Gd-EOB-DTPA-enhanced MRI had a better quantitative kinetic parameter analysis effect for arterial peritumoral enhancement on predicting MVI of sHCC in clinical practice.

Distinguishing Hepatocellular Carcinoma From Hepatic Inflammatory Pseudotumor Using a Nomogram Based on Contrast-Enhanced Ultrasound

BackgroundHepatocellular carcinoma (HCC) and hepatic iflammatory pseudotumor (IPT) share similar symptoms and imaging features, which makes it challenging to distinguish from each other in clinical practice. This study aims to develop a predictive model based on contrast-enhanced ultrasound (CEUS) and clinical features to discriminate HCC from IPT.MethodsSixty-two IPT and 146 HCC patients were enrolled in this study, where pathological diagnosis served as the reference standard for diagnosis. Clinical and ultrasound imaging data including CEUS features: enhancement degree during arterial phase, portal phase and delayed phase, enhancement pattern, early washout within 60 s, feeding artery, peritumoral vessels, peritumoral enhancement, and margin of nonenhanced area were retrospectively collected. Imaging data were reviewed by two experienced ultrasound doctors. Patients were randomly assigned to training and validation sets. Chi-squared test followed by LASSO regression was performed on ultrasonographic features in the training set to identify the most valuable features that distinguish HCC from IPT, based on which the sonographic score formula was generated. With the significant clinical and ultrasonographic indicators, a nomogram was developed. The performance of the nomogram was verified by ROC curve and decision curve analysis (DCA) with the comparison with sonographic score and the ultrasound doctor’s diagnosis.ResultsThe most valuable ultrasonographic features that distinguish between HCC and IPT were enhancement degree during arterial phase, early washout, peritumoral vessels, peritumoral enhancement, and liver background. The sonographic score based on these features was verified to be an independent factor that predicts the diagnosis (p = 0.003). Among the clinical indicators, AFP (p = 0.009) and viral hepatitis infection (p = 0.004) were significant. Sonographic score, AFP, and viral hepatitis were used to construct a predictive nomogram. The AUC of the nomogram was 0.989 and 0.984 in training and validation sets, respectively, which were higher than those of sonographic score alone (0.938 and 0.958) or the ultrasound doctor’s diagnosis (0.794 and 0.832). DCA showed the nomogram provided the greatest clinical usefulness.ConclusionA predictive nomogram based on a sonographic signature improved the diagnostic performance in distinguishing HCC and IPT, which may help with individualized diagnosis and treatment in clinical practice.

Radiomic Features of Multi-ROI and Multi-Phase MRI for the Prediction of Microvascular Invasion in Solitary Hepatocellular Carcinoma

ObjectivesTo develop and validate an MR radiomics-based nomogram to predict the presence of MVI in patients with solitary HCC and further evaluate the performance of predictors for MVI in subgroups (HCC ≤ 3 cm and &gt; 3 cm).Materials and MethodsBetween May 2015 and October 2020, 201 patients with solitary HCC were analysed. Radiomic features were extracted from precontrast T1WI, arterial phase, portal venous phase, delayed phase and hepatobiliary phase images in regions of the intratumoral, peritumoral and their combining areas. The mRMR and LASSO algorithms were used to select radiomic features related to MVI. Clinicoradiological factors were selected by using backward stepwise regression with AIC. A nomogram was developed by incorporating the clinicoradiological factors and radiomics signature. In addition, the radiomic features and clinicoradiological factors related to MVI were separately evaluated in the subgroups (HCC ≤ 3 cm and &gt; 3 cm).ResultsHistopathological examinations confirmed MVI in 111 of the 201 patients (55.22%). The radiomics signature showed a favourable discriminatory ability for MVI in the training set (AUC, 0.896) and validation set (AUC, 0.788). The nomogram incorporating peritumoral enhancement, tumour growth type and radiomics signature showed good discrimination in the training (AUC, 0.932) and validation sets (AUC, 0.917) and achieved well-fitted calibration curves. Subgroup analysis showed that tumour growth type was a predictor for MVI in the HCC ≤ 3 cm cohort and peritumoral enhancement in the HCC &gt; 3 cm cohort; radiomic features related to MVI varied between the HCC ≤ 3 cm and HCC &gt; 3 cm cohort. The performance of the radiomics signature improved noticeably in both the HCC ≤ 3 cm (AUC, 0.953) and HCC &gt; 3 cm cohorts (AUC, 0.993) compared to the original training set.ConclusionsThe preoperative nomogram integrating clinicoradiological risk factors and the MR radiomics signature showed favourable predictive efficiency for predicting MVI in patients with solitary HCC. The clinicoradiological factors and radiomic features related to MVI varied between subgroups (HCC ≤ 3 cm and &gt; 3 cm). The performance of radiomics signature for MVI prediction was improved in both the subgroups.

MRI Features for Predicting Microvascular Invasion of Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis

<b><i>Purpose:</i></b> Microvascular invasion (MVI) is an important prognostic factor in patients with hepatocellular carcinoma (HCC). However, the reported results of magnetic resonance imaging (MRI) features for predicting MVI of HCC are variable and conflicting. Therefore, this meta-analysis aimed to identify the significant MRI features for MVI of HCC and to determine their diagnostic value. <b><i>Methods:</i></b> Original studies reporting the diagnostic performance of MRI for predicting MVI of HCC were identified in MEDLINE and EMBASE up until January 15, 2020. Study quality was assessed using QUADAS-2. A bivariate random-effects model was used to calculate the meta-analytic pooled diagnostic odds ratio (DOR) and 95% confidence interval (CI) for each MRI feature for diagnosing MVI in HCC. The meta-analytic pooled sensitivity and specificity were calculated for the significant MRI features. <b><i>Results:</i></b> Among 235 screened articles, we found 36 studies including 4,274 HCCs. Of the 15 available MRI features, 7 were significantly associated with MVI: larger tumor size (&#x3e;5 cm) (DOR = 5.2, 95% CI [3.0–9.0]), rim arterial enhancement (4.2, 95% CI [1.7–10.6]), arterial peritumoral enhancement (4.4, 95% CI [2.8–6.9]), peritumoral hypointensity on hepatobiliary phase imaging (HBP) (8.2, 95% CI [4.4–15.2]), nonsmooth tumor margin (3.2, 95% CI [2.2–4.4]), multifocality (7.1, 95% CI [2.6–19.5]), and hypointensity on T1-weighted imaging (T1WI) (4.9, 95% CI [2.5–9.6]). Both peritumoral hypointensity on HBP and multifocality showed very high meta-analytic pooled specificities for diagnosing MVI (91.1% [85.4–94.8%] and 93.3% [74.5–98.5%], respectively). <b><i>Conclusions:</i></b> Seven MRI features including larger tumor size, rim arterial enhancement, arterial peritumoral enhancement, peritumoral hypointensity on HBP, nonsmooth margin, multifocality, and hypointensity on T1WI were significant predictors for MVI of HCC. These MRI features predictive of MVI can be useful in the management of HCC.

Combined hepatocellular-cholangiocarcinoma: which preoperative clinical data and conventional MRI characteristics have value for the prediction of microvascular invasion and clinical significance?

Objectives To explore which preoperative clinical data and conventional MRI findings may indicate microvascular invasion (MVI) of combined hepatocellular-cholangiocarcinoma (cHCC-CCA) and have clinical significance. Methods The study enrolled 113 patients with histopathologically confirmed cHCC-CCA (MVI-positive group [n = 56], MVI-negative group [n = 57]). Two radiologists retrospectively assessed the preoperative MRI features (qualitative analysis of morphology and dynamic enhancement features), and each lesion was assigned according to the LI-RADS. Preoperative clinical data were also evaluated. Logistic regression analyses were used to assess the relative value of these parameters as potential predictors of MVI. Recurrence-free survival (RFS) rates after hepatectomy in the two groups were estimated using Kaplan–Meier survival curves and compared using the log-rank test. Results The majority of cHCC-CCAs were categorized as LR-M. On multivariate analysis, a higher serum AFP level (OR, 0.523; 95% CI, 0.282–0.971; p = 0.040), intratumoral fat deposition (OR, 14.368; 95% CI, 2.749–75.098; p = 0.002), and irregular arterial peritumoral enhancement (OR, 0.322; 95% CI, 0.164–0.631; p = 0.001) were independent variables associated with the MVI of cHCC-CCA. After hepatectomy, patients with MVI of cHCC-CCA showed earlier recurrence than those without MVI (hazard ratio [HR], 0.402; 95% CI, 0.189–0.854, p = 0.013). Conclusion A higher serum AFP level and irregular arterial peritumoral enhancement are potential predictive biomarkers for the MVI of cHCC-CCA, while intratumoral fat detected on MRI suggests a low risk of MVI. Furthermore, cHCC-CCAs with MVI may have worse surgical outcomes with regard to early recurrence than those without MVI. Key Points • Higher serum levels of AFP combined with irregular arterial peritumoral enhancement are independent risk factors for the MVI of cHCC-CCA, while fat deposition might be a protective factor. • cHCC-CCA with MVI may have a higher risk of early recurrence after surgery. • Most cHCC-CCAs were categorized as LR-M in this study, and no significant difference was found in MVI based on LI-RADS category.

A Nomogram Predicting Microvascular Invasion Risk in BCLC 0/A Hepatocellular Carcinoma after Curative Resection

Background. Numerous studies have shown that hepatocellular carcinoma (HCC) without microvascular invasion (MVI) may have better outcomes. This study established a preoperative MVI risk nomogram mainly incorporating three related risk factors of MVI in BCLC 0/A HCC after surgery. Methods. Independent predictors for the risk of MVI were investigated, and an MVI risk nomogram was established based on 60 patients in the training group who underwent curative hepatectomy for BCLC 0/A HCC and validated using a dataset in the validation group. Results. Univariate analysis in the training group showed that hepatitis viral B (HBV) DNA (P=0.034), tumor size (P<0.001), CT value in the venous phase (P=0.039), CT value in the delayed phase (P=0.017), peritumoral enhancement (P=0.013), visible small blood vessels in the arterial phase (P=0.002), and distance from the tumor to the inferior vena cava (IVC) (DTI, P=0.004) were risk factors significantly associated with the presence of MVI. According to multivariate analysis, the independent predictive factors of MVI, including tumor size (P=0.002), CT value in the delayed phase (P=0.018), and peritumoral enhancement (P=0.057), were incorporated in the corresponding nomogram. The nomogram displayed an unadjusted C-index of 0.851 and a bootstrap-corrected C-index of 0.832. Calibration curves also showed good agreement on the presence of MVI. ROC curve analyses showed that the nomogram had a large AUC (0.851). Conclusions. The proposed nomogram consisting of tumor size, CT value in the delayed phase, and peritumoral enhancement was associated with MVI risk in BCLC 0/A HCC following curative hepatectomy.

Preoperative MRI features and clinical laboratory indicators for predicting the early therapeutic response of hepatocellular carcinoma to transcatheter arterial chemoembolization combined with High-intensity focused ultrasound treatment

Objectives: To evaluate the value of preoperative MRI features and laboratory indicators in predicting the early response of hepatocellular carcinoma (HCC) to transcatheter arterial chemoembolization (TACE) combined with high-intensity focused ultrasound (HIFU) treatment and to establish a preoperative prediction model. Methods: A total of 188 patients with 223 tumors who underwent TACE/HIFU treatment from January 2011 to June 2017 were included. Tumors were divided into three groups (< 2 cm, 2 – 5 cm,> 5 cm) and classified as non-complete response (NCR) and complete response (CR) cohorts according to the Response Evaluation Criteria in Cancer of the Liver (RECICL) 2015 revised version. Univariate analysis and multivariate logistic regression analysis were used to determine independent predictors, and receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic power of each predictor. The prediction model was derived on the β coefficient of the multivariate regression analysis of the predictors. Results: Irregular margins in the 2 – 5 cm group were closely related to early NCR. Irregular margins, arterial peritumoral enhancement and abnormal alpha-fetoprotein (AFP) were independent predictors of early NCR in the > 5 cm group. The prediction model of this group suggests that irregular margins combined with arterial peritumoral enhancement and abnormal AFP combined with irregular margins and arterial peritumoral enhancement predict an increased risk of early NCR. Conclusion: Irregular margins of 2 – 5 cm tumors and irregular margins, arterial peritumoral enhancement, and abnormal AFP of tumors > 5 cm can be applied to predict the early response of HCC to TACE/HIFU treatment. Advances in knowledge: TACE combined with HIFU treatment may be able to significantly improve survival in patients with advanced HCC. Conventional MRI features and laboratory indicators are readily available without complex post-processing. It is feasible to predict the response of HCC after TACE/HIFU treatment based on preoperative conventional MRI features and laboratory indicators, the combination of multiple features predicts high-risk of non-complete response.