Prediction of microvascular invasion of hepatocellular carcinoma using gadoxetic acid-enhanced MR and (18)F-FDG PET/CT

Clinical application of dual-layer spectral CT multi-parameter feature to predict microvascular invasion in hepatocellular carcinoma

OBJECTIVE

This study aimed to investigate the feasibility of using dual-layer spectral CT multi-parameter feature to predict microvascular invasion of hepatocellular carcinoma.

METHODS

This retrospective study enrolled 50 HCC patients who underwent multiphase contrast-enhanced spectral CT studies preoperatively. Combined clinical data, radiological features with spectral CT quantitative parameter were constructed to predict MVI. ROC was applied to identify potential predictors of MVI. The CT values obtained by simulating the conventional CT scans with 70 keV images were compared with those obtained with 40 keV images.

RESULTS

50 hepatocellular carcinomas were detected with 30 lesions (Group A) with microvascular invasion and 20 (Group B) without. There were significant differences in AFP,tumer size, IC, NIC,slope and effective atomic number in AP and ICrr in VP between Group A ((1000(10.875,1000),4.360±0.3105, 1.7750 (1.5350,1.8825) mg/ml, 0.1785 (0.1621,0.2124), 2.0362±0.2108,8.0960±0.1043,0.2830±0.0777) and Group B (4.750(3.325,20.425),3.190±0.2979,1.4700 (1.4500,1.5775) mg/ml, 0.1441 (0.1373,0.1490),1.8601±0.1595, 7.8105±0.7830 and 0.2228±0.0612) (all p < 0.05). Using 0.1586 as the threshold for NIC, one could obtain an area-under-curve (AUC) of 0.875 in ROC to differentiate between tumours with and without microvascular invasion. AUC was 0.625 with CT value at 70 keV and improved to 0.843 at 40 keV.

CONCLUSION

Dual-layer spectral CT provides additional quantitative parameters than conventional CT to enhance the differentiation between hepatocellular carcinoma with and without microvascular invasion. Especially, the normalized iodine concentration (NIC) in arterial phase has the greatest potential application value in determining whether microvascular invasion exists, and can offer an important reference for clinical treatment plan and prognosis assessment.

Multiparametric assessment of microvascular invasion in hepatocellular carcinoma using gadoxetic acid-enhanced MRI

PURPOSE

To elucidate how precisely microvascular invasion (MVI) in hepatocellular carcinoma (HCC) can be predicted using multiparametric assessment of gadoxetic acid-enhanced MRI.

METHODS

In this retrospective single-center study, patients who underwent liver resection or transplantation of HCC were evaluated. Data obtained in patients who underwent liver resection were used as the training set. Nine kinds of MR findings for predicting MVI were compared between HCCs with and without MVI by univariate analysis, followed by multiple logistic regression analysis. Using significant findings, a predictive formula for diagnosing MVI was obtained. The diagnostic performance of the formula was investigated in patients who underwent liver resection (validation set 1) and in patients who underwent liver transplantation (validation set 2) using a receiver operating characteristic curve analysis. The area under the curves (AUCs) of these three groups were compared.

RESULTS

A total of 345 patients with 356 HCCs were selected for analysis. Tumor diameter (D) (P = 0.021), tumor washout (TW) (P < 0.01), and peritumoral hypointensity in the hepatobiliary phase (PHH) (P < 0.01) were significantly associated with MVI after multivariate analysis. The AUCs for predicting MVI of the predictive formula were as follows: training set, 0.88 (95% confidence interval (CI) 0.82,0.93); validation set 1, 0.81 (95% CI 0.73,0.87); validation set 2, 0.67 (95% CI 0.51,0.80). The AUCs were not significantly different among three groups (training set vs validation set 1; P = 0.15, training set vs validation set 2; P = 0.09, validation set 1 vs validation set 2; P = 0.29, respectively).

CONCLUSION

Our multiparametric assessment of gadoxetic acid-enhanced MRI performed quite precisely and with good reproducibility for predicting MVI.

Predicting microvascular invasion in hepatocellular carcinoma with a CT- and MRI-based multimodal deep learning model

PURPOSE

To investigate the value of a multimodal deep learning (MDL) model based on computed tomography (CT) and magnetic resonance imaging (MRI) for predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC).

METHODS

A total of 287 patients with HCC from our institution and 58 patients from another individual institution were included. Among these, 119 patients with only CT data and 116 patients with only MRI data were selected for single-modality deep learning model development, after which select parameters were migrated for MDL model development with transfer learning (TL). In addition, 110 patients with simultaneous CT and MRI data were divided into a training cohort (n = 66) and a validation cohort (n = 44). We input the features extracted from DenseNet121 into an extreme learning machine (ELM) classifier to construct a classification model.

RESULTS

The area under the curve (AUC) of the MDL model was 0.844, which was superior to that of the single-phase CT (AUC = 0.706-0.776, P < 0.05), single-sequence MRI (AUC = 0.706-0.717, P < 0.05), single-modality DL model (AUCall-phase CT = 0.722, AUCall-sequence MRI = 0.731; P < 0.05), clinical (AUC = 0.648, P < 0.05), but not to that of the delay phase (DP) and in-phase (IP) MRI and portal venous phase (PVP) CT models. The MDL model achieved better performance than models described above (P < 0.05). When combined with clinical features, the AUC of the MDL model increased from 0.844 to 0.871. A nomogram, combining deep learning signatures (DLS) and clinical indicators for MDL models, demonstrated a greater overall net gain than the MDL models (P < 0.05).

CONCLUSION

The MDL model is a valuable noninvasive technique for preoperatively predicting MVI in HCC.

The potential of 18F-FDG PET/CT metabolic parameter-based nomogram in predicting the microvascular invasion of hepatocellular carcinoma before liver transplantation

PURPOSE

Microvascular invasion (MVI) is a critical factor in predicting the recurrence and prognosis of hepatocellular carcinoma (HCC) after liver transplantation (LT). However, there is a lack of reliable preoperative predictors for MVI. The purpose of this study is to evaluate the potential of an 18F-FDG PET/CT-based nomogram in predicting MVI before LT for HCC.

METHODS

83 HCC patients who obtained 18F-FDG PET/CT before LT were included in this retrospective research. To determine the parameters connected to MVI and to create a nomogram for MVI prediction, respectively, Logistic and Cox regression models were applied. Analyses of the calibration curve and receiver operating characteristic (ROC) curves were used to assess the model's capability to differentiate between clinical factors and metabolic data from PET/CT images.

RESULTS

Among the 83 patients analyzed, 41% were diagnosed with histologic MVI. Multivariate logistic regression analysis revealed that Child-Pugh stage, alpha-fetoprotein, number of tumors, CT Dmax, and Tumor-to-normal liver uptake ratio (TLR) were significant predictors of MVI. A nomogram was constructed using these predictors, which demonstrated strong calibration with a close agreement between predicted and actual MVI probabilities. The nomogram also showed excellent differentiation with an AUC of 0.965 (95% CI 0.925-1.000).

CONCLUSION

The nomogram based on 18F-FDG PET/CT metabolic characteristics is a reliable preoperative imaging biomarker for predicting MVI in HCC patients before undergoing LT. It has demonstrated excellent efficacy and high clinical applicability.

Application of texture signatures based on multiparameter-magnetic resonance imaging for predicting microvascular invasion in hepatocellular carcinoma: Retrospective study

BACKGROUND

Despite continuous changes in treatment methods, the survival rate for advanced hepatocellular carcinoma (HCC) patients remains low, highlighting the importance of diagnostic methods for HCC.

AIM

To explore the efficacy of texture analysis based on multi-parametric magnetic resonance (MR) imaging (MRI) in predicting microvascular invasion (MVI) in preoperative HCC.

METHODS

This study included 105 patients with pathologically confirmed HCC, categorized into MVI-positive and MVI-negative groups. We employed Original Data Analysis, Principal Component Analysis, Linear Discriminant Analysis (LDA), and Non-LDA (NDA) for texture analysis using multi-parametric MR images to predict preoperative MVI. The effectiveness of texture analysis was determined using the B11 program of the MaZda4.6 software, with results expressed as the misjudgment rate (MCR).

RESULTS

Texture analysis using multi-parametric MRI, particularly the MI + PA + F dimensionality reduction method combined with NDA discrimination, demonstrated the most effective prediction of MVI in HCC. Prediction accuracy in the pulse and equilibrium phases was 83.81%. MCRs for the combination of T2-weighted imaging (T2WI), arterial phase, portal venous phase, and equilibrium phase were 22.86%, 16.19%, 20.95%, and 20.95%, respectively. The area under the curve for predicting MVI positivity was 0.844, with a sensitivity of 77.19% and specificity of 91.67%.

CONCLUSION

Texture analysis of arterial phase images demonstrated superior predictive efficacy for MVI in HCC compared to T2WI, portal venous, and equilibrium phases. This study provides an objective, non-invasive method for preoperative prediction of MVI, offering a theoretical foundation for the selection of clinical therapy.

Preoperative Prediction of Microvascular Invasion with Gadoxetic Acid-Enhanced Magnetic Resonance Imaging in Patients with Single Hepatocellular Carcinoma: The Implication of Surgical Decision on the Extent of Liver Resection

Introduction

Microvascular invasion (MVI) is one of the most important prognostic factors for hepatocellular carcinoma (HCC) recurrence, but its application in preoperative clinical decisions is limited. This study aimed to identify preoperative predictive factors for MVI in HCC and further evaluate oncologic outcomes of different types and extents of hepatectomy according to stratified risk of MVI.

Methods

Patients with surgically resected single HCC (≤5 cm) who underwent preoperative gadoxetic acid-enhanced magnetic resonance imaging (MRI) were included in a single-center retrospective study. Two radiologists reviewed the images with no clinical, pathological, or prognostic information. Significant predictive factors for MVI were identified using logistic regression analysis against pathologic MVI and used to stratify patients. In the subgroup analysis, long-term outcomes of the stratified patients were analyzed using the Kaplan-Meier method with log-rank test and compared between anatomical and nonanatomical or major and minor resection.

Results

A total of 408 patients, 318 men and 90 women, with a mean age of 56.7 years were included. Elevated levels of tumor markers (alpha-fetoprotein [α-FP] ≥25 ng/mL and PIVKA-II ≥40 mAU/mL) and three MRI features (tumor size ≥3 cm, non-smooth tumor margin, and arterial peritumoral enhancement) were independent predictive factors for MVI. As the MVI risk increased from low (no predictive factor) and intermediate (1-2 factors) to high-risk (3-4 factors), recurrence-free and overall survival of each group significantly decreased (p = 0.001). In the high MVI risk group, 5-year cumulative recurrence rate was significantly lower in patients who underwent major compared to minor hepatectomy (26.6 vs. 59.8%, p = 0.027).

Conclusion

Tumor markers and MRI features can predict the risk of MVI and prognosis after hepatectomy. Patients with high MVI risk had the worst prognosis among the three groups, and major hepatectomy improved long-term outcomes in these high-risk patients.

Clinical-Radiologic Morphology-Radiomics Model on Gadobenate Dimeglumine-Enhanced MRI for Identification of Highly Aggressive Hepatocellular Carcinoma: Temporal Validation and Multiscanner Validation

BACKGROUND

Highly aggressive hepatocellular carcinoma (HCC) is characterized by high tumor recurrence and poor outcomes, but its definition and imaging characteristics have not been clearly described.

PURPOSE

To develop and validate a fusion model on gadobenate dimeglumine-enhanced MRI for identifying highly aggressive HCC.

STUDY TYPE

Retrospective.

POPULATION

341 patients (M/F = 294/47) with surgically resected HCC, divided into a training cohort (n = 177), temporal validation cohort (n = 77), and multiscanner validation cohort (n = 87).

FIELD STRENGTH/SEQUENCE

3T, dynamic contrast-enhanced MRI with T1-weighted volumetric interpolated breath-hold examination gradient-echo sequences, especially arterial phase (AP) and hepatobiliary phase (HBP, 80-100 min).

ASSESSMENT

Clinical factors and diagnosis assessment based on radiologic morphology characteristics associated with highly aggressive HCCs were evaluated. The radiomics signatures were extracted from AP and HBP. Multivariable logistic regression was performed to construct clinical-radiologic morphology (CR) model and clinical-radiologic morphology-radiomics (CRR) model. A nomogram based on the optimal model was established. Early recurrence-free survival (RFS) was evaluated in actual groups and risk groups calculated by the nomogram.

STATISTICAL TESTS

The performance was evaluated by receiver operating characteristic curve (ROC) analysis, calibration curves analysis, and decision curves. Early RFS was evaluated by using Kaplan-Meier analysis. A P value <0.05 was considered statistically significant.

RESULTS

The CRR model incorporating corona enhancement, cloud-like hyperintensity on HBP, and radiomics signatures showed the highest diagnostic performance. The area under the curves (AUCs) of CRR were significantly higher than those of the CR model (AUC = 0.883 vs. 0.815, respectively, for the training cohort), 0.874 vs. 0.769 for temporal validation, and 0.892 vs. 0.792 for multiscanner validation. In both actual and risk groups, highly and low aggressive HCCs showed statistically significant differences in early recurrence.

DATA CONCLUSION

The clinical-radiologic morphology-radiomics model on gadobenate dimeglumine-enhanced MRI has potential to identify highly aggressive HCCs and non-invasively obtain prognostic information.

LEVEL OF EVIDENCE

4 TECHNICAL EFFICACY: Stage 2.

The Role of Artificial Intelligence and Texture Analysis in Interventional Radiological Treatments of Liver Masses: A Narrative Review

Liver lesions, including both benign and malignant tumors, pose significant challenges in interventional radiological treatment planning and prognostication. The emerging field of artificial intelligence (AI) and its integration with texture analysis techniques have shown promising potential in predicting treatment outcomes, enhancing precision, and aiding clinical decision-making. This comprehensive review aims to summarize the current state-of-the-art research on the application of AI and texture analysis in determining treatment response, recurrence rates, and overall survival outcomes for patients undergoing interventional radiological treatment for liver lesions. Furthermore, the review addresses the challenges associated with the implementation of AI and texture analysis in clinical practice, including data acquisition, standardization of imaging protocols, and model validation. Future directions and potential advancements in this field are discussed. Integration of multi-modal imaging data, incorporation of genomics and clinical data, and the development of predictive models with enhanced interpretability are proposed as potential avenues for further research. In conclusion, the application of AI and texture analysis in predicting outcomes of interventional radiological treatment for liver lesions shows great promise in augmenting clinical decision-making and improving patient care. By leveraging these technologies, clinicians can potentially enhance treatment planning, optimize intervention strategies, and ultimately improve patient outcomes in the management of liver lesions.

Preoperative assessment of microvascular invasion risk using gadoxetate-enhanced MRI for predicting outcomes after liver transplantation for single hepatocellular carcinoma within the Milan criteria

OBJECTIVE

To compare therapeutic outcomes after liver transplantation (LT) between hepatocellular carcinomas (HCC) with low and high risk for microvascular invasion (MVI) within the Milan criteria evaluated preoperatively.

METHODS

Eighty patients with a single HCC who underwent LT as the initial therapy between 2008 and 2017 were included from two tertiary referral medical centers in a HBV-predominant population. A preoperative MVI-risk model was used to identify low- and high-risk patients. Recurrence-free survival (RFS) after LT between the two risk groups was compared using Kaplan-Meier curves with the log-rank test. Prognostic factors for RFS were identified using a multivariable Cox hazard regression analysis.

RESULTS

Eighty patients were included (mean age, 51.8 years +/- 7.5 [standard deviation], 65 men). Patients were divided into low-risk (n = 64) and high-risk (n = 16) groups for MVI. The RFS rates after LT were significantly lower in the MVI high-risk group compared to the low-risk group at 1 year (75.0% [95% CI: 56.5-99.5%] vs. 96.9% [92.7-100%], p = 0.048), 3 years (62.5% [42.8-91.4%] vs. 95.3% [90.3-100%], p = 0.008), and 5 years (62.5% [42.8-91.4%] vs. and 95.3% [90.3-100%], p = 0.008). In addition, multivariable analysis showed that MVI high risk was the only significant factor for poor RFS (p = 0.016).

CONCLUSION

HCC patients with a high risk of MVI showed significantly lower RFS after LT than those without. This model could aid in selecting optimal candidates in addition to the Milan criteria when considering upfront LT for patients with HCC if alternative treatment options are available.

CLINICAL RELEVANCE STATEMENT

High risk for microvascular invasion (MVI) in hepatocellular carcinoma patients lowered recurrence-free survival after liver transplantation, despite meeting the Milan criteria. Identifying MVI risk could aid candidate selection for upfront liver transplantation, particularly if alternative treatments are available.

KEY POINTS

• A predictive model-derived microvascular invasion (MVI) high- and low-risk groups had a significant difference in the incidence of MVI on pathology. • Recurrence-free survival after liver transplantation (LT) for single hepatocellular carcinoma (HCC) within the Milan criteria was significantly different between the MVI high- and low-risk groups. • The peak incidence of tumor recurrence was 20 months after liver transplantation, probably indicating that HCC with high risk for MVI had a high risk of early (≤ 2 years) tumor recurrence.

Recurrence-free Survival After Liver Transplantation Versus Surgical Resection for Hepatocellular Carcinoma: Role of High-risk MRI Features

BACKGROUND

This study aimed to evaluate recurrence-free survival (RFS) and overall survival (OS) after liver transplantation (LT) or liver resection (LR) for hepatocellular carcinoma (HCC) and perform subgroup analysis for HCC with high-risk imaging findings for recurrence on preoperative liver magnetic resonance imaging (MRI; high-risk MRI features).

METHODS

We included patients with HCC eligible for both LT and LR and received either of the treatments between June 2008 and February 2021 from 2 tertiary referral medical centers after propensity score-matching. RFS and OS were compared between LT and LR using Kaplan-Meier curves with the log-rank test.

RESULTS

Propensity score-matching yielded 79 patients in the LT group and 142 patients in the LR group. High-risk MRI features were noted in 39 patients (49.4%) in the LT group and 98 (69.0%) in the LR group. The Kaplan-Meier curves for RFS and OS were not significantly different between the 2 treatments among the high-risk group (RFS, P  = 0.079; OS, P  = 0.755). Multivariable analysis showed that treatment type was not a prognostic factor for RFS and OS ( P  = 0.074 and 0.937, respectively).

CONCLUSIONS

The advantage of LT over LR for RFS may be less evident among patients with high-risk MRI features.

A multivariate model based on gadoxetic acid-enhanced MRI using Li-RADS v2018 and other imaging features for preoperative prediction of dual‑phenotype hepatocellular carcinoma

OBJECTIVE

To investigate the diagnostic value of liver imaging reporting and data system (LI-RADS) v2018 and other imaging features in dual-phenotype hepatocellular carcinoma (DPHCC), establish a prediagnostic model based on gadoxetic acid-enhanced MRI, and explore the prognostic significance after surgery of the DPHCC.

MATERIALS AND METHODS

Preoperative enhanced MRI findings and the clinical and pathological data of patients with surgically confirmed HCC were analysed retrospectively. Image analysis was based on LI-RADS v2018 and other image features. Univariate analysis was used to screen for predictive factors of DPHCC, and multivariate logistic regression analysis was used to determine the predictive factors. A regression diagnostic model was established. Receiver operating characteristic (ROC) curve analysis was used to determine the critical value, area under curve (AUC), and the corresponding 95% confidence interval (95% CI). The diagnostic performance was verified by fivefold cross-validation. Cox regression analysis was used to determine the prognostic factors associated with early recurrence after surgical resection.

RESULTS

In total, 158 patients were included, of whom 79 had DPHCC and 79 had non-DPHCC. Multivariate analysis showed that rim arterial phase hyperenhancement (Rim APHE) and targetoid restriction were independent risk factors for DPHCC (P < 0.05). The AUC (95% CI) of the model was 0.862 (0.807-0.918), sensitivity was 81.01%, and specificity was 89.874%. Cox regression analysis showed that DPHCC, microvascular invasion, tumour diameter, and an increase of alpha-fetoprotein were independent factors for recurrence.

CONCLUSION

Rim APHE and targetoid restriction were sensitive imaging features of DPHCC before surgery, and the identification of DPHCC has important prognostic significance for early recurrence.

Characterization of Microvascular Invasion in Hepatocellular Carcinoma Using Computational Modeling of Interstitial Fluid Pressure and Velocity

BACKGROUND

Most solid tumors show increased interstitial fluid pressure (IFP), and this increased IFP is an obstacle to treatment. A noninvasive model for measuring IFP in hepatocellular carcinoma (HCC) is an unresolved issue.

PURPOSE

To develop a noninvasive model to measure IFP and interstitial fluid velocity (IFV) in HCC and to characterize the microvascular invasion (MVI) status by using this model.

STUDY TYPE

Retrospective.

POPULATION

A total of 97 HCC patients (mean age 57.6 ± 10.9 years, 77.3% males), 53 of them with MVI and 44 of them without MVI.

FIELD STRENGTH/SEQUENCE

A 3-T, three-dimensional spoiled gradient-recalled echo.

ASSESSMENT

MVI was defined as microscopic vascular invasion of small vessels within the peritumoral liver tissue. The volumes of interest (VOIs) were manually delineated and enclosed the tumor lesion and healthy liver parenchyma, respectively. The extended Tofts model (ETM) was used to estimate permeability parameters from all the VOIs. Subsequently, the continuity partial differential equation (PDE) was implemented and IFP and IFV were acquired.

STATISTICAL TESTS

Wilcoxon signed-ranks tests, histogram analysis, Mann-Whitney U test, Fisher's exact test, least absolute shrinkage and selection operator (LASSO) logistic regression, receiver operating characteristic (ROC) curve analysis with the area under the curve (AUC), Youden index, DeLong test, and Benjamini-Hochberg correction. A P value <0.05 was considered statistically significant.

RESULTS

The HCC lesions exhibited elevated IFP and reduced IFV. There were no significant differences in any measured demographic and clinical features between the MVI-positive and MVI-negative groups, except for tumor size. Nine IFP histogram analysis-derived parameters and seven IFV histogram analysis-derived parameters could be used to characterize the MVI status. LASSO regression selected five features: IFP maximum, IFP 10th percentile, IFP 90th percentile, IFV SD, and IFV 10th percentile. The combination of these features showed the highest AUC (0.781) and specificity (77.3%).

DATA CONCLUSION

A noninvasive IFP and IFV measurement model for HCC was developed. Specific IFP- and IFV-derived parameters exhibited significant association with the MVI status.

EVIDENCE LEVEL

3.

TECHNICAL EFFICACY

Stage 2.

Current Status of Cancer Genomics and Imaging Phenotypes: What Radiologists Need to Know

Ongoing discoveries in cancer genomics and epigenomics have revolutionized clinical oncology and precision health care. This knowledge provides unprecedented insights into tumor biology and heterogeneity within a single tumor, among primary and metastatic lesions, and among patients with the same histologic type of cancer. Large-scale genomic sequencing studies also sparked the development of new tumor classifications, biomarkers, and targeted therapies. Because of the central role of imaging in cancer diagnosis and therapy, radiologists need to be familiar with the basic concepts of genomics, which are now becoming the new norm in oncologic clinical practice. By incorporating these concepts into clinical practice, radiologists can make their imaging interpretations more meaningful and specific, facilitate multidisciplinary clinical dialogue and interventions, and provide better patient-centric care. This review article highlights basic concepts of genomics and epigenomics, reviews the most common genetic alterations in cancer, and discusses the implications of these concepts on imaging by organ system in a case-based manner. This information will help stimulate new innovations in imaging research, accelerate the development and validation of new imaging biomarkers, and motivate efforts to bring new molecular and functional imaging methods to clinical radiology. Keywords: Oncology, Cancer Genomics, Epignomics, Radiogenomics, Imaging Markers Supplemental material is available for this article. © RSNA, 2023.

Update on Positron Emission Tomography/Magnetic Resonance Imaging: Cancer and Inflammation Imaging in the Clinic

Hybrid PET/MRI is highly valuable, having made significant strides in overcoming technical challenges and offering unique advantages such as reduced radiation, precise data coregistration, and motion correction. Growing evidence highlights the value of PET/MRI in broad clinical aspects, including inflammatory and oncological imaging in adults, pregnant women, and pediatrics, potentially surpassing PET/CT. This newly integrated solution may be preferred over PET/CT in many clinical conditions. However, further technological advancements are required to facilitate its broader adoption as a routine diagnostic modality.

Achievement of Complete Response and Drug-Free Status by Atezolizumab plus Bevacizumab Combined with or without Curative Conversion in Patients with Transarterial Chemoembolization-Unsuitable, Intermediate-Stage Hepatocellular Carcinoma: A Multicenter Proof-Of-Concept Study

Introduction

Atezolizumab plus bevacizumab therapy is extremely effective in the treatment of intermediate-stage hepatocellular carcinoma (HCC), with a response rate of 44%, as reported in the IMbrave150 trial. When tumor shrinkage is obtained, achieving complete response (CR) is possible in many cases using curative conversion with resection, ablation, or superselective transarterial chemoembolization (TACE) with curative intent. This concept, i.e., curative conversion by combining systemic therapy and locoregional therapy, has not been reported before. This multicenter proof-of-concept study was conducted to show the value of curative conversion in immunotherapy-treated intermediate-stage HCC meeting TACE-unsuitable criteria.

Methods

This study included 110 consecutive Child-Pugh A patients who received atezolizumab plus bevacizumab as first-line treatment for unresectable and TACE-unsuitable intermediate-stage HCC at seven centers in Japan. CR rate, drug-free rate, time to CR, change in liver function, efficacy in positron emission tomography (PET)-positive HCC, progression-free survival (PFS), and overall survival (OS) were assessed in patients who achieved CR using resection, ablation, superselective TACE with curative intent following atezolizumab plus bevacizumab or atezolizumab plus bevacizumab alone.

Results

Clinical or pathological CR was achieved in 38 patients (35%) (median observation period: 21.2 months). The modalities of curative conversion in 35 patients were as follows: resection, 7; ablation, 13; and superselective TACE, 15. Three patients achieved clinical CR with atezolizumab plus bevacizumab therapy alone. Among the 38 CR patients, 25 achieved drug-free status. PFS was not reached, and 3 patients experienced recurrence after reaching CR. Regarding OS, there were no deaths in any of the CR patients. The albumin-bilirubin score did not deteriorate after locoregional therapy or resection. Of seven PET-positive patients who achieved CR with atezolizumab plus bevacizumab followed by curative conversion, five achieved drug-free status.

Conclusion

The achievement of CR rate by curative conversion in patients treated with atezolizumab plus bevacizumab as the preceding therapy for unresectable and TACE-unsuitable intermediate-stage HCC was 35%. Overall, 23% of patients achieved drug-free status and no recurrence was observed from this patient subgroup with CR and drug-free status. Thus, achieving CR and/or drug-free status should be a therapeutic goal for patients with intermediate-stage HCC without vascular invasion or extrahepatic spread.

A Reliable and Repeatable Model for Predicting Microvascular Invasion in Patients With Hepatocellular Carcinoma

RATIONALE AND OBJECTIVES

The reproducibility of imaging models for predicting microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC) remains questionable due to inconsistent interpretation of image signs. Our aim was to screen for high-consensus MRI features to develop a repeatable model for predicting MVI.

MATERIALS AND METHODS

We included 219 patients with HCC who underwent surgical resection, and patients were divided into a training cohort (n = 145) and a validation cohort (n = 74). Morphological characteristics, signal features on hepatobiliary phases, and dynamic enhancement patterns were qualitatively interobserver evaluated. Interobserver agreement was assessed using Cohen's κ for selecting features with high interobserver agreement. Risk factors that were significant in stepwise multivariate analysis and that could be measured with good interobserver agreement were used to construct a predictive model, which was assessed in the validation cohort. The diagnostic performance of the model was evaluated based on area under the receiver operating characteristic curve (AUC).

RESULTS

Multivariate analysis identified nonsmooth tumor margin, absence of radiologic capsule, and intratumoral artery as independent risk factors of MVI. These MRI-based features showed good or nearly perfect interobserver agreement between radiologists (κ > 0.6). The predictive model predicted MVI well in the training (AUC 0.734) and validation cohorts (AUC 0.759) and fitted well to calibration curves.

CONCLUSION

MRI features included nonsmooth tumor margin, absence of radiologic capsule, and intratumoral artery that can be assessed with high interobserver agreement can predict MVI in HCC patients. The predictive model described here may be useful to radiologists, regardless of experience level.

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.

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 &lt; 0.05). Furthermore, the sharp-type margin was thinner than the rough-type margin (all P &lt; 0.05). Moreover, the sharp-type group had a high incidence of tumors with a diameter of &lt; 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 &lt; 0.05), whereas most of those with a rough-type margin experienced disease progression (84.8%, P &lt; 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.

Development of a deep learning-based auto-segmentation algorithm for hepatocellular carcinoma (HCC) and application to predict microvascular invasion of HCC using CT texture analysis: preliminary results

BACKGROUND

Automatic segmentation has recently been developed to yield objective data. Prediction of microvascular invasion (MVI) of hepatocellular carcinoma (HCC) using radiomics has been reported.

PURPOSE

To develop a deep learning-based auto-segmentation algorithm (DL-AS) for the detection of HCC and to predict MVI using computed tomography (CT) texture analysis.

MATERIAL AND METHODS

We retrospectively collected training data from 249 patients with HCC and validation set from 35 patients. Lesions of the training set were manually drawn by radiologist, in the delayed phase. 2D U-Net was selected as the DL architecture. Using the validation set, one radiologist manually drew 2D and 3D regions of interest twice, and the developed DL-AS was performed twice with a one-month time interval. The reproducibility was calculated using intraclass correlation coefficients (ICC). Logistic regression was performed to predict MVI.

RESULTS

ICC was in the range of 0.190-0.998/0.341-0.997 in the manual 3D/2D segmentation. In contrast, it was perfect in 3D/2D using DL-AS, with a success rate of 88.6% for the detection of HCC. For predicting MVI, sphericity was a significant parameter (odds ratio <0.001; 95% confidence interval <0.001-0.206; P = 0.020) for predicting MVI using 2D DL-AS. However, 3D DL-AS segmentation did not yield a predictive parameter.

CONCLUSION

The auto-segmentation of HCC using DL-AS provides perfect reproducibility, although it failed to detect 11.4% (4/35). However, the extracted parameters yielded different important predictors of MVI in HCC. Sphericity was a significant predictor in 2D DL-AS and 3D manual segmentation, while discrete compactness was a significant predictor in 2D manual segmentation.

Preoperative Evaluation of Gd-EOB-DTPA-Enhanced MRI Radiomics-Based Nomogram in Small Solitary Hepatocellular Carcinoma (≤3 cm) With Microvascular Invasion: A Two-Center Study

BACKGROUND

Preoperative evaluation of microvascular invasion (MVI) in small solitary hepatocellular carcinoma (HCC; maximum lesion diameter ≤ 3 cm) is important for treatment decisions.

PURPOSE

To apply gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced MRI to develop and validate a nomogram for preoperative evaluation of MVI in small solitary HCC and to compare the effectiveness of radiomics evaluation models based on different volumes of interest (VOIs).

STUDY TYPE

Retrospective.

POPULATION

A total of 196 patients include 62 MVI-positive and 134 MVI-negative patients were enrolled (training cohort, n = 105; testing cohort, n = 45; external validation cohort, n = 46).

FIELD STRENGTH/SEQUENCE

3.0 T, fat suppressed fast-spin-echo T2-weighted and Gd-EOB-DTPA-enhanced T1-weighted magnetization-prepared rapid gradient-echo sequences.

ASSESSMENT

Radiomics features were extracted on T2-weighted, arterial phase (AP), and hepatobiliary phase (HBP) images from different VOIs (VOI_intratumor and VOI_{intratumor+peritumor} ) and filtered by the least absolute shrinkage selection operator (LASSO) regression. From VOI_intratumor and VOI_{intratumor+peritumor} , eight radiomics models were constructed based on three MRI sequences (T2-weighted, AP, and HBP) and fused sequences (combined of three sequences). Nomograms were constructed of a clinical-radiological (CR) model and a clinical-radiological-radiomics (CRR) model.

STATISTICAL TESTS

One-way analysis of variance, independent t-test, Chi-square test or Fisher's exact test, Wilcoxon rank-sum test, LASSO, logistic regression analysis, area under the curve (AUC), nomograms, decision curve, net reclassification improvement (NRI), integrated discrimination improvement (IDI) analyses, and DeLong test.

RESULTS

Among eight radiomics models, the fused sequences-based VOI_{intratumor+peritumor} radiomics model showed the best performance. The CRR model containing the best performance radiomics model and CR model with the AUC values were 0.934, 0.889, and 0.875, respectively. NRI and IDI analyses showed that the CRR model improved evaluation efficacy over the CR model for all three cohorts (all P-value <0.05).

DATA CONCLUSION

The CRR model nomogram could preoperatively evaluate MVI in small solitary HCC. The radiomics model based on VOI_{intratumor+peritumor} might achieve better evaluation results.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY STAGE: 2.

Texture analysis of contrast-enhanced magnetic resonance imaging predicts microvascular invasion in hepatocellular carcinoma

BACKGROUND

Microvascular invasion is one of the important risk factors of postoperative recurrence of hepatocellular carcinoma. Texture analysis uses mathematical methods to analyze the gray's quantitative value and distribution of images, for quantifying the heterogeneity of tissues.

PURPOSE

To investigate the feasibility of predicting MVI in HCC by analyzing the texture features of hepatic MR-enhanced images.

METHODS

110 patients with HCC who underwent MR-enhanced examinations were included in this study, were divided into MVI-positive group (n = 52) and MVI-negative group (n = 58) according to postoperative pathology. Clinical, pathological data and MR imaging features were collected. 11 texture parameters were selected from the gray histogram and gray level co-occurrence matrix (GLCM). Texture parameters of MR-enhanced images were calculated for statistical analysis.

RESULTS

There were statistically significant differences in tumor size, location, degree of differentiation, AFP level, signal, pseudocapsule, margin, peritumoral enhancement and intratumoral artery between MVI-positive group and MVI-negative group (P < 0.05). The AUC value of combining MR image features in prediction of MVI was 0.693(sensitivity and specificity: 53.8 %, 82.8 %, respectively). There were statistically significant differences in the texture parameters of GLCM between two groups (P < 0.05). The AUC value of combining texture parameters in prediction of MVI was 0.797 (sensitivity and specificity: 88.2 %, 62.7 %, respectively).

CONCLUSION

MR image features and texture analysis have certain predictive effect on MVI, which are mutually verified and complementary. The texture parameters of GLCM could reflect tumor heterogeneity, which have great potential to help with preoperative decision. The combination of MR image features and texture analysis may improve the efficiency in prediction of MVI.

Peritumoral Imaging Manifestations on Gd-EOB-DTPA-Enhanced MRI for Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis

Purpose

The aim was to investigate the association between microvascular invasion (MVI) and the peritumoral imaging features of gadolinium ethoxybenzyl DTPA-enhanced magnetic resonance imaging (Gd-EOB-DTPA-enhanced MRI) in hepatocellular carcinoma (HCC).

Methods

Up until Feb 24, 2022, the PubMed, Embase, and Cochrane Library databases were carefully searched for relevant material. The software packages utilized for this meta-analysis were Review Manager 5.4.1, Meta-DiSc 1.4, and Stata16.0. Summary results are presented as sensitivity (SEN), specificity (SPE), diagnostic odds ratios (DORs), area under the receiver operating characteristic curve (AUC), and 95% confidence interval (CI). The sources of heterogeneity were investigated using subgroup analysis.

Results

An aggregate of nineteen articles were remembered for this meta-analysis: peritumoral enhancement on the arterial phase (AP) was described in 13 of these studies and peritumoral hypointensity on the hepatobiliary phase (HBP) in all 19 studies. The SEN, SPE, DOR, and AUC of the 13 investigations on peritumoral enhancement on AP were 0.59 (95% CI, 0.41−0.58), 0.80 (95% CI, 0.75−0.85), 4 (95% CI, 3−6), and 0.73 (95% CI, 0.69−0.77), respectively. The SEN, SPE, DOR, and AUC of 19 studies on peritumoral hypointensity on HBP were 0.55 (95% CI, 0.45−0.64), 0.87 (95% CI, 0.81−0.91), 8 (95% CI, 5−12), and 0.80 (95% CI, 0.76−0.83), respectively. The subgroup analysis of two imaging features identified ten and seven potential factors for heterogeneity, respectively.

Conclusion

The results of peritumoral enhancement on the AP and peritumoral hypointensity on HBP showed high SPE but low SEN. This indicates that the peritumoral imaging features on Gd-EOB-DTPA-enhanced MRI can be used as a noninvasive, excluded diagnosis for predicting hepatic MVI in HCC preoperatively. Moreover, the results of this analysis should be updated when additional data become available. Additionally, in the future, how to improve its SEN will be a new research direction.

A nomogram based on multi-modal ultrasound for prediction of microvascular invasion and recurrence of hepatocellular carcinoma

OBJECTIVE

To establish and validate a nomogram based on multi-modal ultrasound for preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC), and to assess the ability thereof to stratify recurrence-free survival (RFS).

METHODS

A total of 287 HCC patients undergoing surgical resection were prospectively enrolled, including 210 patients in the training cohort and 77 patients in the test cohort. All patients underwent conventional ultrasound, contrast-enhanced ultrasonography, and shear wave elastography examinations within one week before surgery. Taking histopathological examination result as the reference standard, independent factors associated with MVI in HCC were determined by logistic regression and a nomogram was established and further evaluated. The Kaplan-Meier method was used to analyze the prognostic value of histologic MVI status and nomogram-predicted MVI status.

RESULTS

Multivariate analysis showed that tumor diameter, echogenicity, tumor shape, arterial phase peritumoral enhancement and enhancement level in portal venous phase were independent predictors of MVI (all p < 0.05). The nomogram based on these variables showed good discrimination and calibration with the areas under the receiver operating characteristic curve (AUC) of 0.821 (0.762-0.870) and 0.789 (0.681-0.874) in the training and test cohorts. There was a significant difference in RFS between the nomogram-predicted MVI positive and the nomogram-predicted MVI negative groups in training and test cohorts (p < 0.001 and p = 0.004 respectively).

CONCLUSIONS

The multimodal ultrasound features were effective imaging markers for preoperative prediction of MVI of HCC and the nomogram might be an effective tool to stratify the risk of recurrence and guide the individualized treatment of HCC.

Liver Transplantation for Hepatocellular Carcinoma: How Should We Improve the Thresholds?

Simple Summary

The ideal treatment for hepatocellular carcinoma (HCC) is liver transplantation (LT), which both eliminates the HCC and cures the diseased liver. Once considered an experimental treatment with dismal survival rates, LT for HCC entered a new era with the establishment of the Milan criteria over 20 years ago. However, over the last two decades, the Milan criteria, which are based on tumor morphology, have come under intense scrutiny and are now largely regarded as too restrictive, and limit the access of transplantation for many patients who would otherwise achieve good clinical outcomes. The liver transplant community has been making every effort to reach a goal of establishing more reliable selection criteria. This article addresses how the criteria have been extended, as well as the concept of pre-transplant down-staging to maximize the eligibility.

Abstract

Hepatocellular carcinoma (HCC) is the third highest cause of cancer-related mortality, and liver transplantation is the ideal treatment for this disease. The Milan criteria provided the opportunity for HCC patients to undergo LT with favorable outcomes and have been the international gold standard and benchmark. With the accumulation of data, however, the Milan criteria are not regarded as too restrictive. After the implementation of the Milan criteria, many extended criteria have been proposed, which increases the limitations regarding the morphological tumor burden, and incorporates the tumor’s biological behavior using surrogate markers. The paradigm for the patient selection for LT appears to be shifting from morphologic criteria to a combination of biologic, histologic, and morphologic criteria, and to the establishment of a model for predicting post-transplant recurrence and outcomes. This review article aims to characterize the various patient selection criteria for LT, with reference to several surrogate markers for the biological behavior of HCC (e.g., AFP, PIVKA-II, NLR, 18F-FDG PET/CT, liquid biopsy), and the response to locoregional therapy. Furthermore, the allocation rules in each country and the present evidence on the role of down-staging large tumors are addressed.

The value of preoperative 18F-FDG PET metabolic and volumetric parameters in predicting microvascular invasion and postoperative recurrence of hepatocellular carcinoma

BACKGROUND

Microvascular invasion (MVI) is very important in the evaluation of hepatocellular carcinoma (HCC), but diagnosis is determined by postoperative pathology; thus, preoperative noninvasive methods will play an active role. The purpose of the study was to assess the performance of metabolic parameters of preoperative 18F-fluorodeoxyglucose PET/computerized tomography (18F-FDG PET/CT) in the prediction of MVI and postoperative recurrence in primary hepatocellular carcinoma.

METHODS

We retrospectively collected 72 patients with HCC who have performed 18F-FDG PET/CT scan before partial hepatectomy between 2016 and 2019. We used both normal liver tissue and inferior vena cava as the reference background and combined with clinicopathological features, 18F-FDG PET/CT metabolic and volumetric indices to predict MVI and postoperative recurrence of primary HCC before surgery.

RESULTS

Twenty-one of the 72 patients recurred, in recurrent cases showed higher maximum standard uptake value (SUVmax), TNR (ratio of tumor SUVmax to mean SUV [SUVmean] of the background tissue), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) than nonrecurrence cases (P < 0.001). All 18F-FDG PET metabolic and volumetric indices for predicting postoperative HCC recurrence were significant on receiver-operating-characteristic (ROC) curve analyses (P < 0.05). TNRIVC, TNRNL, MTVIVC, MTVNL TLGIVC and TLGNL were significant factors for predicting MVI in HCC (P < 0.05). On multivariate analyses, MVI, SUVmax, TNRIVC, TNRNL, MTVIVC, MTVNL, TLGIVC and TLGNL (P < 0.05) are independent risk factors for predicting postoperative HCC recurrence. TNRIVC is the most relevant PET/CT parameter for predicting MVI in HCC, and MTVIVC is the most valuable for predicting postoperative HCC recurrence. Moreover, the PET/CT parameters are more accurate for prognosis with inferior vena cava as a reference background than with normal liver tissue.

CONCLUSION

18F-FDG PET/CT metabolic and volumetric indices are effective predictors, and could noninvasively provide more comprehensive predictive information on MVI and postoperative recurrence of primary HCC before surgery.

[Radiologic Diagnosis of Hepatocellular Carcinoma]

There are various causes of hepatocellular carcinoma, including viral hepatitis, and treatment strategies are often established based on the radiology diagnosis, unlike other carcinomas. The liver imaging reporting and data system (LI-RADS) is a diagnostic system developed by the American College of Radiologists for clear communication and standardized reports of the liver imaging findings. It was recently included in the clinical guidance of the American Association for the Study of Liver Diseases. In addition, the radiologic findings of hepatocellular carcinoma (HCC) enable a prediction of the prognosis after treatment and a diagnosis of diseases because the use of gadoxetic acid MRI has become more common. Thus, the role of radiology for the diagnosis and treatment of HCC is expected to be developed further.

Progress of MRI Radiomics in Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is the sixth most common cancer in the world and the third leading cause of cancer-related death. Although the diagnostic scheme of HCC is currently undergoing refinement, the prognosis of HCC is still not satisfactory. In addition to certain factors, such as tumor size and number and vascular invasion displayed on traditional imaging, some histopathological features and gene expression parameters are also important for the prognosis of HCC patients. However, most parameters are based on postoperative pathological examinations, which cannot help with preoperative decision-making. As a new field, radiomics extracts high-throughput imaging data from different types of images to build models and predict clinical outcomes noninvasively before surgery, rendering it a powerful aid for making personalized treatment decisions preoperatively.

Objective

This study reviewed the workflow of radiomics and the research progress on magnetic resonance imaging (MRI) radiomics in the diagnosis and treatment of HCC.

Methods

A literature review was conducted by searching PubMed for search of relevant peer-reviewed articles published from May 2017 to June 2021.The search keywords included HCC, MRI, radiomics, deep learning, artificial intelligence, machine learning, neural network, texture analysis, diagnosis, histopathology, microvascular invasion, surgical resection, radiofrequency, recurrence, relapse, transarterial chemoembolization, targeted therapy, immunotherapy, therapeutic response, and prognosis.

Results

Radiomics features on MRI can be used as biomarkers to determine the differential diagnosis, histological grade, microvascular invasion status, gene expression status, local and systemic therapeutic responses, and prognosis of HCC patients.

Conclusion

Radiomics is a promising new imaging method. MRI radiomics has high application value in the diagnosis and treatment of HCC.

Diagnostic performance of the FDG-PET/CT in patients with resected mucinous colorectal liver metastases

BACKGROUND

and purpose: FDG-PET/CT has gained acceptance for tumours staging. Few and conflicting data exist on the sensitivity of FDG-PET/CT in identifying colorectal mucinous liver metastases (mucCRLM). The aim of this study was to evaluate the diagnostic performance of the FDG-PET/CT in patients with mucCRLM who underwent liver surgery.

METHODS

All patients affected by mucCRLM scheduled for liver resection who had undergone preoperative FDG-PET/CT between 2005 and 2018 were analyzed. Diagnostic performance of FDG-PET/CT was assessed in organ and lesion-based analysis.

RESULTS

58 patients out of 131 (44.2%) affected by mucCRLM fulfilled the inclusion criteria. 118 mucCRLM were detected. FDG-PET/CT confirmed 71 (60.2%) CRLM in 51 patients. The sensitivity and specificity of FDG-PET/CT were 89.4% and 100% in the organ-based analysis and 60.7% and 100% in lesion-based analysis. Absence of micro-vascular invasion (100% vs. 23%, p < 0.001) and median percentage of viable tumour cells were associated with FDG-PET/CT false negative (15% vs. 60%, p = 0.007). At ROC analysis viable tumour cells percentage >25% was associated with low risk of false negative (AUC 0.848; p = 0.006).

CONCLUSIONS

FDG-PET/CT had a significant rate of false negative results in patients with mucinous colorectal liver metastases. Negative FDG-PET/CT in patients with low percentage of viable tumour cells after chemotherapy should be considered with caution.

Imaging Features at the Periphery: Hemodynamics, Pathophysiology, and Effect on LI-RADS Categorization

Liver lesions have different enhancement patterns at dynamic contrast-enhanced imaging. The Liver Imaging Reporting and Data System (LI-RADS) applies the enhancement kinetic of liver observations in its algorithms for imaging-based diagnosis of hepatocellular carcinoma (HCC) in at-risk populations. Therefore, careful analysis of the spatial and temporal features of these enhancement patterns is necessary to increase the accuracy of liver mass characterization. The authors focus on enhancement patterns that are found at or around the margins of liver observations-many of which are recognized and defined by LI-RADS, such as targetoid appearance, rim arterial phase hyperenhancement, peripheral washout, peripheral discontinuous nodular enhancement, enhancing capsule appearance, nonenhancing capsule appearance, corona enhancement, and periobservational arterioportal shunts-as well as peripheral and periobservational enhancement in the setting of posttreatment changes. Many of these are considered major or ancillary features of HCC, ancillary features of malignancy in general, features of non-HCC malignancy, features associated with benign entities, or features related to treatment response. Distinction between these different patterns of enhancement can help with achieving a more specific diagnosis of HCC and better assessment of response to local-regional therapy. ^©RSNA, 2021.

Liver Transplantation in Patients with Hepatocellular Carcinoma beyond the Milan Criteria: A Comprehensive Review

The Milan criteria (MC) were developed more than 20 years ago and are still considered the benchmark for liver transplantation (LT) in patients with hepatocellular carcinoma (HCC). However, the strict application of MC might exclude some patients who may receive a clinical benefit of LT. Several expanded criteria have been proposed. Some of these consider pretransplant morphological and biological variables of the tumor, others consider post-LT variables such as the histology of the tumor, and others combine pre- and post-LT variables. More recently, the HCC response to locoregional treatments before transplantation emerged as a surrogate marker of the biological aggressiveness of the tumor to be used as a better selection criterion for LT in patients beyond the MC at presentation. This essential review aims to present the current data on the pretransplant selection criteria for LT in patients with HCC exceeding the MC at presentation based on morphological and histological characteristics of the tumor and to critically discuss those that have been validated in clinical practice. Moreover, the role of HCC biological markers and the tumor response to downstaging procedures as new tools for selecting patients with a tumor burden outside of the MC for LT is evaluated.

Diagnostic performance of imaging features in the HBP of gadoxetate disodium-enhanced MRI for microvascular invasion in hepatocellular carcinoma: a meta-analysis

BACKGROUND

Microvascular invasion (MVI) is a major risk factor for early recurrence in patients with hepatocellular carcinoma (HCC). Preoperative accurate evaluation of the presence of MVI could enormously benefit its treatment and prognosis.

PURPOSE

To evaluate and compare the diagnostic performance of two imaging features (non-smooth tumor margin and peritumor hypointensity) in the hepatobiliary phase (HBP) to preoperatively diagnose the presence of MVI in HCC.

MATERIAL AND METHODS

Original articles were collected from Medline/PubMed, Web of Science, EMBASE, and the Cochrane Library up to 17 January 2021 linked to gadoxetate disodium-enhanced magnetic resonance imaging (MRI) on 1.5 or 3.0 T. The pooled sensitivity, specificity, and summary area under the receiver operating characteristic curve (AUC) were calculated and meta-regression analyses were performed.

RESULTS

A total of 14 original articles involving 2193 HCCs were included. The pooled sensitivity and specificity of non-smooth tumor margin and peritumor hypointensity were 73% and 61%, and 43% and 90%, respectively, for the diagnosis of MVI in HCC. The summary AUC of non-smooth tumor margin (0.74) was comparable to that of peritumor hypointensity (0.76) (z = 0.693, P = 0.488). The meta-regression analysis identified four covariates as possible sources of heterogeneity: average size; time interval between index test and reference test; blindness to index test during reference test; and risk of bias score.

CONCLUSION

This meta-analysis showed moderate and comparable accuracy for predicting MVI in HCC using either non-smooth tumor margin or peritumor hypointensity in HBP. Four discovered covariates accounted for the heterogeneity.

A decade of multi-modality PET and MR imaging in abdominal oncology

OBJECTIVES

To investigate trends observed in a decade of published research on multimodality PET(/CT)+MR imaging in abdominal oncology, and to explore how these trends are reflected by the use of multimodality imaging performed at our institution.

METHODS

First, we performed a literature search (2009-2018) including all papers published on the multimodality combination of PET(/CT) and MRI in abdominal oncology. Retrieved papers were categorized according to a structured labelling system, including study design and outcome, cancer and lesion type under investigation and PET-tracer type. Results were analysed using descriptive statistics and evolutions over time were plotted graphically. Second, we performed a descriptive analysis of the numbers of MRI, PET/CT and multimodality PET/CT+MRI combinations (performed within a ≤14 days interval) performed during a similar time span at our institution.

RESULTS

Published research papers involving multimodality PET(/CT)+MRI combinations showed an impressive increase in numbers, both for retrospective combinations of PET/CT and MRI, as well as hybrid PET/MRI. Main areas of research included new PET-tracers, visual PET(/CT)+MRI assessment for staging, and (semi-)quantitative analysis of PET-parameters compared to or combined with MRI-parameters as predictive biomarkers. In line with literature, we also observed a vast increase in numbers of multimodality PET/CT+MRI imaging in our institutional data.

CONCLUSIONS

The tremendous increase in published literature on multimodality imaging, reflected by our institutional data, shows the continuously growing interest in comprehensive multivariable imaging evaluations to guide oncological practice.

ADVANCES IN KNOWLEDGE

The role of multimodality imaging in oncology is rapidly evolving. This paper summarizes the main applications and recent developments in multimodality imaging, with a specific focus on the combination of PET+MRI in abdominal oncology.

Therapies for hepatocellular carcinoma: overview, clinical indications, and comparative outcome evaluation-part one: curative intention

Hepatocellular carcinoma (HCC) offers unique management challenges as it commonly occurs in the setting of underlying chronic liver disease. The management of HCC is directed primarily by the clinical stage. The most commonly used staging system is the Barcelona-Clinic Liver Cancer system, which considers tumor burden based on imaging, liver function and the patient's performance status. Early-stage HCC can be managed with therapies of curative intent including surgical resection, liver transplantation, and ablative therapies. This manuscript reviews the various treatment options for HCC with a curative intent, such as locablative therapy types, surgical resection, and transplant. Indications, contraindications and outcomes of the various treatment options are reviewed. Multiple concepts relating to liver transplant are discussed including Milan criteria, OPTN policy, MELD exception points, downstaging to transplant and bridging to transplant.

Intraprocedurally EOB-MRI/US fusion imaging focusing on hepatobiliary phase findings can help to reduce the recurrence of hepatocellular carcinoma after radiofrequency ablation

BACKGROUND & AIMS

To explore the ability of gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid magnetic resonance imaging (EOB-MRI)/ultrasound (US) fusion imaging (FI) to improve the prognosis of radiofrequency ablation (RFA) by ablating the characteristic findings of hepatocellular carcinoma (HCC) in hepatobiliary phase (HBP) imaging.

METHODS

We retrospectively recruited 115 solitary HCC lesions with size of (15.9 ± 4.6) mm. They were all treated by RFA and preoperative EOB-MRI. According to the modalities guiding RFA performance, the lesions were grouped into contrast enhanced US (CEUS)/US guidance group and EOB-MRI/US FI guidance group. For the latter group, the ablation scope was set to cover the HBP findings (peritumoral hypointensity and irregular protruding margin). The presence of HBP findings, the modalities guided RFA, the recurrence rate were observed.

RESULTS

After an average follow-up of 377 days, local tumor progression (LTP) and intrahepatic distant recurrence (IDR) were 14.8% and 38.4%, respectively. The lesions having HBP findings exhibited a higher recurrence rate (73.7%) than the lesions without HBP findings (42.9%) (p = 0.002) and a low overall recurrence-free curve using the Kaplan-Meier method (p = 0.038). Using EOB-MRI/US FI as guidance, there was no difference in the recurrence rate between the groups with and without HBP findings (p = 0.799). In lesions with HBP findings, RFA guided by EOB-MRI/US FI (53.8%) produced a lower recurrence rate than CEUS/US (84.0%) (p = 0.045).

CONCLUSIONS

The intraprocedurally application of EOB-MRI/US FI to determine ablation scope according to HBP findings is feasible and beneficial for prognosis of RFA.

Diagnostic test accuracies of F-18 FDG PET/CT for prediction of microvascular invasion of hepatocellular carcinoma: A meta-analysis

PURPOSE

The aim of the current meta-analysis was to evaluate diagnostic accuracies of preoperative F-18 fluorodeoxyglucose (FDG) positron emission tomography (PET) or positron emission tomography/computed tomography (PET/CT) for prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients.

METHODS

The scientific database such as PubMed, Cochrane, and Embase database were searched for studies evaluating diagnostic accuracies of preoperative F-18 FDG PET or PET/CT for prediction of MVI in HCC patients up to November 30, 2020.

RESULTS

Fourteen eligible studies (1276 patients) were enrolled. The pooled sensitivity for F-18 FDG PET or PET/CT was 0.67 (95% CI; 0.57-0.76) with heterogeneity and a pooled specificity of 0.80 (95% CI; 0.74-0.85) with heterogeneity. Likelihood ratio (LR) syntheses gave an overall positive likelihood ratio (LR+) of 3.3 (95% CI; 2.5-4.5) and negative likelihood ratio (LR-) of 0.41 (95% CI; 0.31-0.55). The pooled diagnostic odds ratio (DOR) was 8 (95% CI; 5-14). Summary receiver operating characteristic (ROC) curve indicates that the area under the curve was 0.81 (95% CI; 0.78-0.84).

CONCLUSION

The current meta-analysis showed a low sensitivity and moderate specificity of F-18 FDG PET or PET/CT for the prediction of MVI in HCC patients. F-18 FDG PET or PET/CT might not be useful for the preoperative prediction of MVI in HCC patients and should not be used to exclude MVI. Therefore, cautious application and interpretation should be paid to the F-18 FDG PET or PET/CT for the prediction of MVI in HCC patients preoperatively.

2-[18F]FDG PET/CT as a Predictor of Microvascular Invasion and High Histological Grade in Patients with Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) generally presents a low avidity for 2-deoxy-2-[18F]fluoro-d-glucose (FDG) in PET/CT although an increased FDG uptake seems to relate to more aggressive biological factors. To define the prognostic value of PET/CT with FDG in patients with an HCC scheduled for a tumor resection, forty-one patients were prospectively studied. The histological factors of a poor prognosis were determined and FDG uptake in the HCC lesions was analyzed semi-quantitatively (lean body mass-corrected standardized uptake value (SUL) and tumor-to-liver ratio (TLR) at different time points). The PET metabolic parameters were related to the histological characteristics of the resected tumors and to the evolution of patients. Microvascular invasion (MVI) and a poor grade of differentiation were significantly related to a worse prognosis. The SULpeak of the lesion 60 min post-FDG injection was the best parameter to predict MVI while the SULpeak of the TLR at 60 min was better for a poor differentiation. Moreover, the latter parameter was also the best preoperative variable available to predict any of these two histological factors. Patients with an increased TLRpeak60 presented a significantly higher incidence of poor prognostic factors than the rest (75% vs. 28.6%, p = 0.005) and a significantly higher incidence of recurrence at 12 months (38% vs. 0%, p = 0.014). Therefore, a semi-quantitative analysis of certain metabolic parameters on PET/CT can help identify, preoperatively, patients with histological factors of a poor prognosis, allowing an adjustment of the therapeutic strategy for those patients with a higher risk of an early recurrence.

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.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

KEY POINTS

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

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

OBJECTIVE

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

Background

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

Methods

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

Results

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

Conclusions

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

A Nomogram Estimation for the Risk of Microvascular Invasion in Hepatocellular Carcinoma Patients Meeting the Milan Criteria

OBJECTIVE

We aimed to develop and validate a nomogram for preoperatively estimating the risk of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) within the Milan criteria.

METHODS

The clinical data of 312 HCC patients who underwent liver surgery at the xxx from Jan 2017 to Dec 2019 were retrospectively collected. Then, the study population was categorized into the training and validation group based on the date of surgery. To identify risk factors related to MVI, we conducted a series of logistic regression analyses. By combining these risk factors, a nomogram was then established. We further clarified the usability of our model through the area under the ROC curve (AUC), decision curve analysis (DCA), and calibration curve.

RESULTS

Pathological examination revealed MVI in 108 patients with HCC (34.6%). Three independent predictors were identified: level of alpha-fetoprotein (AFP) exceeds 194 ng/mL (OR = 2.20, 95% CI: 1.13-4.31, p = 0.021), size of tumor (OR = 1.59; 95% CI: 1.18-2.12; P < 0.001) and number of tumors (OR = 3.37, 95% CI: 1.64-7.28, p < 0.001). A nomogram was subsequently built with an AUC of 0.73 and 0.74 respectively in the training cohort and validation cohort. The calibration curve showed a relatively high consistency between predicted probability and observed outcomes. Besides, the DCA revealed that the model was clinically beneficial for preoperatively predicting MVI in HCC.

CONCLUSIONS

A model for evaluating the risk of MVI HCC patients was developed and validated. The model could provide clinicians with a relatively reliable basis for optimizing treatment decisions.

Radiomics analysis of [18F]FDG PET/CT for microvascular invasion and prognosis prediction in very-early- and early-stage hepatocellular carcinoma

As a reliable preoperative predictor for microvascular invasion (MVI) and disease-free survival (DFS) is lacking, we developed a radiomics nomogram of [¹⁸F]FDG PET/CT to predict MVI status and DFS in patients with very-early- and early-stage (BCLC 0, BCLC A) hepatocellular carcinoma (HCC).

METHODS

Patients (N = 80) with BCLC0-A HCC who underwent [¹⁸F]FDG PET/CT before surgery were enrolled in this retrospective study and were randomized to a training cohort and a validation cohort. Texture features from patients obtained using Lifex software in the training cohort were subjected to LASSO regression to select the most useful predictive features of MVI and DFS. Then, the radiomics nomogram was constructed using the radiomics signature and clinical features and further validated.

RESULTS

To predict MVI, the [¹⁸F]FDG PET/CT radiomics signature consisted of five texture features from the PET and six texture features from CT. The signature was significantly associated with MVI status in the training cohort (P = 0.001). None of the clinical features was independent predictors for MVI status (P > 0.05). The area under the curve value of the M-PET/CT model was 0.891 (95% CI: 0.799-0.984) in the training cohort and showed good discrimination and calibration. To predict DFS, the [¹⁸F]FDG PET/CT radiomics nomogram (D-PET/CT model) and a clinicopathologic nomogram were built in the training cohort. The D-PET/CT model, which integrated the D-PET/CT radiomics signature with INR and TB, provided better predictive performance (C-index: 0.831, 95% CI: 0.761-0.900) and larger net benefits than the simple clinical model, as determined by decision curve analyses.

CONCLUSION

The newly developed [¹⁸F]FDG PET/CT radiomics signature was an independent biomarker for the estimation of MVI and DFS in patients with very-early- and early-stage HCC. Moreover, PET/CT nomogram, which incorporated the radiomics signature of [¹⁸F]FDG PET/CT and clinical risk factors in patients with very-early- and early-stage HCC, performed better for individualized DFS estimation, which might enable a step forward in precise medicine.

A 2020 update on liver transplant for hepatocellular carcinoma

INTRODUCTION

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

AREA COVERED

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

EXPERT OPINION

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

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

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

CT Image-Based Texture Analysis to Predict Microvascular Invasion in Primary Hepatocellular Carcinoma

The objective of this study was to determine the clinical value of computed tomography (CT) image-based texture analysis in predicting microvascular invasion of primary hepatocellular carcinoma (HCC). CT images of patients with HCC from May 2017 to May 2019 confirmed by surgery and histopathology were retrospectively analyzed. Image features including tumor margin, tumor capsule, peritumoral enhancement, hypoattenuating halo, intratumoral arteries, and tumor-liver differences were assessed. All patients were divided into microvascular invasion (MVI)-negative group (n = 34) and MVI-positive group (n = 68). Preoperative CT images were further imported into MaZda software, where the regions of interest of the lesions were manually delineated. Texture features of lesions based on pre-contrast, arterial, portal, and equilibrium phase CT images were extracted. Thirty optimal texture parameters were selected from each phase by Fisher's coefficient (Fisher), classification error probability combined with average correlation coefficient (POE+ACC), and mutual information (MI). Finally, receiver operating characteristic curve analysis was performed. The results showed that the Edmonson-Steiner grades, tumor size, tumor margin, and intratumoral artery characteristics were significantly different between the two groups (P = 0.012, < 0.001, < 0.001, = 0.003, respectively). There were 58 parameters with significant differences between the MVI-negative and MVI-positive groups (P < 0.001 for all). Among them, 12, 14, 17, and 15 parameters were derived from the pre-contrast phase, arterial phase, portal phase, and equilibrium phase respectively. According to the ROC analysis, optimal texture parameters based on the pre-contrast, arterial, portal, and equilibrium phases were 135dr_GLevNonU (AUC, 0.766; the cutoff value, 1055.00), Vertl_RLNonUni (AUC, 0.764; the cutoff value, 5974.38), 45dgr_GLevNonU (AUC, 0.762; the cutoff value, 924.34), and Vertl_RLNonUni (AUC, 0.754; the cutoff value, 4868.80), respectively. Texture analysis of preoperative CT images may be used as a non-invasive method to predict microvascular invasion in patients with primary hepatocellular carcinomas, and further to guide the treatment and evaluate prognosis. The most valuable parameters were derived from the gray-level run-length matrix.

The application of texture quantification in hepatocellular carcinoma using CT and MRI: a review of perspectives and challenges

Recently, radiomic texture quantification of tumors has received much attention from radiologists, scientists, and stakeholders because several results have shown the feasibility of using the technique to diagnose and manage oncological conditions. In patients with hepatocellular carcinoma, radiomics has been applied in all stages of tumor evaluation, including diagnosis and characterization of the genotypic behavior of the tumor, monitoring of treatment responses and prediction of various clinical endpoints. It is also useful in selecting suitable candidates for specific treatment strategies. However, the clinical validation of hepatocellular carcinoma radiomics is limited by challenges in imaging protocol and data acquisition parameters, challenges in segmentation techniques, dimensionality reduction, and modeling methods. Identification of the best segmentation and optimal modeling methods, as well as texture features most stable to imaging protocol variability would go a long way in harmonizing HCC radiomics for personalized patient care. This article reviews the process of HCC radiomics, its clinical applications, associated challenges, and current optimization strategies.

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.

When to call it off: defining transplant candidacy limits in liver donor liver transplantation for hepatocellular carcinoma

Background

Living donor liver transplantation (LDLT) is an acceptable treatment option for hepatocellular carcinoma (HCC). Traditional transplant criteria aim at best utilization of donor organs with low risk of post transplant recurrence. In LDLT, long term recurrence free survival (RFS) of 50% is considered acceptable. The objective of the current study was to determine preoperative factors associated with high recurrence rates in LDLT.

Methods

Between April 2012 and December 2019, 898 LDLTs were performed at our center. Out of these, 242 were confirmed to have HCC on explant histopathology. We looked at preoperative factors associated with ≤ 50%RFS at 4 years. For survival analysis, Kaplan Meier curves were used and Cox regression analysis was used to identify independent predictors of recurrence.

Results

Median AFP was 14.4(0.7–11,326.7) ng/ml. Median tumor size was 2.8(range = 0.1–11) cm and tumor number was 2(range = 1–15). On multivariate analysis, AFP > 600 ng/ml [HR:6, CI: 1.9–18.4, P = 0.002] and microvascular invasion (MVI) [HR:5.8, CI: 2.5–13.4, P <  0.001] were independent predictors of 4 year RFS ≤ 50%. When AFP was > 600 ng/ml, MVI was seen in 88.9% tumors with poor grade and 75% of tumors outside University of California San Francisco criteria. Estimated 4 year RFS was 78% for the entire cohort. When AFP was < 600 ng/ml, 4 year RFS for well-moderate and poor grade tumors was 88 and 73%. With AFP > 600 ng/ml, RFS was 53% and 0 with well-moderate and poor grade tumors respectively (P <  0.001).

Conclusion

Patients with AFP < 600 ng/ml have acceptable outcomes after LDLT. In patients with AFP > 600 ng/ml, a preoperative biopsy to rule out poor differentiation should be considered for patient selection.

Predicting tumor recurrence using metabolic indices of 18F-FDG PET/CT prior to orthotopic liver transplantationfor hepatocellular carcinoma

The present study analyzed the ability of metabolic burden indices from ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) to predict tumor recurrence following orthotopic liver transplantation (OLT) in patients with hepatocellular carcinoma (HCC). Seven major metabolic indices were measured by ¹⁸F-FDG PET/CT in 93 patients with HCC, prior to OLT. The Mann-Whitney U test was then used to predict the association of metabolic indices, including the maximum standardized uptake value (SUVmax), tumor-to-mediastinum SUV ratio, tumor-to-normal-liver SUV ratio, SUV normalized to lean body mass metabolic tumor volume (MTV), total lesion glycolysis (TLG) and uptake-volume product (UVP), with the recurrence risk. The Deauville-like scoring system was used to quantify the recurrence risk. Univariate and multivariable Cox regression models were performed to determine survival rate. The results showed that Deauville-like score (PET-negative vs. -positive), MTV (cutoff value, 13.36), TLG (cutoff value, 62.21) and UVP (cutoff value, 66.60) had high prediction performance for tumor recurrence (P<0.05). TLG had the highest receiver operating characteristics area under the curve of 0.725. Among the clinical factors, high level of α-fetoprotein (AFP, ≥144 ng/ml), Milan criteria, tumor number (>3), involvement of both right and left lobes, and tumor size (>5 cm) were found to be significant predictors of tumor recurrence. Patients in the low metabolic group had longer recurrence-free survival (RFS) times compared with those in the high metabolic group, regardless of whether they met the Milan criteria or not. AFP, uptake-volume product according the SUV mean of mediastinum (UVP-M), Milan criteria, lymph node metastasis, and the number of tumors were significant prognostic factors for RFS (P<0.05) in both univariate and multivariate survival analyses. Additionally, the MVI was a significant prognostic factor based on univariate survival analyses. Overall, the present study demonstrated the metabolic burden indices measured by PET/CT, Deauville-like score, MTV, TLG and UVP as significant prognostic factors in patients with HCC following OLT. The combination of metabolic indices measured by PET/CT and the existing criteria, such as the Milan criteria, may play an important role in evaluating the suitability of OLT in specific patients.

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

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

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

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

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