Macrotrabecular-massive hepatocellular carcinoma: A distinctive histological subtype with clinical relevance

Deep Learning Classification and Quantification of Pejorative and Nonpejorative Architectures in Resected Hepatocellular Carcinoma from Digital Histopathologic Images

Liver resection is one of the best treatments for small hepatocellular carcinoma (HCC), but post-resection recurrence is frequent. Biotherapies have emerged as an efficient adjuvant treatment, making the identification of patients at high risk of recurrence critical. Microvascular invasion (mVI), poor differentiation, pejorative macrotrabecular architectures, and vessels encapsulating tumor clusters architectures are the most accurate histologic predictors of recurrence, but their evaluation is time-consuming and imperfect. Herein, a supervised deep learning-based approach with ResNet34 on 680 whole slide images (WSIs) from 107 liver resection specimens was used to build an algorithm for the identification and quantification of these pejorative architectures. This model achieved an accuracy of 0.864 at patch level and 0.823 at WSI level. To assess its robustness, it was validated on an external cohort of 29 HCCs from another hospital, with an accuracy of 0.787 at WSI level, affirming its generalization capabilities. Moreover, the largest connected areas of the pejorative architectures extracted from the model were positively correlated to the presence of mVI and the number of tumor emboli. These results suggest that the identification of pejorative architectures could be an efficient surrogate of mVI and have a strong predictive value for the risk of recurrence. This study is the first step in the construction of a composite predictive algorithm for early post-resection recurrence of HCC, including artificial intelligence-based features.

Preoperative CT features for characterization of vessels that encapsulate tumor clusters in hepatocellular carcinoma

PURPOSE

To explore the capability of preoperative CT imaging features, in combination with clinical indicators, for predicting vessels that encapsulate tumor clusters (VETC) pattern and prognosis in hepatocellular carcinoma (HCC).

MATERIALS AND METHODS

From January 2015 to May 2022, patients with HCC who underwent curative resection and preoperative enhanced CT were retrospectively included. Clinical indicators and imaging featuresassociated with the VETC pattern were determined by logistic regression analyses. The early recurrence (ER) rate was determined using the Kaplan-Meier survival curve. Factors associated with ER after surgical resection were identified by Cox regression analyses.

RESULT

A total of 243 patients with HCCwere evaluated. The total bilirubin > 17.1 μmol/L (odds ratio [OR] 3.43, 95 % Confidence Interval [CI] 1.70, 6.91, p = 0.001), serum α-fetoprotein > 100 ng/mL (OR 2.41, 95 % CI 1.25, 4.67, p = 0.009), intratumor artery (IA) (OR 2.00, 95 % CI 1.04, 3.86,p = 0.039) and arterial peritumoral enhancement (OR 2.60, 95 % CI 1.13, 5.96, p = 0.025) were independent risk factors for VETC+-HCC. The VETC+status andCT feature ofIA were associated with an increased risk of recurrence, with a shorter median RFS, compared to those without these factors (p < 0.001 and p = 0.019, respectively). In multivariable Cox regression analysis, the VETC+(hazard ratio [HR] 2.60, 95 % CI 1.66, 4.09, p < 0.001), morphological patterns of confluent multinodular growth (HR 1.79, 95 % CI 1.10, 2.91,p = 0.019), the number of the tumors (≥2) (HR 2.69, 95 % CI 1.56, 4.65, p < 0.001), and the IA (HR 1.73, 95 % CI 1.12, 2.66, p = 0.013) were independent predictors of ER in patients with HCC after surgical resection.

CONCLUSION

Preoperative CT features combined with clinical indicators could predict VETC pattern, and the CT features, along with VETC status, were of prognostic significance for early postoperative recurrence in patients with HCC.

CLINICAL RELEVANCE STATEMENT

Preoperative CT features combined with clinical indicators could predict VETC pattern, and the CT features, along with VETC status, were of prognostic significance for early recurrence in patients with HCC after surgical resection.

A nomogram for preoperative prediction of vessels encapsulating tumor clusters (VETC) pattern and prognosis of hepatocellular carcinoma

BACKGROUND

Vessels encapsulating tumor clusters (VETC) pattern of hepatocellular carcinoma (HCC) are associated with unfavorable prognosis. This study aimed to establish a nomogram model to predict VETC patterns based on preoperative CT imaging features.

PATIENTS AND METHODS

Patients who underwent surgical resection between January 1, 2016 and August 31, 2022 were retrospectively included. Predictors associated with VETC pattern were determined by using logistic regression analyses, and a nomogram model was constructed. Prognostic factors associated with recurrence-free survival (RFS) after surgical resection were identified by using Cox regression analyses.

RESULTS

A total of 84 patients were included for CT analysis. All patients underwent radical surgical resection. AST/ALT >1.07(odds ratio [OR], 4.91; 95 ​% CI: 1.11, 21.68; P ​< ​0.05), intratumoral necrosis (OR, 4.99; 95 ​% CI: 1.25, 19.99; P ​< ​0.05) and enhancing capsule (OR, 3.32; 95 ​% CI: 1.27, 8.94; P ​< ​0.05) were independent predictors of VETC pattern. These features were used for the construction of nomogram model, which showed comparable prediction performance, with AUC value of 0.767 (95%CI [0.662, 0.852]). CK19 status (Hazard ratio [HR], 2.02; 95 ​% CI: 1.06, 3.86; P ​< ​0.05), the number of tumors (HR, 3.31; 95 ​% CI: 1.47, 7.45; P ​< ​0.05) and VETC pattern (HR, 2.52; 95 ​% CI: 1.31, 4.86; P ​< ​0.05) were independent predictors of postoperative RFS.

CONCLUSION

A nomogram model based on preoperative CT imaging features could be used for the characterization of VETC pattern, and has prognostic significance for postoperative RFS in patients with HCC.

Imaging Prognostic Biomarkers in Hepatocellular Carcinoma: A Comprehensive Review

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide with its incidence on the rise globally. This paper provides a comprehensive review of prognostic imaging markers in HCC, emphasizing their role in risk stratification and clinical decision-making. We explore quantitative and qualitative criteria derived from imaging studies, such as computed tomography (CT) and magnetic resonance imaging (MRI), which can offer valuable insights into the biological behavior of the tumor. While many of these markers are not yet widely integrated into current clinical guidelines, they represent a promising future direction for approaching this highly heterogeneous cancer. However, standardization and validation of these markers remain important challenges. We conclude by emphasizing the importance of ongoing research to enhance clinical practices and improve outcomes for patients with HCC.

British Society of Gastroenterology guidelines for the management of hepatocellular carcinoma in adults

Deaths from the majority of cancers are falling globally, but the incidence and mortality from hepatocellular carcinoma (HCC) is increasing in the United Kingdom and in other Western countries. HCC is a highly fatal cancer, often diagnosed late, with an incidence to mortality ratio that approaches 1. Despite there being a number of treatment options, including those associated with good medium to long-term survival, 5-year survival from HCC in the UK remains below 20%. Sex, ethnicity and deprivation are important demographics for the incidence of, and/or survival from, HCC. These clinical practice guidelines will provide evidence-based advice for the assessment and management of patients with HCC. The clinical and scientific data underpinning the recommendations we make are summarised in detail. Much of the content will have broad relevance, but the treatment algorithms are based on therapies that are available in the UK and have regulatory approval for use in the National Health Service.

Outcomes in Patients with Macrotrabecular-Massive Subtype Hepatocellular Carcinoma Treated with Yttrium-90 Transarterial Radioembolization

PURPOSE

To compare the outcomes of yttrium-90 transarterial radioembolization (TARE) in patients with hepatocellular carcinoma (HCC) with and without macrotrabecular-massive (MTM) subtypes.

MATERIALS AND METHODS

Forty-one consecutive patients with HCC (male, 90.3%; mean age, 65.3 years [SD ± 10.7]) who underwent yttrium-90 TARE between September 2014 and January 2022 were grouped into the MTM-HCC (n = 17, 41.5%) and non-MTM-HCC (n = 24, 58.5%) groups based on their histopathological subtypes. Demographic, clinical, and radiological characteristics were compared. Survival, univariate, and multivariate analyses were performed, and prognostic factors were evaluated.

RESULTS

In MTM-HCC group, the rates of moderately to poorly differentiated tumors were significantly higher (13/17 vs 8/16, P = .007), and new intrahepatic/extrahepatic metastases were detected more frequently (12/17 vs 15/24, P = .038). Median overall survival (OS) in the cohort was 29 months (range, 17.1-40.9 months), whereas patients with MTM-HCC had a significantly shorter median OS (20 vs 44 months, P = .014). In univariate analysis, MTM-HCC subtype (hazard ratio [HR], 2.690; P = .021), the presence of satellite nodules (HR, 3.810; P = .004), and macrovascular invasion (HR, 3.321; P = .012) were identified as significant prognostic factors. In multivariate analysis, MTM-HCC subtype and macrovascular invasion were determined as independent poor prognostic factors (P = .038 and P = .012, respectively).

CONCLUSIONS

In patients with HCC treated with yttrium-90 TARE, both the rates of moderately to poorly differentiated histopathological classes and the development of intrahepatic or extrahepatic metastases were significantly higher in the MTM-HCC subtype. OS was worse in patients with MTM-HCC, and macrovascular invasion and MTM-HCC subtype were identified as independent poor prognostic factors.

Nomogram for preoperative estimation of microvascular invasion risk in hepatocellular carcinoma

Microvascular invasion (MVI) is an adverse prognostic indicator of tumor recurrence after surgery for hepatocellular carcinoma (HCC). Therefore, developing a nomogram for estimating the presence of MVI before liver resection is necessary. We retrospectively included 260 patients with pathologically confirmed HCC at the Fifth Medical Center of Chinese PLA General Hospital between January 2021 and April 2024. The patients were randomly divided into a training cohort (n = 182) for nomogram development, and a validation cohort (n = 78) to confirm the performance of the model (7:3 ratio). Significant clinical variables associated with MVI were then incorporated into the predictive nomogram using both univariate and multivariate logistic analyses. The predictive performance of the nomogram was assessed based on its discrimination, calibration, and clinical utility. Serum carnosine dipeptidase 1 ([CNDP1] OR 2.973; 95 % CI 1.167-7.575; p = 0.022), cirrhosis (OR 8.911; 95 % CI 1.922-41.318; p = 0.005), multiple tumors (OR 4.095; 95 % CI 1.374-12.205; p = 0.011), and tumor diameter ≥3 cm (OR 4.408; 95 % CI 1.780-10.919; p = 0.001) were independent predictors of MVI. Performance of the nomogram based on serum CNDP1, cirrhosis, number of tumors and tumor diameter was achieved with a concordance index of 0.833 (95 % CI 0.771-0.894) and 0.821 (95 % CI 0.720-0.922) in the training and validation cohorts, respectively. It fitted well in the calibration curves, and the decision curve analysis further confirmed its clinical usefulness. The nomogram, incorporating significant clinical variables and imaging features, successfully predicted the personalized risk of MVI in HCC preoperatively.

Histological predictors of aggressive recurrence of hepatocellular carcinoma after liver resection

BACKGROUND AND AIMS

Assessment of recurrence risk after liver resection (LR) is critical in hepatocellular carcinoma (HCC), particularly with the advent of effective adjuvant therapy. The aim of the study was to analyze the clinical and pathological factors associated with recurrence, aggressive recurrence, and survival after LR.

METHOD

Retrospective study in which all single HCC (BCLC-0/A) patients treated with LR between February 2000 and November 2020 were included. The main clinical variables were recorded. Histological features were blindly evaluated by two independent pathologists. Aggressive recurrence was defined as those that exceeded the Milan criteria at 1st recurrence.

RESULTS

A total of 218 patients were included (30% BCLC 0 and 70% BCLC A), median (IQR) tumor size of 28 (19-42mm). The prevalence of microvascular invasion and/or satellitosis (mVI/S) was 39%, with a kappa-index between both pathologists of 0.8. After a median follow-up of 49 (23-85) months, 61/218 (28%) patients died, 32/218 (15%) underwent LT, 127 (58%) developed HCC recurrence. The prevalence of aggressive recurrence was 35% (44/127 Milan-out, with 20 cases at advanced stage), and the 5-year survival was 81%. The presence of mVI/S was the only independent predictor of recurrence [HR:1.83 (1.28-2.61), p<0.001], aggressive recurrence [HR:3.31(1.74-6.29), p<0.001] and mortality [HR:2.23(1.27- 3.91), p:0.005]. The presence of MTM was significantly associated with a higher prevalence of mVI/S, Edmonson Steiner grade III-IV, AFP values and vessels that encapsulate tumor clusters, but MTM was not significantly associated with recurrence, aggressive recurrence, or OS.

CONCLUSION

The presence of mVI/S was the only independent risk factor for aggressive recurrence and mortality. This has important implications for early-stage patient management, especially in the setting of adjuvant immunotherapy or ab initio LT.

Evaluation and Prognostication of Gd-EOB-DTPA MRI and CT in Patients With Macrotrabecular-Massive Hepatocellular Carcinoma

BACKGROUND

Macrotrabecular-massive hepatocellular carcinoma (MTM-HCC) is highly aggressive. Comparing the diagnosis ability of CT and gadoxetate disodium (Gd-EOB-DTPA) MRI for MTM-HCC are lacking.

PURPOSE

To compare the performance of Gd-EOB-DTPA MRI and CT for differentiating MTM-HCC from non-MTM-HCC, and determine the prognostic indicator.

STUDY TYPE

Retrospective.

SUBJECTS

Post-surgery HCC patients, divided into the training (N = 272) and external validation (N = 44) cohorts.

FIELD STRENGTH/SEQUENCE

3.0 T, T1-weighted imaging, in-opp phase, and T1-weighted volumetric interpolated breath-hold examination/liver acquisition with volume acceleration; enhanced CT.

ASSESSMENT

Three radiologists evaluated clinical characteristics (sex, age, liver disease, liver function, blood routine, alpha-fetoprotein [AFP] and prothrombin time international normalization ratio [PT-INR]) and imaging features (tumor length, intratumor fat, hemorrhage, arterial phase peritumoral enhancement, intratumor necrosis or ischemia, capsule, and peritumoral hepatobiliary phase [HBP] hypointensity). Compared the performance of CT and MRI for diagnosing MTM-HCC. Follow-up occurred every 3-6 months, and nomogram demonstrated the probability of MTM-HCC.

STATISTICAL TESTS

Fisher test, t-test or Wilcoxon rank-sum test, area under the curve (AUC), 95% confidence interval (CI), multivariable logistic regression, Kaplan-Meier curve, and Cox proportional hazards. Significance level: P < 0.05.

RESULTS

Gd-EOB-DTPA MRI (AUC: 0.793; 95% CI, 0.740-0.839) outperformed CT (AUC: 0.747; 95% CI, 0.691-0.797) in the training cohort. The nomogram, incorporating AFP, PT-INR, and MRI features (non-intratumor fat, incomplete capsule, intratumor necrosis or ischemia, and peritumoral HBP hypointensity) demonstrated powerful performance for diagnosing MTM-HCC with an AUC of 0.826 (95% CI, 0.631-1.000) in the external validation cohort. Median follow-up was 347 days (interquartile range [IQR], 606 days) for the training cohort and 222 days (IQR, 441 days) for external validation cohort. Intratumor necrosis or ischemia was an independent indicator for poor prognosis.

DATA CONCLUSION

Gd-EOB-DTPA MRI might assist in preoperative diagnosis of MTM-HCC, and intratumor necrosis or ischemia was associated with poor prognosis.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY: Stage 2.

Prognostic significance of MRI features in patients with solitary large hepatocellular carcinoma following surgical resection

OBJECTIVE

To assess the prognostic impact of preoperative MRI features on outcomes for single large hepatocellular carcinoma (HCC) (≥ 8 cm) after surgical resection.

MATERIAL AND METHODS

This retrospective study included 151 patients (mean age: 59.2 years; 126 men) with a single large HCC who underwent gadoxetic acid-enhanced MRI and surgical resection between 2008 and 2020. Clinical variables, including tumor markers and MRI features (tumor size, tumor margin, and the proportion of hypovascular component on hepatic arterial phase (AP) (≥ 50% vs. < 50% tumor volume) were evaluated. Cox proportional hazards model analyzed overall survival (OS), recurrence-free survival (RFS), and associated factors.

RESULTS

Among 151 HCCs, 37.8% and 62.2% HCCs were classified as ≥ 50% and < 50% AP hypovascular groups, respectively. The 5- and 10-year OS and RFS rates in all patients were 62.0%, 52.6% and 41.4%, 38.5%, respectively. Multivariable analysis revealed that ≥ 50% AP hypovascular group (hazard ratio [HR] 1.7, p = 0.048), tumor size (HR 1.1, p = 0.006), and alpha-fetoprotein ≥ 400 ng/mL (HR 2.6, p = 0.001) correlated with poorer OS. ≥ 50% AP hypovascular group (HR 1.9, p = 0.003), tumor size (HR 1.1, p = 0.023), and non-smooth tumor margin (HR 2.1, p = 0.009) were linked to poorer RFS. One-year RFS rates were lower in the ≥ 50% AP hypovascular group than in the < 50% AP hypovascular group (47.4% vs 66.9%, p = 0.019).

CONCLUSION

MRI with ≥ 50% AP hypovascular component and larger tumor size were significant factors associated with poorer OS and RFS after resection of single large HCC (≥ 8 cm). These patients require careful multidisciplinary management to determine optimal treatment strategies.

CLINICAL RELEVANCE STATEMENT

Preoperative MRI showing a ≥ 50% arterial phase hypovascular component and larger tumor size can predict worse outcomes after resection of single large hepatocellular carcinomas (≥ 8 cm), underscoring the need for tailored, multidisciplinary treatment strategies.

KEY POINTS

MRI features offer insights into the postoperative prognosis for large hepatocellular carcinoma. Hypovascular component on arterial phase ≥ 50% and tumor size predicted poorer overall survival and recurrence-free survival. These findings can assist in prioritizing aggressive and multidisciplinary approaches for patients at risk for poor outcomes.

Imaging and prognostic characterization of fat-containing hepatocellular carcinoma subtypes

PURPOSE

Steatohepatitic hepatocellular carcinoma (SH-HCC) is characterized by intratumoral fat with > 50% inflammatory changes. However, intratumoral fat (with or without inflammation) can also be found in not-otherwise specified HCC (NOS-HCC). We compared the imaging features and outcome of resected HCC containing fat on pathology including SH-HCC (> 50% steatohepatitic component), NOS-HCC with < 50% steatohepatitic component (SH-NOS-HCC), and fatty NOS-HCC (no steatohepatitic component).

MATERIAL AND METHODS

From September 2012 to June 2021, 94 patients underwent hepatic resection for fat-containing HCC on pathology. Imaging features and categories were assessed using LIRADS v2018. Fat quantification was performed on chemical-shift MRI. Recurrence-free and overall survival were estimated.

RESULTS

Twenty-one patients (26%) had nonalcoholic steatohepatitis (NASH). The median intra-tumoral fat fraction was 8%, with differences between SH-HCC and SH-NOS-HCC (9.5% vs. 5% p = 0.03). There was no difference in major LI-RADS features between all groups; most tumors were classified as LR-4/5. A mosaic architecture on MRI was rare (7%) in SH-HCC, a fat in mass on CT was more frequently depicted (48%) in SH-HCC. A combination of NASH with no mosaic architecture on MRI or NASH with fat in mass on CT yielded excellent specificity for diagnosing SH-HCC (97.6% and 97.7%, respectively). The median recurrence-free and overall survival were 58 and 87 months, with no difference between groups (p = 0.18 and p = 0.69).

CONCLUSION

In patients with NASH, an SH-HCC may be suspected in L4/LR-5 observations with no mosaic architecture at MRI or with fat in mass on CT. Oncological outcomes appear similar between fat-containing HCC subtypes.

Diagnostic Model for Proliferative HCC Using LI-RADS: Assessing Therapeutic Outcomes in Hepatectomy and TKI-ICI Combination

BACKGROUND

Proliferative hepatocellular carcinoma (HCC), aggressive with poor prognosis, and lacks reliable MRI diagnosis.

PURPOSE

To develop a diagnostic model for proliferative HCC using liver imaging reporting and data system (LI-RADS) and assess its prognostic value.

STUDY TYPE

Retrospective.

POPULATION

241 HCC patients underwent hepatectomy (90 proliferative HCCs: 151 nonproliferative HCCs), divided into the training (N = 167) and validation (N = 74) sets. 57 HCC patients received combination therapy with tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs).

FIELD STRENGTH/SEQUENCE

3.0 T, T1- and T2-weighted, diffusion-weighted, in- and out-phase, T1 high resolution isotropic volume excitation and dynamic gadoxetic acid-enhanced imaging.

ASSESSMENT

LI-RADS v2018 and other MRI features (intratumoral artery, substantial hypoenhancing component, hepatobiliary phase peritumoral hypointensity, and irregular tumor margin) were assessed. A diagnostic model for proliferative HCC was established, stratifying patients into high- and low-risk groups. Follow-up occurred every 3-6 months, and recurrence-free survival (RFS), progression-free survival (PFS) and overall survival (OS) in different groups were compared.

STATISTICAL TESTS

Fisher's test or chi-square test, t-test or Mann-Whitney test, logistic regression, Harrell's concordance index (C-index), Kaplan-Meier curves, and Cox proportional hazards. Significance level: P < 0.05.

RESULTS

The diagnostic model, incorporating corona enhancement, rim arterial phase hyperenhancement, infiltrative appearance, intratumoral artery, and substantial hypoenhancing component, achieved a C-index of 0.823 (training set) and 0.804 (validation set). Median follow-up was 32.5 months (interquartile range [IQR], 25.1 months) for postsurgery patients, and 16.8 months (IQR: 13.2 months) for combination-treated patients. 99 patients experienced recurrence, and 30 demonstrated tumor nonresponse. Differences were significant in RFS and OS rates between high-risk and low-risk groups post-surgery (40.3% vs. 65.8%, 62.3% vs. 90.1%, at 5 years). In combination-treated patients, PFS rates differed significantly (80.6% vs. 7.7% at 2 years).

DATA CONCLUSION

The MR-based model could pre-treatment identify proliferative HCC and assist in prognosis evaluation.

LEVEL OF EVIDENCE: 4

TECHNICAL EFFICACY

Stage 2.

Quantitative information from gadobenate dimeglumine-enhanced MRI can predict proliferative subtype of solitary hepatocellular carcinoma: a multicenter retrospective study

OBJECTIVES

To investigate the value of quantitative parameters derived from gadobenate dimeglumine-enhanced magnetic resonance imaging (MRI) for predicting molecular subtype of hepatocellular carcinoma (HCC) and overall survival.

METHODS

This multicenter retrospective study included 218 solitary HCC patients who underwent gadobenate dimeglumine-enhanced MRI. All HCC lesions were resected and pathologically confirmed. The lesion-to-liver contrast enhancement ratio (LLCER) and lesion-to-liver contrast (LLC) were measured in the hepatobiliary phase. Potential risk factors for proliferative HCC were assessed by logistic regression. The ability of LLCER and LLC to predict proliferative HCC was assessed by the receiver operating characteristic (ROC) curve. Prognostic factors were evaluated using the Cox proportional hazards regression model for survival outcomes.

RESULTS

LLCER was an independent predictor of proliferative HCC (odds ratio, 0.015; 95% confidence interval [CI], 0.008-0.022; p < 0.001). The area under the ROC curve was 0.812 (95% CI, 0.748-0.877), higher than that of LLC, alpha-fetoprotein > 100 ng/ml, satellite nodules, and rim arterial phase hyperenhancement (all p ≤ 0.001). HCC patients with LLCER < -4.59% had a significantly higher incidence of proliferative HCC than those with the LLCER ≥ -4.59%. During the follow-up period, LLCER was an independent predictor of overall survival (hazard ratio, 0.070; 95% CI, 0.015-0.324; p = 0.001) in HCC patients.

CONCLUSIONS

Gadobenate dimeglumine-enhanced quantitative parameter in the hepatobiliary phase can predict the proliferative subtype of solitary HCC with a moderately high accuracy.

CLINICAL RELEVANCE STATEMENT

Quantitative information from gadobenate dimeglumine-enhanced MRI can provide crucial information on hepatocellular carcinoma subtypes. It might be valuable to design novel therapeutic strategies, such as targeted therapies or immunotherapy.

KEY POINTS

• The lesion-to-liver contrast enhancement ratio (LLCER) is an independent predictor of proliferative hepatocellular carcinoma (HCC). • The ability of LLCER to predict proliferative HCC outperformed lesion-to-liver contrast, alpha-fetoprotein > 100 ng/ml, satellite nodules, and rim arterial phase hyperenhancement. • HCC patients with LLCER < -4.59% had a significantly higher incidence of proliferative HCC than those with the LLCER ≥ -4.59%.

Diagnostic and Prognostic Ability of Contrast-Enhanced Unltrasound and Biomarkers in Hepatocellular Carcinoma Subtypes

OBJECTIVE

To investigate the diagnostic and prognostic value of contrast-enhanced ultrasound (CEUS) and clinical indicators of the vessels encapsulating tumor clusters (VETC) pattern and macrotrabecular-massive subtype in hepatocellular carcinoma (MTM-HCC).

METHODS

This retrospective study included patients who underwent preoperative CEUS and hepatectomy for HCC between August 2018 and August 2021. Multivariable logistic regression was performed to select independent correlated factors of VETC-HCC and MTM-HCC to develop nomogram models. The association between model outcomes and early postoperative HCC recurrence was assessed using Kaplan-Meier curve and Cox regression analysis.

RESULTS

The training cohort included 182 patients (54.3 ± 11.3 years, 168 males) and the validation cohort included 91 patients (54.8 ± 10.6 years, 81 males). Multivariate logistic regression analysis revealed that α-fetoprotein (AFP) levels (odds ratio [OR]: 2.26, 95% confidence interval [CI]: 1.49-3.42, p < 0.001), intratumoral nonenhancement (OR: 2.40, 95% CI: 1.02-5.64, p = 0.044), and the perfusion pattern in the CEUS arterial phase (OR: 2.27, 95% CI: 1.05-4.91, p = 0.038) were independent predictors of VETC-HCC. Besides, the former two were also independently associated with MTM-HCC (AFP level: OR: 2.36, 95% CI: 1.36-4.09, p = 0.002; intratumoral nonenhancement: OR: 3.72, 95% CI: 1.02-13.56, p = 0.046). Nomogram models were constructed based on the aforementioned indicators. Kaplan-Meier curve analysis indicated that predicted VETC-HCC or MTM-HCC exhibited higher rates of early recurrence (log-rank p < 0.001 and p = 0.002, respectively). Cox regression analysis showed that a high risk of VETC-HCC was independently correlated with early recurrence (p = 0.011).

CONCLUSION

CEUS combined with AFP levels can predict VETC-HCC/MTM-HCC and prognosis preoperatively.

MRI imaging features for predicting macrotrabecular-massive subtype hepatocellular carcinoma: a systematic review and meta-analysis

PURPOSE

To identify significant MRI features associated with macrotrabecular-massive hepatocellular carcinoma (MTM-HCC), and to assess the distribution of Liver Imaging Radiology and Data System (LI-RADS, LR) category assignments.

METHODS

PubMed and EMBASE were searched up to March 28, 2023. Random-effects model was constructed to calculate pooled diagnostic odds ratios (DORs) and 95% confidence intervals (CIs) for each MRI feature for differentiating MTM-HCC from NMTM-HCC. The pooled proportions of LI-RADS category assignments in MTM-HCC and NMTM-HCC were compared using z-test.

RESULTS

Ten studies included 1978 patients with 2031 HCCs (426 (20.9%) MTM-HCC and 1605 (79.1%) NMTM-HCC). Six MRI features showed significant association with MTM-HCC: tumor in vein (TIV) (DOR = 2.4 [95% CI, 1.6-3.5]), rim arterial phase hyperenhancement (DOR =2.6 [95% CI, 1.4-5.0]), corona enhancement (DOR = 2.6 [95% CI, 1.4-4.5]), intratumoral arteries (DOR = 2.6 [95% CI, 1.1-6.3]), peritumoral hypointensity on hepatobiliary phase (DOR = 2.2 [95% CI, 1.5-3.3]), and necrosis (DOR = 4.2 [95% CI, 2.0-8.5]). The pooled proportions of LI-RADS categories in MTM-HCC were LR-3, 0% [95% CI, 0-2%]; LR-4, 11% [95% CI, 6-16%]; LR-5, 63% [95% CI, 55-71%]; LR-M, 12% [95% CI, 6-19%]; and LR-TIV, 13% [95% CI, 6-22%]. In NMTM-HCC, the pooled proportions of LI-RADS categories were LR-3, 1% [95% CI, 0-2%]; LR-4, 8% [95% CI, 3-15%]; LR-5, 77% [95% CI, 71-82%]; LR-M, 5% [95% CI, 3-7%]; and LR-TIV, 6% [95% CI, 2-11%]. MTM-HCC had significantly lower proportion of LR-5 and higher proportion of LR-M and LR-TIV categories.

CONCLUSIONS

Six MRI features showed significant association with MTM-HCC. Additionally, compared to NMTM-HCC, MTM-HCC are more likely to be categorized LR-M and LR-TIV and less likely to be categorized LR-5.

CLINICAL RELEVANCE STATEMENT

Several MR imaging features can suggest macrotrabecular-massive hepatocellular carcinoma subtype, which can assist in guiding treatment plans and identifying potential candidates for clinical trials of new treatment strategies.

KEY POINTS

• Macrotrabecular-massive hepatocellular carcinoma is a subtype of HCC characterized by its aggressive nature and unfavorable prognosis. • Tumor in vein, rim arterial phase hyperenhancement, corona enhancement, intratumoral arteries, peritumoral hypointensity on hepatobiliary phase, and necrosis on MRI are indicative of macrotrabecular-massive hepatocellular carcinoma. • Various MRI characteristics can be utilized for the diagnosis of the macrotrabecular-massive hepatocellular carcinoma subtype. This can prove beneficial in guiding treatment decisions and identifying potential candidates for clinical trials involving novel treatment approaches.

Hepatitis B virus-related hepatocellular carcinoma has superior overall survival compared with other etiologies

BACKGROUND

Whether the etiology of chronic liver disease (CLD) impacts the overall survival (OS) of patients with hepatocellular carcinoma (HCC) remains unclear. We aim to clarify this issue.

MATERIALS AND METHODS

Between 2011 and 2020, 3941 patients who were newly diagnosed with HCC at our institution were enrolled in this study. In patients with multiple CLD etiologies, etiology was classified using the following hierarchy: hepatitis C virus (HCV) > hepatitis B virus (HBV) > alcohol-related > all negative. All negative was defined as negative for HCV, HBV, and alcohol use disorder.

RESULTS

Among 3941 patients, 1407 patients were classified with HCV-related HCC, 1677 patients had HBV-related HCC, 145 patients had alcohol-related HCC, and 712 patients had all-negative HCC. Using the all-negative group as the reference group, multivariate analysis showed that HBV is an independent predictor of mortality (hazard ratio: 0.856; 95% confidence interval: 0.745-0.983; p = 0.027). Patients with HBV-related HCC had superior OS compared with patients with other CLD etiologies (p<0.001). Subgroup analyses were performed, for Barcelona Clinic Liver Cancer (BCLC) stages 0-A (p<0.001); serum alpha-fetoprotein (AFP) levels≧20 ng/ml (p<0.001); AFP levels < 20 ng/ml (p<0.001); age > 65 years (p<0.001); and the use of curative treatments (p = 0.002). No significant difference in OS between HBV and other etiologies was observed among patients aged ≤ 65 years (p = 0.304); with BCLC stages B-D (p = 0.973); or who underwent non-curative treatments (p = 0.1).

CONCLUSION

Patients with HBV-related HCC had superior OS than patients with other HCC etiologies.

Blockade of PD-1 and CTLA-4: A potent immunotherapeutic approach for hepatocellular carcinoma

Immune checkpoints (ICPs) can promote tumor growth and prevent immunity-induced cancer cell apoptosis. Fortunately, targeting ICPs, such as programmed cell death 1 (PD-1) or cytotoxic T lymphocyte associated protein 4 (CTLA-4), has achieved great success in the past few years and has gradually become an effective treatment for cancers, including hepatocellular carcinoma (HCC). However, many patients do not respond to ICP therapy due to acquired resistance and recurrence. Therefore, clarifying the specific mechanisms of ICP in the development of HCC is very important for enhancing the efficacy of anti-PD-1 and anti-CTLA-4 therapy. In particular, antigen presentation and interferon-γ (IFN-γ) signaling were reported to be involved in the development of resistance. In this review, we have explained the role and regulatory mechanisms of ICP therapy in HCC pathology. Moreover, we have also elaborated on combinations of ICP inhibitors and other treatments to enhance the antitumor effect. Collectively, recent advances in the pharmacological targeting of ICPs provide insights for the development of a novel alternative treatment for HCC.

Automated Assessment of T2-Weighted MRI to Differentiate Malignant and Benign Primary Solid Liver Lesions in Noncirrhotic Livers Using Radiomics

RATIONALE AND OBJECTIVES

Distinguishing malignant from benign liver lesions based on magnetic resonance imaging (MRI) is an important but often challenging task, especially in noncirrhotic livers. We developed and externally validated a radiomics model to quantitatively assess T2-weighted MRI to distinguish the most common malignant and benign primary solid liver lesions in noncirrhotic livers.

MATERIALS AND METHODS

Data sets were retrospectively collected from three tertiary referral centers (A, B, and C) between 2002 and 2018. Patients with malignant (hepatocellular carcinoma and intrahepatic cholangiocarcinoma) and benign (hepatocellular adenoma and focal nodular hyperplasia) lesions were included. A radiomics model based on T2-weighted MRI was developed in data set A using a combination of machine learning approaches. The model was internally evaluated on data set A through cross-validation, externally validated on data sets B and C, and compared to visual scoring of two experienced abdominal radiologists on data set C.

RESULTS

The overall data set included 486 patients (A: 187, B: 98, and C: 201). The radiomics model had a mean area under the curve (AUC) of 0.78 upon internal validation on data set A and a similar AUC in external validation (B: 0.74 and C: 0.76). In data set C, the two radiologists showed moderate agreement (Cohen's κ: 0.61) and achieved AUCs of 0.86 and 0.82.

CONCLUSION

Our T2-weighted MRI radiomics model shows potential for distinguishing malignant from benign primary solid liver lesions. External validation indicated that the model is generalizable despite substantial MRI acquisition protocol differences. Pending further optimization and generalization, this model may aid radiologists in improving the diagnostic workup of patients with liver lesions.

Prediction of macrotrabecular-massive hepatocellular carcinoma by using MR-based models and their prognostic implications

PURPOSE

To evaluate the efficacy of MRI-based radiomics and clinical models in predicting MTM-HCC. Additionally, to investigate the ability of the radiomics model designed for MTM-HCC identification in predicting disease-free survival (DFS) in patients with HCC.

METHODS

A total of 336 patients who underwent oncological resection for HCC between June 2007 and March 2021 were included. 127 patients in Cohort1 were used for MTM-HCC identification, and 209 patients in Cohort2 for prognostic analyses. Radiomics analysis was performed using volumes of interest of HCC delineated on pre-operative MRI images. Radiomics and clinical models were developed using Random Forest algorithm in Cohort1 and a radiomics probability (RP) of MTM-HCC was obtained from the radiomics model. Based on the RP, patients in Cohort2 were divided into a RAD-MTM-HCC (RAD-M) group and a RAD-non-MTM-HCC (RAD-nM) group. Univariate and multivariate Cox regression analyses were employed to identify the independent predictors for DFS of patients in Cohort2. Kaplan-Meier curves were used to compare the DFS between different groups pf patients based on the predictors.

RESULTS

The radiomics model for identifying MTM-HCC showed AUCs of 0.916 (95% CI: 0.858-0.960) and 0.833 (95% CI: 0.675-0.935), and the clinical model showed AUCs of 0.760 (95% CI: 0.669-0.836) and 0.704 (95% CI: 0.532-0.843) in the respective training and validation sets. Furthermore, the radiomics biomarker RP, portal or hepatic vein tumor thrombus, irregular rim-like arterial phase hyperenhancement (IRE) and AFP were independent predictors of DFS in patients with HCC. The DFS of RAD-nM group was significantly higher than that of the RAD-M group (p < .001).

CONCLUSION

MR-based clinical and radiomic models have the potential to accurately diagnose MTM-HCC. Moreover, the radiomics signature designed to identify MTM-HCC also can be used to predict prognosis in patients with HCC, realizing the diagnostic and prognostic aims at the same time.

Radiological diagnosis of hepatocellular carcinoma does not preclude biopsy before treatment

Background & Aims

The diagnosis of hepatocellular carcinoma (HCC) in patients with cirrhosis relies on non-invasive criteria based on international guidelines. The advent of systemic therapies warrants reconsideration of the role of biopsy specimens in the diagnosis of HCC. Accordingly, we investigated the diagnostic performance of the LI-RADS 2018 and the AASLD 2011 criteria.

Methods

Consecutive patients with cirrhosis who underwent a biopsy for suspected HCC between 2015 and 2020 were included. The available imaging studies (computed tomography and/or magnetic resonance imaging) were blindly reviewed by two independent radiologists. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were assessed for LI-RADS, AASLD, and biopsies.

Results

In total, 167 patients underwent both available biopsy and imaging. Of the 137 relevant biopsies, 114 patients had HCC (83.2%), 12 (9%) had non-HCC malignant lesions, and 11 (8%) had benign nodules. The PPV and NPV of the biopsies were 100% and 62%, respectively; 30 biopsies were non-contributive. The PPV and NPV of the LI-RADS categories were 89% and 32.8% for LR-5 and 85.5% and 54.5% for LR-4 + 5 + TIV, respectively. The PPV and NPV of the 2011 AASLD criteria were 93.2% and 35.6%, respectively. The interobserver kappa (k = 0.380) for the LR-5 categories was reasonable. Of 100 LR-5 nodules, 11 were misclassified, in particular one case was a colorectal metastasis, and two cases were cholangiocarcinomas, of which nine were identified through biopsy, whereas six were correctly classified according to LI-RADS (LR-M or LR-TIV). Fifty percent of macrotrabecular HCC and 48.4% of poorly differentiated HCC (Edmonson 3 and 4) were not classified as LR-5.

Conclusions

LI-RADS 2018 did not outperform the AASLD 2011 score as a non-invasive diagnosis of HCC. Tumor biopsy allowed restoration of an accurate diagnosis in 11% of LR-5 cases. A combined radiological and histological diagnosis should be considered mandatory for good treatment assessment.

Impact and Implications

Although biopsy is not required for hepatocellular carcinoma diagnosis when the LI-RADS criteria are met according to current guidelines, our study underscores the limits of radiology and the need for biopsy when hepatocellular carcinoma is suspected. Histological findings could change therapeutics of liver tumors even if only for a small proportion of patients. Histological proof of the type of cancer is a standard in oncology.

A multitask deep learning radiomics model for predicting the macrotrabecular-massive subtype and prognosis of hepatocellular carcinoma after hepatic arterial infusion chemotherapy

BACKGROUND

The macrotrabecular-massive (MTM) is a special subtype of hepatocellular carcinoma (HCC), which has commonly a dismal prognosis. This study aimed to develop a multitask deep learning radiomics (MDLR) model for predicting MTM and HCC patients' prognosis after hepatic arterial infusion chemotherapy (HAIC).

METHODS

From June 2018 to March 2020, 158 eligible patients with HCC who underwent surgery were retrospectively enrolled in MTM related cohorts, and 752 HCC patients who underwent HAIC were included in HAIC related cohorts during the same period. DLR features were extracted from dual-phase (arterial phase and venous phase) contrast-enhanced computed tomography (CECT) of the entire liver region. Then, an MDLR model was used for the simultaneous prediction of the MTM subtype and patient prognosis after HAIC. The MDLR model for prognostic risk stratification incorporated DLR signatures, clinical variables and MTM subtype.

FINDINGS

The predictive performance of the DLR model for the MTM subtype was 0.968 in the training cohort [TC], 0.912 in the internal test cohort [ITC] and 0.773 in the external test cohort [ETC], respectively. Multivariable analysis identified portal vein tumor thrombus (PVTT) (p = 0.012), HAIC response (p < 0.001), HAIC sessions (p < 0.001) and MTM subtype (p < 0.001) as indicators of poor prognosis. After incorporating DLR signatures, the MDLR model yielded the best performance among all models (AUC, 0.855 in the TC, 0.805 in the ITC and 0.792 in the ETC). With these variables, the MDLR model provided two risk strata for overall survival (OS) in the TC: low risk (5-year OS, 44.9%) and high risk (5-year OS, 4.9%).

INTERPRETATION

A tool based on MDLR was developed to consider that the MTM is an important prognosis factor for HCC patients. MDLR showed outstanding performance for the prognostic risk stratification of HCC patients who underwent HAIC and may help physicians with therapeutic decision making and surveillance strategy selection in clinical practice.

Hepatocellular Carcinoma: Optimal Radiological Evaluation before Liver Transplantation

Liver transplantation (LT) is the recommended curative-intent treatment for patients with early or intermediate-stage hepatocellular carcinoma (HCC) who are ineligible for resection. Imaging plays a central role in staging and for selecting the best LT candidates. This review will discuss recent developments in pre-LT imaging assessment, in particular LT eligibility criteria on imaging, the technical requirements and the diagnostic performance of imaging for the pre-LT diagnosis of HCC including the recent Liver Imaging Reporting and Data System (LI-RADS) criteria, the evaluation of the response to locoregional therapy, as well as the non-invasive prediction of HCC aggressiveness and its impact on the outcome of LT. We will also briefly discuss the role of nuclear medicine in the pre-LT evaluation and the emerging role of artificial intelligence models in patients with HCC.

Tumor necrosis as a predictor of early tumor recurrence after resection in patients with hepatoma

BACKGROUND

Tumor necrosis is a significant risk factor affecting patients' prognosis after liver resection (LR) for hepatocellular carcinoma (HCC). We aimed to develop a model with tumor necrosis as a variable to predict early tumor recurrence in HCC patients undergoing LR.

MATERIALS AND METHODS

Patients who underwent LR between 2010 and 2018 for newly diagnosed HCC but did not receive neoadjuvant therapy were enrolled in this retrospective study. Six predictive factors based on pathological features-tumor size > 5 cm, multiple tumors, high-grade tumor differentiation, tumor necrosis, microvascular invasion, and cirrhosis-were chosen a priori based on clinical relevance to construct a multivariate logistic regression model. The variables were always retained in the model. The impact of each variable on early tumor recurrence within one year of LR was estimated and visualized using a nomogram. The nomogram's performance was evaluated using calibration plots with bootstrapping.

RESULTS

Early tumor recurrence was observed in 161 (21.3%) patients. The concordance index of the proposed nomogram was 0.722. The calibration plots showed good agreement between nomogram predictions and actual observations of early recurrence.

CONCLUSION

We developed a nomogram incorporating tumor necrosis to predict early recurrence of HCC after LR. Its predictive accuracy is satisfactory.

Development of a Model including MRI Features for Predicting Advanced-stage Recurrence of Hepatocellular Carcinoma after Liver Resection

Background Identifying patients at high risk for advanced-stage hepatocellular carcinoma (HCC) recurrence after liver resection may improve patient survival. Purpose To develop a model including MRI features for predicting postoperative advanced-stage HCC recurrence. Materials and Methods This single-center, retrospective study includes consecutive adult patients who underwent preoperative contrast-enhanced MRI and curative-intent resection for early- to intermediate-stage HCC (from December 2011 to April 2021). Three radiologists evaluated 52 qualitative features on MRI scans. In the training set, Fine-Gray proportional subdistribution hazard analysis was performed to identify clinical, laboratory, imaging, pathologic, and surgical variables to include in the predictive model. In the test set, the concordance index (C-index) was computed to compare the developed model with current staging systems. The Kaplan-Meier survival curves were compared using the log-rank test. Results The study included 532 patients (median age, 54 years; IQR, 46-62 years; 465 male patients), 302 patients from the training set (median age, 54 years; IQR, 46-63 years; 265 male patients), and 128 patients from the test set (median age, 53 years; IQR, 46-63 years; 108 male patients). Advanced-stage recurrence was observed in 38 of 302 (12.6%) and 15 of 128 (11.7%) of patients from the training and test sets, respectively. Serum neutrophil count (109/L), tumor size (in centimeters), and arterial phase hyperenhancement proportion on MRI scans were associated with advanced-stage recurrence (subdistribution hazard ratio range, 1.16-3.83; 95% CI: 1.02, 7.52; P value range, <.001 to .02) and included in the predictive model. The model showed better test set prediction for advanced-stage recurrence than four staging systems (2-year C-indexes, 0.82 [95% CI: 0.74, 0.91] vs 0.63-0.68 [95% CI: 0.52, 0.82]; P value range, .001-.03). Patients at high risk for HCC recurrence (model score, ≥15 points) showed increased advanced-stage recurrence and worse all-stage recurrence-free survival (RFS), advanced-stage RFS, and overall survival than patients at low risk for HCC recurrence (P value range, <.001 to .02). Conclusion A model combining serum neutrophil count, tumor size, and arterial phase hyperenhancement proportion predicted advanced-stage HCC recurrence better than current staging systems and may identify patients at high risk. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Tsai and Mellnick in this issue.

Gd-EOB MRI for HCC subtype differentiation in a western population according to the 5th edition of the World Health Organization classification

OBJECTIVES

To investigate the value of gadoxetic acid (Gd-EOB)-enhanced magnetic resonance imaging (MRI) for noninvasive subtype differentiation of HCCs according to the 5th edition of the WHO Classification of Digestive System Tumors in a western population.

METHODS

This retrospective study included 262 resected lesions in 240 patients with preoperative Gd-EOB-enhanced MRI. Subtypes were assigned by two pathologists. Gd-EOB-enhanced MRI datasets were assessed by two radiologists for qualitative and quantitative imaging features, including imaging features defined in LI-RADS v2018 and area of hepatobiliary phase (HBP) iso- to hyperintensity.

RESULTS

The combination of non-rim arterial phase hyperenhancement with non-peripheral portal venous washout was more common in "not otherwise specified" (nos-ST) (88/168, 52%) than other subtypes, in particular macrotrabecular massive (mt-ST) (3/15, 20%), chromophobe (ch-ST) (1/8, 13%), and scirrhous subtypes (sc-ST) (2/9, 22%) (p = 0.035). Macrovascular invasion was associated with mt-ST (5/16, p = 0.033) and intralesional steatosis with steatohepatitic subtype (sh-ST) (28/32, p < 0.001). Predominant iso- to hyperintensity in the HBP was only present in nos-ST (16/174), sh-ST (3/33), and clear cell subtypes (cc-ST) (3/13) (p = 0.031). Associations were found for the following non-imaging parameters: age and sex, as patients with fibrolamellar subtype (fib-ST) were younger (median 44 years (19-66), p < 0.001) and female (4/5, p = 0.023); logarithm of alpha-fetoprotein (AFP) was elevated in the mt-ST (median 397 µg/l (74-5370), p < 0.001); type II diabetes mellitus was more frequent in the sh-ST (20/33, p = 0.027).

CONCLUSIONS

Gd-EOB-MRI reproduces findings reported in the literature for extracellular contrast-enhanced MRI and CT and may be a valuable tool for noninvasive HCC subtype differentiation.

CLINICAL RELEVANCE STATEMENT

Better characterization of the heterogeneous phenotypes of HCC according to the revised WHO classification potentially improves both diagnostic accuracy and the precision of therapeutic stratification for HCC.

KEY POINTS

• Previously reported imaging features of common subtypes in CT and MRI enhanced with extracellular contrast agents are reproducible with Gd-EOB-enhanced MRI. • While uncommon, predominant iso- to hyperintensity in the HBP was observed only in NOS, clear cell, and steatohepatitic subtypes. • Gd-EOB-enhanced MRI offers imaging features that are of value for HCC subtype differentiation according to the 5th edition of the WHO Classification of Digestive System Tumors.

Pathological overview of steatohepatitic hepatocellular carcinoma in a surgical series

AIMS

According to the last WHO classification, steatohepatitic hepatocellular carcinoma (SH-HCC) is recognized as a distinct HCC subtype, even though a consensual definition is still lacking. The objectives of the study were to carefully describe the morphological features of SH-HCC and evaluate its impact on prognosis.

METHODS AND RESULTS

We conducted a single-centre retrospective study including 297 surgically resected HCC. Pathological features including SH criteria (steatosis, ballooning, Mallory-Denk bodies, fibrosis, and inflammation) were assessed. SH-HCC was defined by the presence of at least four of the five SH criteria and the SH component represented >50% of the tumour area. According to this definition, 39 (13%) HCC cases corresponded to SH-HCC and 30 cases (10%) corresponded to HCC with an SH component (<50%). SH criteria in SH-HCC and non-SH-HCC were distributed as follows: ballooning (100% versus 11%), fibrosis (100% versus 81%), inflammation (100% versus 67%), steatosis (92% versus 8%), and Mallory-Denk bodies (74% versus 3%). Inflammation markers (c-reactive protein [CRP] and serum amyloid A [SAA]) were significantly more expressed in SH-HCC compared to non-SH-HCC (82% versus 14%, P = <0.001). Five-year recurrence-free survival (RFS) and 5-year overall survival (OS) were similar for SH-HCC and non-SH-HCC (P = 0.413 and P = 0.866, respectively). The percentage of SH component does not impact OS and RFS.

CONCLUSION

We confirm in a large cohort the relatively high prevalence (13%) of SH-HCC. Ballooning is the most specific criteria for this subtype. The percentage of the SH component does not impact prognosis.

Clinico-histological and molecular features of hepatocellular carcinoma from nonalcoholic fatty liver disease

Patients with nonalcoholic fatty liver disease (NAFLD) continue to increase with the epidemics of obesity, and NAFLD is estimated to become the most prevalent etiology of hepatocellular carcinoma (HCC). Recently, NAFLD-HCC has been recognized to have clinico-histologically and molecularly distinct features from those from other etiologies, including a lower incidence rate of HCC and less therapeutic efficacy to immune checkpoint inhibitors (ICIs). Consistent with the clinical observations that up to 50% of NAFLD-HCC occurs in the absence of cirrhosis, the imbalance of pro- and antitumorigenic hepatic stellate cells termed as myHSC and cyHSC can contribute to the creation of an HCC-prone hepatic environment, independent of the absolute fibrosis abundance. Immune deregulations by accumulated metabolites in NAFLD-affected livers, such as a fatty-acid-induced loss of cytotoxic CD4 T cells serving for immune surveillance and "auto-aggressive" CXCR6+ CD8 T cells, may promote hepatocarcinogenesis and diminish therapeutic response to ICIs. Steatohepatitic HCC (SH-HCC), characterized by the presence of fat accumulation in tumor cells, ballooned tumor cells, Mallory-Denk body, interstitial fibrosis, and intratumor immune cell infiltration, may represent a metabolic reprogramming for adapting to a lipid-rich tumor microenvironment by downregulating CPT2 and leveraging its intermediates as an "oncometabolite." Genome-wide analyses suggested that SH-HCC may be more responsive to ICIs given its mutual exclusiveness with β-catenin mutation/activation that promotes immune evasion. Thus, further understanding of NAFLD-specific hepatocarcinogenesis and HCC would enable us to improve the current daily practice and eventually the prognoses of patients with NAFLD.

Advances in Histological and Molecular Classification of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a primary liver cancer characterized by hepatocellular differentiation. HCC is molecularly heterogeneous with a wide spectrum of histopathology. The prognosis of patients with HCC is generally poor, especially in those with advanced stages. HCC remains a diagnostic challenge for pathologists because of its morphological and phenotypic diversity. However, recent advances have enhanced our understanding of the molecular genetics and histological subtypes of HCC. Accurate diagnosis of HCC is important for patient management and prognosis. This review provides an update on HCC pathology, focusing on molecular genetics, histological subtypes, and diagnostic approaches.

Reduced Lipid Peroxidation Predicts Unfavorable Prognosis in Hepatocellular Carcinoma, but Not Intrahepatic Cholangiocarcinoma

Primary liver cancer, including hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA), remains a significant contributor to cancer-related mortality worldwide. Oxidative stress and lipid peroxidation play a key role in chronic liver diseases and have been shown to be pivotal for tumor initiation and progression. 4-hydroxy-nonenal (4-HNE), one of the major mediators of oxidative stress and a well-established biomarker for lipid peroxidation, can act as a signal transducer, inducing inflammation and exerting carcinogenic effects. However, the role of 4-HNE in primary liver cancer remains poorly explored. In this study, we investigated 4-HNE levels in 797 liver carcinomas, including 561 HCC and 236 iCCA, by immunohistochemistry. We then correlated 4-HNE levels with comprehensive clinical data and survival outcomes. In HCC, lower expression levels of 4-HNE were associated with vascular invasion, a high tumor grade, a macrotrabecular-massive HCC subtype, and poor overall survival. Concerning iCCA, large duct iCCA showed significantly higher 4-HNE levels when compared to small duct iCCA. Yet, in iCCA, 4-HNE levels did not correlate with known prognostic parameters or survival outcomes. To conclude, in HCC but not in iCCA, low amounts of 4-HNE predict unfavorable survival outcomes and are associated with aggressive tumor behavior. These findings provide insights into the role of 4-HNE in liver cancer progression and may enable novel therapeutic strategies.

Imaging prognostication and tumor biology in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common primary liver malignancy, and represents a significant global health burden with rising incidence rates, despite a more thorough understanding of the etiology and biology of HCC, as well as advancements in diagnosis and treatment modalities. According to emerging evidence, imaging features related to tumor aggressiveness can offer relevant prognostic information, hence validation of imaging prognostic features may allow for better noninvasive outcomes prediction and inform the selection of tailored therapies, ultimately improving survival outcomes for patients with HCC.

CYP2E1 triggered GRP78/ATF6/CHOP signaling axis inhibit apoptosis and promotes progression of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the leading cause of cancer-related death worldwide. Cytochrome P450 2E1 (CYP2E1) is an enzyme, primarily involved in the metabolism of xenobiotics and procarcinogens. The present study was designed to investigate the potential role of CYP2E1 triggered endoplasmic reticulum stress in the progression of HCC through inhibition of apoptosis. In vitro CYP2E1 promotes HepG2 cell migration, reduced chromatin condensation, enhanced intracellular ROS accumulation and induce cell cycle progression. Conversely this effect was averted by CYP2E1 siRNA, selective inhibitor Diallyl sulphide (DAS) and antioxidants (vitamin C and E). In vivo Diethylnitrosamine (DEN) induced HCC rats showed decreased body weight and increased relative liver weight. Moreover, macro trabecular-massive HCC (MTM-HCC) histological subtyping showed pathological features like well-differentiated tumors, micro-trabecular and pseudo glandular patterns, megakaryocytes and cholestasis. Masson's trichrome staining revealed an intensive accumulation of collagen fibers in the extracellular matrix (ECM). Increased CYP2E1, VEGF and PCNA enhance the carcinogenicity as revealed in immunohistochemistry results. Immunoblot analysis showed reduced expression of copper-zinc superoxide dismutase (CuZnSOD) and manganese superoxide dismutase (MnSOD) in cytosolic as well as mitochondrial fraction of rat liver tissue respectively. Also, increased level of CYP2E1 stimulated the upregulation of unfolded proteins response (UPR) and ER stress-related proteins such as Glucose regulatory protein 78 (GRP78), activating transcription factor 6 (ATF6) and CCAAT enhancer-binding protein (C/EBP) homologous protein (CHOP). Meanwhile, CYP2E1 stimulated ER-stress reduces BCL2 and downregulates the cleaved caspase 3 thus suppresses apoptosis. in. Furthermore, immunofluorescence revealed increased expression level of α-SMA in the HCC rat liver tissue. The level of CYP2E1 mRNA was significantly increased. Altogether, these findings indicate that CYP2E1 has a dynamic role in the pathogenesis of HCC and might be a budding agent in liver carcinogenesis therapy.

Hepatocellular Carcinoma Genetic Classification

ABSTRACT

Hepatocellular carcinoma (HCC) represents a significant global burden, with management complicated by its heterogeneity, varying presentation, and relative resistance to therapy. Recent advances in the understanding of the genetic, molecular, and immunological underpinnings of HCC have allowed a detailed classification of these tumors, with resultant implications for diagnosis, prognostication, and selection of appropriate treatments. Through the correlation of genomic features with histopathology and clinical outcomes, we are moving toward a comprehensive and unifying framework to guide our diagnostic and therapeutic approach to HCC.

Refining Liver Biopsy in Hepatocellular Carcinoma: An In-Depth Exploration of Shifting Diagnostic and Therapeutic Applications

The field of hepatocellular carcinoma (HCC) has faced significant change on multiple levels in the past few years. The increasing emphasis on the various HCC phenotypes and the emergence of novel, specific therapies have slowly paved the way for a personalized approach to primary liver cancer. In this light, the role of percutaneous liver biopsy of focal lesions has shifted from a purely confirmatory method to a technique capable of providing an in-depth characterization of any nodule. Cancer subtype, gene expression, the mutational profile, and tissue biomarkers might soon become widely available through biopsy. However, indications, expectations, and techniques might suffer changes as the aim of the biopsy evolves from providing minimal proof of the disease to high-quality specimens for extensive analysis. Consequently, a revamped position of tissue biopsy is expected in HCC, following the reign of non-invasive imaging-only diagnosis. Moreover, given the advances in techniques that have recently reached the spotlight, such as liquid biopsy, concomitant use of all the available methods might gather just enough data to improve therapy selection and, ultimately, outcomes. The current review aims to discuss the changing role of liver biopsy and provide an evidence-based rationale for its use in the era of precision medicine in HCC.

Dual-Energy CT Deep Learning Radiomics to Predict Macrotrabecular-Massive Hepatocellular Carcinoma

Background It is unknown whether the additional information provided by multiparametric dual-energy CT (DECT) could improve the noninvasive diagnosis of the aggressive macrotrabecular-massive (MTM) subtype of hepatocellular carcinoma (HCC). Purpose To evaluate the diagnostic performance of dual-phase contrast-enhanced multiparametric DECT for predicting MTM HCC. Materials and Methods Patients with histopathologic examination-confirmed HCC who underwent contrast-enhanced DECT between June 2019 and June 2022 were retrospectively recruited from three independent centers (center 1, training and internal test data set; centers 2 and 3, external test data set). Radiologic features were visually analyzed and combined with clinical information to establish a clinical-radiologic model. Deep learning (DL) radiomics models were based on DL features and handcrafted features extracted from virtual monoenergetic images and material composition images on dual phase using binary least absolute shrinkage and selection operators. A DL radiomics nomogram was developed using multivariable logistic regression analysis. Model performance was evaluated with the area under the receiver operating characteristic curve (AUC), and the log-rank test was used to analyze recurrence-free survival. Results A total of 262 patients were included (mean age, 54 years ± 12 [SD]; 225 men [86%]; training data set, n = 146 [56%]; internal test data set, n = 35 [13%]; external test data set, n = 81 [31%]). The DL radiomics nomogram better predicted MTM than the clinical-radiologic model (AUC = 0.91 vs 0.77, respectively, for the training set [P < .001], 0.87 vs 0.72 for the internal test data set [P = .04], and 0.89 vs 0.79 for the external test data set [P = .02]), with similar sensitivity (80% vs 87%, respectively; P = .63) and higher specificity (90% vs 63%; P < .001) in the external test data set. The predicted positive MTM groups based on the DL radiomics nomogram had shorter recurrence-free survival than predicted negative MTM groups in all three data sets (training data set, P = .04; internal test data set, P = .01; and external test data set, P = .03). Conclusion A DL radiomics nomogram derived from multiparametric DECT accurately predicted the MTM subtype in patients with HCC. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Chu and Fishman in this issue.

Understanding the causes of recurrent HCC after liver resection and radiofrequency ablation

INTRODUCTION

Surgical resection and radiofrequency ablation are preferred options for early-stage disease, with 5-year recurrence rates as high as 70% when patients are treated according to guidelines. With increasing availability of therapeutic options, including but not limited to, immune-checkpoint inhibitors (ICI), tyrosine kinase inhibitors, antiangiogenics, and adoptive cell therapies, understanding the causes of recurrence and identifying its predictors should be priorities in the hepatocellular carcinoma (HCC) research agenda.

AREAS COVERED

Current knowledge of HCC predictors of recurrence is reviewed, and recent insights about its underlying mechanisms are presented. In addition, results from recent clinical trials investigating treatment combinations are critically appraised.

EXPERT OPINION

HCC recurrence is either due to progressive growth of microscopic residual disease, or to de novo cancer development in the context of a diseased liver, each occurring in an early (<2years) vs. late (≥2 years) fashion. Collectively, morphological, proteomic, and transcriptomic data suggest vascular invasion and angiogenesis as key drivers of HCC recurrence. Agents aimed at blocking either of these two hallmarks should be prioritized at the moment of early-stage HCC clinical trial design. Emerging results from clinical trials testing ICI in early-stage HCC underscore the importance of defining the best treatment sequence and the most appropriate combination strategies. Lastly, as different responses to systemic therapies are increasingly defined according to the HCC etiology, patient enrolment into clinical trials should take into account the biological characteristics of their inherent disease.

Preoperative prediction of macrotrabecular-massive hepatocellular carcinoma through dynamic contrast-enhanced magnetic resonance imaging-based radiomics

BACKGROUND

Macrotrabecular-massive hepatocellular carcinoma (MTM-HCC) is closely related to aggressive phenotype, gene mutation, carcinogenic pathway, and immunohistochemical markers and is a strong independent predictor of early recurrence and poor prognosis. With the development of imaging technology, successful applications of contrast-enhanced magnetic resonance imaging (MRI) have been reported in identifying the MTM-HCC subtype. Radiomics, as an objective and beneficial method for tumour evaluation, is used to convert medical images into high-throughput quantification features that greatly push the development of precision medicine.

AIM

To establish and verify a nomogram for preoperatively identifying MTM-HCC by comparing different machine learning algorithms.

METHODS

This retrospective study enrolled 232 (training set, 162; test set, 70) hepatocellular carcinoma patients from April 2018 to September 2021. A total of 3111 radiomics features were extracted from dynamic contrast-enhanced MRI, followed by dimension reduction of these features. Logistic regression (LR), K-nearest neighbour (KNN), Bayes, Tree, and support vector machine (SVM) algorithms were used to select the best radiomics signature. We used the relative standard deviation (RSD) and bootstrap methods to quantify the stability of these five algorithms. The algorithm with the lowest RSD represented the best stability, and it was used to construct the best radiomics model. Multivariable logistic analysis was used to select the useful clinical and radiological features, and different predictive models were established. Finally, the predictive performances of the different models were assessed by evaluating the area under the curve (AUC).

RESULTS

The RSD values based on LR, KNN, Bayes, Tree, and SVM were 3.8%, 8.6%, 4.3%, 17.7%, and 17.4%, respectively. Therefore, the LR machine learning algorithm was selected to construct the best radiomics signature, which performed well with AUCs of 0.766 and 0.739 in the training and test sets, respectively. In the multivariable analysis, age [odds ratio (OR) = 0.956, P = 0.034], alpha-fetoprotein (OR = 10.066, P < 0.001), tumour size (OR = 3.316, P = 0.002), tumour-to-liver apparent diffusion coefficient (ADC) ratio (OR = 0.156, P = 0.037), and radiomics score (OR = 2.923, P < 0.001) were independent predictors of MTM-HCC. Among the different models, the predictive performances of the clinical-radiomics model and radiological-radiomics model were significantly improved compared to those of the clinical model (AUCs: 0.888 vs 0.836, P = 0.046) and radiological model (AUCs: 0.796 vs 0.688, P = 0.012), respectively, in the training set, highlighting the improved predictive performance of radiomics. The nomogram performed best, with AUCs of 0.896 and 0.805 in the training and test sets, respectively.

CONCLUSION

The nomogram containing radiomics, age, alpha-fetoprotein, tumour size, and tumour-to-liver ADC ratio revealed excellent predictive ability in preoperatively identifying the MTM-HCC subtype.

Macrotrabecular-massive subtype-based nomogram to predict early recurrence of hepatocellular carcinoma after surgery

OBJECTIVES

To analyze the predictive factors on early postoperative recurrence of hepatocellular carcinoma (HCC) and to establish a new nomogram to predict early postoperative recurrence of HCC.

METHODS

A retrospective analysis of 383 patients who had undergone curative resection between February 2012 and September 2020 in our center was performed. The Kaplan-Meier method was used for survival curve analysis. Univariate and multivariate Cox regression were performed to identify independent risk factors associated with early recurrence, and a nomogram for predicting early recurrence of HCC was established.

RESULTS

A total of 152/383 patients developed recurrence after surgery, of which 83 had recurrence within 1 year. Multivariate Cox regression analysis showed that preoperative alpha-fetoprotein level ≥400 ng/ml (P = 0.001), tumor diameter ≥5 cm (P = 0.009) and MVI (P = 0.007 and macrotrabecular-massive HCC (P = 0.003) were independent risk factors for early postoperative recurrence of HCC. The macrotrabecular-massive-based nomogram obtained a good C-index (0.74) for predicting early recurrence of HCC, and the area under the curve for predicting early recurrence was 0.767, which was better than the single American Joint Committee on Cancer T stage and Barcelona Clinic Liver Cancer stage.

CONCLUSIONS

The nomogram based on macrotrabecular-massive HCC can effectively predict early postoperative recurrence of HCC.

MTM-HCC at Previous Liver Resection as a Predictor of Overall Survival in Salvage Liver Transplantation

OBJECTIVES

Salvage liver transplantation (sLT) is considered an effective method to treat hepatocellular carcinoma (HCC) recurrence. This multicenter research aimed to identify the prognostic factors associated with recurrence-free survival (RFS) and overall survival (OS) after sLT.

MATERIAL AND METHODS

A retrospective analysis of 114 patients who had undergone sLT for recurrent HCC between February 2012 and September 2020 was performed. The baseline and clinicopathological data of the patients were collected.

RESULTS

The 1-, 3-, and 5-year RFS rates after sLT were 88.9%, 75.2%, and 69.2%, respectively, and the OS rates were 96.4%, 78.3%, and 70.8%. A time from liver resection (LR) to recurrence < 1 year, disease beyond the Milan criteria at sLT and macrotrabecular massive (MTM)-HCC were identified as risk factors for RFS and were further identified as independent risk factors. A time from LR to recurrence < 1 year, disease beyond the Milan criteria at sLT and MTM-HCC were also risk factors for OS and were further identified as independent risk factors.

CONCLUSIONS

Compared with primary liver transplantation (pLT), more prognostic factors are available from patients who had undergone LR. We suggest that in cases of HCC recurrence within 1 year after LR, disease beyond the Milan criteria at sLT and MTM-HCC patients, sLT should be used with caution.

MRI features associated with HCC histologic subtypes: a western American and European bicenter study

OBJECTIVES

To evaluate if preoperative MRI can predict the most frequent HCC subtypes in North American and European patients treated with surgical resection.

METHODS

A total of 119 HCCs in 97 patients were included in the North American group and 191 HCCs in 176 patients were included in the European group. Lesion subtyping was based on morphologic features and immuno-histopathological analysis. Two radiologists reviewed preoperative MRI and evaluated the presence of imaging features including LI-RADS major and ancillary features to identify clinical, biologic, and imaging features associated with the main HCC subtypes.

RESULTS

Sixty-four percent of HCCs were conventional. The most frequent subtypes were macrotrabecular-massive (MTM-15%) and steatohepatitic (13%). Necrosis (OR = 3.32; 95% CI: 1.39, 7.89; p = .0064) and observation size (OR = 1.011; 95% CI: 1.0022, 1.019; p = .014) were independent predictors of MTM-HCC. Fat in mass (OR = 15.07; 95% CI: 6.57, 34.57; p < .0001), tumor size (OR = 0.97; 95% CI: 0.96, 0.99; p = .0037), and absence of chronic HCV infection (OR = 0.24; 95% CI: 0.084, 0.67; p = .0068) were independent predictors of steatohepatitic HCC. Independent predictors of conventional HCCs were viral C hepatitis (OR = 3.20; 95% CI: 1.62, 6.34; p = .0008), absence of fat (OR = 0.25; 95% CI: 0.12, 0.52; p = .0002), absence of tumor in vein (OR = 0.34; 95% CI: 0.13, 0.84; p = .020), and higher tumor-to-liver ADC ratio (OR = 1.96; 95% CI: 1.14, 3.35; p = .014) CONCLUSION: MRI is useful in predicting the most frequent HCC subtypes even in cohorts with different distributions of liver disease etiologies and tumor subtypes which might have future treatment and management implications.

KEY POINTS

• Representation of both liver disease etiologies and HCC subtypes differed between the North American and European cohorts of patients. • Retrospective two-center study showed that liver MRI is useful in predicting the most frequent HCC subtypes.

Comparison of imaging findings of macrotrabecular-massive hepatocellular carcinoma using CT and gadoxetic acid-enhanced MRI

OBJECTIVES

To investigate the imaging findings of macrotrabecular-massive hepatocellular carcinoma (MTM-HCC) on CT and MRI, and examine their diagnostic performance and prognostic significance.

METHODS

We retrospectively enrolled 220 consecutive patients who underwent hepatic resection between June 2009 and December 2013 for single treatment-naïve HCC, who have preoperative CT and gadoxetic acid-enhanced MRI. Independent reviews of histopathology and imaging were performed by two reviewers. Previously reported imaging findings, LI-RADS category, and CT attenuation of MTM-HCC were investigated. The diagnostic performance of the MTM-HCC diagnostic criteria was compared across imaging modalities.

RESULTS

MTM-HCC was associated with ≥ 50% arterial phase hypovascular component, intratumoral artery, arterial phase peritumoral enhancement, and non-smooth tumor margin on CT and MRI (p < .05). Arterial phase hypovascular components were less commonly observed on MRI subtraction images than on CT or MRI, while non-rim arterial phase hyperenhancement and LR-5 were more commonly observed on MRI subtraction images than on MRI (p < .05). MTM-HCC showed lower tumor attenuation in the CT arterial phase (p = .01). Rhee's criteria, defined as ≥ 50% hypovascular component and ≥ 2 ancillary findings (intratumoral artery, arterial phase peritumoral enhancement, and non-smooth tumor margin), showed similar diagnostic performance for MRI (sensitivity, 41%; specificity, 97%) and CT (sensitivity, 31%; specificity, 94%). Rhee's criteria on CT were independent prognostic factors for overall survival.

CONCLUSION

The MRI diagnostic criteria for MTM-HCC are applicable on CT, showing similar diagnostic performance and prognostic significance. For MTM-HCC, arterial phase subtraction images can aid in the HCC diagnosis by depicting subtle arterial hypervascularity.

KEY POINTS

• MTM-HCC on CT demonstrated previously described MRI findings, including arterial phase hypovascular component, intratumoral artery, arterial phase peritumoral enhancement, and necrosis. • The MRI diagnostic criteria for MTM-HCC were also applicable to CT, showing comparable diagnostic performance and prognostic significance. • On arterial phase subtraction imaging, MTM-HCC more frequently demonstrated non-rim enhancement and LR-5 and less frequently LR-M than MRI arterial phase, which may aid in the diagnosis of HCC.

The Organ Procurement and Transplantation Network hepatocellular carcinoma classification: Alignment with Liver Imaging Reporting and Data System, current gaps, and future direction

The Organ Procurement and Transplantation Network (OPTN) updated its allocation policy for liver transplantation to align with the Liver Imaging Reporting and Data System (LI-RADS) for the diagnosis of hepatocellular carcinoma (HCC). LI-RADS computed tomography/magnetic resonance imaging algorithm had achieved congruency with the American Association for the Study of Liver Diseases (AASLD) HCC Practice Guidance in 2018, and therefore, alignment of OPTN, LI-RADS, and AASLD unifies HCC diagnostic approaches. The two changes to the OPTN HCC classification are adoption of LI-RADS terminology or lexicon for HCC major imaging features as well as the modification of OPTN Class-5A through the adoption of LI-RADS-5 criteria. However, despite this significant milestone, the OPTN allocation policy may benefit from further refinements such as adoption of treatment response assessment criteria after locoregional therapy and categorization criteria for lesions with atypical imaging appearances that are not specific for HCC. In this review, we detail the changes to the OPTN HCC classification to achieve alignment with LI-RADS, discuss current limitations of the OPTN classification, and explore future directions.

Dynamic CT and Gadoxetic Acid-enhanced MRI Characteristics of P53-mutated Hepatocellular Carcinoma

Background Imaging markers of hepatocellular carcinoma (HCC) on the basis of molecular classification are important for predicting malignancy grade and prognosis. P53-mutated HCC is a major aggressive subtype; however, its imaging characteristics have not been clarified. Purpose To clarify the imaging characteristics of P53-mutated HCC at dynamic CT and gadoxetic acid-enhanced MRI that are correlated with its clinical features, pathologic findings, and prognosis. Materials and Methods In this retrospective single-center study, patients with surgically resected HCC between January 2015 and May 2018 in a university hospital were evaluated. HCC was classified into P53-mutated HCC and non-P53-mutated HCC using immunostaining. Dynamic CT and gadoxetic acid-enhanced MRI findings, clinical features, pathologic findings, and prognosis were compared using Mann-Whitney test, χ² test, multivariable regression analysis, receiver operating characteristic analysis, Kaplan-Meier method, and log-rank test. Immunohistochemical expression of P53, organic anion transporting polypeptide 1B3 (OATP1B3), and CD34 were evaluated, and the correlations were analyzed using the Pearson correlation test. Results In total, 149 patients (mean age, 67 years ± 9 [SD]; 103 men) with 173 HCCs were evaluated. P53-mutated HCC (n = 28) demonstrated higher serum α-fetoprotein (median, 127.5 ng/mL vs 5.5 ng/mL; P < .001), larger size (40.4 mm ± 29.7 vs 26.4 mm ± 20.5; P = .001), and higher rates of poorly differentiated HCC (22 of 28 [79%] vs 24 of 145 [17%]; P < .001). Dilated vasculature in the arterial phase of dynamic CT (odds ratio, 14; 95% CI: 3, 80; P = .002) and a lower relative enhancement ratio in the hepatobiliary phase (odds ratio, 0.05; 95% CI: 0.01, 0.34; cutoff value, 0.69; P = .002) independently predicted P53-mutated HCC. OATP1B3 expression and P53 expression were inversely correlated (P = .002; R = -0.24). Five-year overall survival was worse for P53-mutated HCC (50.0% vs 72.6%; P = .02). Conclusion Dilated vasculature at the arterial phase of dynamic CT and a lower relative enhancement ratio at the hepatobiliary phase of gadoxetic acid-enhanced MRI were useful markers for P53-mutated hepatocellular carcinoma with poor prognosis. © RSNA, 2022 Online supplemental material is available for this article.

18F-FDG PET/CT-based radiomics nomogram for preoperative prediction of macrotrabecular-massive hepatocellular carcinoma: a two-center study

PURPOSE

To explore the potential of β-2-[18F] fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) in the evaluation of macrotrabecular-massive (MTM) hepatocellular carcinoma (HCC) and to apply radiomics approach to build a radiomics nomogram for predicting MTM-HCC.

METHODS

This study included 140 (training cohort:101; validation cohort:39) HCC patients who underwent preoperative ¹⁸F-FDG PET/CT at two institutions. The clinical features and tumor FDG metabolism measured by the tumor-to-liver ratio (TLR) via ¹⁸F-FDG PET/CT were retrospectively collected. Radiomics features were extracted from ¹⁸F-FDG PET/CT images and a radiomics score (Rad-score) was calculated. A radiomics nomogram was then constructed by combining Rad-score and independent clinical features and was assessed with a calibration curve. The performance of the radiomics nomogram, Rad-score and TLR was evaluated by receiver operating characteristic (ROC) curves and decision curve analysis (DCA).

RESULTS

A total of six top weighted radiomics features were selected from PET/CT images by the least absolute shrinkage and selection operator (LASSO) regression algorithm and were used to construct a Rad-score. Multivariate analysis identified Rad-score (OR = 2.183, P = 0.004), age ≤ 50 years (OR = 3.136, P = 0.036), AST > 40U/L (OR = 0.270, P = 0.017) and TLR (OR = 1.641, P = 0.049) as independent predictors of MTM-HCC. The radiomics nomogram had a higher area under the curves (AUCs) than the Rad-score and TLR for predicting MTM-HCC in both training (0.849 [95% CI 0.774-0.924] vs. 0.764 [95% CI 0.669-0.843], 0.763 [95% CI 0.668-0.842]) and validation (0.749 [95% CI 0.584-0.873] vs. 0.690 [95% CI 0.522-0.828], 0.541 [95% CI 0.374-0.701]) cohorts. DCA showed the radiomics nomogram to be more clinically useful than Rad-score and TLR.

CONCLUSIONS

Tumor FDG metabolism is significantly associated with MTM-HCC. A ¹⁸F-FDG PET/CT-based radiomics nomogram may be useful for preoperatively predicting the MTM subtype in primary HCC patients, contributing to pretreatment decision-making.

Genetics of Hepatocellular Carcinoma: From Tumor to Circulating DNA

Hepatocellular carcinoma (HCC) accounts for 90% of primary hepatic malignancies and is one of the major causes of cancer-related death. Over the last 15 years, the molecular landscape of HCC has been deciphered, with the identification of the main driver genes of liver carcinogenesis that belong to six major biological pathways, such as telomere maintenance, Wnt/b-catenin, P53/cell cycle regulation, oxidative stress, epigenetic modifiers, AKT/mTOR and MAP kinase. The combination of genetic and transcriptomic data composed various HCC subclasses strongly related to risk factors, pathological features and prognosis. However, translation into clinical practice is not achieved, mainly because the most frequently mutated genes are undruggable. Moreover, the results derived from the analysis of a single tissue sample may not adequately catch the intra- and intertumor heterogeneity. The analysis of circulating tumor DNA (ctDNA) is broadly developed in other types of cancer for early diagnosis, prognosis and monitoring under systemic treatment in order to identify primary and secondary mechanisms of resistance. The aim of this review is to describe recent data about the HCC molecular landscape and to discuss how ctDNA could be used in the future for HCC detection and management.

Radiomics: A radiological evidence-based artificial intelligence technique to facilitate personalized precision medicine in hepatocellular carcinoma

The high postoperative recurrence rates in hepatocellular carcinoma (HCC) remain a major hurdle in its management. Appropriate staging and treatment selection may alleviate the extent of fatal recurrence. However, effective methods to preoperatively evaluate pathophysiologic and molecular characteristics of HCC are lacking. Imaging plays a central role in HCC diagnosis and stratification due to the non-invasive diagnostic criteria. Vast and crucial information is hidden within image data. Other than providing a morphological sketch for lesion diagnosis, imaging could provide new insights to describe the pathophysiological and genetic landscape of HCC. Radiomics aims to facilitate diagnosis and prognosis of HCC using artificial intelligence techniques to harness the immense information contained in medical images. Radiomics produces a set of archetypal and robust imaging features that are correlated to key pathological or molecular biomarkers to preoperatively risk-stratify HCC patients. Inferred with outcome data, comprehensive combination of radiomic, clinical and/or multi-omics data could also improve direct prediction of response to treatment and prognosis. The evolution of radiomics is changing our understanding of personalized precision medicine in HCC management. Herein, we review the key techniques and clinical applications in HCC radiomics and discuss current limitations and future opportunities to improve clinical decision making.

Vessels That Encapsulate Tumor Clusters (VETC) Predict cTACE Response in Hepatocellular Carcinoma

Background

To investigate the correlation between hepatocellular carcinoma (HCC) pathological types and conventional transarterial chemoembolization (cTACE), and to evaluate the predictive value of the pathological types for efficacy of cTACE.

Methods

We investigated 186 naive HCC patients from 2 hospitals, including 63 patients with recurrence after surgical resection, and 123 unresectable cases, who underwent at least one cTACE procedure as the first treatment. All patients were histologically diagnosed with HCC by surgical resection and/or liver biopsy. Lipiodol deposition rate, ORR (objective response rate), PFS (progression-free survival), OS (overall survival) were compared among different HCC pathological types.

Results

This study evaluated 186 naive HCC patients and 189 tumor nodules. Vessels that encapsulate tumor clusters (VETC), macrotrabecular-massive (MTM), CK19-positive types were identified in 38% (72/189), 40% (76/189), and 28% (53/189) of the whole cohort, respectively. VETC, MTM and CK19-negative HCCs derived significantly better lipiodol deposition rate and ORR. cTACE prolonged the PFS of VETC and CK19-negative HCCs compared with non-VETC and CK19-positive HCCs in the recurrence, liver biopsy and combining whole cohorts, whereas the OSs of different pathological types were not significantly different. Multivariate analysis showed that VETC (OR, 4.671, 95% CI [1.954, 11.166], P<0.001) and CK19-positive type (OR, 0.127, 95% CI [0.044, 0.362], P<0.001) were independent predictive factors for the first cTACE response. However, only VETC type was significantly associated with the second cTACE response in multivariate analysis (OR, 3.31, 95% CI [1.24, 8.83], P=0.017), suggesting that VETC might be a more useful predictor of cTACE response.

Conclusion

Our study suggests that VETC is an effective predictor of cTACE response in patients with HCC.

Corona enhancement combined with microvascular invasion for prognosis prediction of macrotrabecular-massive hepatocellular carcinoma subtype

Objectives

The macrotrabecular-massive (MTM) subtype of hepatocellular carcinoma (HCC) is aggressive and associated with an unfavorable prognosis. This study aimed to characterize MTM-HCC features based on contrast-enhanced MRI and to evaluate the prognosis of imaging characteristics combined with pathology for predicting early recurrence and overall survival after surgery.

Methods

This retrospective study included 123 patients with HCC that underwent preoperative contrast-enhanced MRI and surgery, between July 2020 and October 2021. Multivariable logistic regression was performed to investigate factors associated with MTM-HCC. Predictors of early recurrence were determined with a Cox proportional hazards model and validated in a separate retrospective cohort.

Results

The primary cohort included 53 patients with MTM-HCC (median age 59 years; 46 male and 7 females; median BMI 23.5 kg/m2) and 70 subjects with non-MTM HCC (median age 61.5 years; 55 male and 15 females; median BMI 22.6 kg/m2) (All P>0.05). The multivariate analysis identified corona enhancement (odds ratio [OR]=2.52, 95% CI: 1.02-6.24; P=0.045) as an independent predictor of the MTM-HCC subtype. The multiple Cox regression analysis identified corona enhancement (hazard ratio [HR]=2.56, 95% CI: 1.08-6.08; P=0.033) and MVI (HR=2.45, 95% CI: 1.40-4.30; P=0.002) as independent predictors of early recurrence (area under the curve=0.790, P<0.001). The prognostic significance of these markers was confirmed by comparing results in the validation cohort to those from the primary cohort. Corona enhancement combined with MVI was significantly associated with poor outcomes after surgery.

Conclusions

A nomogram for predicting early recurrence based on corona enhancement and MVI could be used to characterize patients with MTM-HCC and predict their prognosis for early recurrence and overall survival after surgery.

Generative adversarial networks (GAN)-based data augmentation of rare liver cancers: The SFR 2021 Artificial Intelligence Data Challenge

PURPOSE

The 2021 edition of the Artificial Intelligence Data Challenge was organized by the French Society of Radiology together with the Centre National d'Études Spatiales and CentraleSupélec with the aim to implement generative adversarial networks (GANs) techniques to provide 1000 magnetic resonance imaging (MRI) cases of macrotrabecular-massive (MTM) hepatocellular carcinoma (HCC), a rare and aggressive subtype of HCC, generated from a limited number of real cases from multiple French centers.

MATERIALS AND METHODS

A dedicated platform was used by the seven inclusion centers to securely upload their anonymized MRI examinations including all three cross-sectional images (one late arterial and one portal-venous phase T1-weighted images and one fat-saturated T2-weighted image) in compliance with general data protection regulation. The quality of the database was checked by experts and manual delineation of the lesions was performed by the expert radiologists involved in each center. Multidisciplinary teams competed between October 11^th, 2021 and February 13^th, 2022.

RESULTS

A total of 91 MTM-HCC datasets of three images each were collected from seven French academic centers. Six teams with a total of 28 individuals participated in this challenge. Each participating team was asked to generate one thousand 3-image cases. The qualitative evaluation was performed by three radiologists using the Likert scale on ten randomly selected cases generated by each participant. A quantitative evaluation was also performed using two metrics, the Frechet inception distance and a leave-one-out accuracy of a 1-Nearest Neighbor algorithm.

CONCLUSION

This data challenge demonstrates the ability of GANs techniques to generate a large number of images from a small sample of imaging examinations of a rare malignant tumor.

Preoperative prediction model for macrotrabecular-massive hepatocellular carcinoma based on contrast-enhanced CT and clinical characteristics: a retrospective study

Objective

To investigate the predictive value of contrast-enhanced computed tomography (CECT) imaging features and clinical factors in identifying the macrotrabecular-massive (MTM) subtype of hepatocellular carcinoma (HCC) preoperatively.

Methods

This retrospective study included 101 consecutive patients with pathology-proven HCC (35 MTM subtype vs. 66 non-MTM subtype) who underwent liver surgery and preoperative CECT scans from January 2017 to November 2021. The imaging features were evaluated by two board-certified abdominal radiologists independently. The clinical characteristics and imaging findings were compared between the MTM and non-MTM subtypes. Univariate and multivariate logistic regression analyses were performed to investigate the association of clinical-radiological variables and MTM-HCCs and develop a predictive model. Subgroup analysis was also performed in BCLC 0-A stage patients. Receiver operating characteristic (ROC) curves analysis was used to determine the optimal cutoff values and the area under the curve (AUC) was employed to evaluate predictive performance.

Results

Intratumor hypoenhancement (odds ratio [OR] = 2.724; 95% confidence interval [CI]: 1.033, 7.467; p = .045), tumors without enhancing capsules (OR = 3.274; 95% CI: 1.209, 9.755; p = .03), high serum alpha-fetoprotein (AFP) (≥ 228 ng/mL, OR = 4.101; 95% CI: 1.523, 11.722; p = .006) and high hemoglobin (≥ 130.5 g/L; OR = 3.943; 95% CI: 1.466, 11.710; p = .009) were independent predictors for MTM-HCCs. The clinical-radiologic (CR) model showed the best predictive performance, achieving an AUC of 0.793, sensitivity of 62.9% and specificity of 81.8%. The CR model also effectively identify MTM-HCCs in early-stage (BCLC 0-A stage) patients.

Conclusion

Combining CECT imaging features and clinical characteristics is an effective method for preoperatively identifying MTM-HCCs, even in early-stage patients. The CR model has high predictive performance and could potentially help guide decision-making regarding aggressive therapies in MTM-HCC patients.

Prolonged Survival after Recurrence in HCC Resected Patients Using Repeated Curative Therapies: Never Give Up!

Surgical resection is the optimal treatment for HCC, despite a high risk of recurrence. Few data are available on patient’s survival after resection. This is a retrospective study of tumor recurrence occurring after hepatectomy for HCC from 2000 to 2016. Univariate and multivariate analyses were performed to identify prognostic factors of survival after recurrence (SAR). Among 387 patients, 226 recurred (58.4%) with a median SAR of 26 months. Curative treatments (liver transplantation, repeat hepatectomy, thermal ablation) were performed for 44.7% of patients. Independent prognostic factors for SAR were micro-vascular invasion on the primary surgical specimen, size of the initial tumor >5 cm, preoperative AFP, albumin and platelet levels, male gender, number, size and localization of tumors at recurrence, time to recurrence, Child−Pugh score and treatment at recurrence. In subgroup analysis, early recurrence (46%) was associated with a decrease in SAR, by contrast with late recurrence. However, the overall survival (OS) of patients with early recurrence and curative treatment did not significantly differ from that of non-recurring patients. For late recurrence, OS did not significantly differ from that of non-recurring patients, regardless of the proposed treatment. Aggressive and repeat treatments are therefore key to improve prognosis of patients with HCC.