Validated preoperative computed tomography risk estimation for postoperative hepatocellular carcinoma recurrence

MRI-based clinical-radiomics nomogram model for predicting microvascular invasion in hepatocellular carcinoma

BACKGROUND

Preoperative microvascular invasion (MVI) of liver cancer is an effective method to reduce the recurrence rate of liver cancer. Hepatectomy with extended resection and additional adjuvant or targeted therapy can significantly improve the survival rate of MVI+ patients by eradicating micrometastasis. Preoperative prediction of MVI status is of great clinical significance for surgical decision-making and the selection of other adjuvant therapy strategies to improve the prognosis of patients.

PURPOSE

Established a radiomics machine learning model based on multimodal MRI and clinical data, and analyzed the preoperative prediction value of this model for microvascular invasion (MVI) of hepatocellular carcinoma (HCC).

METHOD

The preoperative liver MRI data and clinical information of 130 HCC patients who were pathologically confirmed to be pathologically confirmed were retrospectively studied. These patients were divided into MVI-positive group (MVI+) and MVI-negative group (MVI-) based on postoperative pathology. After a series of dimensionality reduction analysis, six radiomic features were finally selected. Then, linear support vector machine (linear SVM), support vector machine with rbf kernel function (rbf-SVM), logistic regression (LR), Random forest (RF) and XGBoost (XGB) algorithms were used to establish the MVI prediction model for preoperative HCC patients. Then, rbf-SVM with the best predictive performance was selected to construct the radiomics score (R-score). Finally, we combined R-score and clinical-pathology-image independent predictors to establish a combined nomogram model and corresponding individual models. The predictive performance of individual models and combined nomogram was evaluated and compared by receiver operating characteristic curve (ROC).

RESULT

Alpha-fetoprotein concentration, peritumor enhancement, maximum tumor diameter, smooth tumor margins, tumor growth pattern, presence of intratumor hemorrhage, and RVI were independent predictors of MVI. Compared with individual models, the final combined nomogram model (AUC: 0.968, 95% CI: 0.920-1.000) constructed by radiometry score (R-score) combined with clinicopathological parameters and apparent imaging features showed the optimal predictive performance.

CONCLUSION

This multi-parameter combined nomogram model had a good performance in predicting MVI of HCC, and had certain auxiliary value for the formulation of surgical plan and evaluation of prognosis.

A knowledge-enhanced interpretable network for early recurrence prediction of hepatocellular carcinoma via multi-phase CT imaging

BACKGROUND

Predicting early recurrence (ER) of hepatocellular carcinoma (HCC) accurately can guide treatment decisions and further enhance survival. Computed tomography (CT) imaging, analyzed by deep learning (DL) models combining domain knowledge, has been employed for the prediction. However, these DL models utilized late fusion, restricting the interaction between domain knowledge and images during feature extraction, thereby limiting the prediction performance and compromising decision-making interpretability.

METHODS

We propose a novel Vision Transformer (ViT)-based DL network, referred to as Dual-Style ViT (DSViT), to augment the interaction between domain knowledge and images and the effective fusion among multi-phase CT images for improving both predictive performance and interpretability. We apply the DSViT to develop pre-/post-operative models for predicting ER. Within DSViT, to balance the utilization between domain knowledge and images within DSViT, we propose an adaptive self-attention mechanism. Moreover, we present an attention-guided supervised learning module for balancing the contributions of multi-phase CT images to prediction and a domain knowledge self-supervision module for enhancing the fusion between domain knowledge and images, thereby further improving predictive performance. Finally, we provide the interpretability of the DSViT decision-making.

RESULTS

Experiments on our multi-phase data demonstrate that DSViTs surpass the existing models across multiple performance metrics and provide the decision-making interpretability. Additional validation on a publicly available dataset underscores the generalizability of DSViT.

CONCLUSIONS

The proposed DSViT can significantly improve the performance and interpretability of ER prediction, thereby fortifying the trustworthiness of artificial intelligence tool for HCC ER prediction in clinical settings.

What Imaging Modality Is More Effective in Predicting Early Recurrence of Hepatocellular Carcinoma after Hepatectomy Using Radiomics Analysis: CT or MRI or Both?

BACKGROUND

It is of great importance to predict the early recurrence (ER) of hepatocellular carcinoma (HCC) after hepatectomy using preoperative imaging modalities. Nevertheless, no comparative studies have been conducted to determine which modality, CT or MRI with radiomics analysis, is more effective.

METHODS

We retrospectively enrolled 119 HCC patients who underwent preoperative CT and MRI. A total of 3776 CT features and 4720 MRI features were extracted from the whole tumor. The minimum redundancy and maximum relevance algorithm (MRMR) and least absolute shrinkage and selection operator (LASSO) regression were applied for feature selection, then support vector machines (SVMs) were applied for model construction. Multivariable logistic regression analysis was employed to construct combined models that integrate clinical-radiological-pathological (CRP) traits and radscore. Receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) were used to compare the efficacy of CT, MRI, and CT and MRI models in the test cohort.

RESULTS

The CT model and MRI model showed no significant difference in the prediction of ER in HCC patients (p = 0.911). Radiomics^CT&MRI demonstrated a superior predictive performance than either Radiomics^CT or Radiomics^MRI alone (p = 0.032, 0.039). The combined CT and MRI model can significantly stratify patients at high risk of ER (area under the curve (AUC) of 0.951 in the training set and 0.955 in the test set) than the CT model (AUC of 0.894 and 0.784) and the MRI model (AUC of 0.856 and 0.787). DCA demonstrated that the CT and MRI model provided a greater net benefit than the models without radiomics analysis.

CONCLUSIONS

No significant difference was found in predicting the ER of HCC between CT models and MRI models. However, the multimodal radiomics model derived from CT and MRI can significantly improve the prediction of ER in HCC patients after resection.

Correlation between magnetic resonance images of peritumor margin enhancement and prognosis in hepatocellular carcinoma after drug-eluting bead transcatheter arterial chemoembolization

Purpose

The aim of this study is to investigate the morphological characteristics and clinical significance of magnetic resonance (MR) images of peritumor margin enhancement in hepatocellular carcinoma (HCC) after drug-eluting bead transcatheter arterial chemoembolization (DEB-TACE).

Methods

From January 2017 to December 2020, a total of 162 patients who received a diagnosis of HCC were included in our study. We began the follow-up with magnetic resonance imaging (MRI) for complete response assessment, and peritumor margin enhancements were classified as sharp and rough types according to morphology. During the follow-up, data such as progression or remission of the two enhancement modalities, morphological changes in terms of margin enhancements observed in MR images, and alpha-fetoprotein (AFP) levels were recorded.

Results

In the follow-up period of 36 months, 70 and 92 patients with sharp- and rough-type peritumor margins, respectively, were observed. At the end of the follow-up, patients with sharp-type margins had lower AFP levels and longer progression-free survival than those with rough-type margins (P < 0.05). Furthermore, the sharp-type margin was thinner than the rough-type margin (all P < 0.05). Moreover, the sharp-type group had a high incidence of tumors with a diameter of < 5 cm, whereas the rough-type group had a high incidence of tumors with a diameter of ≥ 5 cm. Continuous enhancements of peritumor margins in MRI were greater in the sharp-type group than in the rough-type group. Most of the patients with a sharp-type margin achieved disease remission (94.3%, P < 0.05), whereas most of those with a rough-type margin experienced disease progression (84.8%, P < 0.05).

Conclusions

Patients with HCC with a sharp-type margin enhancement on MRI after DEB-TACE mostly demonstrated benign lesions with a good prognosis, whereas those with a rough-type margin mostly demonstrated malignant growth.

Predicting hepatocellular carcinoma early recurrence after ablation based on magnetic resonance imaging radiomics nomogram

BACKGROUND

The aim of this study is to investigate a model for predicting the early recurrence of hepatocellular carcinoma (HCC) after ablation.

METHODS

A total of 181 patients with HCC after ablation (train group was 119 cases; validation group was 62 cases) were enrolled. The cases of early recurrence in the set of train and validation were 63 and 31, respectively. Radiomics features were extracted from the enhanced magnetic resonance imaging scanning, including pre-contrast injection, arterial phase, late arterial phase, portal venous phase, and delayed phase. The least absolute shrinkage and selection operator cox proportional hazards regression after univariate and multivariate analysis was used to screen radiomics features and build integrated models. The nomograms predicting recurrence and survival of patients of HCC after ablation were established based on the clinical, imaging, and radiomics features. The area under the curve (AUC) of the receiver operating characteristic curve and C-index for the train and validation group was used to evaluate model efficacy.

RESULTS

Four radiomics features were selected out of 34 texture features to formulate the rad-score. Multivariate analyses suggested that the rad-score, number of lesions, integrity of the capsule, pathological type, and alpha-fetoprotein were independent influencing factors. The AUC of predicting early recurrence at 1, 2, and 3 years in the train group was 0.79 (95% CI: 0.72-0.88), 0.72 (95% CI: 0.63-0.82), and 0.71 (95% CI: 0.61-0.83), respectively. The AUC of predicting early recurrence at 1, 2, and 3 years in the validation group was 0.72 (95% CI: 0.58-0.84), 0.61 (95% CI: 0.45-0.78) and 0.64 (95% CI: 0.40-0.87).

CONCLUSION

The model for early recurrence of HCC after ablation based on the clinical, imaging, and radiomics features presented good predictive performance. This may facilitate the early treatment of patients.

Multi-Sequence MR-Based Radiomics Signature for Predicting Early Recurrence in Solitary Hepatocellular Carcinoma ≤5 cm

Purpose

To investigate the value of radiomics features derived from preoperative multi-sequence MR images for predicting early recurrence (ER) in patients with solitary hepatocellular carcinoma (HCC) ≤5 cm.

Methods

One hundred and ninety HCC patients were enrolled and allocated to training and validation sets (n = 133:57). The clinical–radiological model was established by significant clinical risk characteristics and qualitative imaging features. The radiomics model was constructed using the least absolute shrinkage and selection operator (LASSO) logistic regression algorithm in the training set. The combined model was formed by integrating the clinical–radiological risk factors and selected radiomics features. The predictive performance was assessed by the area under the receiver operating characteristic curve (AUC).

Results

Arterial peritumoral hyperenhancement, non-smooth tumor margin, satellite nodules, cirrhosis, serosal invasion, and albumin showed a significant correlation with ER. The AUC of the clinical–radiological model was 0.77 (95% CI: 0.69–0.85) and 0.76 (95% CI: 0.64–0.88) in the training and validation sets, respectively. The radiomics model constructed using 12 radiomics features selected by LASSO regression had an AUC of 0.85 (95% CI: 0.79–0.91) and 0.84 (95% CI: 0.73–0.95) in the training and validation sets, respectively. The combined model further improved the prediction performance compared with the clinical–radiological model, increasing AUC to 0.90 (95% CI: 0.85–0.95) in the training set and 0.88 (95% CI: 0.80–0.97) in the validation set (p < 0.001 and p = 0.012, respectively). The calibration curve fits well with the standard curve.

Conclusions

The predictive model incorporated the clinical–radiological risk factors and radiomics features that could adequately predict the individualized ER risk in patients with solitary HCC ≤5 cm.

Knockdown of ST6Gal-I expression in human hepatocellular carcinoma cells inhibits their exosome-mediated proliferation- and migration-promoting effects

Abnormal sialylation is a distinctive feature of human hepatocellular carcinoma (HCC) and is closely related to its malignant properties. Exosomes have characteristic protein and lipid composition; however, the results concerning glycoprotein composition and glycosylation are scarce. In this study, liquid chromatography-tandem mass spectrometry (LC-MS/MS) identified multiple microvesicle-related sialylated proteins including CD63, a classic marker of exosomes. The silencing of α2,6-sialyltransferase I (ST6Gal-I) significantly reduced the levels of α2,6-sialylated glycoconjugates on CD63 and the surface of HCC-derived exosomes (HCC-exo). And surface glycoconjugates play important roles in exosomes biogenesis and in their interaction with other cells. Compared to exosomes derived from naive HCC cells, α2,6-sialylation degradation abolished both the proliferation-promoting and migration-promoting effects of HCC-exo. Further analysis revealed that the Akt/GSK-3β or JNK1/2 signaling mediates HCC-exo-mediated proliferation in HCC cells, while ST6Gal-I silencing deactivated this pathway. These findings suggest that a loss of α2,6-sialylation decreases HCC progression through the loss of cancer cell-derived exosomes; furthermore, it opens novel perspectives to further explore the functional role of glycans in the biology of exosomes.

Intrahepatic recurrence of hepatocellular carcinoma after resection: an update

Hepatocellular carcinoma recurrence occurs in 40-70% of patients after hepatic resection. Despite the high frequency of hepatocellular cancer relapse, there is no established guidance for the management of such cases. The evaluation of prognostic factors that indicate a high risk of recurrence after surgery such as the tumor number and size and the presence of microvascular invasion may guide the therapeutic strategy and point out which patients should be strictly monitored. Additionally, the administration of adjuvant treatment or ab initio liver transplantation in selected patients with high-risk characteristics could have a significant impact on the prevention of relapse and overall survival. Once the recurrence has occurred in the liver remnant, the available therapeutic options include re-resection, salvage liver transplantation and locoregional treatments, although the therapeutic choice is often challenging and should be based on the characteristics of the recurrent tumor, the patient profile and most importantly the timing of relapse. Aggressive combination treatments are often required in challenging cases of early relapse. The results of the above treatment strategies are reviewed and compared to determine the optimal management of patients with recurrent hepatocellular cancer following liver resection.

Preoperative MR imaging for predicting early recurrence of solitary hepatocellular carcinoma without microvascular invasion

OBJECTIVES

This study aimed to identify preoperative MR imaging features for predicting early recurrence after curative resection of solitary hepatocellular carcinoma (HCC) without microvascular invasion (MVI).

METHODS

124 patients with MVI-negative HCC who underwent preoperative dynamic contrast-enhanced 1.5-T MR imaging before surgical resection were included. Liver Imaging Reporting and Data System (LI-RADS v2018) imaging features and three non-LI-RADS MR imaging features for predicting early recurrence (intrahepatic recurrence<2 years) were identified by univariable and multivariable analyses. A nomogram was constructed for individualized risk estimation, and its predictive accuracy and discriminative ability were identified by concordance index (C-index) and calibration curve.

RESULTS

In multivariable analysis, tumor size (p = 0.045), nonsmooth tumor margin (p = 0.013), and presence of mosaic architecture (p = 0.035) were independent significant variables associated with early recurrence. These were all incorporated to establish the nomogram. The C-index of the nomogram was 0.743 (95 % CI: 0.697-0.788).

CONCLUSION

At dynamic contrast-enhanced MR imaging, tumor size, nonsmooth tumor margin, and presence of mosaic architecture may be helpful to predict early recurrence of solitary HCC without MVI after curative resection.

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.

Predicting Hepatocellular Carcinoma Recurrence Beyond Milan Criteria After Liver Resection for Solitary Hepatocellular Carcinoma

BACKGROUND AND PURPOSE

Several hepatectomy patients with HCC who are initially transplantable (within MC) developed untransplantable HCC recurrence (beyond MC) after primary curative liver resection. The purpose of our study is to identify the risk factors of untransplantable hepatocellular carcinoma (HCC) recurrence after primary curative resection of solitary HCC and solitary HCC within Milan criteria (MC).

METHODS

We retrospectively reviewed 592 patients with recurrent HCC who underwent liver resection due to solitary HCC between 2005 and 2011.

RESULTS

All patients were Child-Pugh class A. At primary curative hepatectomy, 411 patients (69.4%) were diagnosed with HCC within MC and 181 patients (30.6%) had HCC beyond MC. The mean time from primary hepatectomy to recurrence was 14 months (range, 1-116 months). At HCC recurrence, 93 patients (15.7%) were diagnosed beyond MC. Multivariate analysis showed that microvascular invasion and a tumor grade of 3 or 4 were closely associated with a high risk of HCC recurrence beyond MC in patients who had hepatectomy for solitary HCC. Of the 411 patients within MC at primary curative hepatectomy, 54 patients (13.9%) developed HCC recurrence beyond MC. Multivariate analysis also showed that microvascular invasion and a tumor grade of 3 or 4 were closely associated with HCC recurrence beyond MC in these patients.

CONCLUSIONS

The present study suggests that the presence of certain unfavorable histological factors in patients who underwent initial liver resection of transplantable HCC within MC with good liver function predicted the development of recurrent HCC beyond MC.

Circulating exosomal miRNAs: clinical significance in human cancers

Introduction: The identification of novel noninvasive biomarkers to ameliorate early-diagnosis, and disease prognosis, as well as to support personalized treatment and monitoring decisions is of first clinical priority for cancer patients' care. Exosomes are natural endosome-derived extracellular vesicles that have emerged as crucial mediators of intercellular communication and tumor progression. Considering that deregulated miRNA levels have been described in numerous human malignancies and that tumor-derived exosomes reflect miRNA expression of donor tumor cells, the evaluation of exosome-derived circulating miRNAs (exomiRs) may offer a new promising class of noninvasive molecular markers to improve patients' management and quality-of-life. Areas covered: In the current review we have summarized the existing knowledge on the clinical relevance of circulating exosomal miRNAs in improving cancer diagnosis and prognosis, and thus supporting personalized patients' management Expert commentary: Cancer research has highlighted the abundance of exomiRs in patients' plasma and serum samples, as well as their biomarker capabilities in the vast majority of human malignancies studied so far. Their analytical stability constitutes exomiRs ideal molecular markers to overcome numerous limitations of cancer clinical management, while future large-scale studies should unveil exomiRs translational utility in modern cancer molecular diagnostics.

Preoperative color Doppler ultrasonography predicts early recurrence in AFP-positive hepatocellular carcinoma

The present study aimed to evaluate the hepatic hemodynamics of patients with α-fetoprotein (AFP)-positive hepatocellular carcinoma (HCC) and early recurrence (ER), as determined by color Doppler ultrasound. Screening with color Doppler ultrasound was performed in 150 patients with AFP-positive HCC, yielding 43 cases with postoperative ER. In addition, 35 healthy controls were enrolled in the study for comparison of the blood flow parameters between the healthy control and the HCC groups. Receiver operating characteristic curve analysis was performed to evaluate the predicted effect of Doppler for the ER of HCC. The average mean flow velocity of portal vein in patients with HCC (14.686±5.873 cm/s) was significantly lower in the HCC group compared with the healthy control group (17.631±3.569 cm/s; P=0.005). Additionally, the preoperative portal vein diameter in the HCC group was significantly higher compared with that in the healthy control group (P=0.001). Regarding the effect of surgery, the portal vein diameter was significantly increased in the patients postoperatively compared with preoperatively (P=0.003), while the pulsation and resistance indexes exhibited a decreasing trend in the postoperative group (P=0.001 and P=0.003, respectively). Notably, patients with HCC and ER presented with a higher resistance index (1.163±0.342) compared with the ER-free group (1.023±0.176; P=0.004). Furthermore, a significant difference in hepatic artery pulsation index was also observed between the ER group (0.673±0.075) and the ER-free group (0.624±0.056; P=0.018), indicating that an increased hepatic artery pulsation index may significantly predict the ER of HCC. In addition, areas under the curve of 0.683 and 0.700, respectively, suggested that the hepatic artery resistance and pulsation indexes may be used to diagnose ER in HCC (P=0.009 and P=0.004, respectively). Taken together, Doppler ultrasound provides a reliable and accurate quantification of hepatic hemodynamics for detecting ER in HCC with a good diagnostic accuracy.

Outcomes and Prognostic Factors of Spontaneously Ruptured Hepatocellular Carcinoma

BACKGROUND

Spontaneous tumor rupture is a rare and life-threatening complication of hepatocellular carcinoma (HCC). The best treatment strategy remains unclear.

METHODS

The clinical data of 137 patients with spontaneously ruptured HCC from 2010 to 2015 were reviewed retrospectively. We investigated the outcome and prognostic factors of various treatment strategies.

RESULTS

Of the 137 patients, 53, 45, 3, and 36 patients underwent transcatheter arterial chemoembolization (TACE) alone, liver resection (LR) (LR alone or TACE + LR), surgical hemostasis, and conservative therapy. The patients undergoing LR had longest overall survival (OS). In the TACE alone group, independent factors affecting 30-day mortality were MELD score ≥ 12, AFP ≥ 1000 ng/ml, and largest tumor size ≥ 10 cm. AFP ≥ 1000 ng/ml, largest tumor size ≥ 10 cm, and no tumor capsule were significantly associated with poorer OS. In the LR group, largest tumor size ≥ 10 cm and no tumor capsule were the only independent prognostic factors for poorer OS and recurrence-free survival (RFS). Hypovolemic shock was an independent prognostic factor for poorer OS. The differences in OS between the TACE + LR group and LR alone group were not significant (P = 0.955). However, the RFS is significantly better in the LR alone group than those in the TACE + LR group (P = 0.031).

CONCLUSION

For resectable tumor, LR is the treatment of choice for patients with spontaneous ruptured HCC and preserved liver function. The delay in LR due to preoperative TACE may account for its worse RFS compared with LR alone. In patients with an unresectable tumor, TACE therapy alone improved survival over conservative therapy.

Outcomes and Prognostic Factors of Spontaneously Ruptured Hepatocellular Carcinoma

BACKGROUND

Spontaneous tumor rupture is a rare and life-threatening complication of hepatocellular carcinoma (HCC). The best treatment strategy remains unclear.

METHODS

The clinical data of 137 patients with spontaneously ruptured HCC from 2010 to 2015 were reviewed retrospectively. We investigated the outcome and prognostic factors of various treatment strategies.

RESULTS

Of the 137 patients, 53, 45, 3, and 36 patients underwent transcatheter arterial chemoembolization (TACE) alone, liver resection (LR) (LR alone or TACE + LR), surgical hemostasis, and conservative therapy. The patients undergoing LR had longest overall survival (OS). In the TACE alone group, independent factors affecting 30-day mortality were MELD score ≥ 12, AFP ≥ 1000 ng/ml, and largest tumor size ≥ 10 cm. AFP ≥ 1000 ng/ml, largest tumor size ≥ 10 cm, and no tumor capsule were significantly associated with poorer OS. In the LR group, largest tumor size ≥ 10 cm and no tumor capsule were the only independent prognostic factors for poorer OS and recurrence-free survival (RFS). Hypovolemic shock was an independent prognostic factor for poorer OS. The differences in OS between the TACE + LR group and LR alone group were not significant (P = 0.955). However, the RFS is significantly better in the LR alone group than those in the TACE + LR group (P = 0.031).

CONCLUSION

For resectable tumor, LR is the treatment of choice for patients with spontaneous ruptured HCC and preserved liver function. The delay in LR due to preoperative TACE may account for its worse RFS compared with LR alone. In patients with an unresectable tumor, TACE therapy alone improved survival over conservative therapy.

Value of Imaging Findings in the Prediction of Microvascular Invasion in Hepatocellular Carcinoma

BACKGROUND

The purpose of this study was to determine the utility of some imaging findings in predicting microvascular invasion (MVI) and hepatocellular carcinoma (HCC) recurrence risk after liver transplantation.

METHOD

This retrospective study included 123 patients with histopathologically proven HCC at explant. All HCCs were classified as MVI positive (group I) or negative (group II) based on histopathological findings. In each group, multifocality, largest tumor size, bulging (tumor causing liver capsule expansion), beak sign (the acute angle between the tumor and liver parenchyma), and diffusion restriction on diffusion weighted images (DWI) were evaluated. These findings were compared between the groups by Student's t test. The relation between the parameters and MVI was analyzed by using the Spearman's correlation test.

RESULTS

Of the total patients, 30.1% had MVI (group I) and 69.9% (group II) did not have MVI. Presence of beak sign (P ≤ .005), bulging sign (P = .002), and diffusion restriction (P = .045) were significantly more frequent in group I than group II. The beak sign, bulging sign, and diffusion restriction were correlated with presence of MVI. Largest tumor size and multifocality were higher in group I than group II, but the differences were not statistically significant.

CONCLUSION

Radiologists and transplant surgeons should be aware of some clue imaging findings, especially beak and bulging signs because these findings may predict the presence of MVI in HCC. These patients might benefit from histologic confirmation of the tumor characteristics through biopsy and subsequent bridging treatment options before liver transplantation to reduce the risk of recurrence.

Prognostic value of preoperative computed tomography in HBV-related hepatocellular carcinoma patients after curative resection

Background: Preoperative treatments are considered for patients with worse outcome to improve overall survival and reduce tumor relapse. This study developed a prognostic risk estimation for patients with hepatitis B virus (HBV)-related solitary hepatocellular carcinoma after curative resection, including preoperative computed tomography (CT) signatures. Methods: Preoperative multiphasic CTs for 166 patients with operable HCC were performed in our hospital from 15 November 2013 through 15 May 2015. Follow-up information, until 5 June 2017, included: CT, pathological and clinical characteristics, and recurrence and metastases of HCC confirmed by pathological or radiological diagnosis. The parameters were analyzed by the Kaplan-Meier method and Cox proportional hazards regression analysis. Results: In multivariate analyses, overall survival was not significantly associated with any of the analyzed prognostic risk factors, but did show that the following were significant prognostic risk factors for disease-free survival: larger tumor size, positive radiogenomic venous invasion, non-smooth tumor margin, and histological microvascular invasion. These were all incorporated into the nomogram. The calibration curves for predicting the probability of disease-free survival between the nomogram and actual observation showed good conformity. Conclusion: In patients with HBV-related HCC, CT signatures were a noninvasive significant indicator of disease-free survival. Thus, consideration of CT signatures may optimize preoperative treatment strategies for the individual patient.

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

BACKGROUND

This study was performed to prospectively develop and validate a radiomics nomogram for predicting postoperative early recurrence (≤1 year) of hepatocellular carcinoma (HCC) using whole-lesion radiomics features on preoperative gadoxetic acid-enhanced magnetic resonance (MR) images.

METHODS

In total, 155 patients (training cohort: n = 108; validation cohort: n = 47) with surgically confirmed HCC were enrolled in this IRB-approved prospective study. Three-dimensional whole-lesion regions of interest were manually delineated along the tumour margins on multi-sequence MR images. Radiomics features were generated and selected to build a radiomics score using the least absolute shrinkage and selection operator (LASSO) method. Clinical characteristics and qualitative imaging features were identified by two independent radiologists and combined to establish a clinical-radiological nomogram. A radiomics nomogram comprising the radiomics score and clinical-radiological risk factors was constructed based on multivariable logistic regression analysis. Diagnostic performance and clinical usefulness were measured by receiver operation characteristic (ROC) and decision curves.

RESULTS

In total, 14 radiomics features were selected to construct the radiomics score. For the clinical-radiological nomogram, the alpha-fetoprotein (AFP) level, gross vascular invasion and non-smooth tumour margin were included. The radiomics nomogram integrating the radiomics score with clinical-radiological risk factors showed better discriminative performance (AUC = 0.844, 95%CI, 0.769 to 0.919) than the clinical-radiological nomogram (AUC = 0.796, 95%CI, 0.712 to 0.881; P = 0.045), with increased clinical usefulness confirmed using a decision curve analysis.

CONCLUSIONS

Incorporating multiple predictive factors, the radiomics nomogram demonstrated great potential in the preoperative prediction of early HCC recurrence after surgery.

Exosomes and Hepatocellular Carcinoma: From Bench to Bedside

As hepatocellular carcinoma (HCC) usually occurs in the background of cirrhosis, which is an end-stage form of liver diseases, treatment options for advanced HCC are limited, due to poor liver function. The exosome is a nanometer-sized membrane vesicle structure that originates from the endosome. Exosome-mediated transfer of proteins, DNAs and various forms of RNA, such as microRNA (miRNA), long noncoding RNA (lncRNA) and messenger RNA (mRNA), contributes to the development of HCC. Exosomes mediate communication between both HCC and non-HCC cells involved in tumor-associated cells, and several molecules are implicated in exosome biogenesis. Exosomes may be potential diagnostic biomarkers for early-stage HCC. Exosomal proteins, miRNAs and lncRNAs could provide new biomarker information for HCC. Exosomes are also potential targets for the treatment of HCC. Notably, further efforts are required in this field. We reviewed recent literature and demonstrated how useful exosomes are for diagnosing patients with HCC, treating patients with HCC and predicting the prognosis of HCC patients.

Texture analysis on gadoxetic acid enhanced-MRI for predicting Ki-67 status in hepatocellular carcinoma: A prospective study

Objective

To investigate the value of whole-lesion texture analysis on preoperative gadoxetic acid enhanced magnetic resonance imaging (MRI) for predicting tumor Ki-67 status after curative resection in patients with hepatocellular carcinoma (HCC).

Methods

This study consisted of 89 consecutive patients with surgically confirmed HCC. Texture features were extracted from multiparametric MRI based on whole-lesion regions of interest. The Ki-67 status was immunohistochemical determined and classified into low Ki-67 (labeling index ≤15%) and high Ki-67 (labeling index >15%) groups. Least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression were applied for generating the texture signature, clinical nomogram and combined nomogram. The discrimination power, calibration and clinical usefulness of the three models were evaluated accordingly. Recurrence-free survival (RFS) rates after curative hepatectomy were also compared between groups.

Results

A total of 13 texture features were selected to construct a texture signature for predicting Ki-67 status in HCC patients (C-index: 0.878, 95% confidence interval: 0.791-0.937). After incorporating texture signature to the clinical nomogram which included significant clinical variates (AFP, BCLC-stage, capsule integrity, tumor margin, enhancing capsule), the combined nomogram showed higher discrimination ability (C-index: 0.936vs. 0.795, P<0.001), good calibration (P>0.05 in Hosmer-Lemeshow test) and higher clinical usefulness by decision curve analysis. RFS rate was significantly lower in the high Ki-67 group compared with the low Ki-67 group after curative surgery (63.27%vs. 85.00%, P<0.05).

Conclusions

Texture analysis on gadoxetic acid enhanced MRI can serve as a noninvasive approach to preoperatively predict Ki-67 status of HCC after curative resection. The combination of texture signature and clinical factors demonstrated the potential to further improve the prediction performance.

Peritumoral tissue on preoperative imaging reveals microvascular invasion in hepatocellular carcinoma: a systematic review and meta-analysis

BACKGROUND

Histologic microvascular invasion (MVI) substantially worsens the prognosis of patients with hepatocellular carcinoma, and can only be diagnosed postoperatively. Preoperative assessment of MVI by imaging has been focused on tumor-related features, while peritumoral imaging features have been indicated elsewhere to be more accurate. The aim of the present study is to evaluate the association between peritumoral imaging features and MVI.

METHODS

Literature search was performed using the PubMed, Embase, and Cochrane Library databases. Summary results of the association between peritumoral imaging features and MVI were presented as the odds ratio (OR) and the 95% confidence interval. Meta-regression and subgroup analyses were performed when heterogeneity was detected. Diagnostic accuracy analysis was also conducted for identified features.

RESULTS

Ten studies were included in the analysis. Moderate and low heterogeneities were found among the seven studies on peritumoral enhancement and four studies on peritumoral hypointensity on HBP, respectively. Summary results revealed a significant association between MVI and peritumoral enhancement (OR 4.04 [2.23, 7.32], p < 0.05), and peritumoral hypointensity on HBP (OR 10.62 [5.31, 21.26], p < 0.05). Diagnostic accuracy analysis revealed high specificity (0.90-0.94) but low sensitivity (0.29-0.40) for both features to assess MVI.

CONCLUSION

The two peritumoral imaging features are significantly associated with MVI. The two features highly suggest MVI only when present with a high false negative rate. Promotion of their diagnostic efficiency can be a worthwhile task for future research.

Preoperative computed tomography and serum α-fetoprotein to predict microvascular invasion in hepatocellular carcinoma

To determine the diagnostic value of computed tomography (CT) for prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC). Preoperative CTs for 160 patients with 57 MVI-positive and 103 MVI-negative HCCs diagnosed by surgical pathology were reviewed retrospectively. CT parameters and serum α-fetoprotein (AFP) level were analyzed in SPSS 16.0. Although univariate analysis showed that tumor size (P = .012), grade (Z = -2.114, P = .034), and peritumoral enhancement (χ = 4.464, P = .035) were associated with MVI, multiple logistic regression analysis showed that capsular invasion (odds ratio [OR] = 23.469, P < .001), margins (OR = 6.751, P < .001), and serum AFP level (OR = 1.001, P = .038) were associated with MVI in HCC (P < .05). Radiographic hepatic capsular invasion and nonsmooth tumor margins identified by preoperative CT images, along with AFP levels greater than 232.2 ng/mL, are important predictors of MVI.

Modification of the method to establish a hepatic VX2 carcinoma model in rabbits

The hepatic VX2 carcinoma model in rabbits is widely used for the preclinical study of hepatocellular carcinoma. In the present study, a modification was made to the conventional method to establish the animal model, as the conventional method gives rise to frequent tumor seeding due to the drop-out of tumor fragments. In order to evaluate each distinct method of establishing the model, the rabbits were divided into two groups: Group A (the conventional method; n=20) and group B (the modified method; n=20). All surgical details were recorded for reference. At 14 days post-surgery, contrast-enhanced computed tomography (CECT) and autopsy were conducted. Microscopic morphology of tumor cells was observed using hematoxylin and eosin (H&E) and transmission electron microscopy (TEM). Vascular endothelial growth factor (VEGF) and cluster of differentiation (CD)31 were detected via immunochemistry and reverse transcription-polymerase chain reaction. In total, 19 rabbits in each group succeeded in model establishment. Throughout the surgery, group A experienced a longer surgery time compared with group B (group A vs. group B, 22.57±1.34 vs. 20.17±1.50 min; P<0.001), an increased tumor fragment drop-out frequency (group A vs. group B, 1.84±0.96 vs. 1.16±0.38; P=0.008) and an increased peritoneal nodule incidence (group A vs. group B, 35 vs. 5%, P=0.042). As for CECT, H&E and TEM, hepatic VX2 allografts in the two groups demonstrated similar imaging presentations and tumor cell morphology. In addition, VEGF and CD31 levels did not differ between the two groups. In conclusion, the modified method for the establishment of hepatic VX2 carcinoma model in rabbits may decrease tumor fragment drop-out frequency during surgery and incidence of tumor seeding without affecting the properties of VX2 carcinoma.