Preoperative gadoxetic acid-enhanced MRI for predicting microvascular invasion in patients with single hepatocellular carcinoma

Importance of Microvascular Invasion Risk and Tumor Size on Recurrence and Survival of Hepatocellular Carcinoma After Anatomical Resection and Non-anatomical Resection

Purpose: To establish a valid prediction model to prognose the occurrence of microvascular invasion (MVI), and to compare the efficacy of anatomic resection (AR) or non-anatomic resection (NAR) for hepatocellular carcinoma (HCC). Methods: Two hundred twenty-eight patients with HCC who underwent surgical treatment were enrolled. Their hematological indicators, MRI imaging features, and outcome data were acquired. Result: In the multivariable analysis, alpha-fetoprotein >15 ng/mL, neutrophil to lymphocyte ratio >3.8, corona enhancement, and peritumoral hypointensity on hepatobiliary phase were associated with MVI. According on these factors, the AUROC of the predictive model in the primary and validation cohorts was 0.884 (95% CI: 0.829, 0.938) and 0.899 (95% CI: 0.821, 0.967), respectively. Patients with high risk of MVI or those with low risk of MVI but tumor size >5 cm in the AR group were associated with a lower rate of recurrence and death than patients in the NAR group; however, when patients are in the state of low-risk MVI with tumor size >5 cm, there is no difference in the rate of recurrence and death between AR and NAR. Conclusion: Our predictive model for HCC with MVI is convenient and accurate. Patients with high-risk of MVI or low-risk of MVI but tumor size >5 cm executing AR is of great necessity.

Prediction of Microvascular Invasion in Hepatocellular Carcinoma With a Multi-Disciplinary Team-Like Radiomics Fusion Model on Dynamic Contrast-Enhanced Computed Tomography

Objective

To investigate microvascular invasion (MVI) of HCC through a noninvasive multi-disciplinary team (MDT)-like radiomics fusion model on dynamic contrast enhanced (DCE) computed tomography (CT).

Methods

This retrospective study included 111 patients with pathologically proven hepatocellular carcinoma, which comprised 57 MVI-positive and 54 MVI-negative patients. Target volume of interest (VOI) was delineated on four DCE CT phases. The volume of tumor core (V_tc) and seven peripheral tumor regions (V_pt, with varying distances of 2, 4, 6, 8, 10, 12, and 14 mm to tumor margin) were obtained. Radiomics features extracted from different combinations of phase(s) and VOI(s) were cross-validated by 150 classification models. The best phase and VOI (or combinations) were determined. The top predictive models were ranked and screened by cross-validation on the training/validation set. The model fusion, a procedure analogous to multidisciplinary consultation, was performed on the top-3 models to generate a final model, which was validated on an independent testing set.

Results

Image features extracted from V_tc+V_pt(12mm) in the portal venous phase (PVP) showed dominant predictive performances. The top ranked features from V_tc+V_pt(12mm) in PVP included one gray level size zone matrix (GLSZM)-based feature and four first-order based features. Model fusion outperformed a single model in MVI prediction. The weighted fusion method achieved the best predictive performance with an AUC of 0.81, accuracy of 78.3%, sensitivity of 81.8%, and specificity of 75% on the independent testing set.

Conclusion

Image features extracted from the PVP with V_tc+V_pt(12mm) are the most reliable features indicative of MVI. The MDT-like radiomics fusion model is a promising tool to generate accurate and reproducible results in MVI status prediction in HCC.

Rim-arterial enhancing primary hepatic tumors with other targetoid appearance show early recurrence after radiofrequency ablation

OBJECTIVES

To evaluate early (≤ 2 years) local tumor progression (LTP), intrahepatic distant metastasis (IDR), and extrahepatic metastasis (EM) of primary hepatic malignant tumors with arterial rim enhancement (RE) after RFA in comparison with non-RE tumors.

METHODS

Three hundred forty-nine patients who underwent RFA for primary hepatic malignant tumors between January 2009 and December 2016 were included. The patients' tumors were classified into non-RE, RE only (RO), and RE plus other targetoid appearances (REoT). Cumulative LTP, IDR, and EM rates at 1 and 2 years after RFA were calculated using the Kaplan-Meier method and compared using the log-rank test. Prognostic factors for the outcomes were assessed using a Cox proportional hazards model.

RESULTS

There were 303 non-RE, 19 RO, and 27 REoT tumors. The REoT tumors had a significantly higher rate of IDR and EM than non-RE (p = 0.04 for IDR; and p < 0.01 for EM, respectively) at 1 year after RFA. At 2 years, LTP and EM rates were significantly higher for REoT than for non-RE (p = 0.001 for LTP; and p = 0.444 for EM, respectively). The RO tumors did not have different outcomes than non-RE at 1 and 2 years after RFA. Multivariable analysis verified that REoT was a significant factor for IDR (p = 0.04) and EM (p = 0.01) at 1 year and LTP (p = 0.02) at 2 years.

CONCLUSIONS

Tumors with REoT had poor LTP, IDR, and EM within 2 years after RFA than non-RE tumors. However, tumors with RO showed similar results as non-RE tumors.

KEY POINTS

• Tumors with Rim enhancement plus other targetoid appearances (REoT) had a significantly higher rate of recurrence than non-rim enhancing (RE) tumors at 1 and 2 years after RFA. • Tumors with rim enhancement only did not have different outcomes than non-RE at 1 and 2 years after RFA.

Effect of Microvascular Invasion Risk on Early Recurrence of Hepatocellular Carcinoma After Surgery and Radiofrequency Ablation

OBJECTIVE

We compared surgical resection (SR) and radiofrequency ablation (RFA) as first-line treatment in patients with hepatocellular carcinoma (HCC) based on the risk of microvascular invasion (MVI).

BACKGROUND

The best curative treatment modality between SR and RFA in patients with HCC with MVI remains unclear.

METHODS

Data from 2 academic cancer center-based cohorts of patients with a single, small (≤3 cm) HCC who underwent SR were used to derive (n = 276) and validate (n = 101) prediction models for MVI using clinical and imaging variables. The MVI prediction model was developed using multivariable logistic regression analysis and externally validated. Early recurrence (<2 years) based on risk stratification between SR (n = 276) and RFA (n = 240) was evaluated via propensity score matching.

RESULTS

In the multivariable analysis, alpha-fetoprotein (≥15 ng/mL), protein induced by vitamin K absence-II (≥48 mAU/mL), arterial peritumoral enhancement, and hepatobiliary peritumoral hypointensity on magnetic resonance imaging were associated with MVI. Incorporating these factors, the area under the receiver operating characteristic curve of the predictive model was 0.87 (95% confidence interval: 0.82-0.92) and 0.82 (95% confidence interval: 0.74-0.90) in the derivation and validation cohorts, respectively. SR was associated with a lower rate of early recurrence than RFA based on the risk of MVI after propensity score matching (P < 0.05).

CONCLUSIONS

Our model predicted the risk of MVI in patients with a small (≤ 3 cm) HCC with high accuracy. Patients with MVI who had undergone RFA were more vulnerable to recurrence than those who had undergone SR.

Value of gadoxetic acid-enhanced MRI for microvascular invasion of small hepatocellular carcinoma: a retrospective study

Background

The objective of this study was to analyze the accuracy of gadolinium–ethoxybenzyl–diethylenetriamine penta–acetic acid enhanced magnetic resonance imaging (Gd–EOB–DTPA–MRI) for predicting microvascular invasion (MVI) in patients with small hepatocellular carcinoma (sHCC) preoperatively.

Methods

A total of 60 sHCC patients performed with preoperative Gd–EOB–DTPA–MRI in the Harbin Medical University Cancer Hospital from October 2018 to October 2019 were involved in the study. Univariate and multivariate analyses were performed by chi–square test and logistic regression analysis. The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of Gd–EOB–DTPA–MRI were performed by receiver operating characteristic (ROC) curves.

Results

Univariate analysis indicated that alanine aminotransferase (≥ 39.00U/L), poorly differentiated pathology, and imaging features including grim enhancement, capsule enhancement, arterial halo sign and hepatobiliary features (tumor highly uptake, halo sign, spicule sign and brush sign) were associated with the occurrence of MVI (p < 0.05). Multivariate analysis revealed that rim enhancement and hepatobiliary spicule sign were independent predictors of MVI (p < 0.05). The area under the ROC curve was 0.917 (95% confidence interval 0.838–0.996), and the sensitivity was 94.74%.

Conclusions

The morphologies of hepatobiliary phase imaging, especially the spicule sign, showed high accuracy in diagnosing MVI of sHCC. Rim enhancement played a significant role in diagnosing MVI of sHCC.

Preoperative identification of microvascular invasion in hepatocellular carcinoma by XGBoost and deep learning

PURPOSE

Microvascular invasion (MVI) is a valuable predictor of survival in hepatocellular carcinoma (HCC) patients. This study developed predictive models using eXtreme Gradient Boosting (XGBoost) and deep learning based on CT images to predict MVI preoperatively.

METHODS

In total, 405 patients were included. A total of 7302 radiomic features and 17 radiological features were extracted by a radiomics feature extraction package and radiologists, respectively. We developed a XGBoost model based on radiomics features, radiological features and clinical variables and a three-dimensional convolutional neural network (3D-CNN) to predict MVI status. Next, we compared the efficacy of the two models.

RESULTS

Of the 405 patients, 220 (54.3%) were MVI positive, and 185 (45.7%) were MVI negative. The areas under the receiver operating characteristic curves (AUROCs) of the Radiomics-Radiological-Clinical (RRC) Model and 3D-CNN Model in the training set were 0.952 (95% confidence interval (CI) 0.923-0.973) and 0.980 (95% CI 0.959-0.993), respectively (p = 0.14). The AUROCs of the RRC Model and 3D-CNN Model in the validation set were 0.887 (95% CI 0.797-0.947) and 0.906 (95% CI 0.821-0.960), respectively (p = 0.83). Based on the MVI status predicted by the RRC and 3D-CNN Models, the mean recurrence-free survival (RFS) was significantly better in the predicted MVI-negative group than that in the predicted MVI-positive group (RRC Model: 69.95 vs. 24.80 months, p < 0.001; 3D-CNN Model: 64.06 vs. 31.05 months, p = 0.027).

CONCLUSION

The RRC Model and 3D-CNN models showed considerable efficacy in identifying MVI preoperatively. These machine learning models may facilitate decision-making in HCC treatment but requires further validation.

Development and validation of a nomogram combining hematological and imaging features for preoperative prediction of microvascular invasion in hepatocellular carcinoma patients

Background

Microvascular invasion (MVI) is a significant hazard factor that influences the recurrence and survival of hepatocellular carcinoma (HCC) patients after undergoing hepatectomy. This study aimed to develop and validate a nomogram that combines hematological and imaging features of HCC patients to preoperatively predict MVI, and investigate the effect of wide resection margin (≥1 cm) on the prognosis of MVI-positive HCC patients.

Methods

A total of 709 HCC patients who underwent hepatectomy at the Liver Cancer Institute of Zhongshan Hospital, Fudan University between June 1, 2015 and December 30, 2016 were included in this study and divided into training (496 patients) and validation cohort (213 patients). Least absolute shrinkage and selection operator (Lasso) regression and multivariable logistic regression were used for variables’ selection and development of the predictive model. The model was presented as a nomogram, and its performance was assessed in terms of discrimination, calibration and clinical usefulness.

Results

Independent prognostic factors such as alkaline phosphatase (ALP, >125 U/L), alpha-fetoprotein (AFP, within 20–400 or >400 ng/mL), protein induced by vitamin K absence-II (PVIKA-II, within 40–400 or >400 mAU/mL), tumor number, diameter, pseudo-capsule, tumor growth pattern and intratumor hemorrhage were incorporated in the nomogram. The model showed good discrimination and calibration, with a concordance index (0.82, 95% CI, 0.782–0.857) in the training cohort and C-index (0.80, 95% CI, 0.772–0.837) in the validation cohort. Decision curve analysis (DCA) also showed that this model is clinically useful. Moreover, HCC patients with wide resection margin had a significantly lower 3-year recurrence rate than those with narrower resection margin (0.5–1 cm).

Conclusions

This study presents an optimal model for preoperative prediction of MVI and shows that wide resection margin for MVI-positive HCC patients has a better prognosis. This model can help surgeons choose the best treatment options for HCC patients before and after the operation.

Impact of preoperative TACE on incidences of microvascular invasion and long-term post-hepatectomy survival in hepatocellular carcinoma patients: A propensity score matching analysis

BACKGROUND

To study the influence of preoperative transcatheter arterial chemoembolization (TACE) on the incidence of microvascular invasion (MVI) and long-term survival outcomes in hepatocellular carcinoma (HCC) patients.

METHODS

Between January 1, 2010 and December 1, 2014, consecutive HCC patients who underwent curative liver resection were enrolled in this study. Univariable and multivariable regression analyses were used to identify independent predictive factors of MVI. Propensity score matching (PSM) was used to compare the incidences of MVI and prognosis between patients who did and did not receive preoperative TACE. Factors associated with Disease-Free Survival (DFS) and Overall survival (OS) were identified using Cox regression analyses.

RESULTS

Of 1624 patients, 590 received preoperative TACE. The incidence of MVI was significantly lower in patients with preoperative TACE than those without preoperative TACE (39.15% vs. 45.36%, p = 0.015). After PSM, the incidences of MVI were similar in the two groups (38.85% vs. 41.10%, p = 0.473). Multivariable regression analysis revealed preoperative TACE to have no impact on the incidence of MVI. Before PSM, survival of patients with preoperative TACE was significantly worse than those without preoperative TACE (p = 0.032 for DFS and p = 0.027 for OS). After PSM, the difference became insignificant (p = 0.465 for DFS and p = 0.307 for OS). After adjustment for other prognostic variables in the propensity-matched cohort, preoperative TACE was still found not to be associated with DFS and OS after HCC resection. Both before and after PSM, the prognosis of patients was not significantly different between the two groups for BCLC stages 0, A, and B.

CONCLUSIONS

Preoperative TACE did not influence the incidence of MVI and prognosis of patients with HCC who underwent 'curative' liver resection.

Comparison of MRI and CT for the Prediction of Microvascular Invasion in Solitary Hepatocellular Carcinoma Based on a Non-Radiomics and Radiomics Method: Which Imaging Modality Is Better?

BACKGROUND

Computed tomography (CT) and magnetic resonance imaging (MRI) are both capable of predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC). However, which modality is better is unknown.

PURPOSE

To intraindividually compare CT and MRI for predicting MVI in solitary HCC and investigate the added value of radiomics analyses.

STUDY TYPE

Retrospective.

SUBJECTS

Included were 402 consecutive patients with HCC (training set:validation set = 300:102).

FIELD STRENGTH/SEQUENCE

T2-weighted, diffusion-weighted, and contrast-enhanced T1-weighted imaging MRI at 3.0T and contrast-enhanced CT.

ASSESSMENT

CT- and MR-based radiomics signatures (RS) were constructed using the least absolute shrinkage and selection operator regression. CT- and MR-based radiologic (R) and radiologic-radiomics (RR) models were developed by univariate and multivariate logistic regression. The performance of the RS/models was compared between two modalities. To investigate the added value of RS, the performance of the R models was compared with the RR models in HCC of all sizes and 2-5 cm in size.

STATISTICAL TESTS

Model performance was quantified by the area under the receiver operating characteristic curve (AUC) and compared using the Delong test.

RESULTS

Histopathologic MVI was identified in 161 patients (training set:validation set = 130:31). MRI-based RS/models tended to have a marginally higher AUC than CT-based RS/models (AUCs of CT vs. MRI, P: RS, 0.801 vs. 0.804, 0.96; R model, 0.809 vs. 0.832, 0.09; RR model, 0.835 vs. 0.872, 0.54). The improvement of RR models over R models in all sizes was not significant (P = 0.21 at CT and 0.09 at MRI), whereas the improvement in 2-5 cm was significant at MRI (P < 0.05) but not at CT (P = 0.16).

DATA CONCLUSION

CT and MRI had a comparable predictive performance for MVI in solitary HCC. The RS of MRI only had significant added value for predicting MVI in HCC of 2-5 cm.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Deep Learning With 3D Convolutional Neural Network for Noninvasive Prediction of Microvascular Invasion in Hepatocellular Carcinoma

BACKGROUND

Microvascular invasion (MVI) is a critical prognostic factor of hepatocellular carcinoma (HCC). However, it could only be obtained by postoperative histological examination.

PURPOSE

To develop an end-to-end deep-learning models based on MRI images for preoperative prediction of MVI in HCC patients who underwent surgical resection.

STUDY TYPE

Retrospective.

POPULATION

Two hundred and thirty-seven patients with histologically confirmed HCC.

FIELD STRENGTH

1.5 T and 3.0 T.

SEQUENCE

Axial T₂ -weighted (T₂ -w) with turbo spin echo sequence, T₂ -Spectral Presaturation with Inversion Recovery (T₂ -SPIR), and dynamic contrast-enhanced (DCE) imaging with fat suppressed enhanced T₁ high-resolution isotropic volume examination.

ASSESSMENT

The patients were randomly divided into training (N = 158) and validation (N = 79) sets. Data augmentation by random rotation was performed on the training set and the sample size increased to 1940 for each MR sequence. A three-dimensional convolutional neural network (3D CNN) was used to develop four deep-learning models, including three single-layer models based on single-sequence, and fusion model combining three sequences. MVI status was obtained from the postoperative pathology reports.

STATISTICAL TESTS

The dice similarity coefficient (DSC) and Hausdorff distance (HD) were applied to assess the similarity and reproducibility between the manual segmentations of tumor from two radiologists. Receiver operating characteristic curve analysis was used to evaluate model performance. MVI was identified in 92 (38.8%) patients. Good reproducibility with interobserver DSCs of 0.90, 0.89, and 0.89 and HDs of 4.09, 3.67, and 3.60 was observed for PVP, T₂ WI, and T₂ -SPIR, respectively. The fusion model achieved an area under the curve (AUC) of 0.81, sensitivity of 69%, and specificity of 79% in the training set and 0.72, sensitivity of 55%, and specificity of 81% in the validation set.

DATA CONCLUSION

3D CNN model may serve as a noninvasive tool to predict MVI in HCC, whereas its accuracy needs to be enhanced with larger cohort.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Imaging Predictors of Survival in Patients with Single Small Hepatocellular Carcinoma Treated with Transarterial Chemoembolization

OBJECTIVE

Clinical outcomes of patients who undergo transarterial chemoembolization (TACE) for single small hepatocellular carcinoma (HCC) are not consistent, and may differ based on certain imaging findings. This retrospective study was aimed at determining the efficacy of pre-TACE CT or MR imaging findings in predicting survival outcomes in patients with small HCC upon being treated with TACE. Besides, the study proposed to build a risk prediction model for these patients.

MATERIALS AND METHODS

Altogether, 750 patients with functionally good hepatic reserve who received TACE as the first-line treatment for single small HCC between 2004 and 2014 were included in the study. These patients were randomly assigned into training (n = 525) and validation (n = 225) sets.

RESULTS

According to the results of a multivariable Cox analysis, three pre-TACE imaging findings (tumor margin, tumor location, enhancement pattern) and two clinical factors (age, serum albumin level) were selected and scored to create predictive models for overall, local tumor progression (LTP)-free, and progression-free survival in the training set. The median overall survival time in the validation set were 137.5 months, 76.1 months, and 44.0 months for low-, intermediate-, and high-risk groups, respectively (p < 0.001). Time-dependent receiver operating characteristic curves of the predictive models for overall, LTP-free, and progression-free survival applied to the validation cohort showed acceptable areas under the curve values (0.734, 0.802, and 0.775 for overall survival; 0.738, 0.789, and 0.791 for LTP-free survival; and 0.671, 0.733, and 0.694 for progression-free survival at 3, 5, and 10 years, respectively).

CONCLUSION

Pre-TACE CT or MR imaging findings could predict survival outcomes in patients with small HCC upon treatment with TACE. Our predictive models including three imaging predictors could be helpful in prognostication, identification, and selection of suitable candidates for TACE in patients with single small HCC.

Multi-scale and multi-parametric radiomics of gadoxetate disodium-enhanced MRI predicts microvascular invasion and outcome in patients with solitary hepatocellular carcinoma ≤ 5 cm

Objectives

To develop radiomics-based nomograms for preoperative microvascular invasion (MVI) and recurrence-free survival (RFS) prediction in patients with solitary hepatocellular carcinoma (HCC) ≤ 5 cm.

Methods

Between March 2012 and September 2019, 356 patients with pathologically confirmed solitary HCC ≤ 5 cm who underwent preoperative gadoxetate disodium–enhanced MRI were retrospectively enrolled. MVI was graded as M0, M1, or M2 according to the number and distribution of invaded vessels. Radiomics features were extracted from DWI, arterial, portal venous, and hepatobiliary phase images in regions of the entire tumor, peritumoral area ≤ 10 mm, and randomly selected liver tissue. Multivariate analysis identified the independent predictors for MVI and RFS, with nomogram visualized the ultimately predictive models.

Results

Elevated alpha-fetoprotein, total bilirubin and radiomics values, peritumoral enhancement, and incomplete or absent capsule enhancement were independent risk factors for MVI. The AUCs of MVI nomogram reached 0.920 (95% CI: 0.861–0.979) using random forest and 0.879 (95% CI: 0.820–0.938) using logistic regression analysis in validation cohort (n = 106). With the 5-year RFS rate of 68.4%, the median RFS of MVI-positive (M2 and M1) and MVI-negative (M0) patients were 30.5 (11.9 and 40.9) and > 96.9 months (p < 0.001), respectively. Age, histologic MVI, alkaline phosphatase, and alanine aminotransferase independently predicted recurrence, yielding AUC of 0.654 (95% CI: 0.538–0.769, n = 99) in RFS validation cohort. Instead of histologic MVI, the preoperatively predicted MVI by MVI nomogram using random forest achieved comparable accuracy in MVI stratification and RFS prediction.

Conclusions

Preoperative radiomics-based nomogram using random forest is a potential biomarker of MVI and RFS prediction for solitary HCC ≤ 5 cm.

Key Points

• The radiomics score was the predominant independent predictor of MVI which was the primary independent risk factor for postoperative recurrence.

• The radiomics-based nomogram using either random forest or logistic regression analysis has obtained the best preoperative prediction of MVI in HCC patients so far.

• As an excellent substitute for the invasive histologic MVI, the preoperatively predicted MVI by MVI nomogram using random forest (MVI-RF) achieved comparable accuracy in MVI stratification and outcome, reinforcing the radiologic understanding of HCC angioinvasion and progression.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00330-020-07601-2.

Radiomics Analysis of MR Imaging with Gd-EOB-DTPA for Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma: Investigation and Comparison of Different Hepatobiliary Phase Delay Times

Purpose

To investigate whether the radiomics analysis of MR imaging in the hepatobiliary phase (HBP) can be used to predict microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC).

Method

A total of 130 patients with HCC, including 80 MVI-positive patients and 50 MVI-negative patients, who underwent MR imaging with Gd-EOB-DTPA were enrolled. Least absolute shrinkage and selection operator (LASSO) regression was applied to select radiomics parameters derived from MR images obtained in the HBP 5 min, 10 min, and 15 min images. The selected features at each phase were adopted into support vector machine (SVM) classifiers to establish models. Multiple comparisons of the AUCs at each phase were performed by the Delong test. The decision curve analysis (DCA) was used to analyze the classification of MVI-positive and MVI-negative patients.

Results

The most predictive features between MVI-positive and MVI-negative patients included 9, 8, and 14 radiomics parameters on HBP 5 min, 10 min, and 15 min images, respectively. A model incorporating the selected features produced an AUC of 0.685, 0.718, and 0.795 on HBP 5 min, 10 min, and 15 min images, respectively. The predictive model for HBP 5 min, 10 min and 15 min showed no significant difference by the Delong test. DCA indicated that the predictive model for HBP 15 min outperformed the models for HBP 5 min and 10 min.

Conclusions

Radiomics parameters in the HBP can be used to predict MVI, with the HBP 15 min model having the best differential diagnosis ability.

Gadoxetic acid-enhanced MRI of macrotrabecular-massive hepatocellular carcinoma and its prognostic implications

BACKGROUND & AIMS

Despite the clinical and genetic significance of macrotrabecular-massive hepatocellular carcinoma (MTM-HCC), its characteristics on imaging have not been described. This study aimed to characterise MTM-HCC on gadoxetic acid-enhanced MRI and to evaluate the diagnostic accuracy and prognostic value of these imaging characteristics.

METHODS

We enrolled 3 independent cohorts from 2 tertiary care centres. The 3 cohorts consisted of a total of 476 patients who underwent gadoxetic acid-enhanced MRI and surgical resection for treatment-naïve single HCCs. Independent review of histopathology and MRI by 2 reviewers was performed for each cohort, and inter-reader agreement was evaluated. Based on the result of MRI review in the training cohort (cohort 1), we developed 2 diagnostic criteria for MTM-HCC and evaluated their prognostic significance. The diagnostic performance and prognostic significance were validated in 2 validation cohorts (cohorts 2 and 3).

RESULTS

We developed 2 diagnostic MRI criteria (MRIC) for MTM-HCC: MRIC-1, ≥20% arterial phase hypovascular component; MRIC-2, ≥50% hypovascular component and 2 or more ancillary findings (intratumoural artery, arterial phase peritumoural enhancement, and non-smooth tumour margin). MRIC-1 showed high sensitivity and negative predictive value (88% and 95% in the training cohort, and 88% and 97% in the pooled validation cohorts, respectively), whereas MRIC-2 demonstrated moderate sensitivity and high specificity (47% and 94% in the training cohort, and 46% and 96% in the pooled validation cohorts, respectively). MRIC-2 was an independent poor prognostic factor for overall survival in both training and pooled validation cohorts.

CONCLUSIONS

Using gadoxetic acid-enhanced MRI findings, including an arterial phase hypovascular component, we could stratify the probability of MTM-HCC and non-invasively obtain prognostic information.

LAY SUMMARY

Macrotrabecular-massive hepatocellular carcinoma (MTM-HCC) is a histopathologic subtype of HCC characterised by aggressive biological behaviour and poor prognosis. We developed imaging criteria based on liver MRI that could be used for the non-invasive diagnosis of MTM-HCC. HCCs showing imaging findings of MTM-HCC were associated with poor outcomes after hepatic resection.

Potential application of dynamic contrast enhanced ultrasound in predicting microvascular invasion of hepatocellular carcinoma

OBJECTIVE

To investigate the clinical value of dynamic contrast enhanced ultrasound (D-CEUS) in predicting the microvascular invasion (MVI) of hepatocellular carcinoma (HCC).

PATIENTS AND METHODS

In this retrospective study, 16 patients with surgery and histopathologically proved HCC lesions were included. Patients were classified according to the presence of MVI: MVI positive group (n = 6) and MVI negative group (n = 10). Contrast enhanced ultrasound (CEUS) examinations were performed within a week before surgery. Dynamic analysis was performed by VueBox® software (Bracco, Italy). Three regions of interests (ROIs) were set in the center of HCC lesions, at the margin of HCC lesions and in the surrounding liver parenchyma accordingly. Time intensity curves (TICs) were generated and quantitative perfusion parameters including WiR (wash-in rate), WoR (wash-out rate), WiAUC (wash-in area under the curve), WoAUC (wash-out area under the curve) and WiPi (wash-in perfusion index) were obtained and analyzed.

RESULTS

All of HCC lesions showed arterial hyperenhancement (100 %) and at the late phase as hypoenhancement (75%) in CEUS. Among all CEUS quantitative parameters, the WiAUC and WoAUC were higher in MVI positive group than in MVI negative group in the center HCC lesions (P < 0.05), WiAUC, WoAUC and WiPI were higher in MVI positive group than in MVI negative group at the margin of HCC lesions. WiR and WoR were significant higher in MVI positive group.

CONCLUSIONS

D-CEUS with quantitative perfusion analysis has potential clinical value in predicting the existence of MVI in HCC lesions.

MRI Findings of Liver Parenchyma Peripheral to Colorectal Liver Metastasis: A Potential Predictor of Long-term Prognosis

Background Gadoxetic acid (Gd-EOB-DTPA)-enhanced MRI is superior to CT in the detection of colorectal liver metastases (CRLMs) smaller than 10 mm. However, few studies have used MRI findings to predict patients' long-term prognosis. Purpose To investigate the relationship between Gd-EOB-DTPA-enhanced MRI findings in the liver parenchyma peripheral to CRLM and both pathologic vessel invasion and long-term prognosis. Materials and Methods This retrospective study included patients who underwent Gd-EOB-DTPA-enhanced MRI before curative surgery for CRLM, without neoadjuvant chemotherapy, between July 2008 and June 2015. Early enhancement, reduced Gd-EOB-DTPA uptake, and bile duct dilatation peripheral to the CRLM at MRI were evaluated by three abdominal radiologists. All tumor specimens were reevaluated for the presence or absence of portal vein, hepatic vein, and bile duct invasion. Predictors of recurrence-free survival (RFS) and overall survival (OS) after surgery were identified with Cox proportional hazard model with the Bayesian information criterion. Previously reported prognosticators were selected for multivariable analyses. The median follow-up period was 60 months (range, 9-127 months). Results Overall, 106 patients (mean age, 65 years ± 12 [standard deviation]; 68 men) with 148 CRLMs were evaluated. Bile duct dilatation peripheral to the tumor was associated with pathologic portal vein invasion (sensitivity, 12 of 50 [24%]; specificity, 89 of 98 [91%]; P = .02), bile duct invasion (sensitivity, eight of 19 [42%]; specificity, 116 of 129 [90%]; P = .001), poor RFS (P = .03; hazard ratio [HR] = 2.4 [95% confidence interval {CI}: 1.3, 4.2]), and poor OS (P = .01; HR = 2.4 [95% CI: 1.2, 4.9]). For RFS and OS, early enhancement and reduced Gd-EOB-DTPA uptake peripheral to the CRLM were eliminated by means of variable selection in the multivariable analysis, but the combination of these findings with bile duct dilatation provided a predictor of poor OS (P = .001; HR = 3.3 [95% CI: 1.6, 6.8]). Conclusion MRI signal intensity changes peripheral to the colorectal liver metastasis were predictors of long-term prognosis after curative surgery without neoadjuvant chemotherapy. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Bashir in this issue.

Effect of surgical margin on recurrence based on preoperative circulating tumor cell status in hepatocellular carcinoma

BACKGROUND

High rates of recurrence after resection severely worsen hepatocellular carcinoma (HCC) prognosis. This study aims to explore whether circulating tumor cell (CTC) is helpful in determine the appropriate liver resection margins for HCC patients.

METHODS

HCC patients who underwent liver resection were enrolled into training (n=117) or validation (n=192) cohorts, then classified as CTC-positive (CTC≥1) or CTC-negative (CTC=0). A standardized pathologic sampling method was used in the training cohort to quantify microvascular invasion (mVI) and the farthest mVI from the tumor (FMT).

FINDINGS

CTC number positively correlated with mVI counts (r=0.655, P<0.001) and FMT (r=0.495, P<0.001). The CTC-positive group had higher mVI counts (P=0.032) and greater FMT P=0.008) than the CTC-negative group. In the CTC-positive group, surgical margins of >1 cm independently protected against early recurrence (training cohort, P=0.004; validation cohort, P=0.001) with lower early recurrence rates (training cohort, 20.0% vs. 65.1%, P=0.005; validation cohort, 36.4% vs. 65.1%, P=0.003) compared to surgical margins of ≤1 cm. No differences in postoperative liver function were observed between patients with margins >1 cm vs. ≤1 cm. Surgical margin size minimally impacted early postoperative HCC recurrence in CTC-negative patients when using 0.5 cm or 1 cm as the threshold.

INTERPRETATIONS

Preoperative CTC status predicts mVI severity in HCC patients and is a potential factor for determining optimal surgical margin size to ensure disease eradication and conserve liver function. A surgical margin of >1 cm should be achieved for patients with positive CTC.

FUNDING

A full list of funding bodies that contributed to this study can be found in the Acknowledgement section.

The Long-To-Short-Axis Ratio and Multifocality are Associated With TP53 Mutation Status in Surgically Resected Hepatocellular Carcinomas

RATIONALE AND OBJECTIVES

In hepatocellular carcinoma (HCC), the tumor protein 53 (TP53) gene is frequently mutated and the mutations have been associated with poor prognosis. We aim to retrospectively identify the relationship between TP53 mutation status, tumor size (long-axis diameter, short-axis diameter, and long-to-short-axis ratio [L/S ratio]), margin and multifocality in surgically resected HCC.

MATERIALS AND METHODS

The image features and TP53 mutation data from 78 patients generated with National Cancer Institute's multi-institutional The Cancer Genome Atlas (TCGA)/The Cancer Imaging Archive databases were assessed. Binary logistic regression analyses were performed to identify independent factors of harboring TP53 mutation status. The final model was selected by using the backward elimination method.

RESULTS

TP53 mutations were found in 19 (31.5%) of 78 patients. TP53 mutation rates were significantly higher (a) in L/S ratio ≤ 1.2 14 of 41 [34.1%]) lesions than in L/S ratio >1.2 lesions (five of 37 [13.5%]) (p = 0.034) and (b) in nonmultifocality (17 of 54[31.5%]) than in multifocality lesions (two of 24 [8.3%]) (p = 0.028). On univariate logistic regression analysis, L/S ratio (≤1.20 vs >1.20. odds ratio [OR]: 3.319; p = 0.040; 95% confidence interval [CI]: 1.059-10.401 Area Under Curve (AUC) = 0.634) and multifocality (no vs yes OR: 5.054; p = 0.041; 95% CI: 1.065-23.986 AUC = 0.640) were associated with TP53 mutations. On multivariate logistic regression analysis, L/S ratio (≤1.20 vs >1.20 OR: 3.430; p = 0.040; 95% CI: 1.058-11.118) and multifocality (no vs yes OR: 5.232; p = 0.041; 95% CI: 1.072-25.526) were associated with TP53 mutations. The area under the receiver operating characteristic curve for predicting TP53 mutation status was 0.714 (95% CI: 0.590-0.837).

CONCLUSION

Our study focusing on identifying imaging aspects related to TP53 positive HCC. L/S ratio of HCC in combination with multifocality might be used to prognosticate TP53 mutation status. And the discriminatory power for this prediction model was good.

Interobserver Variability and Diagnostic Performance of Gadoxetic Acid-enhanced MRI for Predicting Microvascular Invasion in Hepatocellular Carcinoma

Background Accurate identification of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) before treatment is critical for selecting a proper treatment strategy. Purpose To evaluate the interobserver agreement and the diagnostic performance of the MRI assessment of MVI in HCC according to the level of radiologist experience. Materials and Methods This retrospective study included 100 patients with surgically confirmed HCCs smaller than 5 cm who underwent gadoxetic acid-enhanced MRI between 2013 and 2016. Eight postfellowship radiologists (four with 7-13 years of experience [more experienced] and four with 3-6 years of experience [less experienced]) evaluated four imaging features (nonsmooth tumor margin, irregular rim-like enhancement in the arterial phase, peritumoral arterial phase hyperenhancement, peritumoral hepatobiliary phase hypointensity) and assigned the possibility of MVI. Interobserver agreement was determined by using Fleiss κ statistics according to reviewer experience and tumor size (≤3 cm vs >3 cm). With reference standards of histopathologic specimens, the diagnostic performance in the identification of MVI was assessed by using receiver operating characteristic curve analysis. Results In 100 patients (mean age, 58 years ± 10 [standard deviation]; 70 men) with 100 HCCs (mean size, 2.8 cm ± 0.9), 39 (39%) HCCs had MVI. The overall interobserver agreement was fair to moderate for the imaging features and their combinations (κ = 0.38-0.47) and MVI probability (κ = 0.41; 95% confidence interval: 0.33, 0.45). More experienced reviewers demonstrated higher agreement in MVI probability than less experienced reviewers (κ = 0.55 vs 0.36, respectively; P = .002). Diagnostic performance of each reviewer was modest for MVI prediction (area under the receiver operating characteristic curve [AUC] range, 0.60-0.74). The AUCs for the diagnosis of MVI were lower for HCCs larger than 3 cm (range, 0.55-0.69) than for those less than or equal to 3 cm (range, 0.59-0.75). Conclusion Considerable interobserver variability exists in the assessment of microvascular invasion in hepatocellular carcinoma using MRI, even for more experienced radiologists. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Tang in this issue.

Radiomics Analysis Based on Multiparametric MRI for Predicting Early Recurrence in Hepatocellular Carcinoma After Partial Hepatectomy

BACKGROUND

Preoperative prediction of early recurrence (ER) of hepatocellular carcinoma (HCC) plays a critical role in individualized risk stratification and further treatment guidance.

PURPOSE

To investigate the role of radiomics analysis based on multiparametric MRI (mpMRI) for predicting ER in HCC after partial hepatectomy.

STUDY TYPE

Retrospective.

POPULATION

In all, 113 HCC patients (ER, n = 58 vs. non-ER, n = 55), divided into training (n = 78) and validation (n = 35) cohorts.

FIELD STRENGTH/SEQUENCE

1.5T or 3.0T, gradient-recalled-echo in-phase T₁ -weighted imaging (I-T₁ WI) and opposed-phase T₁ WI (O-T₁ WI), fast spin-echo T₂ -weighted imaging (T₂ WI), spin-echo planar diffusion-weighted imaging (DWI), and gradient-recalled-echo contrast-enhanced MRI (CE-MRI).

ASSESSMENT

In all, 1146 radiomics features were extracted from each image sequence, and radiomics models based on each sequence and their combination were established via multivariate logistic regression analysis. The clinicopathologic-radiologic (CPR) model and the combined model integrating the radiomics score with the CPR risk factors were constructed. A nomogram based on the combined model was established.

STATISTICAL TESTS

Receiver operating characteristic (ROC) curve analysis was used to evaluate the discriminative performance of each model. The potential clinical usefulness was evaluated by decision curve analysis (DCA).

RESULTS

The radiomics model based on I-T₁ WI, O-T₁ WI, T₂ WI, and CE-MRI sequences presented the best performance among all radiomics models with an area under the ROC curve (AUC) of 0.771 (95% confidence interval (CI): 0.598-0.894) in the validation cohort. The combined nomogram (AUC: 0.873; 95% CI: 0.756-0.989) outperformed the radiomics model and the CPR model (AUC: 0.742; 95% CI: 0.577-0.907). DCA demonstrated that the combined nomogram was clinically useful.

DATA CONCLUSION

The mpMRI-based radiomics analysis has potential to predict ER of HCC patients after hepatectomy, which could enhance risk stratification and provide support for individualized treatment planning.

EVIDENCE LEVEL

4.

TECHNICAL EFFICACY

Stage 4.

Hepatobiliary phase of gadoxetic acid-enhanced MRI in patients with HCC: prognostic features before resection, ablation, or TACE

OBJECTIVES

Patients with hepatocellular carcinoma (HCC) receiving different treatments might have specific prognostic factors that can be captured in the hepatobiliary phase (HBP) of gadoxetic acid-enhanced magnetic resonance imaging (GA-MRI). We aimed to identify the clinical findings and HBP features with prognostic value in patients with HCC.

METHODS

In this retrospective, single-institution study, we included patients with Barcelona Clinic Liver Cancer very early/early stage HCC who underwent GA-MRI before treatment. After performing propensity score matching, 183 patients received the following treatments: resection, radiofrequency ablation (RFA), and transarterial chemoembolization (TACE) (n = 61 for each). Cox regression models were used to identify clinical factors and HBP features associated with disease-free survival (DFS) and overall survival (OS).

RESULTS

In the resection group, large tumor size was associated with poor DFS (hazard ratio [HR] 4.159 per centimeter; 95% confidence interval [CI], 1.669-10.365) and poor OS (HR 8.498 per centimeter; 95% CI, 1.072-67.338). In the RFA group, satellite nodules on HBP images were associated with poor DFS (HR 5.037; 95% CI, 1.061-23.903) and poor OS (HR 9.398; 95% CI, 1.480-59.668). Peritumoral hypointensity on HBP images was also associated with poor OS (HR 13.062; 95% CI, 1.627-104.840). In addition, serum albumin levels and the prothrombin time-international normalized ratio were associated with DFS and/or OS. Finally, in the TACE group, no variables were associated with DFS/OS.

CONCLUSIONS

Different HBP features and clinical factors were associated with DFS/OS among patients with HCC receiving different treatments.

KEY POINTS

• In patients who underwent resection for HCC, a large tumor size on HBP images was associated with poor disease-free survival and overall survival. • In the RFA group, satellite nodules and peritumoral hypointensity on HBP images, along with decreased serum albumin levels and PT-INR, were associated with poor disease-free survival and/or overall survival. • In the TACE group, no clinical or HBP imaging features were associated with disease-free survival or overall survival.

Radiomic Feature-Based Predictive Model for Microvascular Invasion in Patients With Hepatocellular Carcinoma

Objective

This study aimed to build and evaluate a radiomics feature-based model for the preoperative prediction of microvascular invasion (MVI) in patients with hepatocellular carcinoma.

Methods

A total of 145 patients were retrospectively included in the study pool, and the patients were divided randomly into two independent cohorts with a ratio of 7:3 (training cohort: n = 101, validation cohort: n = 44). For a pilot study of this predictive model another 18 patients were recruited into this study. A total of 1,231 computed tomography (CT) image features of the liver parenchyma without tumors were extracted from portal-phase CT images. A least absolute shrinkage and selection operator (LASSO) logistic regression was applied to build a radiomics score (Rad-score) model. Afterwards, a nomogram, including Rad-score as well as other clinicopathological risk factors, was established with a multivariate logistic regression model. The discrimination efficacy, calibration efficacy, and clinical utility value of the nomogram were evaluated.

Results

The Rad-score scoring model could predict MVI with the area under the curve (AUC) of 0.637 (95% CI, 0.516–0.758) in the training cohort as well as of 0.583 (95% CI, 0.395–0.770) in the validation cohort; however, the aforementioned discriminative approach could not completely outperform those existing predictors (alpha fetoprotein, neutrophilic granulocyte, and preoperative hemoglobin). The individual predictive nomogram which included the Rad-score, alpha fetoprotein, neutrophilic granulocyte, and preoperative hemoglobin showed a better discrimination efficacy with AUC of 0.865 (95% CI, 0.786–0.944), which was higher than the conventional methods’ AUCs (nomogram vs Rad-score, alpha fetoprotein, neutrophilic granulocyte, and preoperative hemoglobin at P < 0.001, P = 0.025, P < 0.001, and P = 0.001, respectively). When applied to the validation cohort, the nomogram discrimination efficacy was still outbalanced those above mentioned three remaining methods (AUC: 0.705; 95% CI, 0.537–0.874). The calibration curves of this proposed method showed a satisfying consistency in both cohorts. A prospective pilot analysis showed that the nomogram could predict MVI with an AUC of 0.844 (95% CI, 0.628–1.000).

Conclusions

The radiomics feature-based predictive model improved the preoperative prediction of MVI in HCC patients significantly. It could be a potentially valuable clinical utility.

Can LI-RADS imaging features at gadoxetic acid-enhanced MRI predict aggressive features on pathology of single hepatocellular carcinoma?

PURPOSE

To investigate whether Liver Imaging Reporting and Data System (LI-RADS) imaging features at preoperative gadoxetic acid-enhanced MRI can predict microvascular invasion (MVI) and histologic grade of hepatocellular carcinoma (HCC) and to evaluate their associations with recurrence after curative resection of single HCC.

MATERIALS AND METHODS

From July 2015 to September 2018, 111 consecutive patients with pathologically confirmed HCC who underwent gadoxetic acid-enhanced MRI within 1 month before surgery were included in this retrospective study. Significant MRI findings and clinical parameters for predicting MVI, high-grade HCCs and postoperative recurrence were identified by logistic regression model and Cox proportional hazards model.

RESULTS

Twenty-six of 111 (23.4 %) patients had MVI and 36 of 111 (32.4 %) patients had high-grade HCCs, whereas 44 of 95 (46.3 %) patients experienced recurrence. Tumor size > 5 cm (OR = 9.852; p < 0.001) and absence of nodule-in-nodule architecture (OR = 8.302; p = 0.001) were independent predictors of MVI. Enhancing capsule (OR = 4.396; p = 0.004) and corona enhancement (OR = 3.765; p = 0.021) were independent predictors of high-grade HCCs. Blood products in mass (HR = 2.275; p = 0.009), corona enhancement (HR = 4.332; p < 0.001), and serum AFP level > 400 ng/mL (HR = 2.071; p = 0.023) were independent predictors of recurrence.

CONCLUSION

LI-RADS imaging features can be used as potential biomarkers for predicting aggressive pathologic features and recurrence of HCC. The identification of prognostic LI-RADS imaging features may facilitate the selection of surgical candidates and optimize the management of HCC patients.

Computational quantitative measures of Gd-EOB-DTPA enhanced MRI hepatobiliary phase images can predict microvascular invasion of small HCC

PURPOSE

This study was designed to preoperatively predict microvascular invasion (MVI) of solitary small hepatocellular carcinoma (sHCC) by quantitative analysis of Gd-EOB-DTPA enhanced hepatobiliary phase (HBP) magnetic resonance imaging (MRI).

METHOD

Sixty-one patients, 19 with and 42 without histologically confirmed MVI following hepatic resection for solitary sHCC (≤ 3 cm), were preoperatively examined with Gd-EOB-DTPA-enhanced MRI. The regions of interest (ROIs) of the hepatic lesions were manually delineated on the maximum cross-sectional area in the HBP images and used to calculate the lesion boundary index (LBI) and marginal gray changes (MGC). Histogram analysis was performed to measure standard deviations (STD) and coefficients of variation (CV). Correlations between quantitative parameters and MVI were evaluated and differences between MVI positive and negative groups were assessed.

RESULTS

The average LBI (0.85 ± 0.07) and MGC (0.48 ± 0.27) values of the negative group were significantly higher (p < 0.05) than the corresponding LBI (0.72 ± 0.07) and MGC (0.28 ± 0.18) values of the positive group. STDs and CVs in the negative group were significantly smaller (p < 0.05) than those of the positive group. Receiver operating characteristic (ROC) analysis revealed that LBI had the best predictive value with an AUC, sensitivity, and specificity of 0.91, 87 %, and 80 %, respectively.

CONCLUSIONS

Quantitative analysis of HBP images is useful for predicting MVI and beneficial to clinicians in making decisions before treatment.

A 2020 update on liver transplant for hepatocellular carcinoma

INTRODUCTION

Hepatocellular carcinoma is the most frequent liver tumor and is associated with chronic liver disease in 90% of cases. In selected cases, liver transplantation represents an effective therapy with excellent overall survival.

AREA COVERED

Since the introduction of Milan criteria in 1996, numerous alternative selection systems to LT for HCC patients have been proposed. Debate remains about how best to select HCC patients for transplant and how to prioritize them on the waiting list.

EXPERT OPINION

The selection of the best scoring system to propose in the context of LT for HCC is far to be identified. In this review, we analyze and categorize the various selection systems, assessing their roles in the different decisional phases.

Preoperative prediction of microvascular invasion in non-metastatic hepatocellular carcinoma based on nomogram analysis

Purpose

The presence of microvascular invasion (MVI) is an unfavorable prognostic factor for hepatocellular carcinoma (HCC). This study aimed to construct a nomogram-based preoperative prediction model of MVI, thereby assisting to preoperatively select proper surgical procedures.

Methods

A total of 714 non-metastatic HCC patients undergoing radical hepatectomy were retrospectively selected from Zhongshan Hospital between 2010 and 2018, followed by random assignment into training (N = 520) and validation cohorts (N = 194). Nomogram-based prediction model for MVI risk was constructed by incorporating independent risk factors of MVI presence identified from multivariate backward logistic regression analysis in the training cohort. The performance of nomogram was evaluated by calibration curve and ROC curve. Finally, decision curve analysis (DCA) was used to determine the clinical utility of the nomogram.

Results

In total, 503 (70.4%) patients presented MVI. Multivariate analysis in the training cohort revealed that age (OR: 0.98), alpha-fetoprotein (≥400 ng/mL) (OR: 2.34), tumor size (>5 cm) (OR: 3.15), cirrhosis (OR: 2.03) and γ-glutamyl transpeptidase (OR: 1.61) were significantly associated with MVI presence. The incorporation of five risk factors into a nomogram-based preoperative estimation of MVI risk demonstrated satisfactory discriminative capacity, with C-index of 0.702 and 0.690 in training and validation cohorts, respectively. Calibration curve showed good agreement between actual and predicted MVI risks. Finally, DCA revealed the clinical utility of the nomogram.

Conclusion

The nomogram showed a satisfactory discriminative capacity of MVI risk in HCC patients, and could be used to preoperatively estimate MVI risk, thereby establishing more rational therapeutic strategies.

Preoperative Prediction for Early Recurrence Can Be as Accurate as Postoperative Assessment in Single Hepatocellular Carcinoma Patients

Objective

To evaluate the performance of predicting early recurrence using preoperative factors only in comparison with using both pre-/postoperative factors.

Materials and Methods

We retrospectively reviewed 549 patients who had undergone curative resection for single hepatcellular carcinoma (HCC) within Milan criteria. Multivariable analysis was performed to identify pre-/postoperative high-risk factors of early recurrence after hepatic resection for HCC. Two prediction models for early HCC recurrence determined by stepwise variable selection methods based on Akaike information criterion were built, either based on preoperative factors alone or both pre-/postoperative factors. Area under the curve (AUC) for each receiver operating characteristic curve of the two models was calculated, and the two curves were compared for non-inferiority testing. The predictive models of early HCC recurrence were internally validated by bootstrap resampling method.

Results

Multivariable analysis on preoperative factors alone identified aspartate aminotransferase/platelet ratio index (OR, 1.632; 95% CI, 1.056–2.522; p = 0.027), tumor size (OR, 1.025; 95% CI, 0.002–1.049; p = 0.031), arterial rim enhancement of the tumor (OR, 2.350; 95% CI, 1.297–4.260; p = 0.005), and presence of nonhypervascular hepatobiliary hypointense nodules (OR, 1.983; 95% CI, 1.049–3.750; p = 0.035) on gadoxetic acid-enhanced magnetic resonance imaging as significant factors. After adding postoperative histopathologic factors, presence of microvascular invasion (OR, 1.868; 95% CI, 1.155–3.022; p = 0.011) became an additional significant factor, while tumor size became insignificant (p = 0.119). Comparison of the AUCs of the two models showed that the prediction model built on preoperative factors alone was not inferior to that including both pre-/postoperative factors {AUC for preoperative factors only, 0.673 (95% confidence interval [CI], 0.623–0.723) vs. AUC after adding postoperative factors, 0.691 (95% CI, 0.639–0.744); p = 0.0013}. Bootstrap resampling method showed that both the models were valid.

Conclusion

Risk stratification solely based on preoperative imaging and laboratory factors was not inferior to that based on postoperative histopathologic risk factors in predicting early recurrence after curative resection in within Milan criteria single HCC patients.

Intra-individual comparison of dual portal venous phases for non-invasive diagnosis of hepatocellular carcinoma at gadoxetic acid-enhanced liver MRI

OBJECTIVES

To compare the diagnostic performances of first and second portal venous phases (PVP1 and PVP2) in revealing washout and capsule appearance for non-invasive HCC diagnoses in gadoxetic acid-enhanced MRI (Gd-EOB-MRI).

METHODS

This retrospective study included 123 at-risk patients with 160 hepatic observations (HCCs, n = 116; non-HCC malignancies, n = 18; benign, n = 26) showing arterial phase hyper-enhancement (APHE) ≥ 1 cm at Gd-EOB-MRI. The mean time intervals from gadoxetic acid injection to PVP1 and PVP2 acquisitions were 53 ± 2 s and 73 ± 3 s, respectively. After evaluating image findings independently, imaging findings and diagnoses were finalized by a consensus of two radiologists using either PVP1 or PVP2 image sets according to the LI-RADS v2018 or EASL criteria. Sensitivity, specificity, and accuracy were compared.

RESULTS

Among HCCs, more washout and enhancing capsule were observed in PVP2 (83.6% and 27.6%) than in PVP1 (50.9% and 19.8%) (p < 0.001, both). The PVP2 set presented significantly higher sensitivity (83.6% vs. 53.5%, LI-RADS; 82.8% vs. 50.0%, EASL; p < 0.001, both) and accuracy (0.88 vs. 0.73, LI-RADS; 0.88 vs. 0.72, EASL; p < 0.001, both) than the PVP1 set without significant specificity loss (93.2% vs. 93.2%, by LI-RADS or EASL; p = 0.32, both). None of the non-HCC malignancy was non-invasively diagnosed as HCC in both PVP image sets.

CONCLUSION

Late acquisition of PVP detected washout and enhancing capsule of HCC more sensitively than early acquisition, enabling accurate diagnoses of HCC, according to LI-RADS or EASL criteria.

KEY POINTS

• Among HCCs, more washout and enhancing capsules were observed in PVP2 than PVP1, quantitatively and qualitatively. • The portal venous phase acquired at around 70 s after contrast media administration (PVP2) provided significantly higher sensitivity and AUC value than PVP1 by using LI-RADS v2018 or EASL criteria. • More HCCs were categorized as LR-5 in PVP2 than in PVP1 images, and the specificity of PVP2 (93.5%) was comparable with PVP1 (93.5%).

Integrated nomograms to predict overall survival and recurrence-free survival in patients with combined hepatocellular cholangiocarcinoma (cHCC) after liver resection

The current clinical classification of primary liver cancer is unable to efficiently predict the prognosis of combined hepatocellular cholangiocarcinoma (cHCC). Accurate satellite nodules (SAT) and microvascular invasion (MVI) prediction in cHCC patients is very important for treatment decision making and prognostic evaluation. The aim of this work was to explore important factors affecting the prognosis of cHCC patients after liver resection and to develop preoperative nomograms to predict SAT and MVI in cHCC patients. The nomogram was developed using the data from 148 patients who underwent liver resection for cHCC patients at our hospital between January 2006 and December 2014. Based on the results of the multivariate analysis, a nomogram integrating all significant independent factors affecting overall survival and recurrence-free survival was constructed to predict the prognosis of cHCC. Next, risk factors for SAT and MVI were evaluated with logistic regression. Blood signatures were established using the LASSO regression, and then, we combined the clinical risk factors and blood signatures of the patients to establish predictive models for SAT and MVI. The C-index of the nomogram for predicting survival was 0.685 (95% CI, 0.638 to 0.732), which was significantly higher than the C-index for other liver cancer classification systems.

Gadoxetic acid-enhanced MRI radiomics signature: prediction of clinical outcome in hepatocellular carcinoma after surgical resection

BACKGROUND

This study aimed to evaluate the efficiency of gadoxetic acid-enhanced MRI-based radiomics features for prediction of overall survival (OS) in hepatocellular carcinoma (HCC) patients after surgical resection.

METHODS

This prospective study approved by the Institutional Review Board enrolled 120 patients with pathologically confirmed HCC. Radiomics signatures (rad-scores) were built from radiomics features in 3 different regions of interest (ROIs) with the least absolute shrinkage and selection operator (LASSO) cox regression analysis. Preoperative clinical characteristics and semantic imaging features potentially associated with patient survival were evaluated to develop a clinic-radiological model. The radiomics features and clinic-radiological predictors were integrated into a joint model using multivariable Cox regression analysis. Kaplan-Meier analysis and log-rank tests were performed to compare the discriminative performance and evaluated on the validation cohort.

RESULTS

The radiomics signatures showed a significant association with patient survival in both cohorts (all P<0.001). The BCLC (Barcelona clinic liver cancer) stage, non-smooth tumor margin, and the combined rad-score were independently associated with OS. Moreover, the combined model incorporating with clinic-radiological and radiomics features showed an improved predictive performance with C-index of 0.92 [95% confidence interval (CI): 0.87-0.97], compared to the clinic-radiological model (C-index, 0.86, 95% CI: 0.79-0.94; P=0.039) or the combined rad-score (C-index, 0.88, 95% CI: 0.81-0.95; P=0.016).

CONCLUSIONS

Radiomics features along with clinic-radiological predictors can efficiently aid in preoperative HCC prognosis prediction after surgical resection and enable a step forward precise medicine.

Preoperative Prediction Power of Imaging Methods for Microvascular Invasion in Hepatocellular Carcinoma: A Systemic Review and Meta-Analysis

Background: To compare the predictive power between radiomics and non-radiomics (conventional imaging and functional imaging methods) for preoperative evaluation of microvascular invasion (MVI) in hepatocellular carcinoma (HCC).

Methods: Comprehensive publications were screened in PubMed, Embase, and Cochrane Library. Studies focusing on the discrimination values of imaging methods, including radiomics and non-radiomics methods, for MVI evaluation were included in our meta-analysis.

Results: Thirty-three imaging studies with 5,462 cases, focusing on preoperative evaluation of MVI status in HCC, were included. The sensitivity and specificity of MVI prediction in HCC were 0.78 [95% confidence interval (CI): 0.75–0.80; I² = 70.7%] and 0.78 (95% CI: 0.76–0.81; I² = 0.0%) for radiomics, respectively, and were 0.73 (95% CI: 0.71–0.75; I² = 83.7%) and 0.82 (95% CI: 0.80–0.83; I² = 86.5%) for non-radiomics, respectively. The areas under the receiver operation curves for radiomics and non-radiomics to predict MVI status in HCC were 0.8550 and 0.8601, respectively, showing no significant difference.

Conclusion: The imaging method is feasible to predict the MVI state of HCC. Radiomics method based on medical image data is a promising application in clinical practice and can provide quantifiable image features. With the help of these features, highly consistent prediction performance will be achieved in anticipation.

Contrast-enhanced CT radiomics for preoperative evaluation of microvascular invasion in hepatocellular carcinoma: A two-center study

Background

The present study constructed and validated the use of contrast‐enhanced computed tomography (CT)‐based radiomics to preoperatively predict microvascular invasion (MVI) status (positive vs negative) and risk (low vs high) in patients with hepatocellular carcinoma (HCC).

Methods

We enrolled 637 patients from two independent institutions. Patients from Institution I were randomly divided into a training cohort of 451 patients and a test cohort of 111 patients. Patients from Institution II served as an independent validation set. The LASSO algorithm was used for the selection of 798 radiomics features. Two classifiers for predicting MVI status and MVI risk were developed using multivariable logistic regression. We also performed a survival analysis to investigate the potentially prognostic value of the proposed MVI classifiers.

Results

The developed radiomics signature predicted MVI status with an area under the receiver operating characteristic curve (AUC) of .780, .776, and .743 in the training, test, and independent validation cohorts, respectively. The final MVI status classifier that integrated two clinical factors (age and α‐fetoprotein level) achieved AUC of .806, .803, and .796 in the training, test, and independent validation cohorts, respectively. For MVI risk stratification, the AUCs of the radiomics signature were .746, .664, and .700 in the training, test, and independent validation cohorts, respectively, and the AUCs of the final MVI risk classifier‐integrated clinical stage were .783, .778, and .740, respectively. Survival analysis showed that our MVI status classifier significantly stratified patients for short overall survival or early tumor recurrence.

Conclusions

Our CT radiomics‐based models were able to predict MVI status and MVI risk of HCC and might serve as a reliable preoperative evaluation tool.

Prediction of prognostic risk factors in hepatocellular carcinoma with transarterial chemoembolization using multi-modal multi-task deep learning

BACKGROUND

Due to heterogeneity of hepatocellular carcinoma (HCC), outcome assessment of HCC with transarterial chemoembolization (TACE) is challenging.

METHODS

We built histologic-related scores to determine microvascular invasion (MVI) and Edmondson-Steiner grade by training CT radiomics features using machine learning classifiers in a cohort of 494 HCCs with hepatic resection. Meanwhile, we developed a deep learning (DL)-score for disease-specific survival by training CT imaging using DL networks in a cohort of 243 HCCs with TACE. Then, three newly built imaging hallmarks with clinicoradiologic factors were analyzed with a Cox-Proportional Hazard (Cox-PH) model.

FINDINGS

In HCCs with hepatic resection, two imaging hallmarks resulted in areas under the curve (AUCs) of 0.79 (95% confidence interval [CI]: 0.71-0.85) and 0.72 (95% CI: 0.64-0.79) for predicting MVI and Edmondson-Steiner grade, respectively, using test data. In HCCs with TACE, higher DL-score (hazard ratio [HR]: 3.01; 95% CI: 2.02-4.50), American Joint Committee on Cancer (AJCC) stage III+IV (HR: 1.71; 95% CI: 1.12-2.61), Response Evaluation Criteria in Solid Tumors (RECIST) with stable disease + progressive disease (HR: 2.72; 95% CI: 1.84-4.01), and TACE-course > 3 (HR: 0.65; 95% CI: 0.45-0.76) were independent prognostic factors. Using these factors via a Cox-PH model resulted in a concordance index of 0.73 (95% CI: 0.71-0.76) for predicting overall survival and AUCs of 0.85 (95% CI: 0.81-0.89), 0.90 (95% CI: 0.86-0.94), and 0.89 (95% CI: 0.84-0.92), respectively, for predicting 3-year, 5-year, and 10-year survival.

INTERPRETATION

Our study offers a DL-based, noninvasive imaging hallmark to predict outcome of HCCs with TACE.

FUNDING

This work was supported by the key research and development program of Jiangsu Province (Grant number: BE2017756).

Hepatobiliary MR contrast agent uptake as a predictive biomarker of aggressive features on pathology and reduced recurrence-free survival in resectable hepatocellular carcinoma: comparison with dual-tracer 18F-FDG and 18F-FCH PET/CT

OBJECTIVES

To compare the performance of the quantitative analysis of the hepatobiliary phase (HBP) tumor enhancement in gadobenate dimeglumine (Gd-BOPTA)-enhanced MRI and of dual-tracer 18F-FDG and 18F-fluorocholine (FCH) PET/CT for the prediction of tumor aggressiveness and recurrence-free survival (RFS) in resectable hepatocellular carcinoma (HCC).

METHODS

This retrospective, IRB approved study included 32 patients with 35 surgically proven HCCs. All patients underwent Gd-BOPTA-enhanced MRI including delayed HBP images, 18F-FDG PET/CT, and (for 29/32 patients) 18F-FCH PET/CT during the 2 months prior to surgery. For each lesion, the lesion-to-liver contrast enhancement ratio (LLCER) on MRI HBP images and the SUV_max tumor-to-liver ratio (SUV_T/L) for both tracers were calculated. Their predictive value for aggressive pathological features-including the histological grade and microvascular invasion (MVI)-and RFS were analyzed and compared using area under receiver operating characteristic (AUROC) curves and Cox regression models, respectively.

RESULTS

The AUROCs for the identification of aggressive HCCs on pathology with LLCER, 18F-FDG SUV_T/L, and 18F-FCH SUV_T/L were 0.92 (95% CI 0.78, 0.98), 0.89 (95% CI 0.74, 0.97; p = 0.70), and 0.64 (95% CI 0.45, 0.80; p = 0.035). At multivariate Cox regression analysis, LLCER was identified as an independent predictor of RFS (HR (95% CI) = 0.91 (0.84, 0.99), p = 0.022). LLCER - 4.72% or less also accurately predicted moderate-poor differentiation grade (Se = 100%, Sp = 92.9%) and MVI (Se = 93.3%, Sp = 60%) and identified patients with poor RFS after surgical resection (p = 0.030).

CONCLUSIONS

HBP tumor enhancement after Gd-BOPTA injection may help identify aggressive HCC pathological features, and patients with reduced recurrence-free survival after surgical resection.

KEY POINTS

• In patients with resectable HCC, the quantitative analysis of the HBP tumor enhancement in Gd-BOPTA-enhanced MRI (LLCER) accurately identifies moderately-poorly differentiated and/or MVI-positive HCCs. • After surgical resection for HCC, patients with LLCER - 4.72% or less had significantly poorer recurrence-free survival than patients with LLCER superior to - 4.72%. • Gd-BOPTA-enhanced MRI with delayed HBP images may be suggested as part of pre-surgery workup in patients with resectable 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.

Impact of Surgical Margin on the Prognosis of Early Hepatocellular Carcinoma (≤5 cm): A Propensity Score Matching Analysis

Aim: The influence of surgical margin on the prognosis of patients with early solitary hepatocellular carcinoma (HCC) (≤5 cm) is undetermined.

Methods: The data of 904 patients with early solitary HCC who underwent liver resection were collected for recurrence-free survival (RFS) and overall survival (OS). Propensity score matching (PSM) was performed to balance the potential bias.

Results: Log-rank tests showed that 2 mm was the best cutoff value to discriminate the prognosis of early HCC. Liver resection with a >2 mm surgical margin distance (wide-margin group) led to better 5-year RFS and OS rate compared with liver resection with a ≤2 mm surgical margin distance (narrow-margin group) among patients both before (RFS: 59.1% vs. 39.6%, P < 0.001; OS: 85.3% vs. 73.7%, P < 0.001) and after PSM (RFS: 56.3% vs. 41.0%, P < 0.001; OS: 83.0% vs. 75.0%, P = 0.010). Subgroup analysis showed that a wide-margin resection significantly improved the prognosis of patients with microvascular invasion (RFS: P < 0.001; OS: P = 0.001) and patients without liver cirrhosis (RFS: P < 0.001; OS: P = 0.001) after PSM. Multivariable Cox regression analysis revealed that narrow-margin resection is associated with poorer RFS [hazard ratio (HR) = 1.781, P < 0.001), OS (HR = 1.935, P < 0.001], and early recurrence (HR = 1.925, P < 0.001).

Conclusions: A wide-margin resection resulted in better clinical outcomes than a narrow-margin resection among patients with early solitary HCC, especially for those with microvascular invasion and without cirrhosis. An individual strategy of surgical margin should be formulated preoperation according to both tumor factors and background liver factors.

Prediction of HCC microvascular invasion with gadobenate-enhanced MRI: correlation with pathology

PURPOSE

To assess the accuracy of gadobenate-enhanced MRI for predicting microvascular invasion (MVI) in patients operated for hepatocellular carcinoma (HCC).

METHODS

The 164 patients who met the inclusion criteria were assigned to one of two groups: the MVI-positive group and the MVI-negative group. Imaging results were compared between the two groups using the Kruskal test, chi-square test, independent sample t test, and logistic regression analysis.

RESULTS

Differences in the capsule (p = 0.037) and margin (p = 0.004) of the tumor, rim enhancement (p = 0.002), peritumoral enhancement in the arterial phase (p < 0.001), and peritumoral hypointensity in the hepatobiliary phase (HBP) (p < 0.001) were statistically significant. The results of multivariate analysis identified rim enhancement in the arterial phase (odds ratio (OR) = 2.115; 95% confidence interval (CI), 1.002-4.464; p = 0.049) and peritumoral hypointensity in the HBP (OR = 5.836; 95% CI, 2.442-13.948; p < 0.001) as independent risk factors for MVI. Use of the two predictors in combination identified 32.79% (20/61) of HCCs with MVI with a specificity of 95.15% (98/103).

CONCLUSIONS

Rim enhancement in the arterial phase and peritumoral hypointensity in the HBP were identified as independent risk factors for MVI in patients with HCC.

KEY POINTS

• Rim enhancement in the arterial phase and peritumoral hypointensity in the hepatobiliary phase were independent risk factors for microvascular invasion in patients with HCC. • Use of the two predictors in combination had a sensitivity of 32.79% and a specificity of 95.15% for predicting microvascular invasion.

Evaluation of a serum tumour marker-based recurrence prediction model after radiofrequency ablation for hepatocellular carcinoma

BACKGROUND & AIMS

A recent study showed that serum tumour marker-based MoRAL score (11×√protein induced by vitamin K absence-II [PIVKA] +2×√alpha-foetoprotein [AFP]) can reflect both tumour burden and aggressiveness of hepatocellular carcinoma (HCC). This study aimed to evaluate whether baseline MoRAL score could predict tumour recurrence after radiofrequency ablation (RFA) for very-early/early-stage HCC.

METHODS

A total of 576 HCC patients who underwent RFA as initial treatment were enrolled from two tertiary referral hospitals (256 in development cohort and 320 in validation cohort). The primary endpoint was recurrence-free survival (RFS) and the secondary endpoints included cumulative risks of intrahepatic distant recurrence (IDR) and extrahepatic metastasis (EM).

RESULTS

In the development cohort, MoRAL score was an independent prognostic factor of RFS (P = .02). The optimal cutoff MoRAL score for predicting RFS was 68. Patients with high MoRAL score (>68) showed significantly shorter RFS than did those with low MoRAL score (hazard ratio [HR] = 2.04, P < .001). The 5-year RFS rates were 32.3% and 53.2% in high- and low-MoRAL groups respectively. Risks of both IDR (HR = 1.76, P = .003) and EM (HR = 8.25, P = .006) were also significantly higher in high MoRAL group. These results were reproduced in the validation cohort: RFS (HR = 1.81, P < .001; 5-year RFS rates = 27.7% vs 53.6%) was significantly shorter and risks of IDR (HR = 1.59, P = .003) and EM (HR = 6.19, P = .004) were significantly higher in high MoRAL group.

CONCLUSION

A high MoRAL score of >68 was significant a predictive factor of tumour recurrence after RFA for very-early/early-stage HCC. Moreover, it might be warranted to evaluate EM in patients with high baseline MoRAL scores.

A Case of Hyperintense Liver Metastases of Breast Cancer in the Hepatobiliary Phase on Gadoxetic Acid-Enhanced Magnetic Resonance Imaging

A 64-year-old woman complaining of left arm and breast edema was referred to our hospital. Mammography and ultrasound could not initially show any masses, but magnetic resonance imaging (MRI) showed ill-defined small masses in her left breast. Histological examination showed the tumor to be triple-negative breast cancer. After neoadjuvant chemotherapy, the patient underwent operation. Postoperative histological examination showed massive cancer remnants in the lymph nodes and lymphatics. Enhanced CT taken at the onset of abdominal pain showed multiple liver masses with ring enhancement 17 months after the operation. Gadoxetic acid-enhanced MRI showed hyperintense masses and presumed broad cancer cell permeation to the liver in the hepatobiliary phase. Due to the histologically proven high lymphatic permeability, metastatic sites, and gadoxetic acid-enhanced MRI findings, we judged the liver metastases as lymphatic liver metastases. Due to the marked liver dysfunction at the onset of abdominal pain, the patient received best supportive care and died in 4 months.

Value of T1 mapping on gadoxetic acid-enhanced MRI for microvascular invasion of hepatocellular carcinoma: a retrospective study

BACKGROUND

To evaluate the utility of non-invasive parameters derived from T1 mapping and diffusion-weighted imaging (DWI) on gadoxetic acid-enhanced MRI for predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC).

METHODS

A total of 94 patients with single HCC undergoing partial hepatectomy was analyzed in this retrospective study. Preoperative T1 mapping and DWI on gadoxetic acid-enhanced MRI was performed. The parameters including precontrast, postcontrast and reduction rate of T1 relaxation time and apparent diffusion coefficient (ADC) values were measured for differentiating MVI-positive HCCs (n = 38) from MVI-negative HCCs (n = 56). The receiver operating characteristic curve (ROC) was analyzed to compare the diagnostic performance of the calculated parameters.

RESULTS

MVI-positive HCCs demonstrated a significantly lower reduction rate of T1 relaxation time than that of MVI-negative HCCs (39.4% vs 49.9, P < 0.001). The areas under receiver operating characteristic curve (AUC) were 0.587, 0.728, 0.824, 0,690 and 0.862 for the precontrast, postcontrast, reduction rate of T1 relaxation time, ADC and the combination of reduction rate and ADC, respectively. The cut-off value of the reduction rate and ADC calculated through maximal Youden index in ROC analyses was 44.9% and 1553.5 s/mm². To achieve a better diagnostic performance, the criteria of combining the reduction rate lower than 44.9% and the ADC value lower than 1553.5 s/mm² was proposed with a high specificity of 91.8% and accuracy of 80.9%.

CONCLUSIONS

The proposed criteria of combining the reduction rate of T1 relaxation time lower than 44.9% and the ADC value lower than 1553.5 s/mm² on gadoxetic acid-enhanced MRI holds promise for evaluating MVI status of HCC.

Multiphase Liver MRI for Identifying the Macrotrabecular-Massive Subtype of Hepatocellular Carcinoma

Background The recently described "macrotrabecular-massive" (MTM) histologic subtype of hepatocellular carcinoma (HCC) (MTM-HCC) represents an aggressive form of HCC and is associated with poor survival. Purpose To investigate whether preoperative MRI can help identify MTM-HCCs in patients with HCC. Materials and Methods This retrospective study included patients with HCC treated with surgical resection between January 2008 and February 2018 and who underwent preoperative multiphase contrast material-enhanced MRI. Least absolute shrinkage and selection operator (LASSO)-penalized and multivariable logistic regression analyses were performed to identify clinical, biologic, and imaging features associated with the MTM-HCC subtype. Early recurrence (within 2 years) and overall recurrence were evaluated by using Kaplan-Meier analysis. Multivariable Cox regression analysis was performed to determine predictors of early and overall recurrence. Results One hundred fifty-two patients (median age, 64 years; interquartile range, 56-72 years; 126 men) with 152 HCCs were evaluated. Twenty-six of the 152 HCCs (17%) were MTM-HCCs. LASSO-penalized logistic regression analysis identified substantial necrosis, high serum α-fetoprotein (AFP) level (>100 ng/mL), and Barcelona Clinic Liver Cancer (BCLC) stage B or C as independent features associated with MTM-HCCs. At multivariable analysis, substantial necrosis (odds ratio = 32; 95% confidence interval [CI] = 8.9, 114; P < .001), high serum AFP level (odds ratio = 4.4; 95% CI = 1.3, 16; P = .02), and BCLC stage B or C (odds ratio = 4.2; 95% CI = 1.2, 15; P = .03) were independent predictors of MTM-HCC subtype. Substantial necrosis helped identify 65% (17 of 26; 95% CI: 44%, 83%) of MTM-HCCs (sensitivity) with a specificity of 93% (117 of 126; 95% CI: 87%, 97%). In adjusted models, only the presence of satellite nodules was independently associated with both early (hazard ratio = 3.7; 95% CI: 1.5, 9.4; P = .006) and overall (hazard ratio = 3.0; 95% CI: 1.3, 7.2; P = .01) tumor recurrence. Conclusion At multiphase contrast-enhanced MRI, substantial necrosis helped identify macrotrabecular-massive hepatocellular carcinoma subtype with high specificity. © RSNA, 2020.

Progress in hepatectomy for hepatocellular carcinoma and peri-operation management

The global incidence of liver cancer continues to grow. Liver cancer, especially hepatocellular carcinoma, has high recurrence and mortality rates. Here, we review the past decade's diagnostic, therapeutic, and management strategies for hepatocellular carcinoma, and summarize new patient management approaches, including enhanced recovery after surgery, targeted therapy, and immunotherapy. We compare traditional and innovative management methods, which comprise developments in precision medicine, and consider their limitations. Ongoing innovation and technological advances enable surgeons to gain deeper understandings of the multidimensionality of hepatocellular carcinoma, thereby promoting the continuous development of precision therapy.

RNA sequencing reveals the long noncoding RNA and mRNA profiles and identifies long non-coding RNA TSPAN12 as a potential microvascular invasion-related biomarker in hepatocellular carcinoma

Emerging evidence demonstrates that abnormally expressed long noncoding RNAs (lncRNAs) are involved in the progression of various cancers. However, the expression profiles and functions of lncRNAs in hepatocellular carcinoma (HCC) with microvascular invasion (MVI) remain largely unknown. In this study, we revealed the differential expression profiles of lncRNA and messenger RNA in four pairs of HCC with MVI and adjacent nontumor liver tissues by using high-throughput RNA sequencing. Among these dysregulated lncRNAs, lnc-TSPAN12 was the most significantly upregulated lncRNA in HCC. The results of real time-PCR showed that lnc-TSPAN12 was highly expressed in HCC, including HCC with MVI, and its high expression was associated with unfavorable clinicopathological features and poor prognosis. Moreover, multivariate Cox regression analysis verified that lnc-TSPAN12 was an independent prognostic predictor for overall and recurrence-free survival. Receiver operating characteristic curve analysis indicated that lnc-TSPAN12 could serve as a potential diagnostic biomarker for HCC with MVI. In addition, a loss-of-function experiment demonstrated that lnc-TSPAN12 knockdown inhibited HCC cell migration and invasion in vitro. Our findings suggest that lnc-TSPAN12 may function as an oncogene in HCC progression and could serve as a novel diagnostic/prognostic biomarker and potential therapeutic target for HCC with MVI.

Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma: Initial Application of a Radiomic Algorithm Based on Grayscale Ultrasound Images

Objectives: To establish a radiomic algorithm based on grayscale ultrasound images and to make preoperative predictions of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients. Methods: In this retrospective study, 322 cases of histopathologically confirmed HCC lesions were included. The classifications based on preoperative grayscale ultrasound images were performed in two stages: (1) classifier #1, MVI-negative and MVI-positive cases; (2) classifier #2, MVI-positive cases were further classified as M1 or M2 cases. The gross-tumoral region (GTR) and peri-tumoral region (PTR) signatures were combined to generate gross- and peri-tumoral region (GPTR) radiomic signatures. The optimal radiomic signatures were further incorporated with vital clinical information. Multivariable logistic regression was used to build radiomic models. Results: Finally, 1,595 radiomic features were extracted from each HCC lesion. At the classifier #1 stage, the radiomic signatures based on features of GTR, PTR, and GPTR showed area under the curve (AUC) values of 0.708 (95% CI, 0.603-0.812), 0.710 (95% CI, 0.609-0.811), and 0.726 (95% CI, 0.625-0.827), respectively. Upon incorporation of vital clinical information, the AUC of the GPTR radiomic algorithm was 0.744 (95% CI, 0.646-0.841). At the classifier #2 stage, the AUC of the GTR radiomic signature was 0.806 (95% CI, 0.667-0.944). Conclusions: Our radiomic algorithm based on grayscale ultrasound images has potential value to facilitate preoperative prediction of MVI in HCC patients. The GTR radiomic signature may be helpful for further discriminating between M1 and M2 levels among MVI-positive patients.

Direct Comparison of Four Presurgical Stratifying Schemes for Prediction of Microvascular Invasion in Hepatocellular Carcinoma by Gadoxetic Acid-Enhanced MRI

BACKGROUND

Microvascular invasion (MVI) is implicated in the poor prognosis of hepatocellular carcinoma (HCC). Presurgical stratifying schemes have been proposed for HCC-MVI but lack external validation.

PURPOSE

To perform external validation and comparison of four presurgical stratifying schemes for the prediction of MVI using gadoxetic acid-based MRI in a cohort of HCC patients.

STUDY TYPE

Retrospective.

SUBJECTS

Included were 183 surgically resected HCCs from patients who underwent pretreatment MRI.

FIELD STRENGTH/SEQUENCE

This includes 1.5-3.0 T with T₂ , T₁ , diffusion-weighted imaging (DWI), and dynamic gadoxetic acid contrast-enhancement imaging sequences.

ASSESSMENT

A two-trait predictor of venous invasion (TTPVI), Lei model, Lee model, and Xu model were compared. We relied on preoperative characteristics and imaging findings via four independent radiologists who were blinded to histologic results, as required by the tested tools.

STATISTICAL TEST

Tests of accuracy between predicted and observed HCC-MVI rates using receiver operating characteristic (ROC) curve and decision curve analysis. The intraclass correlation coefficient (ICC) and Cronbach's alpha statistics were used to evaluate reproducibility.

RESULTS

HCC-MVI was identified in 52 patients (28.4%). The average ROC curves (AUCs) for HCC-MVI predictions were 0.709-0.880, 0.714-0.828, and 0.588-0.750 for the Xu model, Lei model, and Lee model, respectively. The rates of accuracy were 60.7-81.4%, 69.9-75.9%, and 65.6-73.8%, respectively. Decision curve analyses indicated a higher benefit for the Xu and Lei models compared to the Lee model. The ICC and Cronbach's alpha index were highest in the Lei model (0.896/0.943), followed by the Xu model (0.882/0.804), and the Lee model (0.769/0.715). The TTPVI resulted in a Cronbach's alpha index of 0.606 with a sensitivity of 34.6-61.5% and a specificity of 76.3-91.6%.

DATA CONCLUSION

Stratifying schemes relying on gadoxetic acid-enhanced MRI provide an additional insight into the presence of preoperative MVI. The Xu model outperformed the other models in terms of accuracy when performed by an experienced radiologist. Conversely, the Lei model outperformed the other models in terms of reproducibility.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY STAGE: 2 J. Magn. Reson. Imaging 2020;52:433-447.

Nomogram to Assist in Surgical Plan for Hepatocellular Carcinoma: a Prediction Model for Microvascular Invasion

BACKGROUND

Microvascular invasion (MVI) relates to poor survival in hepatocellular carcinoma (HCC) patients. In this study, we aim at developing a nomogram for MVI prediction and potential assistance in surgical planning.

METHODS

A total of 357 patients were assigned to training (n = 257) and validation (n = 100) cohort. Univariate and multivariate analyses were used to reveal preoperative predictors for MVI. A nomogram incorporating independent predictors was constructed and validated. Disease-free survival was compared between patients, and the potential of the predicted MVI in making surgical procedure was also explored.

RESULTS

Pathological examination confirmed MVI in 140 (39.2%) patients. Imaging features including larger tumor, intra-tumoral artery, tumor type, and higher serum AFP independently correlated with MVI. The nomogram showed desirable performance with an AUROC of 0.803 (95% CI, 0.746-0.860) and 0.814 (95% CI, 0.720-0.908) in the training and validation cohorts, respectively. Good calibration were also revealed by calibration curve in both cohorts. The decision curve analysis indicated that the prediction nomogram was of promising usefulness in clinical work. In addition, survival analysis revealed that patients with positive-predicted MVI suffered a higher risk of early recurrence (P < 0.01). There was no difference in disease-free survival between anatomic or non-anatomic resection in large HCC or small HCC without nomogram-predicted MVI. However, anatomic resection improved disease-free survival in small HCC with nomogram-predicted MVI.

CONCLUSIONS

The nomogram obtained desirable results in predicting MVI. Patients with predicted MVI were associated with early recurrence and anatomic resection was recommended for small HCC patients with predicted MVI.

NIACE score refines the overall survival of hepatocellular carcinoma by Barcelona clinic liver cancer staging

BACKGROUND AND AIM

The NIACE score provides prognostic values for hepatocellular carcinoma (HCC) in European studies. We aim to evaluate the prognostic value of the NIACE score in Asian patients.

METHODS

Patients with HCC were retrospectively enrolled from a tertiary medical center in Taiwan during 2009-2014, and their clinical information were collected. The NIACE score was calculated according to the Nodular numbers, tumor Infiltration, Alpha-fetoprotein level, Child-Pugh score, and Eastern Cooperative Oncology Group score. The prognostic values of NIACE score for overall survival according to individual treatment and the Barcelona clinic liver cancer (BCLC) staging were analyzed.

RESULTS

A total of 468 patients were included with a median follow-up of 30 months. A greater NIACE score correlated with lower median survival and higher BCLC staging. Regardless of treatment modalities, NIACE scores (0, 1-1.5, 2.5-3, and 4-7) significantly predicted survival between groups (log-rank P < 0.001). Specifically, NIACE score (0, 1-1.5, 2.5-3, and 4-7) significantly predicted survival in patients receiving transarterial chemoembolization (log-rank P < 0.001). NIACE score 1, 2.5, and 4 further distinguished overall survival in BCLC A, B, and C patients, respectively (all log-rank P < 0.01). After adjustment of the confounders and the BCLC staging, NIACE score of 2.5-3 and 4-7 (vs 0) had a significantly increased risk of mortality with a hazard ratio of 4.04 (95% confidence interval: 2.14-7.64, P < 0.001) and 7.45 (95% confidence interval: 3.22-17.23, P < 0.001), respectively.

CONCLUSIONS

The NIACE score helps refine differential prognosis among BCLC A, B, and C subgroups of Asian patients with HCC, especially in those receiving transarterial chemoembolization.

The Role of Preoperative Dynamic Contrast-enhanced 3.0-T MR Imaging in Predicting Early Recurrence in Patients With Early-Stage Hepatocellular Carcinomas After Curative Resection

Objectives: Liver resection is potentially curative for early-stage hepatocellular carcinoma (eHCC) in patients with well-preserved liver function. The prognosis of these patients after resection is still unsatisfactory because of frequent early recurrence (ER). Therefore, we investigated the role of preoperative dynamic contrast-enhanced 3.0-T MR imaging in predicting ER of eHCC after curative resection. Methods From May 2014 to October 2017, we retrospectively analyzed 82 patients with eHCC who underwent dynamic MR imaging and subsequently underwent curative resection. Liver Imaging Reporting and Data System (LI-RADS) v2018 major and ancillary imaging features, as well as two non-LI-RADS MR imaging features (irregular tumor margin and tumor number), were evaluated. A multivariate Cox regression analysis was used to identify independent predictors, and two models (preoperative and postoperative prediction models) were developed. Results ER was observed in 25 patients (25/82, 30.5%). In the univariate analyses, preoperative alpha-fetoprotein (AFP) level >200 ng/ml, three MR imaging features (multifocal tumors, corona enhancement, and irregular tumor margin), and microvascular invasion (MVI) were associated with ER. In the multivariate analysis, corona enhancement (hazard ratio [HR]: 2.970; p = 0.013) and irregular tumor margin (HR: 2.377; p = 0.048) were independent predictors in the preoperative prediction model, and preoperative AFP level >200 ng/ml (HR: 2.493; p = 0.044) plus corona enhancement (HR: 3.046; p = 0.014) were independent predictors in the postoperative prediction model (microvascular invasion [MVI] was not; p = 0.061). When combined with both predictors, the specificity for ER in the preoperative prediction model was 98.2% (56/57), which was comparable to that of the postoperative prediction model [96.7% (55/57)]. Conclusions Our results demonstrated that preoperative MR imaging features (corona enhancement and irregular tumor margin) have the potential to preoperatively identify high-risk ER patients with eHCC, with a specificity >90%.