Imaging features of histological subtypes of hepatocellular carcinoma: Implication for LI-RADS

Predicting early recurrence in hepatocellular carcinoma after hepatectomy using GD-EOB-DTPA enhanced MRI-based model

PURPOSE

To develop and validate a comprehensive model for predicting postoperative early recurrence of hepatocellular carcinoma (HCC) based on gadoxetate disodium (Gd-EOB-DTPA)-enhanced MRI.

METHODS

239 patients with HCC who underwent curative surgical resection were recruited from two centers between April 2017 and December 2022. Radiomics features were extracted from the region of interest (ROI) on preoperative Gd-EOB-DTPA-enhanced MR images, and consistency analysis was performed to select stable radiomics features. Significant variables in the univariate and multivariate logistic regression analysis were included in clinical-radiologic model. Nomograms were constructed by combining the best performing radiologic and clinical-radiologic characteristics. Recurrence-free survival (RFS) comparisons were conducted using the log-rank test based on high versus low model-derived scores.

RESULTS

The radiomics model based on multiple phases MR outperformed all other radiomics models and had the best discrimination for early recurrence, with AUC of 0.799 and 0.743 in the training and validation sets, respectively. In the entire cohort, high-risk patients exhibited significantly lower RFS compared to low-risk patients.

CONCLUSION

The nomogram integrating Gd-EOB-DTPA enhanced MRI radiomics features and clinical-radiologic characteristics demonstrate superior predictive performance with postoperative early recurrence in patients with HCC. The model can identify patients at high risk and provide support for individualized treatment planning.

Diagnostic Performance of CT/MRI LI-RADS Version 2018 Major Feature Combinations: Individual Participant Data Meta-Analysis

Background The CT/MRI Liver Imaging Reporting and Data System (LI-RADS) diagnostic algorithm classifies liver observations in patients with high-risk hepatocellular carcinoma (HCC) using imaging features. However, data regarding the diagnostic performance of specific LI-RADS major feature combinations is limited. Purpose To conduct a systematic review and individual participant data (IPD) meta-analysis to establish the positive predictive values (PPVs) of LI-RADS major feature combinations using CT/MRI LI-RADS version 2018 in patients at risk for HCC. Materials and Methods Medline, Embase, Cochrane Central, and Scopus were searched for studies published from January 2014 to February 2023. Studies reporting HCC percentages for LI-RADS categories in patients at high risk for HCC were included. A one-stage random-effects IPD meta-analysis was used to calculate the PPV for HCC diagnosis and 95% CIs of major feature combinations. Wald test was used to compare combinations. Risk of bias (RoB) was assessed using Quality Assessment of Diagnostic Accuracy Studies 2, known as QUADAS-2 (protocol: https://osf.io/ah5kn). Results Forty-six studies including 6765 patients (mean age, 59 years ± 10.69 [SD]; 75% male patients [5081 of 6765]; age range, 18-93 years) with 7500 liver observations were analyzed. High RoB in at least one domain was found in 80% of studies (37 of 46). The pooled PPV estimate for major feature combinations was 58.28% in LR-3 (95% CI: 44.00, 71.29), 80.82% in LR-4 (95% CI: 71.04, 87.86), and 95.81% in LR-5 (95% CI: 91.06, 98.09). The majority of LI-RADS major feature combinations had PPVs that did not differ from others within the same category, supporting the current categorization (P value ranges: LR-3, .17-.73; LR-4, .10 to >.99; LR-5, .08 to >.99). Notably, five major feature combinations differed from the pooled PPV of the LR category. LR-3 was lower without nonrim arterial phase hyperenhancement (APHE) measuring smaller than 20 mm without additional major features (14.81%; 95% CI: 6.35, 30.85; P < .001), and higher with APHE measuring 10-19 mm without additional major features (68.33%; 95% CI: 53.94, 79.90; P = .01). LR-4 was lower without APHE measuring 20 mm or larger with enhancing capsule (50.81%; 95% CI: 28.92, 72.39; P = .009). LR-5 was lower with APHE measuring 10-19 mm with threshold growth (74.40%; 95% CI: 51.06, 89.00; P < .001), and with APHE measuring 20 mm or larger with threshold growth (82.35%; 95% CI: 57.29, 94.20; P = .02). Conclusion This meta-analysis showed that most major feature combinations in the same CT/MRI LI-RADS category had similar PPVs for HCC in patients at high risk for HCC, with the exception of five combinations within LR-3 through LR-5. © RSNA, 2025 Supplemental material is available for this article. See also the editorial by Johnson in this issue.

Is concurrent LR-5 associated with a higher rate of hepatocellular carcinoma in LR-3 or LR-4 observations? An individual participant data meta-analysis

BACKGROUND

The Liver Imaging Reporting and Data System (LI-RADS) does not consider factors extrinsic to the observation of interest, such as concurrent LR-5 observations.

PURPOSE

To evaluate whether the presence of a concurrent LR-5 observation is associated with a difference in the probability that LR-3 or LR-4 observations represent hepatocellular carcinoma (HCC) through an individual participant data (IPD) meta-analysis.

METHODS

Multiple databases were searched from 1/2014 to 2/2023 for studies evaluating the diagnostic accuracy of CT/MRI for HCC using LI-RADS v2014/2017/2018. The search strategy, study selection, and data collection process can be found at https://osf.io/rpg8x . Using a generalized linear mixed model (GLMM), IPD were pooled across studies and modeled simultaneously with a one-stage meta-analysis approach to estimate positive predictive value (PPV) of LR-3 and LR-4 observations without and with concurrent LR-5 for the diagnosis of HCC. Risk of bias was assessed using a composite reference standard and Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2).

RESULTS

Twenty-nine studies comprising 2591 observations in 1456 patients (mean age 59 years, 1083 [74%] male) were included. 587/1960 (29.9%) LR-3 observations in 1009 patients had concurrent LR-5. The PPV for LR-3 observations with concurrent LR-5 was not significantly different from the PPV without LR-5 (45.4% vs 37.1%, p = 0.63). 264/631 (41.8%) LR-4 observations in 447 patients had concurrent LR-5. The PPV for LR-4 observations with concurrent LR-5 was not significantly different from LR-4 observations without concurrent LR-5 (88.6% vs 69.5%, p = 0.08). A sensitivity analysis for low-risk of bias studies (n = 9) did not differ from the primary analysis.

CONCLUSION

The presence of concurrent LR-5 was not significantly associated with differences in PPV for HCC in LR-3 or LR-4 observations, supporting the current LI-RADS paradigm, wherein the presence of synchronous LR-5 may not alter the categorization of LR-3 and LR-4 observations.

Immunotherapy and MASLD-Related HCC: Should We Reconsider the Role of Etiology in the Therapeutic Approach to HCC?

Hepatocellular carcinoma (HCC) accounts for 90% of primary liver cancers and typically arises in the context of chronic liver disease. With the increasing prevalence of metabolic disorders, metabolic dysfunction-associated steatotic liver disease (MASLD) has become the leading cause of chronic liver disease and the most rapidly increasing cause of HCC. The role of dysfunctional innate and adaptive immune responses in the development and progression of HCC is well-established, prompting numerous trials to evaluate the efficacy of immune checkpoint inhibitors (ICIs) in targeting tumor cells. These trials have yielded promising results, and ICIs, in combination with anti-vascular endothelial growth factor (VEGF) monoclonal antibodies, are now approved as first-line therapy for patients with metastatic or unresectable HCC, irrespective of the underlying liver disease. Notably, MASLD itself is characterized by immune system dysfunction, as metabolic inflammation plays a central role in its onset and progression. However, clinical studies and post-hoc analyses suggest that immunotherapy may be less effective in MASLD-associated HCC compared to viral-related HCC. This emerging evidence raises the question of whether the underlying liver disease influences the therapeutic response to ICIs in HCC. It may be time to consider tailoring therapeutic strategies for HCC based on the specific etiological, histological, and genotypical subgroups.

EASL Clinical Practice Guidelines on the management of hepatocellular carcinoma

Liver cancer is the third leading cause of cancer-related deaths worldwide, with hepatocellular carcinoma (HCC) accounting for approximately 90% of primary liver cancers. Advances in diagnostic and therapeutic tools, along with improved understanding of their application, are transforming patient treatment. Integrating these innovations into clinical practice presents challenges and necessitates guidance. These clinical practice guidelines offer updated advice for managing patients with HCC and provide a comprehensive review of pertinent data. Key updates from the 2018 EASL guidelines include personalised surveillance based on individual risk assessment and the use of new tools, standardisation of liver imaging procedures and diagnostic criteria, use of minimally invasive surgery in complex cases together with updates on the integrated role of liver transplantation, transitions between surgical, locoregional, and systemic therapies, the role of radiation therapies, and the use of combination immunotherapies at various stages of disease. Above all, there is an absolute need for a multiparametric assessment of individual risks and benefits, considering the patient's perspective, by a multidisciplinary team encompassing various specialties.

Ultrasonography, contrast-enhanced ultrasonography and contrast-enhanced computer tomography features of hepatic sarcomatoid carcinoma and hepatic sarcoma: a retrospective study of 23 cases

BACKGROUND

Hepatic sarcomatoid carcinoma (HSC) and hepatic sarcoma (HS) are rare malignancies. Without pathology, the differential diagnosis between these two tumors is difficult due to their frequent overlaps in clinical presentations and imaging features. Currently, there are limited analyses about the ultrasound (US), contrast-enhanced ultrasound (CEUS) and contrast-enhanced computer tomography (CECT) characteristics of HSC and HS. Therefore, the purpose of our study is to evaluate the value of US, CEUS and CECT on the differential diagnosis between HSC and HS.

METHODS

From 2015 to 2022, a total of 23 patients with HSC (n = 11) and HS (n = 12) are included in this retrospective study. We analyze the clinical, pathological, and imaging data of these patients. Analysis of differences is performed to determine the consistent and distinctive features.

RESULTS

HSCs have a considerably higher prevalence of chronic hepatitis (p = 0.005) and cirrhosis (p = 0.027) than HSs, while metastases are more prevalent in HSs (p = 0.005). The lesion size of HSCs (8.1 ± 2.2 cm) is slightly larger than that of HSs (6.2 ± 3.4 cm). On conventional US, the characteristics of HS and HSC are similar. In CEUS, HSCs consistently showed heterogeneous enhancement patterns, while HSs, particularly hepatic angiosarcoma (HA), demonstrated a higher prevalence of hyperintensity (75%). On CECT, all masses in both groups exhibited low density. A statistically significant difference in margin clarity was observed between HSC and HS (p = 0.015).

CONCLUSION

HSC and HS generally present as masses with hypo-echoic and hypo-vascularity. HSC usually presents heterogeneous density. The degree of enhancement, the time of wash-out start, and the presence of necrotic areas may contribute to distinguish the different pathological types of HS.

Common pitfalls and diagnostic challenges in the application of LI-RADS CT/MRI algorithms: a comprehensive review

The Liver Imaging Reporting and Data System (LI-RADS) was developed to standardize the interpretation and reporting of liver observations in at-risk populations, aiding in the diagnosis of hepatocellular carcinoma (HCC). Despite its advantages, the application of LI-RADS can be challenging due to the complexity of liver pathology and imaging interpretation. This comprehensive review highlights common pitfalls encountered in LI-RADS application and offers practical strategies to enhance diagnostic accuracy and consistency among radiologists. Key areas of difficulty include misapplication in non-high-risk populations, misinterpretation of major imaging features such as arterial phase hyperenhancement and washout, and incorrect application of ancillary features. Additionally, the review addresses challenges related to atypical HCC presentations and HCC mimics. By recognizing and addressing these pitfalls, radiologists can improve diagnostic accuracy and avoid common mistakes in the diagnosis of HCC.

Myeloid response evaluated by noninvasive CT imaging predicts post-surgical survival and immune checkpoint therapy benefits in patients with hepatocellular carcinoma

Background

The potential of preoperative CT in the assessment of myeloid immune response and its application in predicting prognosis and immune-checkpoint therapy outcomes in hepatocellular carcinoma (HCC) has not been explored.

Methods

A total of 165 patients with pathological slides and multi-phase CT images were included to develop a radiomics signature for predicting the imaging-based myeloid response score (iMRS). Overall survival (OS) and recurrence-free survival (RFS) were assessed according to the iMRS risk group and validated in a surgical resection cohort (n = 98). The complementary advantage of iMRS incorporating significant clinicopathologic factors was investigated by the Cox proportional hazards analysis. Additionally, the iMRS in inferring the benefits of immune checkpoint therapy was explored in an immunotherapy cohort (n = 36).

Results

We showed that AUCs of the optimal radiomics signature for iMRS were 0.941 [95% confidence interval (CI), 0.909-0.973] and 0.833 (0.798-0.868) in the training and test cohorts, respectively. High iMRS was associated with poor RFS and OS. The prognostic performance of the Clinical-iMRS nomogram was better than that of a single parameter (p < 0.05), with a 1-, 3-, and 5-year C-index for RFS of 0.729, 0.709, and 0.713 in the training, test, and surgical resection cohorts, respectively. A high iMRS score predicted a higher proportion of objective response (vs. progressive disease or stable disease; odds ratio, 2.311; 95% CI, 1.144-4.672; p = 0.020; AUC, 0.718) in patients treated with anti-PD-1 and PD-L1.

Conclusions

iMRS may provide a promising method for predicting local myeloid immune responses in HCC patients, inferring postsurgical prognosis, and evaluating benefits of immune checkpoint therapy.

Identification of macrotrabecular-massive hepatocellular carcinoma through multiphasic CT-based representation learning method

BACKGROUND

Macrotrabecular-massive hepatocellular carcinoma (MTM-HCC) represents an aggressive subtype of HCC and is associated with poor survival.

PURPOSE

To investigate the performance of a representation learning-based feature fusion strategy that employs a multiphase contrast-enhanced CT (mpCECT)-based latent feature fusion (MCLFF) model for MTM-HCC identification.

METHODS

A total of 206 patients (54 MTM HCC, 152 non-MTM HCC) who underwent preoperative mpCECT with surgically confirmed HCC between July 2017 and December 2022 were retrospectively included from two medical centers. Multiphasic radiomics features were extracted from manually delineated volume of interest (VOI) of all lesions on each mpCECT phase. Representation learning based MCLFF model was built to fuse multiphasic features for MTM HCC prediction, and compared with competing models using other fusion methods. Conventional imaging features and clinical factors were also evaluated and analyzed. Prediction performance was validated by ROC analysis and statistical comparisons on an internal validation and an external testing dataset.

RESULTS

Fusion of radiomics features from the arterial phase (AP) and portal venous phase (PAP) using MCLFF demonstrated superior performance in MTM HCC prediction, with a higher AUC of 0.857 compared with all competing models in the internal validation set. Integration of multiple radiological or clinical features further improved the overall performance, with the highest AUCs of 0.857 and 0.836 respectively achieved in the internal validation and external testing set.

CONCLUSIONS

Multiphasic radiomics features of AP and PVP fused by the MCLFF have demonstrated substantial potential in the accurate prediction of MTM HCC. Clinical factors and Radiological features in mpCECT contribute incremental values to the developed MCLFF strategy.

Macrotrabecular-Massive Hepatocellular Carcinoma: A Case Report

Macrotrabecular-massive hepatocellular carcinoma (MTM-HCC) is a rare and aggressive molecular subtype of hepatocellular carcinoma (HCC) associated with a poor prognosis. Unlike typical HCC, which commonly arises in the context of cirrhosis, MTM-HCC can develop in non-cirrhotic livers, presenting unique diagnostic and therapeutic challenges. This case report describes a 35-year-old male who presented with persistent epigastric pain, fatigue, and loss of appetite. Clinical examination revealed hepatomegaly, prompting advanced imaging and laboratory investigations. Imaging studies identified a large hepatic mass with portal vein thrombosis and metastatic lesions, while histopathological analysis confirmed the diagnosis of MTM-HCC. The patient initiated treatment with a combination of immune checkpoint inhibitors and anti-angiogenic agents, which represent the current standard for advanced HCC. Despite initial adherence, disease progression was observed after four cycles of therapy. The patient passed away less than two months after his last consultation. This clinical course highlights the aggressive nature of MTM-HCC and its limited responsiveness to existing therapeutic protocols. MTM-HCC is characterized by distinctive histological and molecular features that differentiate it from other HCC subtypes. These include specific genetic mutations and protein expression patterns that contribute to its aggressive behavior and poor prognosis. Advanced imaging modalities combined with histopathological analysis remain crucial for accurate diagnosis and classification. This case emphasizes the critical need for heightened clinical vigilance, particularly in younger patients with atypical presentations of liver disease. It also underscores the importance of developing more effective, tailored therapeutic strategies for MTM-HCC. Further research into its molecular characteristics and inclusion in clinical trials is essential to improving outcomes for patients with this challenging and understudied subtype of liver cancer.

Prognostic Implications of MRI-assessed Intratumoral Fat in Hepatocellular Carcinoma: An Asian and European Cohort Study

Background The clinicopathologic-radiologic and prognostic characteristics of intratumoral fat in hepatocellular carcinoma (HCC) are critical for personalized treatment but remain understudied. Purpose To investigate the clinicopathologic-radiologic associations and prognostic implications of MRI-assessed intratumoral fat in HCCs. Materials and Methods This retrospective cohort study included consecutive adult patients who underwent resection for solitary HCCs and preoperative contrast-enhanced MRI from two tertiary-care hospitals in East Asia (March 2011 to December 2021) and Western Europe (September 2012 to December 2019). MRI scans were independently evaluated by three radiologists at each hospital. Based on Liver Imaging Reporting and Data System (LI-RADS) version 2018, intratumoral fat was defined as "fat in mass more than adjacent liver," and the homogeneous subtype was defined as intratumoral fat "in absence of mosaic and nodule-in-nodule architecture." Recurrence-free survival (RFS) and overall survival (OS) were estimated using the Kaplan-Meier method and compared using the log-rank test. Cox regression analyses were conducted to identify factors associated with RFS and OS. Results A total of 933 patients were included in the Asian (n = 736; median age, 53 years [IQR, 45-62 years]; 626 male) and European (n = 207; median age, 64 years [IQR, 55-70 years]; 161 male) cohorts. MRI-assessed intratumoral fat was detected in 30% (215 of 726) and 31% (64 of 207) of patients in the Asian and European cohorts, respectively (P = .72). In both cohorts, the steatohepatitic subtype, nonperipheral washout, enhancing capsule, and mosaic architecture were more frequent in tumors with intratumoral fat (P value range, <.001 to .04). Intratumoral fat in general was not associated with RFS or OS in either cohort (P value range, .48-.97). However, in the Asian cohort, homogeneous intratumoral fat was associated with longer RFS (hazard ratio [HR], 0.60; P = .009) and OS (HR, 0.33; P = .008) in multivariable Cox regression analyses. Conclusion MRI-assessed intratumoral fat was more frequent in steatohepatitic HCCs and associated with nonperipheral washout, enhancing capsule, and mosaic architecture. Although intratumoral fat was generally nonprognostic, homogeneous intratumoral fat was associated with longer RFS and OS in the Asian cohort. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Harmath in this issue.

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.

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.

Inter-reader agreement for CT/MRI LI-RADS category M imaging features: a systematic review and meta-analysis

BACKGROUNDS/AIMS

To systematically evaluate inter-reader agreement in the assessment of individual liver imaging reporting and data system (LI-RADS) category M (LR-M) imaging features in computed tomography/magnetic resonance imaging (CT/MRI) LIRADS v2018, and to explore the causes of poor agreement in LR-M assignment.

METHODS

Original studies reporting inter-reader agreement for LR-M features on multiphasic CT or MRI were identified using the MEDLINE, EMBASE, and Cochrane databases. The pooled kappa coefficient (κ) was calculated using the DerSimonian-Laird random-effects model. Heterogeneity was assessed using Cochran's Q test and I2 statistics. Subgroup meta-regression analyses were conducted to explore the study heterogeneity.

RESULTS

In total, 24 eligible studies with 5,163 hepatic observations were included. The pooled κ values were 0.72 (95% confidence interval [CI], 0.65-0.78) for rim arterial phase hyperenhancement, 0.52 (95% CI, 0.39-0.65) for peripheral washout, 0.60 (95% CI, 0.50-0.70) for delayed central enhancement, 0.68 (95% CI, 0.57-0.78) for targetoid restriction, 0.74 (95% CI, 0.65-0.83) for targetoid transitional phase/hepatobiliary phase appearance, 0.64 (95% CI, 0.49-0.78) for infiltrative appearance, 0.49 (95% CI, 0.30-0.68) for marked diffusion restriction, and 0.61 (95% CI, 0.48-0.73) for necrosis or severe ischemia. Substantial study heterogeneity was observed for all LR-M features (Cochran's Q test, P<0.01; I2≥89.2%). Studies with a mean observation size of <3 cm, those performed using 1.5-T MRI, and those with multiple image readers, were significantly associated with poor agreement of LR-M features.

CONCLUSIONS

The agreement for peripheral washout and marked diffusion restriction was limited. The LI-RADS should focus on improving the agreement of LR-M features.

Benign and malignant focal liver lesions displaying rim arterial phase hyperenhancement on CT and MRI

Rim arterial phase hyperenhancement is an imaging feature commonly encountered on contrast-enhanced CT and MRI in focal liver lesions. Rim arterial phase hyperenhancement is a subtype of arterial phase hyperenhancement mainly present at the periphery of lesions on the arterial phase. It is caused by a relative arterialization of the periphery compared with the center of the lesion and needs to be differentiated from other patterns of peripheral enhancement, including the peripheral discontinuous nodular enhancement and the corona enhancement. Rim arterial phase hyperenhancement may be a typical or an atypical imaging presentation of many benign and malignant focal liver lesions, challenging the radiologists during imaging interpretation. Benign focal liver lesions that may show rim arterial phase hyperenhancement may have a vascular, infectious, or inflammatory origin. Malignant focal liver lesions displaying rim arterial phase hyperenhancement may have a vascular, hepatocellular, biliary, lymphoid, or secondary origin. The differences in imaging characteristics on contrast-enhanced CT may be subtle, and a multiparametric approach on MRI may be helpful to narrow the list of differentials. This article aims to review the broad spectrum of focal liver lesions that may show rim arterial phase hyperenhancement, using an approach based on the benign and malignant nature of lesions and their histologic origin. CRITICAL RELEVANCE STATEMENT: Rim arterial phase hyperenhancement may be an imaging feature encountered in benign and malignant focal liver lesions and the diagnostic algorithm approach provided in this educational review may guide toward the final diagnosis. KEY POINTS: Several focal liver lesions may demonstrate rim arterial phase hyperenhancement. Rim arterial phase hyperenhancement may occur in vascular, inflammatory, and neoplastic lesions. Rim arterial phase hyperenhancement may challenge radiologists during image interpretation.

Multimodal imaging findings of primary liver clear cell carcinoma: a case presentation

Primary clear cell carcinoma of liver (PCCCL) is a special and relatively rare subtype of hepatocellular carcinoma (HCC), which is more common in people over 50 years of age, with a preference for men and a history of hepatitis B or C and/or cirrhosis. Herein, we present a case of a 60-year-old woman who came to our hospital for medical help with right upper abdominal pain. The imaging examination showed a low-density mass in the right lobe of his liver. In contrast enhanced computed tomography (CT) or T1-weighted imaging, significant enhancement can appear around the tumor during the arterial phase, and over time, the degree of enhancement of the tumor gradually decreases. The lession showed obviously increased fluorine-18 fluorodeoxyglucose (18F-FDG) uptake on positron emission tomography/CT. These imaging findings contribute to the diagnosis of PCCCL and differentiate it from other types of liver tumors.

Proliferative hepatocellular carcinomas in cirrhosis: patient outcomes of LI-RADS category 4/5 and category M

OBJECTIVES

We aimed to compare Liver Imaging Reporting and Data System (LI-RADS) category 4/5 and category M (LR-M) of proliferative hepatocellular carcinomas (HCCs) in cirrhotic patients and evaluate their impacts on prognosis.

METHODS

This retrospective multi-reader study included cirrhotic patients with single treatment-naïve HCC ≤ 5.0 cm who underwent contrast-enhanced CT, MRI, and subsequent hepatic resection within 2 months. The percentages of CT/MRI LR-4/5 and LR-M in proliferative and non-proliferative HCCs were compared. Univariable and multivariable Cox proportional hazards regression analyses were performed to assess the association of LI-RADS categories (LR-4/5 vs. LR-M) and pathologic classification (proliferative vs. non-proliferative) with overall survival (OS) and recurrence-free survival (RFS). Subgroups of patients with proliferative and non-proliferative HCCs were analyzed to compare OS and RFS between LR-4/5 and LR-M.

RESULTS

Of the 204 included patients, 38 were classified as having proliferative HCC. The percentages of LR-M were higher in proliferative than non-proliferative HCC on both CT (15.8% vs. 3.0%, p = 0.007) and MRI (26.3% vs. 9.6%, p = 0.016). Independent of pathologic classification, CT and MRI LR-M were significantly associated with poorer OS (hazard ratio (HR) = 4.58, p = 0.013, and HR = 6.45, p < 0.001) and RFS (HR = 3.66, p = 0.005, and HR = 6.44, p < 0.001) than LR-4/5. MRI LR-M was associated with significantly poorer OS (p ≤ 0.003) and RFS (p < 0.001) than MRI LR-4/5 in both proliferative and non-proliferative HCCs.

CONCLUSIONS

This multi-reader study showed that the percentages of LR-M were significantly higher in proliferative than non-proliferative HCCs. CT/MRI LR-M was significantly associated with poor OS and RFS, independent of the pathologic classification of proliferative versus non-proliferative HCCs.

CLINICAL RELEVANCE STATEMENT

CT and MRI LI-RADS category M can be clinically useful in predicting poor outcomes in patients with proliferative and non-proliferative hepatocellular carcinomas.

KEY POINTS

• The percentages of LR-M tumors on both CT and MRI were significantly higher in proliferative than non-proliferative hepatocellular carcinomas. • Independent of pathologic classification, CT/MRI LR-M categories were correlated with poor overall survival and recurrence-free survival. • Patients with both proliferative and non-proliferative hepatocellular carcinomas categorized as MRI LR-M had significantly poorer overall survival and recurrence-free survival than those categorized as MRI LR-4/5.

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.

Congestive Hepatopathy: Pathophysiology, Workup, and Imaging Findings with Pathologic Correlation

Liver congestion is increasingly encountered in clinical practice and presents diagnostic pitfalls of which radiologists must be aware. The complex altered hemodynamics associated with liver congestion leads to diffuse parenchymal changes and the development of benign and malignant nodules. Distinguishing commonly encountered benign hypervascular lesions, such as focal nodular hyperplasia (FNH)-like nodules, from hepatocellular carcinoma (HCC) can be challenging due to overlapping imaging features. FNH-like lesions enhance during the hepatic arterial phase and remain isoenhancing relative to the background liver parenchyma but infrequently appear to wash out at delayed phase imaging, similar to what might be seen with HCC. Heterogeneity, presence of an enhancing capsule, washout during the portal venous phase, intermediate signal intensity at T2-weighted imaging, restricted diffusion, and lack of uptake at hepatobiliary phase imaging point toward the diagnosis of HCC, although these features are not sensitive individually. It is important to emphasize that the Liver Imaging Reporting and Data System (LI-RADS) algorithm cannot be applied in congested livers since major LI-RADS features lack specificity in distinguishing HCC from benign hypervascular lesions in this population. Also, the morphologic changes and increased liver stiffness caused by congestion make the imaging diagnosis of cirrhosis difficult. The authors discuss the complex liver macro- and microhemodynamics underlying liver congestion; propose a more inclusive approach to and conceptualization of liver congestion; describe the pathophysiology of liver congestion, hepatocellular injury, and the development of benign and malignant nodules; review the imaging findings and mimics of liver congestion and hypervascular lesions; and present a diagnostic algorithm for approaching hypervascular liver lesions. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material.

Radiomics and liver: Where we are and where we are headed?

Hepatic diffuse conditions and focal liver lesions represent two of the most common scenarios to face in everyday radiological clinical practice. Thanks to the advances in technology, radiology has gained a central role in the management of patients with liver disease, especially due to its high sensitivity and specificity. Since the introduction of computed tomography (CT) and magnetic resonance imaging (MRI), radiology has been considered the non-invasive reference modality to assess and characterize liver pathologies. In recent years, clinical practice has moved forward to a quantitative approach to better evaluate and manage each patient with a more fitted approach. In this setting, radiomics has gained an important role in helping radiologists and clinicians characterize hepatic pathological entities, in managing patients, and in determining prognosis. Radiomics can extract a large amount of data from radiological images, which can be associated with different liver scenarios. Thanks to its wide applications in ultrasonography (US), CT, and MRI, different studies were focused on specific aspects related to liver diseases. Even if broadly applied, radiomics has some advantages and different pitfalls. This review aims to summarize the most important and robust studies published in the field of liver radiomics, underlying their main limitations and issues, and what they can add to the current and future clinical practice and literature.

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.

Association of LI-RADS and Histopathologic Features with Survival in Patients with Solitary Resected Hepatocellular Carcinoma

Background Both Liver Imaging Reporting and Data System (LI-RADS) and histopathologic features provide prognostic information in patients with hepatocellular carcinoma (HCC), but whether LI-RADS is independently associated with survival is uncertain. Purpose To assess the association of LI-RADS categories and features with survival outcomes in patients with solitary resected HCC. Materials and Methods This retrospective study included patients with solitary resected HCC from three institutions examined with preoperative contrast-enhanced CT and/or MRI between January 2008 and December 2019. Three independent readers evaluated the LI-RADS version 2018 categories and features. Histopathologic features including World Health Organization tumor grade, microvascular and macrovascular invasion, satellite nodules, and tumor capsule were recorded. Overall survival and disease-free survival were assessed with Cox regression models. Marginal effects of nontargetoid features on survival were estimated using propensity score matching. Results A total of 360 patients (median age, 64 years [IQR, 56-70 years]; 280 male patients) were included. At CT and MRI, the LI-RADS LR-M category was associated with increased risk of recurrence (CT: hazard ratio [HR] = 1.83 [95% CI: 1.26, 2.66], P = .001; MRI: HR = 2.22 [95% CI: 1.56, 3.16], P < .001) and death (CT: HR = 2.47 [95% CI: 1.72, 3.55], P < .001; MRI: HR = 1.80 [95% CI: 1.32, 2.46], P < .001) independently of histopathologic features. The presence of at least one nontargetoid feature was associated with an increased risk of recurrence (CT: HR = 1.80 [95% CI: 1.36, 2.38], P < .001; MRI: HR = 1.93 [95% CI: 1.81, 2.06], P < .001) and death (CT: HR = 1.51 [95% CI: 1.10, 2.07], P < .010) independently of histopathologic features. In matched samples, recurrence was associated with the presence of at least one nontargetoid feature at CT (HR = 2.06 [95% CI: 1.15, 3.66]; P = .02) or MRI (HR = 1.79 [95% CI: 1.01, 3.20]; P = .048). Conclusion In patients with solitary resected HCC, LR-M category and nontargetoid features were negatively associated with survival independently of histopathologic characteristics. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Kartalis and Grigoriadis in this issue.

MRI proton density fat fraction for estimation of tumor grade in steatotic hepatocellular carcinoma

OBJECTIVES

Image-based detection of intralesional fat in focal liver lesions has been established in diagnostic guidelines as a feature indicative of hepatocellular carcinoma (HCC) and associated with a favorable prognosis. Given recent advances in MRI-based fat quantification techniques, we investigated a possible relationship between intralesional fat content and histologic tumor grade in steatotic HCCs.

METHODS

Patients with histopathologically confirmed HCC and prior MRI with proton density fat fraction (PDFF) mapping were retrospectively identified. Intralesional fat of HCCs was assessed using an ROI-based analysis and the median fat fraction of steatotic HCCs was compared between tumor grades G1-3 with non-parametric testing. ROC analysis was performed in case of statistically significant differences (p < 0.05). Subgroup analyses were conducted for patients with/without liver steatosis and with/without liver cirrhosis.

RESULTS

A total of 57 patients with steatotic HCCs (62 lesions) were eligible for analysis. The median fat fraction was significantly higher for G1 lesions (median [interquartile range], 7.9% [6.0─10.7%]) than for G2 (4.4% [3.2─6.6%]; p = .001) and G3 lesions (4.7% [2.8─7.8%]; p = .036). PDFF was a good discriminator between G1 and G2/3 lesions (AUC .81; cut-off 5.8%, sensitivity 83%, specificity 68%) with comparable results in patients with liver cirrhosis. In patients with liver steatosis, intralesional fat content was higher than in the overall sample, with PDFF performing better in distinguishing between G1 and G2/3 lesions (AUC .92; cut-off 8.8%, sensitivity 83%, specificity 91%).

CONCLUSIONS

Quantification of intralesional fat using MRI PDFF mapping allows distinction between well- and less-differentiated steatotic HCCs.

CLINICAL RELEVANCE

PDFF mapping may help optimize precision medicine as a tool for tumor grade assessment in steatotic HCCs. Further investigation of intratumoral fat content as a potential prognostic indicator of treatment response is encouraged.

KEY POINTS

• MRI proton density fat fraction mapping enables distinction between well- (G1) and less- (G2 and G3) differentiated steatotic hepatocellular carcinomas. • In a retrospective single-center study with 62 histologically proven steatotic hepatocellular carcinomas, G1 tumors showed a higher intralesional fat content than G2 and G3 tumors (7.9% vs. 4.4% and 4.7%; p = .004). • In liver steatosis, MRI proton density fat fraction mapping was an even better discriminator between G1 and G2/G3 steatotic hepatocellular carcinomas.

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.

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.

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.

Exploring Opportunities to Enhance the Screening and Surveillance of Hepatocellular Carcinoma in Non-Alcoholic Fatty Liver Disease (NAFLD) through Risk Stratification Algorithms Incorporating Ultrasound Elastography

Non-alcoholic fatty liver disease (NAFLD), with its progressive form, non-alcoholic steatohepatitis (NASH), has emerged as a significant public health concern, affecting over 30% of the global population. Hepatocellular carcinoma (HCC), a complication associated with both cirrhotic and non-cirrhotic NAFLD, has shown a significant increase in incidence. A substantial proportion of NAFLD-related HCC occurs in non-cirrhotic livers, highlighting the need for improved risk stratification and surveillance strategies. This comprehensive review explores the potential role of liver ultrasound elastography as a risk assessment tool for HCC development in NAFLD and highlights the importance of effective screening tools for early, cost-effective detection and improved management of NAFLD-related HCC. The integration of non-invasive tools and algorithms into risk stratification strategies could have the capacity to enhance NAFLD-related HCC screening and surveillance effectiveness. Alongside exploring the potential advancement of non-invasive tools and algorithms for effectively stratifying HCC risk in NAFLD, we offer essential perspectives that could enable readers to improve the personalized assessment of NAFLD-related HCC risk through a more methodical screening approach.

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.

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.

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.

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.

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.

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.

Development and validation of MRI-based model for the preoperative prediction of macrotrabecular hepatocellular carcinoma subtype

BACKGROUND

Macrotrabecular hepatocellular carcinoma (MTHCC) has a poor prognosis and is difficult to diagnose preoperatively. The purpose is to build and validate MRI-based models to predict the MTHCC subtype.

METHODS

Two hundred eight patients with confirmed HCC were enrolled. Three models (model 1: clinicoradiologic model; model 2: fusion radiomics signature; model 3: combined model 1 and model 2) were built based on their clinical data and MR images to predict MTHCC in training and validation cohorts. The performance of the models was assessed using the area under the curve (AUC). The clinical utility of the models was estimated by decision curve analysis (DCA). A nomogram was constructed, and its calibration was evaluated.

RESULTS

Model 1 is easier to build than models 2 and 3, with a good AUC of 0.773 (95% CI 0.696-0.838) and 0.801 (95% CI 0.681-0.891) in predicting MTHCC in training and validation cohorts, respectively. It performed slightly superior to model 2 in both training (AUC 0.747; 95% CI 0.689-0.806; p = 0.548) and validation (AUC 0.718; 95% CI 0.618-0.810; p = 0.089) cohorts and was similar to model 3 in the validation (AUC 0.866; 95% CI 0.801-0.928; p = 0.321) but inferior in the training (AUC 0.889; 95% CI 0.851-0.926; p = 0.001) cohorts. The DCA of model 1 had a higher net benefit than the treat-all and treat-none strategy at a threshold probability of 10%. The calibration curves of model 1 closely aligned with the true MTHCC rates in the training (p = 0.355) and validation sets (p = 0.364).

CONCLUSION

The clinicoradiologic model has a good performance in diagnosing MTHCC, and it is simpler and easier to implement, making it a valuable tool for pretherapeutic decision-making in patients.

State-of-the-art review on the correlations between pathological and magnetic resonance features of cirrhotic nodules

Hepatocellular carcinoma (HCC) has become the second greatest cause of cancer-related mortality worldwide and the newest advancements in liver imaging have improved the diagnosis of both overt malignancies and premalignant lesions, such as cirrhotic or dysplastic nodules, which is crucial to improve overall patient survival rate and to choose the best treatment options. The role of Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) has grown in the last 20 years. In particular, the introduction of hepatospecific contrast agents has strongly increased the definition of precursor nodules and detection of high-grade dysplastic nodules and early HCCs. Nevertheless, the diagnosis of liver tumours in cirrhotic patients sometimes remains challenging for radiologists, thus, in doubtful cases, biopsy and histological analysis become critical in clinical practice. This current review briefly summarizes the history of imaging and histology for HCC, covering the newest techniques and their limits. Then, the article discusses the links between radiological and pathological characteristics of liver lesions in cirrhotic patients, by describing the multistep process of hepatocarcinogenesis. Explaining the evolution of pathologic change from cirrhotic nodules to malignancy, the list of analyzed lesions provides regenerative nodules, low-grade and high-grade dysplastic nodules, small HCC and progressed HCC, including common subtypes (steatohepatitic HCC, scirrhous HCC, macrotrabecular massive HCC) and more rare forms (clear cell HCC, chromophobe HCC, neutrophil-rich HCC, lymphocyte-rich HCC, fibrolamellar HCC). The last chapter covers the importance of the new integrated morphological-molecular classification and its association with radiological features.

Nomogram Estimating Vessels Encapsulating Tumor Clusters in Hepatocellular Carcinoma From Preoperative Gadoxetate Disodium-Enhanced MRI

BACKGROUND

Vessels encapsulating tumor clusters (VETC) pattern is a novel microvascular pattern associated with poor outcomes of hepatocellular carcinoma (HCC). Preoperative estimation of VETC has potential to improve treatment decisions.

PURPOSE

To develop and validate a nomogram based on gadoxetate disodium-enhanced MRI for estimating VETC in HCC and to evaluate whether the estimations are associated with recurrence after hepatic resection.

STUDY TYPE

Retrospective.

POPULATION

A total of 320 patients with HCC and histopathologic VETC pattern assessment from three centers (development cohort:validation cohort = 173:147).

FIELD STRENGTH/SEQUENCE

A3.0  T/turbo spin-echo T2-weighted, spin-echo echo-planar diffusion-weighted, and 3D T1-weighted gradient-echo sequences.

ASSESSMENT

A set of previously reported VETC- and/or prognosis-correlated qualitative and quantitative imaging features were assessed. Clinical and imaging variables were compared based on histopathologic VETC status to investigate factors indicating VETC pattern. A regression-based nomogram was then constructed using the significant factors for VETC pattern. The nomogram-estimated VETC stratification was assessed for its association with recurrence.

STATISTICAL TESTS

Fisher exact test, t-test or Mann-Whitney test, logistic regression analyses, Harrell's concordance index (C-index), nomogram, Kaplan-Meier curves and log-rank tests. P value < 0.05 was considered statistically significant.

RESULTS

Pathological VETC pattern presence was identified in 156 patients (development cohort:validation cohort = 83:73). Tumor size, presence of heterogeneous enhancement with septations or with irregular ring-like structures, and necrosis were significant factors for estimating VETC pattern. The nomogram incorporating these indicators showed good discrimination with a C-index of 0.870 (development cohort) and 0.862 (validation cohort). Significant differences in recurrence rates between the nomogram-estimated high-risk VETC group and low-risk VETC group were found (2-year recurrence rates, 50.7% vs. 30.3% and 49.6% vs. 31.8% in the development and validation cohorts, respectively).

DATA CONCLUSION

The nomogram integrating gadoxetate disodium-enhanced MRI features was associated with VETC pattern preoperatively and with postoperative recurrence in patients with HCC.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY: Stage 2.

Prognostic implications of CT/MRI LI-RADS in hepatocellular carcinoma: State of the art and future directions

Hepatocellular carcinoma (HCC) is the fourth most lethal malignancy with an increasing incidence worldwide. Management of HCC has followed several clinical staging systems that rely on tumour morphologic characteristics and clinical variables. However, these algorithms are unlikely to profile the full landscape of tumour aggressiveness and allow accurate prognosis stratification. Noninvasive imaging biomarkers on computed tomography (CT) or magnetic resonance imaging (MRI) exhibit a promising prospect to refine the prognostication of HCC. The Liver Imaging Reporting and Data System (LI-RADS) is a comprehensive system for standardizing the terminology, techniques, interpretation, reporting and data collection of liver imaging. At present, it has been widely accepted as an effective diagnostic system for HCC in at-risk patients. Emerging data have provided new insights into the potential of CT/MRI LI-RADS in HCC prognostication, which may help refine the prognostic paradigm of HCC that promises to direct individualized management and improve patient outcomes. Therefore, this review aims to summarize several prognostic imaging features at CT/MRI for patients with HCC; the available evidence regarding the use of LI-RDAS for evaluation of tumour biology and clinical outcomes, pitfalls of current literature, and future directions for LI-RADS in the management of HCC.

Nomogram for the Preoperative Prediction of the Macrotrabecular-Massive Subtype of Hepatocellular Carcinoma

Background

The macrotrabecular-massive subtype of hepatocellular carcinoma (MTM-HCC) is an aggressive histological type and results in poor prognosis. We developed a nomogram model based on laboratory results to predict the presence of MTM-HCC.

Methods

A total of 357 HCC patients who underwent radical surgery between January 2015 and December 2020 at Ningbo Medical Center Lihuili Hospital were grouped according to histological type. After propensity score matching (PSM), 267 patients were divided into MTM-HCC (n = 76) and non-MTM-HCC (n = 191) groups. A LASSO regression analysis model was used to select predictive factors. Finally, a nomogram for predicting the presence of MTM-HCC was established. Decision curve analysis (DCA) was conducted to determine the clinical usefulness of the nomogram model by quantifying the net benefits along with the increase in threshold probabilities.

Results

The 1-, 3-, and 5-year disease-free survival (DFS) and overall survival (OS) rates for MTM-HCC were 60.0%, 36.0%, 32.4% and 92.1%, 68.7%, 52.2%, respectively. Survival analysis indicated that the probabilities of achieving DFS and OS were significantly worse in the MTM-HCC group than in the non-MTM-HCC group (P < 0.05). The nomogram model that included AST levels, PT and AFP levels achieved a better C-index of 0.723 (95% CI: 0.659-0.787). DCA revealed that the nomogram model could lead to net benefits and exhibited a wider range of threshold probabilities in the prediction of MTM-HCC.

Conclusion

The nomogram model included AST, PT and AFP could achieve an optimal performance in the preoperative prediction of MTM-HCC.

Multiradiographic Diagnosis of Primary Hepatocellular Carcinoma and Evaluation of Its Postoperative Observation after Interventional Treatment

Objective

To investigate the focal imaging performance of MRI and CT multiphase dynamic enhancement scan examination in primary liver cancer patients, analyze its clinical diagnostic value, and provide a basis for early diagnosis of the disease.

Methods

236 patients with primary liver cancer admitted to our hospital from May 2019 to November 2021 were randomly divided into two groups, the control group was given MRI multiphase dynamic enhancement scan diagnostic method, and the observation group was given CT scan combined with the MRI diagnostic method. The patients' examination results and pathological examination results were compared and analyzed, and the therapeutic effects of patients in the two groups after interventional treatment were compared.

Results

After the imaging and pathological examinations of patients in both groups, it was found that the diagnostic accuracy of patients in the observation group and the therapeutic effect after interventional treatment were significantly better than those in the control group.

Conclusions

Compared with CT multiphase dynamic enhancement scan, MRI multiphase dynamic enhancement scan can show multidirectional and multiangle lesions in primary hepatocellular carcinoma patients, with better characteristics of blood supply to hepatocellular carcinoma and a higher accuracy rate.

Variant Hepatocellular Carcinoma Subtypes According to the 2019 WHO Classification: An Imaging-Focused Review

The 2019 5th edition of the WHO classification of digestive system tumors estimates that up to 35% of hepatocellular carcinomas (HCCs) can be classified as one of eight subtypes defined by molecular characteristics: steatohepatitic, clear cell, macrotrabecular-massive, scirrhous, chromophobe, fibrolamellar, neutrophil-rich, and lymphocyte-rich HCCs. Due to their distinct cellular and architectural characteristics, these subtypes may not display arterial phase hyperenhancement and washout appearance, which are the classic MRI features of HCC, creating challenges in noninvasively diagnosing such lesions as HCC. Moreover, certain subtypes with atypical imaging features have a worse prognosis than other HCCs. A range of distinguishing imaging features may help raise suspicion that a liver lesion represents one of these HCC subtypes. In this review, we describe the MRI features that have been reported in association with various HCC subtypes according to the 2019 WHO classification, with attention given to the current understanding of these subtypes' pathologic and molecular bases and relevance to clinical practice. Imaging findings that differentiate the subtypes from benign liver lesions and non-HCC malignancies are highlighted. Familiarity with these sub-types and their imaging features may allow the radiologist to suggest their presence, though histologic analysis remains needed to establish the diagnosis.

Macrotrabecular-Massive Hepatocellular Carcinoma: Light and Shadow in Current Knowledge

The subject of this narrative review is macrotrabecular-massive hepatocellular carcinoma (MTM‐HCC). Despite their rarity, these tumours are of general interest because of their epidemiological and clinical features and for representing a distinct model of the interaction between the angiogenetic system and neoplastic cells. The MTM‐HCC subtype is associated with various adverse biological and pathological parameters (the Alfa-foetoprotein (AFP) serum level, tumour size, vascular invasion, and satellite nodules) and is a key determinant of patient prognosis, with a strong and independent predictive value for early and overall tumour recurrence. Gene expression profiling has demonstrated that angiogenesis activation is a hallmark feature of MTM-HCC, with overexpression of both angiopoietin 2 (ANGPT2) and vascular endothelial growth factor A (VEGFA).

Imaging features of hepatocellular carcinoma in nonalcoholic fatty liver disease and nonalcoholic steatohepatitis: a systematic review and meta-analysis

PURPOSE

To investigate the imaging features of hepatocellular carcinoma (HCC) in patients with non-alcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH) through a systematic review and meta-analysis.

METHODS

MEDLINE, EMBASE, and the Cochrane Library database were searched for studies providing data on imaging features of HCC in NAFLD and NASH between January 1, 2011 and July 19, 2021. Random effects models were used to calculate the pooled percentages of the three major features of arterial-phase hyperenhancement (APHE), washout, and enhancing capsule. Sensitivity analysis and subgroup analysis were performed according to underlying liver disease (NASH vs. NAFLD) and imaging modality (CT vs. MRI).

RESULTS

Five studies (170 patients with 193 HCCs) were included in the analysis. The pooled percentages of APHE, washout, and enhancing capsule were 94.0% (95% confidence interval [CI] 89.1-96.7%), 72.7% (95% CI 63.3-80.4%), and 57.5% (95% CI 45.1-69.1%), respectively. The percentages of these three major features did not significantly differ between NAFLD and NASH (p ≥ 0.21). MRI showed similar pooled percentages of APHE (94.3% vs. 93.4%, p = 0.82) and washout (70.4% vs. 77.2%, p = 0.38) to CT, but a higher pooled percentage of enhancing capsule (67.1% vs. 44.7%, p = 0.02).

CONCLUSION

HCC in patients with NAFLD and NASH had a similar frequency of APHE to HCC with other etiology. However, it showed a relatively low frequency of washout and enhancing capsule.

A gadoxetic acid-enhanced MRI-based multivariable model using LI-RADS v2018 and other imaging features for preoperative prediction of macrotrabecular-massive hepatocellular carcinoma

PURPOSE

To identify imaging features of macrotrabecular-massive hepatocellular carcinoma (MTM-HCC) using LI-RADS v2018 and other imaging features and to develop a gadoxetic acid-enhanced MRI (EOB-MRI)-based model for pretreatment prediction of MTM-HCC.

MATERIALS AND METHODS

A total of 93 patients with pathologically proven HCC (39 MTM-HCC and 54 non-MTM-HCC) were retrospectively evaluated with EOB-MRI at 3 T. Imaging analysis according to LI-RADS v2018 was evaluated by two readers. Univariate and multivariate analyses were performed to determine independent predictors for MTM-HCC. Different logistic regression models were built based on MRI features, including model A (enhancing capsule, blood products in mass and ascites), model B (enhancing capsule and ascites), model C (blood products in mass and ascites), and model D (blood products in mass and enhancing capsule). Diagnostic performance was assessed by receiver operating characteristic (ROC) curves.

RESULTS

After multivariate analysis, absence of enhancing capsule (odds ratio = 0.102, p = 0.010), absence of blood products in mass (odds ratio = 0.073, p = 0.030), and with ascites (odds ratio = 55.677, p = 0.028) were identified as independent differential factors for the presence of MTM-HCC. Model A yielded a sensitivity, specificity, and AUC of 35.90% (21.20,52.80), 94.44% (84.60, 98.80), and 0.731 (0.629, 0.818). Model A achieved a comparable AUC than model D (0.731 vs. 0.699, p = 0.333), but a higher AUC than model B (0.731 vs. 0.644, p = 0.048) and model C (0.731 vs. 0.650, p = 0.005).

CONCLUSION

The EOB-MRI-based model is promising for noninvasively predicting MTM-HCC and may assist clinicians in pretreatment decisions.