Prediction of microvascular invasion of hepatocellular carcinoma by pre-operative CT imaging

Evaluation of Preoperative Microvascular Invasion in Hepatocellular Carcinoma Through Multidimensional Parameter Combination Modeling Based on Gd-EOB-DTPA MRI

BACKGROUND AND AIMS

The study established and compared the efficacy of the clinicoradiological model, radiomics model and clinicoradiological-radiomics hybrid model in predicting the microvascular invasion (MVI) of hepatocellular carcinoma (HCC) using gadolinium ethoxybenzyl diethylene triaminepentaacetic acid (Gd-EOB-DTPA) enhanced MRI.

METHODS

This was a study that enrolled 602 HCC patients from two institutions. Least absolute shrinkage and selection operator (Lasso) method was used to screen for the most important clinicoradiological and radiomics features that predict MVI pre-operatively. Three machine learning algorithms were used to establish the clinicoradiological, radiomics, and clinicoradiological-radiomics hybrid models. Area under the curve (AUC) of receiver operating characteristic (ROC) curves and Delong's test were used to compare and quantify the predictive performance of the models.

RESULTS

The AUCs of the clinicoradiological model in training and validation cohorts were 0.793 and 0.701, respectively. The radiomics signature of arterial phase (AP) images alone achieved satisfying predictive efficacy for MVI, with AUCs of 0.671 and 0.643 in training and validation cohort, respectively. The combination of clinicoradiological factors and fusion radiomics signature of AP and VP images achieved AUCs of 0.824 and 0.801 in training and validation cohorts, 0.812 and 0.805 in prospective validation and external validation cohorts, respectively. The hybrid model provided the best prediction results. The results of the Delong test revealed that there were statistically significant differences among the clinicoradiological-radiomics hybrid model, clinicoradiological model, and radiomics model (p<0.05).

CONCLUSIONS

The combination of clinicoradiological factors and fusion radiomics signature of AP and VP images based on Gd-EOB-DTPA-enhanced MRI can effectively predict MVI.

Transarterial chemoembolization failure in patients with hepatocellular carcinoma: Incidence, manifestation and risk factors

BACKGROUND

To identify the incidence, manifestation and risk factors of transarterial chemoembolization (TACE) failure defined as untreatable progression (UP) in patients with hepatocellular carcinoma (HCC) on short-term observation.

METHODS

Patients from two hospitals with HCC treated with TACE were considered. According to the definition of UP, TACE failure was considered to be present in at least one of the following situations: situation I, failure to achieve objective response in the targeted tumor after at least two initial TACE treatments; situation II, failure to achieve objective response in local tumor progression or new intrahepatic tumor after another TACE session; situation III, presence of major progression; and situation IV, presence of impaired liver function or performance status that contraindicates TACE treatment. Patients were assessed for TACE failure on follow-up visits after two or three TACE sessions. Risk factors for TACE failure were evaluated with logistic regression analysis.

RESULTS

A total of 206 patients were included. TACE failure occurred in 42 (42/206, 20.4%) patients, of whom 21, 1, 4, 0 and 16 patients manifested as situation I, II, III, IV alone, and combination of situation I with the others, respectively. Multivariate analysis showed that tumor without complete capsule (P < .001) and non-smooth margin (P = .004) were independent predictors of the presence of TACE failure.

CONCLUSIONS

TACE failure was uncommon in patients with HCC, which manifested predominantly as failure of treatment response of the initial intrahepatic tumor. Non-smooth tumor margin and tumors without complete capsule were associated with the presence of TACE failure.

A Synopsis of Artificial Intelligence and its Applications in Surgery

Artificial intelligence (AI) has made steady in-roads into the healthcare scenario over the last decade. While widespread adoption into clinical practice remains elusive, the outreach of this discipline has progressed beyond the physician scientist, and different facets of this technology have been incorporated into the care of surgical patients. New AI applications are developing at rapid pace, and it is imperative that the general surgeon be aware of the broad utility of AI as applicable in his or her day-to-day practice, so that healthcare continues to remain up-to-date and evidence based. This review provides a broad account of the tip of the AI iceberg and highlights it potential for positively impacting surgical care.

Can a proposed double branch multimodality-contribution-aware TripNet improve the prediction performance of the microvascular invasion of hepatocellular carcinoma based on small samples?

OBJECTIVES

To evaluate the potential improvement of prediction performance of a proposed double branch multimodality-contribution-aware TripNet (MCAT) in microvascular invasion (MVI) of hepatocellular carcinoma (HCC) based on a small sample.

METHODS

In this retrospective study, 121 HCCs from 103 consecutive patients were included, with 44 MVI positive and 77 MVI negative, respectively. A MCAT model aiming to improve the accuracy of deep neural network and alleviate the negative effect of small sample size was proposed and the improvement of MCAT model was verified among comparisons between MCAT and other used deep neural networks including 2DCNN (two-dimentional convolutional neural network), ResNet (residual neural network) and SENet (squeeze-and-excitation network), respectively.

RESULTS

Through validation, the AUC value of MCAT is significantly higher than 2DCNN based on CT, MRI, and both imaging (P < 0.001 for all). The AUC value of model with single branch pretraining based on small samples is significantly higher than model with end-to-end training in CT branch and double branch (0.62 vs 0.69, p=0.016, 0.65 vs 0.83, p=0.010, respectively). The AUC value of the double branch MCAT based on both CT and MRI imaging (0.83) was significantly higher than that of the CT branch MCAT (0.69) and MRI branch MCAT (0.73) (P < 0.001, P = 0.03, respectively), which was also significantly higher than common-used ReNet (0.67) and SENet (0.70) model (P < 0.001, P = 0.005, respectively).

CONCLUSION

A proposed Double branch MCAT model based on a small sample can improve the effectiveness in comparison to other deep neural networks or single branch MCAT model, providing a potential solution for scenarios such as small-sample deep learning and fusion of multiple imaging modalities.

Radiological Features of Microvascular Invasion of Hepatocellular Carcinoma in Patients with Non-Alcoholic Fatty Liver Disease

Background: The aim of the present study was to evaluate the presence and the prognostic value of the radiological signs of microvascular invasion (MVI) of hepatocellular carcinoma (HCC) in patients with non-alcoholic fatty liver disease (NAFLD). Methods: Between January 2015 and December 2017, all patients (91 patients) with de novo HCC or HCC recurrence occurring at least 2 years after the last treatment in NAFLD (36 patients) or with hepatitis C virus (HCV) liver disease (55 patients) were included. Each HCC was treated with liver resection and transplantation to obtain the anatomopathological confirmation of MVI. All patients had at least one available computed tomography (CT) scan or magnetic resonance imaging (MRI) performed no more than one month prior to the treatment. The clinical data of each patient, tumor burden (diameter, margins, two-trait predictor of venous invasion (TTPVI), and peritumoral enhancement), the recurrence rate (RR) after a 1-year follow-up, and the time to recurrence (TTR) were collected. Results: The NAFLD–HCC nodules were larger as compared to HCV–HCC (51 mm vs. 36 mm, p = 0.004) and showed a higher prevalence of TTPVI (38.9 vs. 20.0%, p = 0.058). At multivariate analysis, nodule diameter >50 mm was found to be the only independent prognostic factor of TTPVI (hazard ratio: 21.3, 95% confidence interval: 4.2–107.7, p < 0.001), and the presence of TTPVI was confirmed to be the only independent prognostic factors of recurrence (hazard ratio: 2.349, 95% confidence interval: 1.369–4.032, p = 0.002). No correlations were found between TTR and irregular tumor margins or peritumoral enhancement. Conclusion: The NAFLD–HCC patients had larger tumors at diagnosis and showed a more frequent presence of radiological signs of MVI as compared to the HCV–HCC patients. The MVI was related to a more rapid recurrence after curative treatments, demonstrating the prognostic value of this radiological diagnosis.

Can lymphovascular invasion be predicted by contrast-enhanced CT imaging features in patients with esophageal squamous cell carcinoma? A preliminary retrospective study

Background

To investigate the value of contrast-enhanced CT (CECT)-derived imaging features in predicting lymphovascular invasion (LVI) status in esophageal squamous cell carcinoma (ESCC) patients.

Methods

One hundred and ninety-seven patients with postoperative pathologically confirmed esophageal squamous cell carcinoma treated in our hospital between January 2017 and January 2019 were enrolled in our study, including fifty-nine patients with LVI and one hundred and thirty-eight patients without LVI. The CECT-derived imaging features of all patients were analyzed. The CECT-derived imaging features were divided into quantitative features and qualitative features. The quantitative features consisted of the CT attenuation value of the tumor (CTV_Tumor), the CT attenuation value of the normal esophageal wall (CTV_Normal), the CT attenuation value ratio of the tumor-to-normal esophageal wall (TNR), the CT attenuation value difference between the tumor and normal esophageal wall (ΔTN), the maximum thickness of the tumor measured by CECT (Thickness), the maximum length of the tumor measured by CECT (Length), and the gross tumor volume measured by CECT (GTV). The qualitative features consisted of an enhancement pattern, tumor margin, enlarged blood supply or drainage vessels to the tumor (EVFDT), and tumor necrosis. For the clinicopathological characteristics and CECT-derived imaging feature analysis, the chi-squared test was used for categorical variables, the Mann–Whitney U test was used for continuous variables with a nonnormal distribution, and the independent sample t-test was used for the continuous variables with a normal distribution. The trend test was used for ordinal variables. The association between LVI status and CECT-derived imaging features was analyzed by univariable logistic analysis, followed by multivariable logistic regression and receiver operating characteristic (ROC) curve analysis.

Results

The CTV_Tumor, TNR, ΔTN, Thickness, Length, and GTV in the group with LVI were higher than those in the group without LVI (P < 0.05). A higher proportion of patients with heterogeneous enhancement pattern, irregular tumor margin, EVFDT, and tumor necrosis were present in the group with LVI (P < 0.05). As revealed by the univariable logistic analysis, the CECT-derived imaging features, including CTV_Tumor, TNR, ΔTN and enhancement pattern, Thickness, Length, GTV, tumor margin, EVFDT, and tumor necrosis were associated with LVI status (P < 0.05). Only the TNR (OR 8.655; 95% CI 2.125–37.776), Thickness (OR 6.531; 95% CI 2.410–20.608), and tumor margin (OR 4.384; 95% CI 2.004–9.717) were independent risk factors for LVI in the multivariable logistic regression analysis. The ROC curve analysis incorporating the above three CECT-derived imaging features showed that the area under the curve obtained by the multivariable logistic regression model was 0.820 (95% CI 0.754–0.885).

Conclusion

The CECT-derived imaging features, including TNR, Thickness, tumor margin, and their combination, can be used as predictors of LVI status for patients with ESCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12880-022-00804-7.

Nomograms for Predicting Hepatocellular Carcinoma Recurrence and Overall Postoperative Patient Survival

Background

Few studies have focused on the prognosis of patients with hepatocellular carcinoma (HCC) of Barcelona Clinic Liver Cancer (BCLC) stage 0‒C in terms of early recurrence and 5-years overall survival (OS). We sought to develop nomograms for predicting 5-year OS and early recurrence after curative resection of HCC, based on a clinicopathological‒radiological model. We also investigated whether different treatment methods influenced the OS of patients with early recurrence.

Methods

Retrospective data, including clinical pathology, radiology, and follow-up data, were collected for 494 patients with HCC who underwent hepatectomy. Nomograms estimating OS and early recurrence were constructed using multivariate Cox regression analysis, based on the random survival forest (RSF) model. We evaluated the discrimination and calibration abilities of the nomograms using concordance indices (C-index), calibration curves, and Kaplan‒Meier curves. OS curves of different treatments for patients who had recurrence within 2 years after curative surgery were depicted and compared using the Kaplan–Meier method and the log-rank test.

Results

Multivariate Cox regression revealed that BCLC stage, non-smooth margin, maximum tumor diameter, age, aspartate aminotransferase levels, microvascular invasion, and differentiation were prognostic factors for OS and were incorporated into the nomogram with good predictive performance in the training (C-index: 0.787) and testing cohorts (C-index: 0.711). A nomogram for recurrence-free survival was also developed based on four prognostic factors (BCLC stage, non-smooth margin, maximum tumor diameter, and microvascular invasion) with good predictive performance in the training (C-index: 0.717) and testing cohorts (C-index: 0.701). In comparison to the BCLC staging system, the C-index (training cohort: 0.787 vs. 0.678, 0.717 vs. 0.675; external cohort 2: 0.748 vs. 0.624, 0.729 vs. 0.587 respectively, for OS and RFS; external cohort1:0.716 vs. 0.627 for RFS, all p value<0.05), and model calibration curves all showed improved performance. Patients who underwent surgery after tumor recurrence had a higher reOS than those who underwent comprehensive treatments and supportive care.

Conclusions

The nomogram, based on clinical, pathological, and radiological factors, demonstrated good accuracy in estimating OS and recurrence, which can guide follow-up and treatment of individual patients. Reoperation may be the best option for patients with recurrence in good condition.

Can Lymphovascular Invasion be Predicted by Preoperative Contrast-Enhanced CT in Esophageal Squamous Cell Carcinoma?

Objective: To explore whether preoperative contrast-enhanced computed tomogrpahy (CT) can predict lymphovascular invasion (LVI) in esophageal squamous cell carcinoma (ESCC), and provide a reliable reference for the formulation of clinical individualized treatment plans. Methods: This retrospective study enrolled 228 patients with surgically resected and pathologically confirmed ESCC, including 36 patients with LVI and 192 patients without LVI. All patients underwent contrast-enhanced CT (CECT) scan within 2 weeks before the operation. Tumor size (including tumor length and maximum tumor thickness), tumor-to-normal wall enhancement ratio (TNR), and gross tumor volume (GTV) were obtained. All clinical features and CECT-derived parameters associated with LVI were analyzed by univariate and multivariate analysis. The independent predictors for LVI were identified, and their combination was built by multivariate logistic regression analysis, using the significant variables from the univariate analysis as inputs. Results: Univariate analysis of clinical features and CECT-derived parameters revealed that age, TNR, and clinical N stage (cN stage) were significantly associated with LVI. The multivariable analysis results demonstrated that age (odds ratio [OR]: 5.32, 95% confidence interval [CI]: 2.224-12.743, P<.001), TNR (OR: 5.399, 95% CI: 1.609-18.110, P  =  .006), and cN stage (cN1: OR: 2.874, 95% CI: 1.182-6.989, P  =  .02; cN2: OR: 6.876, 95% CI: 2.222-21.227) were identified to be independent predictors for LVI. The combination of age, TNR, and cN stage achieved a relatively higher area under the curve (AUC) (0.798), accuracy (ACC) (65.4%), sensitivity (SEN) (69.4%), specificity (SPE) (79.7%), positive predictive value (PPV) (77.4%), and negative predictive value (NPV) (71.6%). Conclusions: The combination of clinical features and CECT-derived parameters may be effective in predicting LVI status preoperatively in ESCC.

Deep convolutional neural network for preoperative prediction of microvascular invasion and clinical outcomes in patients with HCCs

OBJECTIVES

We aimed to develop and validate a deep convolutional neural network (DCNN) model for preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) and its clinical outcomes using contrast-enhanced computed tomography (CECT) in a large population of candidates for surgery.

METHODS

This retrospective study included 1116 patients with HCC who had undergone preoperative CECT and curative hepatectomy. Radiological (R), DCNN, and combined nomograms were constructed in a training cohort (n = 892) respectively based on clinicoradiological factors, DCNN probabilities, and all factors; the performance of each model was confirmed in a validation cohort (n = 244). Accuracy and the AUC to predict MVI were calculated. Disease-free survival (DFS) and overall survival (OS) after surgery were recorded.

RESULTS

The proportion of MVI-positive patients was respectively 38.8% (346/892) and 35.7 % (87/244) in the training and validation cohorts. The AUCs of the R, DCNN, and combined nomograms were respectively 0.809, 0.929, and 0.940 in the training cohorts and 0.837, 0.865, and 0.897 in the validation cohort. The combined nomogram outperformed the R nomogram in the training (p < 0.001) and validation (p = 0.009) cohorts. There was a significant difference in DFS and OS between the R, DCNN, and combined nomogram-predicted groups with and without MVI (p < 0.001).

CONCLUSIONS

The combined nomogram based on preoperative CECT performs well for preoperative prediction of MVI and outcome.

KEY POINTS

• A combined nomogram based on clinical information, preoperative CECT, and DCNN can predict MVI and clinical outcomes of patients with HCC. • DCNN provides added diagnostic ability to predict MVI. • The AUCs of the combined nomogram are 0.940 and 0.897 in the training and validation cohorts, respectively.

Microvascular invasion may be the determining factor in selecting TACE as the initial treatment in patients with hepatocellular carcinoma

ABSTRACT

The aim of this study was to investigate factors affecting tumor necrosis with transcatheter arterial chemoembolization (TACE). Factors associated with early hepatocellular carcinoma recurrence after curative hepatectomy were also evaluated.Data of 51 patients who underwent surgery after a single session of TACE at a single university hospital were retrospectively analyzed. Factors that might affect tumor necrosis were determined by evaluating the TACE approach and by analyzing computed tomography and TACE findings, pathologic reports, and laboratory findings.In univariate analysis, microvascular invasion (MVI), radiological capsule appearance on the computed tomography, chronic hepatitis B, diabetes mellitus and serum albumin, MVI were significantly associated with tumor necrosis by TACE (P < .02). In multivariate analysis, MVI was the only statistically significant factor in TACE-induced tumor necrosis (P = .001). In univariate and multivariate analysis, MVI was the strongest factor for recurrence-free survival rate within 2 years (P = .008, P = .002).MVI could be a crucial factor in determining TACE as an initial treatment for hepatocellular carcinoma. MVI is also a strong indicator of recurrence within 2 years after curative hepatic resection.

Quantitative Ultrasound Image Analysis Helps in the Differentiation of Hepatocellular Carcinoma (HCC) From Borderline Lesions and Predicting the Histologic Grade of HCC and Microvascular Invasion

OBJECTIVES

Quantitative image analysis is one of the methods to overcome the lack of objectivity of ultrasound (US). The aim of this study was to clarify the correlation between the features from a US image analysis and the histologic grade and microvascular invasion (MVI) of hepatocellular carcinoma (HCC) and differentiation of HCC smaller than 2 cm from borderline lesions.

METHODS

We retrospectively analyzed grayscale US images with histopathologic evidence of HCC or a precancerous lesion using ImageJ version 1.47 software (National Institutes of Health, Bethesda, MD).

RESULTS

A total of 148 nodules were included (borderline lesion, n = 31; early HCC [eHCC], n = 3; well-differentiated HCC [wHCC], n = 16; moderately differentiated HCC [mHCC], n = 79; and poorly differentiated HCC [pHCC], n = 19). A multivariate analysis selected lower minimum gray values (odds ratio [OR], 0.431; P = .003) and a higher standard deviation (OR, 1.880; P = .019) as predictors of HCC smaller than 2 cm. Median (range) minimum gray values of borderline lesions, eHCC, wHCC, mHCC, and pHCC were 29 (0-103), 7 (0-47), 6 (0-60), 10 (0-53), and 2 (0-38), respectively, and gradually decreased from borderline lesions to pHCC (P < 0.001). The multivariate analysis showed a higher aspect ratio (OR, 2.170; P = .001) and lower minimum gray value (OR, 0.475; P = .043) as predictors of MVI. An anechoic area diagnosed by a subjective evaluation was correlated with the minimum gray value (P < .0001). The proportion of the anechoic area gradually increased from eHCC to pHCC (P = .031).

CONCLUSIONS

In a US image analysis, HCC smaller than 2 cm had features of greater heterogeneity and a lower minimum gray value than borderline lesions. Moderately differentiated HCC was smoother than borderline lesions, and the anechoic area correlated with histologic grading. Microvascular invasion was correlated with a slender shape and a lower minimum gray value.

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

PURPOSE

Microvascular invasion (MVI) is an important prognostic factor in patients with hepatocellular carcinoma (HCC). However, the reported results of magnetic resonance imaging (MRI) features for predicting MVI of HCC are variable and conflicting. Therefore, this meta-analysis aimed to identify the significant MRI features for MVI of HCC and to determine their diagnostic value.

METHODS

Original studies reporting the diagnostic performance of MRI for predicting MVI of HCC were identified in MEDLINE and EMBASE up until January 15, 2020. Study quality was assessed using QUADAS-2. A bivariate random-effects model was used to calculate the meta-analytic pooled diagnostic odds ratio (DOR) and 95% confidence interval (CI) for each MRI feature for diagnosing MVI in HCC. The meta-analytic pooled sensitivity and specificity were calculated for the significant MRI features.

RESULTS

Among 235 screened articles, we found 36 studies including 4,274 HCCs. Of the 15 available MRI features, 7 were significantly associated with MVI: larger tumor size (>5 cm) (DOR = 5.2, 95% CI [3.0-9.0]), rim arterial enhancement (4.2, 95% CI [1.7-10.6]), arterial peritumoral enhancement (4.4, 95% CI [2.8-6.9]), peritumoral hypointensity on hepatobiliary phase imaging (HBP) (8.2, 95% CI [4.4-15.2]), nonsmooth tumor margin (3.2, 95% CI [2.2-4.4]), multifocality (7.1, 95% CI [2.6-19.5]), and hypointensity on T1-weighted imaging (T1WI) (4.9, 95% CI [2.5-9.6]). Both peritumoral hypointensity on HBP and multifocality showed very high meta-analytic pooled specificities for diagnosing MVI (91.1% [85.4-94.8%] and 93.3% [74.5-98.5%], respectively).

CONCLUSIONS

Seven MRI features including larger tumor size, rim arterial enhancement, arterial peritumoral enhancement, peritumoral hypointensity on HBP, nonsmooth margin, multifocality, and hypointensity on T1WI were significant predictors for MVI of HCC. These MRI features predictive of MVI can be useful in the management of HCC.

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.

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.

Role of tumor margin and ADC change in defining the need for additional treatments after the first TACE in patients with unresectable HCC

PURPOSE

To define the number of TACE sessions needed to improve patients' overall survival (OS) in different subgroups of unresectable HCC.

METHODS

This retrospective cohort included 180 patients who got TACE between 2005-2016 as the initial treatment for unresectable HCC. Tumor margin (well- vs. ill-defined) was determined by two radiologists at baseline. Well-defined group was divided into two groups (ADC-responders vs. ADC-nonresponders) based on %ADC change (ΔADC-cutoff = 25 %). Accordingly, patients were categorized into three groups, ill-defined, well-defined ADC-responders, or well-defined ADC-nonresponders. Cox-analysis was used to compare the survival benefit of multiple TACE in different groups.

RESULTS

Ill-defined HCC (n = 108) was associated with worse survival (HR = 1.95,p < 0.001). Multiple TACE were associated with increased OS (HR = 0.88,p = 0.033) in these patients, with significant survival improvement after ≥4TACE. ΔADC was not related to OS in ill-defined group. In well-defined group (n = 72), multiple TACE were not associated with improved OS (HR = 0.181,p = 0.090). These patients were categorized into two groups based on ΔADC-cutoff. ADC-responders (ΔADC≥25 %) had the longest survival than other groups(p = 0.015). Multiple TACE sessions were not associated with better OS in this group (HR = 1.004,p = 0.982). By contrast, incremental number of TACE were associated with significantly longer OS in ADC-nonresponders (ΔADC<25 %) (HR = 0.79,p = 0.034). These patients' OS significantly improved after ≥3TACE.

CONCLUSION

The survival benefit of sequential TACE sessions varies for different HCC subgroups. There was no significant survival benefit associated with multiple TACE in well-defined lesions responding to the first TACE. The most survival benefit was for ADC-nonresponder well-defined group and it was least for ill-defined HCC group, regardless of ADC-response.

Post-TACE changes in ADC histogram predict overall and transplant-free survival in patients with well-defined HCC: a retrospective cohort with up to 10 years follow-up

OBJECTIVES

To evaluate the role of change in apparent diffusion coefficient (ADC) histogram after the first transarterial chemoembolization (TACE) in predicting overall and transplant-free survival in well-circumscribed hepatocellular carcinoma (HCC).

METHODS

Institution database was searched for HCC patients who got conventional TACE during 2005-2016. One hundred four patients with well-circumscribed HCC and complete pre- and post-TACE liver MRI were included. Volumetric MRI metrics including tumor volume, mean ADC, skewness, and kurtosis of ADC histograms were measured. Univariate and multivariable Cox models were used to test the independent role of change in imaging parameters to predict survival. P values < 0.05 were considered significant.

RESULTS

In total, 367 person-years follow-up data were analyzed. After adjusting for baseline liver function, tumor volume, and treatment modality, incremental percent change in ADC (ΔADC) was an independent predictor of longer overall and transplant-free survival (p = 0.009). Overall, a decrease in ADC-kurtosis (ΔkADC) showed a strong role in predicting longer survival (p = 0.021). Patients in the responder group (ΔADC ≥ 35%) had the best survival profile, compared with non-responders (ΔADC < 35%) (p < 0.001). ΔkADC, as an indicator of change in tissue homogeneity, could distinguish between poor and fair survival in non-responders (p < 0.001). It was not a measure of difference among responders (p = 0.244). Non-responders with ΔkADC ≥ 1 (homogeneous post-TACE tumor) had the worst survival outcome (HR = 5.70, p < 0.001), and non-responders with ΔkADC < 1 had a fair survival outcome (HR = 2.51, p = 0.029), compared with responders.

CONCLUSIONS

Changes in mean ADC and ADC kurtosis, as a measure of change in tissue heterogeneity, can be used to predict overall and transplant-free survival in well-circumscribed HCC, in order to monitor early response to TACE and identify patients with treatment failure and poor survival outcome.

KEY POINTS

• Changes in the mean and kurtosis of ADC histograms, as the measures of change in tissue heterogeneity, can be used to predict overall and transplant-free survival in patients with well-defined HCC. • A ≥ 35% increase in volumetric ADC after TACE is an independent predictor of good survival, regardless of the change in ADC histogram kurtosis. • In patients with < 35% ADC change, a decrease in ADC histogram kurtosis indicates partial response and fair survival, while ∆kurtosis ≥ 1 correlates with the worst survival outcome.

Prediction of microvascular invasion of hepatocellular carcinoma: value of volumetric iodine quantification using preoperative dual-energy computed tomography

Background

To investigate the potential value of volumetric iodine quantification using preoperative dual-energy computed tomography (DECT) for predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC).

Methods

This retrospective study included patients with single HCC treated through surgical resection who underwent preoperative DECT. Quantitative DECT features, including normalized iodine concentration (NIC) to the aorta and mixed-energy CT attenuation value in the arterial phase, were three-dimensionally measured for peritumoral and intratumoral regions: (i) layer-by-layer analysis for peritumoral layers (outer layers 1 and 2; numbered in close order from the tumor boundary) and intratumoral layers (inner layers 1 and 2) with 2-mm layer thickness and (ii) volume of interest (VOI)-based analysis with different volume coverage (tumor itself; VOI_O1, tumor plus outer layer 1; VOI_O2, tumor plus outer layers 1 and 2; VOI_I1, tumor minus inner layer 1; VOI_I2, tumor minus inner layers 1 and 2). In addition, qualitative CT features, including peritumoral enhancement and tumor margin, were assessed. Qualitative and quantitative CT features were compared between HCC patients with and without MVI. Diagnostic performance of DECT parameters of layers and VOIs was assessed using receiver operating characteristic curve analysis.

Results

A total of 36 patients (24 men, mean age 59.9 ± 8.5 years) with MVI (n = 14) and without MVI (n = 22) were included. HCCs with MVI showed significantly higher NICs of outer layer 1, outer layer 2, VOI_O1, and VOI_O2 than those without MVI (P = 0.01, 0.04, 0.02, 0.02, respectively). Among the NICs of layers and VOIs, the highest area under the curve was obtained in outer layer 1 (0.747). Qualitative features, including peritumoral enhancement and tumor margin, and the mean CT attenuation of each layer and each VOI were not significantly different between HCCs with and without MVI (both P >  0.05).

Conclusions

Volumetric iodine quantification of peritumoral and intratumoral regions in arterial phase using DECT may help predict the MVI of HCC.

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.

Radiomics based on artificial intelligence in liver diseases: where we are?

Radiomics uses computers to extract a large amount of information from different types of images, form various quantifiable features, and select relevant features using artificial-intelligence algorithms to build models, in order to predict the outcomes of clinical problems (such as diagnosis, treatment, prognosis, etc.). The study of liver diseases by radiomics will contribute to early diagnosis and treatment of liver diseases and improve survival and cure rates of liver diseases. This field is currently in the ascendant and may have great development in the future. Therefore, we summarize the progress of current research in this article and then point out the related deficiencies and the direction of future research.

Application of CT radiomics in prediction of early recurrence in hepatocellular carcinoma

PURPOSE

To appraise the ability of the computed tomography (CT) radiomics signature for prediction of early recurrence (ER) in patients with hepatocellular carcinoma (HCC).

METHODS

A set of 325 HCC patients were enrolled in this retrospective study and the whole dataset was divided into 2 cohorts, including "training set" (225 patients) and "test set" (100 patients). All patients who underwent partial hepatectomy were followed up at least within 1 year. 656 Radiomics features were extracted from arterial-phase and portal venous-phase CT images. Lasso regression model was used for data dimension reduction, feature selection, and radiomics signature building. Univariate analysis was used to identify clinical and radiomics significant features. Models (radiomics signature, clinical model, and combined model) were evaluated by area under the curve (AUC) of receiver operating characteristic curve. The models' performances for prediction of ER were assessed.

RESULTS

The radiomics signature was built by 14 selected radiomics features and was significantly associated with ER (P < 0.001); the AUCs of the "train set" and the "test set" were 0.818 (95% CI 0.760-0.865) and 0.719 (95% CI 0.621-0.805), respectively. The tumor size, tumor capsule, and γ-glutamyl transferase (GGT) were significantly associated with ER in the clinical model (P < 0.05). The combined model showed incremental prognostic value, with the AUCs of "training dataset" and "test dataset" were 0.846 (95% CI 0.792-0.890) and 0.737 (95% CI 0.640-0.820), respectively. The radiomics signature, tumor size, and the level of GGT were independent predictors of ER (P < 0.05).

CONCLUSIONS

The CT radiomics signature can be conveniently used to predict the ER in patient with HCC. The combined model performed better for prediction of ER than radiomics signature or clinical model.

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.

Hepatocellular carcinoma macroscopic gross appearance on imaging: predictor of outcome after transarterial chemoembolization in a real-life multicenter French cohort

BACKGROUND

Conventional transarterial chemoembolization (cTACE) with lipiodol is widely performed in patients with hepatocellular carcinoma (HCC) unsuitable for curative treatment. Additional tumor parameters such as HCC macroscopic appearance based on imaging might be helpful for transarterial chemoembolization prognostication and management.

PATIENTS AND METHODS

A total of 405 patients with HCC who underwent cTACE between 2008 and 2016 from a real-life multicenter French cohort were retrospectively reviewed. Tumors were classified into two macroscopic types according to HCC gross appearance on imaging: nodular versus non-nodular. The study population was stratified into two groups: derivation and validation cohorts. Independent prognostic factors of survival based on multivariate cox regression models were determined and then assessed in the validation set. Thereafter, time to progression (TTP) and radiological response rate were investigated for each prognostic factors of survival.

RESULTS

Median overall survival (OS) was 35 months for Barcelona Clinic Liver Cancer (BCLC) stage A, 22 months for BCLC stage B and 12 months for BCLC stage C patients (P < 0.0001). The corresponding TTP for these patients was 12 (7-17) months, 5 (3-6) months and 1.2 (1.2-3) months (P < 0.0001). Multivariate analysis revealed that tumors size and number, non-nodular type, alpha-fetoprotein, aspartate aminotransferase serum levels and impairment of performance status-1 were independent predictors of survival among the study groups. Non-nodular type was the most powerful factor that influences OS, TTP and radiological response rate for the recommended transarterial chemoembolization candidates. TTP was consistent with OS within each stage.

CONCLUSION

HCC macroscopic appearance on imaging is a determinant predictor of outcome after cTACE in a real-life multicenter cohort.

Incomplete tumor capsule on preoperative imaging reveals microvascular invasion in hepatocellular carcinoma: a systematic review and meta-analysis

PURPOSE

Microvascular invasion (MVI), which is difficult to diagnose before surgery, is a major factor affecting postoperative recurrence in patients with hepatocellular carcinoma (HCC). The relationship between the radiological tumor capsule and MVI is controversial. This study aimed to evaluate the association between the tumor capsule and MVI.

METHODS

We searched Medline (by PubMed) and Embase (by OvidSP). Two review authors independently screened titles and abstracts, selected studies about MVI prediction with radiologic tumor capsule and studies with enough data for extracted, assessed the methodological quality and collected data. Summary results were presented as the diagnostic odds ratio (DOR), sensitivity, specificity, and 95% confidence interval.

RESULTS

Fifteen studies with 2038 patients were included; fourteen studies, including 1331 patients, with no significant heterogeneity indicated no relationship between absent tumor capsule and MVI [DOR = 0.90 (0.64, 1.26)]. Six studies, including 541 patients, with no significant heterogeneity showed incomplete capsule could be used to predict MVI of HCC preoperatively [DOR = 1.85 (1.13, 3.04)]. The overall sensitivity and specificity estimate were 0.50 (0.37, 0.64) and 0.64 (0.53, 0.74), respectively. Eight studies, including 1349 patients, with highly significant heterogeneity revealed that complete capsule could be a protective factor for MVI [DOR = 1.97 (1.01, 3.86)].

CONCLUSIONS

For MVI of HCC, incomplete tumor capsule is a risk factor, while a complete tumor capsule might be a protective factor. However, absent capsule doesn't show significant relationship with MVI. This might be due to combination of the risk and protective effects of present capsule in MVI.

Radiogenomics: bridging imaging and genomics

From diagnostics to prognosis to response prediction, new applications for radiomics are rapidly being developed. One of the fastest evolving branches involves linking imaging phenotypes to the tumor genetic profile, a field commonly referred to as "radiogenomics." In this review, a general outline of radiogenomic literature concerning prominent mutations across different tumor sites will be provided. The field of radiogenomics originates from image processing techniques developed decades ago; however, many technical and clinical challenges still need to be addressed. Nevertheless, increasingly accurate and robust radiogenomic models are being presented and the future appears to be bright.

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.

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.

Can microvascular invasion in hepatocellular carcinoma be predicted by diagnostic imaging? A critical review

Imaging still has a limited capacity to detect microvascular invasion (mVI). The objective of this critical review is the evaluation of the most significant predictors of mVI in hepatocellular carcinoma (HCC) detectable by computed tomography, PET/computed tomography and MRI using a mathematical model. We systematically reviewed 15 observational studies from 2008 to 2018 to analyze factors with most impact on mVI detection. The most significant predictors of mVI correlating with imaging techniques were considered. From 1902 patients considered, we individuated 30 total predictors of mVI in a multivariate analysis. The most frequent predictors related to the highest presence with mVI in HCC were: α-fetoprotein (p < 0.0001), tumor size (p < 0.0001) and number of HCC nodules (p = 0.0020).

Magnetic resonance imaging ancillary features used in Liver Imaging Reporting and Data System: An illustrative review

Hepatocellular carcinoma (HCC) usually develops in the setting of chronic liver disease. In the adequate clinical context, both multiphasic contrast-enhanced CT and magnetic resonance imaging are non-invasive modalities that allow accurate diagnosis and staging of HCC, although the latter demonstrates greater sensitivity and specificity. Imaging criteria for HCC diagnosis rely on hemodynamic features such as hyperenhancement in the arterial phase and washout in the portal or equilibrium phase. However, imaging performance drops considerably for small (< 20 mm) nodules because their tendency to exhibit atypical enhancement patterns. In order to improve accuracy in the diagnosis and staging of HCC, particularly in cases of atypical nodules, ancillary features, i.e., imaging characteristics that modify the likelihood of HCC, have been described and incorporated into clinical reports, especially in Liver Imaging Reporting and Data System. In this paper, ancillary imaging features will be reviewed and illustrated.

Prediction of Microvascular Invasion in Hepatocellular Carcinoma: Preoperative Gd-EOB-DTPA-Dynamic Enhanced MRI and Histopathological Correlation

Objective

To investigate the imaging features observed in preoperative Gd-EOB-DTPA-dynamic enhanced MRI and correlated with the presence of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients.

Methods

66 HCCs in 60 patients with preoperative Gd-EOB-DTPA-dynamic enhanced MRI were retrospectively analyzed. Features including tumor size, signal homogeneity, tumor capsule, tumor margin, peritumor enhancement during mid-arterial phase, peritumor hypointensity during hepatobiliary phase, signal intensity ratio on DWI and apparent diffusion coefficients (ADC), T1 relaxation times, and the reduction rate between pre- and postcontrast enhancement images were assessed. Correlation between these features and histopathological presence of MVI was analyzed to establish a prediction model.

Results

Histopathology confirmed that MVI were observed in 17 of 66 HCCs. Univariate analysis showed tumor size (p = 0.003), margin (p = 0.013), peritumor enhancement (p = 0.001), and hypointensity during hepatobiliary phase (p = 0.004) were associated with MVI. A multiple logistic regression model was established, which showed tumor size, margin, and peritumor enhancement were combined predictors for the presence of MVI (α = 0.1). R² of this prediction model was 0.353, and the sensitivity and specificity were 52.9% and 93.0%, respectively.

Conclusion

Large tumor size, irregular tumor margin, and peritumor enhancement in preoperative Gd-EOB-DTPA-dynamic enhanced MRI can predict the presence of MVI in HCC.

A non-smooth tumor margin on preoperative imaging assesses microvascular invasion of hepatocellular carcinoma: A systematic review and meta-analysis

Microvascular invasion (MVI) is rarely diagnosed preoperatively in hepatocellular carcinoma (HCC). The aim of this meta-analysis is to assess the diagnostic power of a non-smooth tumor margin on preoperative imaging for MVI. We performed a literature search using the PubMed, Embase and Cochrane Library databases, and 11 studies were included involving 618 MVI-positive cases and 1030 MVI-negative cases. Considerable heterogeneity was found, and was indicated to be attributable to the mean patient ages in the included studies. In subgroups of studies with a mean patient age older than 60 years and studies with computed tomography (CT) as the imaging method (as opposed to magnetic resonance imaging (MRI)), heterogeneity was low, and the diagnostic odds ratio (DOR) of the single two-dimensional imaging feature for MVI was 21.30 (95% CI [12.52, 36.23]) and 28.78 (95% CI [13.92, 59.36]), respectively; this power was equivalent to or greater than that of certain multivariable-based scoring systems. In conclusion, a non-smooth tumor margin on preoperative imaging is of great value for MVI assessment and should be considered for inclusion in future scoring systems.

Progress and prospects of circular RNAs in Hepatocellular carcinoma: Novel insights into their function

Hepatocellular carcinoma (HCC) is one of the most predominant subjects of liver malignancies, which arouses global concern in the recent years. Advanced studies have found that Circular RNAs (circRNAs) are differentially expressed in HCC, with its regulatory capacity in HCC pathogenesis and metastasis. However, the underlying mechanism remains largely unknown. In this review, we summarized the functions and mechanisms of those aberrantly expressed circRNAs in HCC tissues. We hope to enlighten more comprehensive studies on the detailed mechanisms of circRNAs and explore their potential values in clinic applications. It revealed that hsa_circ_0004018 can be used as a potential biomarker in HCC diagnosis, with its superior sensitivity to alpha-fetoprotein (AFP). Notably, the correlation of circRNA abundance in the proliferation of liver regeneration (LR) has recently been clarified and different circRNA profiles served as candidates for nonalcoholic steatohepatitis (NASH) diagnosis also be discussed. Therefore, the improved understanding of circRNAs in HCC pathogenesis and metastasis proposed a novel basis for the early diagnosis in HCC patients, which provides a useful resource to explore the pathogenesis of HCC.

Can the Contrast-Enhanced Ultrasound Washout Rate Be Used to Predict Microvascular Invasion in Hepatocellular Carcinoma?

The objective of this study was to investigate use of the washout rate of hepatocellular carcinoma on contrast-enhanced ultrasound (CEUS) for pre-operative determination of the presence of microvascular invasion. The study included 271 patients who underwent liver resection for hepatocellular carcinoma between April 2008 and December 2012, and were examined with contrast-enhanced ultrasound before surgery. Patients were followed up at 3-mo intervals for 3 y. Four washout patterns were classified according to the start time of washout: rapid, portal, delayed and slow. Rapid washout, presence of two or more tumors and tumor size ≥5 cm were identified as independent pre-operative predictors of microvascular invasion on multivariate analysis. Recurrence rates for patients with none, one, two or three predictors were 22.6%, 34.7%, 57.6% and 75.0%, respectively. In combination with tumor number and tumor size, contrast-enhanced ultrasound washout rate may have a role in identifying hepatocellular carcinoma patients with microvascular invasion.

Vascular microinvasion from hepatocellular carcinoma: CT findings and pathologic correlation for the best therapeutic strategies

Recurrence of HCC reduces survival rates in patients treated with surgery, and one of the most relevant risk factors for tumour recurrence is microvascular invasion (mVI). The identification of mVI on preoperative examinations could improve surgical planning's and techniques so as to reduce the risk of tumour recurrence. During our study, we have revised 101 CT examinations of the liver performed on patients diagnosed with solitary HCC who had surgical treatment and pathological analysis of the specimens for mVI in order to detect CT signs which could be reliable in mVI prediction. On CT examinations, the tumours were evaluated for margins, capsule, size, contrast enhancement, halo sign and Thad. From our statistical analysis, we found out that irregularity in tumour margins and defects in peritumoural capsule are the most significant characteristics predicting mVI in HCC. Every report on CT examinations performed on surgical candidate patients should include suggestions about mVI probability in order to tailor procedures, reduce tumour recurrence risk and improve survival rates.

Development and validation of a novel predictive scoring model for microvascular invasion in patients with hepatocellular carcinoma

PURPOSE

Microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC) cannot be accurately predicted preoperatively. This study aimed to establish a predictive scoring model of MVI in solitary HCC patients without macroscopic vascular invasion.

METHODS

A total of 309 consecutive HCC patients who underwent curative hepatectomy were divided into the derivation (n=206) and validation cohort (n=103). A predictive scoring model of MVI was established according to the valuable predictors in the derivation cohort based on multivariate logistic regression analysis. The performance of the predictive model was evaluated in the derivation and validation cohorts.

RESULTS

Preoperative imaging features on CECT, such as intratumoral arteries, non-nodular type of HCC and absence of radiological tumor capsule were independent predictors for MVI. The predictive scoring model was established according to the β coefficients of the 3 predictors. Area under receiver operating characteristic (AUROC) of the predictive scoring model was 0.872 (95% CI, 0.817-0.928) and 0.856 (95% CI, 0.771-0.940) in the derivation and validation cohorts. The positive and negative predictive values were 76.5% and 88.0% in the derivation cohort and 74.4% and 88.3% in the validation cohort. The performance of the model was similar between the patients with tumor size ≤5cm and >5cm in AUROC (P=0.910).

CONCLUSIONS

The predictive scoring model based on intratumoral arteries, non-nodular type of HCC, and absence of the radiological tumor capsule on preoperative CECT is of great value in the prediction of MVI regardless of tumor size.

Can lymphovascular invasion be predicted by preoperative multiphasic dynamic CT in patients with advanced gastric cancer?

OBJECTIVES

To determine whether multiphasic dynamic CT can preoperatively predict lymphovascular invasion (LVI) in advanced gastric cancer (AGC).

METHODS

278 patients with AGC who underwent preoperative multiphasic dynamic CT were retrospectively recruited. Tumour CT attenuation difference between non-contrast and arterial (Δ_AP), portal (Δ_PP) and delayed phase (Δ_DP), tumour-spleen attenuation difference in the portal phase (Δ_T-S), tumour contrast enhancement ratios (CERs), tumour-to-spleen ratio (TSR) and tumour volumes were obtained. All CT-derived parameters and clinicopathological variables associated with LVI were analysed by univariate analysis, followed by multivariate and receiver operator characteristics (ROC) analysis. Associations between CT predictors for LVI and histopathological characteristics were evaluated by the chi-square test.

RESULTS

Δ_PP (OR, 1.056; 95% CI: 1.032-1.080) and Δ_T-S (OR, 1.043; 95% CI: 1.020-1.066) are independent predictors for LVI in AGC. Δ_PP, Δ_T-S and their combination correctly predicted LVI in 74.8% (AUC, 0.775; sensitivity, 88.6%; specificity, 54.1%), 68.7% (AUC, 0.747; sensitivity, 68.3%; specificity, 69.4%) and 71.7% (AUC, 0.800; sensitivity, 67.6%; specificity, 77.8%), respectively. There were significant associations between CT predictors for LVI with tumour histological differentiation and Lauren classification.

CONCLUSION

Multiphasic dynamic CT provides a non-invasive method to predict LVI in AGC through quantitative enhancement measurement.

KEY POINTS

• Lymphovascular invasion rarely can be evaluated preoperatively in advanced gastric cancer (AGC). • Δ _PP and Δ _T-S were independent predictors for LVI in patients with AGC. • Δ _PP and Δ _T-S showed acceptable predictive performance for LVI. • Combination of Δ _PP and Δ _T-S improved predictive performance for LVI. • Multiphasic dynamic CT may be a useful adjunct for detecting LVI preoperatively.

The role of quantitation of real-time 3-dimensional contrast-enhanced ultrasound in detecting microvascular invasion: an in vivo study

PURPOSE

This study was to evaluate the role of quantitative perfusion analysis of 3-dimensional (3D) contrast-enhanced ultrasound (CEUS) in detecting microvascular invasion (MVI) of liver tumor in vivo.

METHODS

VX2 tumors were implanted in the livers of sixteen New Zealand rabbits. On day 10, real-time 3D CEUS was performed, and the real-time dynamic images were analyzed using online quantification software. The animals were sacrificed and sent for pathology examinations. According to the gold standard of pathology, the animals were divided into an MVI group and a group without MVI (non-MVI group). Time-intensity curves (TICs) were obtained for the VX2 tumors and the surrounding liver parenchyma, and the parameters peak intensity (PI), mean transit time (MTT), and time to peak (TTP) were compared within and between the MVI and non-MVI groups.

RESULTS

The TTP and MTT of the VX2 tumors were significantly faster than those of the surrounding liver parenchyma in both MVI and non-MVI groups. The PI of the VX2 tumors was significantly lower than that of the surrounding liver parenchyma in the non-MVI group but not the MVI group. The TTP and MTT of the VX2 tumors and surrounding liver parenchyma were not significantly different in the MVI group compared with the non-MVI group, whereas the ΔPI (the PI ratio between the VX2 liver tumors and the reference liver parenchyma) of the VX2 tumors in the MVI group was larger than that in the non-MVI group. VX2 tumors with MVI present different hemodynamic parameters, with a larger ΔPI than tumors without MVI.

CONCLUSIONS

Our data suggest that quantitative perfusion analysis of 3D CEUS might be a promising method for predicting MVI in liver tumors.

Value of MR histogram analyses for prediction of microvascular invasion of hepatocellular carcinoma

The objective is to explore the value of preoperative magnetic resonance (MR) histogram analyses in predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC).Fifty-one patients with histologically confirmed HCC who underwent diffusion-weighted and contrast-enhanced MR imaging were included. Histogram analyses were performed and mean, variance, skewness, kurtosis, 1th, 10th, 50th, 90th, and 99th percentiles were derived. Quantitative histogram parameters were compared between HCCs with and without MVI. Receiver operating characteristics (ROC) analyses were generated to compare the diagnostic performance of tumor size, histogram analyses of apparent diffusion coefficient (ADC) maps, and MR enhancement.The mean, 1th, 10th, and 50th percentiles of ADC maps, and the mean, variance. 1th, 10th, 50th, 90th, and 99th percentiles of the portal venous phase (PVP) images were significantly different between the groups with and without MVI (P <0.05), with area under the ROC curves (AUCs) of 0.66 to 0.74 for ADC and 0.76 to 0.88 for PVP. The largest AUC of PVP (1th percentile) showed significantly higher accuracy compared with that of arterial phase (AP) or tumor size (P <0.001).MR histogram analyses-in particular for 1th percentile for PVP images-held promise for prediction of MVI of HCC.

A Preoperative Measurement of Serum MicroRNA-125b May Predict the Presence of Microvascular Invasion in Hepatocellular Carcinomas Patients

The high recurrence rate remains a major problem that strongly influenced the prognosis of hepatocellular carcinoma (HCC) patients who received hepatectomy. The presence of microvascular invasion (MVI) is regarded as the most important risk factor that contributes to the postoperative recurrence. Our previous study has hinted that serum microRNA-125b (miR-125b) was associated with MVI. The aim of the present study was to identify whether serum miR-125b can serve as a biomarker to reliably predict microvascular invasion (MVI) preoperatively. MiR-125b was quantified in 108 HCC patients’ serum before they received surgery by quantitative real-time PCR (qRT-PCR). Our results revealed that MVI was associated with relapse free survival (RFS) of postoperative HCC patients; surgical margin width was associated with postoperative RFS in MVI present patients, but not in the patients without MVI. Multivariate analysis revealed that miR-125b, tumor size and AFP were the independent predictive factors associated with MVI in this cohort (P = .001, .001, .003, respectively). The probability of the predictive accuracy of miR-125b was 76.95% (51.32% specificity and 87.50% sensitivity), which was almost equal to the classifier established by combination of AFP and tumor size (78.82% probability, 65.63% specificity and 84.21% sensitivity). Furthermore, the combination of tumor size, AFP and miR-125b yielded a ROC curve area of 86.68% (72.37% specificity and 84.38% sensitivity). Our study indicated that serum miR-125b can be used to predict MVI of HCC patients before they received hepatic resection. Therefore, miR-125b can potentially guide individualized treatment, which helps HCC patients, with or without MVI, to benefit from different surgical approach.

Can Current Preoperative Imaging Be Used to Detect Microvascular Invasion of Hepatocellular Carcinoma?

PURPOSE

To determine the accuracy of imaging features, such as tumor dimension, multinodularity, nonsmooth tumor margins, peritumoral enhancement, and radiogenomic algorithm based on the association between imaging features (internal arteries and hypoattenuating halos) and gene expression that the authors called two-trait predictor of venous invasion (TTPVI), in the prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC).

MATERIALS AND METHODS

This single-center retrospective study was approved by the institutional review board, and the requirement for informed consent was waived. One hundred twenty-five patients (median age, 63 years; interquartile range, 53-71 years) with a diagnosis of HCC and indications for hepatic resection were included. Two observers independently reviewed radiologic images to evaluate the following features for MVI: maximum diameter, number of lesions, tumor margins, TTPVI, and peritumoral enhancement. Interobserver agreement was checked, and diagnostic accuracy of radiologic features was investigated.

RESULTS

The total number of HCC nodules was 140. Large tumor size, nonsmooth tumor margins, TTPVI, and peritumoral enhancement were significantly related to the presence of MVI (P < .05 in all cases and for both observers). Multinodularity was not significantly related (P = .158). Moreover, the diagnostic accuracy of the three "worrisome" radiologic features (nonsmooth tumor margins, peritumoral enhancement, and TTPVI) was associated with tumor size: The negative predictive value of the absence of worrisome features decreased from 0.84 for observer 1 and 0.91 for observer 2 for tumors smaller than 2 cm to 0.56 and 0.71, respectively, for tumors larger than 5 cm, whereas the presence of all three worrisome features returned to a positive predictive value of 0.95 for observer 1 and 0.96 for observer 2 independent of tumor size, with no significant interobserver differences (P > .10).

CONCLUSION

"Worrisome" imaging features, such as tumor dimension, nonsmooth tumor margins, peritumoral enhancement, and TTPVI, have high accuracy in the prediction of MVI in HCC.

A computed tomography radiogenomic biomarker predicts microvascular invasion and clinical outcomes in hepatocellular carcinoma

Microvascular invasion (MVI) in hepatocellular carcinoma (HCC) is an independent predictor of poor outcomes subsequent to surgical resection or liver transplantation (LT); however, MVI currently cannot be adequately determined preoperatively. Radiogenomic venous invasion (RVI) is a contrast-enhanced computed tomography (CECT) biomarker of MVI derived from a 91-gene HCC "venous invasion" gene expression signature. Preoperative CECTs of 157 HCC patients who underwent surgical resection (N = 72) or LT (N = 85) between 2000 and 2009 at three institutions were evaluated for the presence or absence of RVI. RVI was assessed for its ability to predict MVI and outcomes. Interobserver agreement for scoring RVI was substantial among five radiologists (κ = 0.705; P < 0.001). The diagnostic accuracy, sensitivity, and specificity of RVI in predicting MVI was 89%, 76%, and 94%, respectively. Positive RVI score was associated with lower overall survival (OS) than negative RVI score in the overall cohort (P < 0.001; 48 vs. >147 months), American Joint Committee on Cancer tumor-node-metastasis stage II (P < 0.001; 34 vs. >147 months), and in LT patients within Milan criteria (P < 0.001; 69 vs. >147 months). Positive RVI score also portended lower recurrence-free survival at 3 years versus negative RVI score (P = 0.001; 27% vs. 62%).

CONCLUSION

RVI is a noninvasive radiogenomic biomarker that accurately predicts histological MVI in HCC surgical candidates. Its presence on preoperative CECT is associated with early disease recurrence and poor OS and may be useful for identifying patients less likely to derive a durable benefit from surgical treatment.

Efficacy of contrast-enhanced ultrasound washout rate in predicting hepatocellular carcinoma differentiation

The aim of this retrospective study was to evaluate the efficacy of contrast-enhanced ultrasound (CEUS) washout rate in predicting hepatocellular carcinoma (HCC) differentiation. Two hundred seventy-one patients underwent liver resection for HCC between April 2008 and December 2012 after being examined by CEUS using the contrast agent SonoVue with a low mechanical index (<0.1) in a routine procedure. Contrast agent washout rates obtained from video images were divided into four categories from slow to fast: WR1 = no washout in all phases (slowest); WR2 = washout after 120 s from contrast injection (late-phase washout); WR3 = washout between 41 and 120 s from contrast injection (portal venous washout); WR4 = washout before 40 s from contrast injection (fastest washout rate). HCC nodules were graded as well, moderately and poorly differentiated. Spearman rank correlation and χ(2)-tests were used to assess group relationships and differences. Receiver operating characteristic curve analysis was used to determine the diagnostic predictive value of CEUS. Among the 271 patients, 18 (6.6%) had well differentiated, 150 (55.4%) had moderately differentiated and 103 (38.0%) had poorly differentiated HCC. Statistical tests indicated that washout rate was significantly correlated with tumor differentiation (p < 0.05), and the poorly differentiated HCCs had earlier washout. At the cutoff point of WR4, CEUS based on washout rate performed poorly in distinguishing poorly differentiated from moderately and well-differentiated HCCs, with a sensitivity, specificity and accuracy (area under the curve) of 24%, 97% and 0.68, respectively. However, at the cutoff point of WR2, the sensitivity, specificity and accuracy of CEUS in differentiating well-differentiated HCC from other HCCs were significantly better: 98%, 78% and 0.96, respectively. Thus, CEUS washout rate may have a role in identifying patients with well-differentiated HCC.

Aggressive Intrasegmental Recurrence of Hepatocellular Carcinoma after Radiofrequency Ablation: Risk Factors and Clinical Significance

PURPOSE

To evaluate the frequency, risk factors, and clinical significance of aggressive intrasegmental recurrence (AIR) found after radiofrequency (RF) ablation for hepatocellular carcinoma (HCC).

MATERIALS AND METHODS

Institutional review board approval was obtained for this retrospective study. Between March 2005 and December 2010, 539 patients (414 men, 125 women; mean age, 57.91 years; age range, 30-82 years) underwent ultrasonography-guided percutaneous RF ablation as a first-line treatment for a single HCC classified as Barcelona Clinic Liver Cancer (BCLC) stage 0 or A. AIR of HCC was defined as (a) initial tumor recurrence with disease-free status at least 6 months after initial RF ablation and (b) the simultaneous development of multiple nodular (at least three) or infiltrative tumor recurrence in the treated segment. Patients were stratified into two groups: those with AIR (n = 20) and those without AIR (n = 519) during follow-up. Risk factors for AIR were assessed with logistic regression analysis, and risk factors for long-term overall survival were assessed with time-dependent Cox proportional hazard models.

RESULTS

In a median follow-up period of 49 months (range, 6-95 months), AIR was observed in 3.7% of the patients (20 of 539 patients), with the frequency increasing to 15% in the subgroup with periportal HCC (11 of 72 patients). AIRs manifested as either multiple nodular type (n = 14, BCLC stage A or B) or diffusely infiltrative type with tumor thrombus formation (n = 6, BCLC stage C). At multivariate analysis, periportal tumor location and younger patient age were significant risk factors for AIR. The presence of AIR during the follow-up period has a significant effect on the overall survival rate (hazard ratio = 5.72, P = .002).

CONCLUSION

The overall frequency of AIR after RF ablation for HCC was low, with periportal location and patient age showing a significant relationship to the development of AIR. The occurrence of AIR had an adverse effect on overall survival rate.

Risk factors for early intrahepatic distant recurrence after radiofrequency ablation for hepatocellular carcinoma in Egyptian patients

OBJECTIVE

Early tumor recurrence, either local or intrahepatic distant recurrence (IDR), after successful radiofrequency ablation (RFA) for hepatocellular carcinoma (HCC) remains a significant problem. The study aimed to determine the potential risk factors for IDR within one year after successful RFA in HCC patients.

METHODS

In total, 105 patients with 138 lesions who underwent RFA and were followed up for at least one year were included in this study. The patients' data was retrospectively reviewed. Multiple host and tumoral potential risk factors were analyzed.

RESULTS

IDR was found in 62 (59.0%) of all patients. Cumulative IDR-free survival rates in all patients studied were 81.9%, 45.4% and 35.2% at 1, 2 and 3 years, respectively, after RFA. Univariate and multivariate analysis showed that both tumor size >2.8 cm and primary multinodular tumors were significant risk factors for IDR within one year after RFA.

CONCLUSIONS

Patients with tumors of >2.8 cm in diameter or multinodular HCC should be closely monitored for early recurrence after RFA. Combined or systemic therapies should be tried for these patients to improve their disease-free and overall survival.