A Non-Invasive Nomogram for Preoperative Prediction of Microvascular Invasion Risk in Hepatocellular Carcinoma

Preoperative prediction of microvascular invasion and relapse-free survival in hepatocellular Carcinoma ≥3 cm using CT radiomics: Development and external validation

OBJECTIVE

To preoperatively predict microvascular invasion (MVI) and relapse-free survival (RFS) in hepatocellular carcinoma (HCC) ≥3 cm by constructing and externally validating a combined radiomics model using preoperative enhanced CT images.

METHODS

This retrospective study recruited adults who underwent surgical resection between September 2016 and August 2020 in our hospital with pathologic confirmation of HCC ≥3 cm and MVI status. For external validation, adults who underwent surgical resection between September 2020 and August 2021 in our hospital were included. Histopathology was the reference standard. The HCC area was segmented on the arterial and portal venous phase CT images to develop a CT radiomics model. A combined model was developed using selected radiomics features, demographic information, laboratory index and radiological features. Analysis of variance and support vector machine were used as features selector and classifier. Receiver operating characteristic (ROC) curves, calibration curves and decision curve analysis (DCA) were used to evaluate models' performance. The Kaplan-Meier method and log-rank test were used to evaluate the predictive value for RFS.

RESULTS

A total of 202 patients were finally enrolled (median age, 59 years, 173 male). Thirteen and 24 features were selected for the CT radiomics model and the combined model, and the area under the ROC curves (AUC) were 0.752 (95 %CI 0.615, 0.889) and 0.890 (95 %CI 0.794, 0.985) in the external validation set, respectively. Calibration curves and DCA showed a higher net clinical benefit of the combined model. The high-risk group (P < 0.001) was an independent predictor for RFS.

CONCLUSIONS

The combined model showed high accuracy for preoperatively predicting MVI and RFS in HCC ≥3 cm.

Real-world efficacy of radiomics versus clinical predictors for microvascular invasion in patients with hepatocellular carcinoma: Large cohort study

AIM

Microvascular invasion (MVI) affects the prognosis and treatment of hepatocellular carcinoma (HCC); however, its preoperative diagnosis is challenging. Analysis of computed tomography (CT) images using radiomics can detect MVI, but its effectiveness depends on the imaging conditions. We compared the efficacies of radiomics, clinical, and combined models for predicting MVI in HCC using nonstandardized scanning protocols.

METHODS

This multicenter study included 533 patients who underwent hepatic resection for HCC. Patients were divided randomly into training (n = 426) and test groups (n = 107). We manually extracted 3D CT features in hepatic arterial, portal venous, and venous phases. The radiomics model was trained by machine learning. A logistic regression model was developed based on clinical information, and a fused model was created integrating clinical information and radiomics prediction score (Rad_Score). We calculated areas under the receiver operating characteristic curves (AUCs) for the radiomics, clinical, and mixed models in the test groups.

RESULTS

The clinical model incorporated hepatitis B virus surface antigen, tumor diameter, and log-transformed α-fetoprotein and des-gamma-carboxyprothrombin. The AUCs of the radiomics and clinical models were comparable (p = 0.76). Rad_Score was not an independent significant factor in the fused model (p = 0.40) and its addition did not improve the accuracy of the clinical model alone (p = 0.51).

CONCLUSIONS

A clinical model is as effective as a CT radiomics model for predicting MVI status in patients with HCC based on real-world scanning data, and integration of both models does not improve the predictive performance compared with a clinical model alone.

Chinese expert consensus on the diagnosis and treatment of hepatocellular carcinoma with microvascular invasion (2024 edition)

Background

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in China. Surgical resection is the preferred treatment for HCC, but the postoperative recurrence and metastasis rates are high. Current evidence shows that microvascular invasion (MVI) is an independent risk factor for postoperative recurrence and metastasis, but there are still many controversies about the diagnosis, classification, prediction, and treatment of MVI worldwide.

Methods

Systematic literature reviews to identify knowledge gaps and support consensus statements and a modified Delphi method to develop evidence- and expert-based guidelines and finalization of the clinical consensus statements based on recommendations from a panel of experts.

Results

After many discussions and revisions, the Chinese Association of Liver Cancer of the Chinese Medical Doctor Association organized domestic experts in related fields to form the "Chinese expert consensus on the diagnosis and treatment of hepatocellular carcinoma with microvascular invasion (2024 edition)" which included eight recommendations to better guide the prediction, diagnosis and treatment of HCC patients with MVI. The MVI pathological grading criteria as outlined in the "Guidelines for Pathological Diagnosis of Primary Liver Cancer" and the Eastern Hepatobiliary Surgery Hospital (EHBH) nomogram for predicting MVI are highly recommended.

Conclusions

We present an expert consensus on the diagnosis and treatment of MVI and potentially improve recurrence-free survival (RFS) and overall survival (OS) for HCC patients with MVI.

A Nomogram Based on MRI Visual Decision Tree to Evaluate Vascular Endothelial Growth Factor in Hepatocellular Carcinoma

BACKGROUNDS

Anti-vascular endothelial growth factor (VEGF) therapy has been developed and recognized as an effective treatment for hepatocellular carcinoma (HCC). However, there remains a lack of noninvasive methods in precisely evaluating VEGF expression in HCC.

PURPOSE

To establish a visual noninvasive model based on clinical indicators and MRI features to evaluate VEGF expression in HCC.

STUDY TYPE

Retrospective.

POPULATION

One hundred forty HCC patients were randomly divided into a training (N = 98) and a test cohort (N = 42).

FIELD STRENGTH/SEQUENCE

3.0 T, T2WI, T1WI including pre-contrast, dynamic, and hepatobiliary phases.

ASSESSMENT

The fusion model constructed by history of smoking, albumin-to-globulin ratio (AGR) and the Radio-Tree model was visualized by a nomogram.

STATISTICAL TESTS

Performances of models were assessed by receiver operating characteristic (ROC) curves. Student's t-test, Mann-Whitney U-test, chi-square test, Fisher's exact test, univariable and multivariable logistic regression analysis, DeLong's test, integrated discrimination improvement (IDI), Hosmer-Lemeshow test, and decision curve analysis were performed. P < 0.05 was considered statistically significant.

RESULTS

History of smoking and AGR ≤1.5 were clinical independent risk factors of the VEGF expression. In training cohorts, values of area under the curve (AUCs) of Radio-Tree model, Clinical-Radiological (C-R) model, fusion model which combined history of smoking and AGR with Radio-Tree model were 0.821, 0.748, and 0.871. In test cohort, the fusion model showed highest AUC (0.844) than Radio-Tree and C-R models (0.819, 0.616, respectively). DeLong's test indicated that the fusion model significantly differed in performance from the C-R model in training cohort (P = 0.015) and test cohort (P = 0.007).

DATA CONCLUSION

The fusion model combining history of smoking, AGR and Radio-Tree model established with ML algorithm showed the highest AUC value than others.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY: Stage 2.

A clinical study exploring the prediction of microvascular invasion in hepatocellular carcinoma through the use of combined enhanced CT and MRI radiomics

OBJECTIVE

To develop a predictive model for microvascular invasion (MVI) in hepatocellular carcinoma (HCC) through radiomics analysis, integrating data from both enhanced computed tomography (CT) and magnetic resonance imaging (MRI).

METHODS

A retrospective analysis was conducted on 93 HCC patients who underwent partial hepatectomy. The gold standard for MVI was based on the histopathological diagnosis of the tissue. The 93 patients were randomly divided into training and validation groups in 7:3 ratio. The imaging data of patients, including CT and MRI, were collected and processed using 3D Slicer to delineate the region of interest (ROI) for each tumor. Radiomics features were extracted from CT and MRI of patients using Python. Lasso regression analysis was used to select optimal radiomics features for MVI in the training group. The optimal radiomics features of CT and MRI were selected to establish the prediction model. The predictive performance of the model was evaluated using the receiver operator characteristic curve (ROC), calibration curve, and decision curve analysis (DCA).

RESULTS

After univariate and multivariate analyses, it was found that tumor diameter was significantly different between the MVI positive and negative groups. After extracting 2153 imaging phenotyping features from the CT and MRI images of the 93 patients using Python, ten standardized coefficient non-zero imaging phenotyping features were finally determined by Lasso regression analysis in the CT and MRI images. A comprehensive predictive model with clinical variable and optimal radiomics features was established. The area under the curve (AUC) of the training group was 0.916 (95%CI: 0.843-1.000), sensitivity: 95.2%, specificity: 79.2%. In the validation group, the predictive model diagnosed MVI with AUC = 0.816 (95%CI: 0.642-0.990), sensitivity: 84.2%, and specificity: 75.0%.

CONCLUSION

The joint model that integrated the optimal radiomics features with clinical variables has good diagnostic performance for MVI of HCC and specific clinical applicability.

Detecting microvascular invasion in hepatocellular carcinoma using the impeded diffusion fraction technique to sense macromolecular coordinated water

OBJECTIVES

Impeded diffusion fraction (IDF) is a novel and promising diffusion-weighted imaging (DWI) technique that allows for the detection of various diffusion compartments, including macromolecular coordinated water, free diffusion, perfusion, and cellular free water. This study aims to investigate the clinical potential of IDF-DWI in detecting microvascular invasion (MVI) in hepatocellular carcinoma (HCC).

METHODS

66 patients were prospectively included. Metrics derived from IDF-DWI and the apparent diffusion coefficient (ADC) were calculated. Multivariate logistic regression was employed to identify clinical risk factors. Diagnostic performance was evaluated using the area under the receiver operating characteristics curve (AUC-ROC), the area under the precision-recall curve (AUC-PR), and the calibration error (cal-error). Additionally, a power analysis was conducted to determine the required sample size.

RESULTS

The results suggested a significantly higher fraction of impeded diffusion (FID) originating from IDF-DWI in MVI-positive HCCs (p < 0.001). Moreover, the ADC was found to be significantly lower in MVI-positive HCCs (p = 0.019). Independent risk factors of MVI included larger tumor size and elevated alpha-fetoprotein (AFP) levels. The nomogram model incorporating ADC, FID, tumor size, and AFP level yielded the highest diagnostic accuracy for MVI (AUC-PR = 0.804, AUC-ROC = 0.783, cal-error = 0.044), followed by FID (AUC-PR = 0.693, AUC-ROC = 0.760, cal-error = 0.060) and ADC (AUC-PR = 0.570, AUC-ROC = 0.651, cal-error = 0.164).

CONCLUSION

IDF-DWI shows great potential in noninvasively, accurately, and preoperatively detecting MVI in HCC and may offer clinical benefits for prognostic prediction and determination of treatment strategy.

Prognostic Value of Preoperative MRI-derived 3D Quantitative Tumor Arterial Burden in Patients with Hepatocellular Carcinoma Receiving Transarterial Chemoembolization

Purpose To investigate the association of tumor arterial burden (TAB) on preoperative MRI with transarterial chemoembolization refractoriness (TACER) and progression-free survival (PFS) in patients with hepatocellular carcinoma (HCC). Materials and Methods This retrospective study included patients with HCC who underwent repeated transarterial chemoembolization (TACE) treatments between January 2013 and December 2020. HCC was confirmed with pathology or imaging, and patients with other tumors, lost follow-up, or with a combination of other treatments were excluded. TACER was defined as viable lesions of more than 50% or increase in tumor number after two or more consecutive TACE treatments, continuous elevation of tumor markers, extrahepatic spread, or vascular invasion. TAB assessed with preoperative MRI was divided into high and low groups according to the median. A Cox proportional hazards model was used to determine the predictors of TACER and PFS. Results A total of 355 patients (median age, 61 years [IQR, 54-67]; 306 [86.2%] men, 49 [13.8%] women) were included. During a median follow-up of 32.7 months, the high TAB group had significantly faster TACER and decreased PFS than the low TAB group (all log-rank P < .001). High TAB was the strongest independent predictor of TACER and PFS in multivariable Cox regression analyses (hazard ratio [HR], 2.23 [95% CI: 1.51, 3.29]; HR, 2.30 [95% CI: 1.61, 3.27], respectively), especially in patients with Barcelona Clinic Liver Cancer stage A or a single tumor. The restricted cubic spline plot demonstrated that the HR of TACER and PFS continuously increased with increasing TAB. Conclusion High preoperative TAB at MRI was a risk factor for faster refractoriness and progression in patients with HCC treated with TACE. Keywords: Interventional-Vascular, MR Angiography, Hepatocellular Carcinoma, Transarterial Chemoembolization, Progression-free Survival, MRI Supplemental material is available for this article. © RSNA, 2024.

The value of varying diffusion curvature MRI for assessing the microvascular invasion of hepatocellular carcinoma

PURPOSE

Varying diffusion curvature (VDC) MRI is an emerging diffusion-weighted imaging (DWI) technique that can capture non-Gaussian diffusion behavior and reflect tissue heterogeneity. However, its clinical utility has hardly been evaluated. We aimed to investigate the value of the VDC technique in noninvasively assessing microvascular invasion (MVI) in hepatocellular carcinoma (HCC).

METHODS

74 patients with HCCs, including 39 MVI-positive and 35 MVI-negative HCCs were included into this prospective study. Quantitative metrics between subgroups, clinical risk factors, as well as diagnostic performance were evaluated. The power analysis was also carried out to determine the statistical power.

RESULTS

MVI-positive HCCs exhibited significantly higher VDC-derived structural heterogeneity measure, D1 (0.680 ± 0.100 × 10-3 vs 0.572 ± 0.148 × 10-3 mm2/s, p = 0.001) and lower apparent diffusion coefficient (ADC) (1.350 ± 0.166 × 10-3 vs 1.471 ± 0.322 × 10-3 mm2/s, p = 0.0495) compared to MVI-negative HCCs. No statistical significance was observed for VDC-derived diffusion coefficient, D0 between the subgroups (p = 0.562). Tumor size (odds ratio (OR) = 1.242) and alpha-fetoprotein (AFP) (OR = 2.527) were identified as risk factors for MVI. A predictive nomogram was constructed based on D1, ADC, tumor size, and AFP, which exhibited the highest diagnostic accuracy (AUC = 0.817), followed by D1 (AUC = 0.753) and ADC (AUC = 0.647). The diagnostic performance of the nomogram-based model was also validated by the calibration curve and decision curve.

CONCLUSION

VDC can aid in the noninvasive and preoperative diagnosis of HCC with MVI, which may result in the clinical benefit in terms of prognostic prediction and clinical decision-making.

Platelet count as a predictor of vascular invasion and extrahepatic metastasis in hepatocellular carcinoma: A systematic review and meta-analysis

BACKGROUND

Vascular invasion (VI) indicates highly invasive tumor biological behavior and is a major determining factor of poor survival and high risk of metastasis in hepatocellular carcinoma (HCC). Epidemiological evidence of the association between pretherapeutic platelet count (PLT) and the risk of VI and extrahepatic metastasis in HCC remains controversial.

METHODS

A systematic retrieval was executed in databases of PubMed, Embase, and Web of Science until Dec 2022. Effect size and 95% confidence interval (CI) were extracted or estimated to synthetically investigate the effects of pretherapeutic PLT on VI and extrahepatic metastasis. Meta-analyses were performed by using a random or a fixed effects model.

RESULTS

Finally, the current meta-analysis included 15 studies with a total of 12,378 HCC patients. It was shown that, patients with a higher pretherapeutic level of PLT had a significantly increased risk of VI (11 studies,8,759 patients; OR = 1.44, 95%CI: 1.02-2.02) and extrahepatic metastasis (6 studies,8, 951 patients; OR = 2.51, 95% CI: 2.19-2.88) in comparison with patients with a lower PLT. Funnel plots and Begg's tests indicated that there were no significant publication biases.

CONCLUSION

This meta-analysis shows that pretherapeutic elevated PLT is associated with an increased risk of VI and extrahepatic metastasis in HCC.

Arachidonic acid metabolism CYP450 pathway is deregulated in hepatocellular carcinoma and associated with microvascular invasion

Arachidonic acid metabolism plays a crucial role in the development and progression of inflammatory and metabolic liver diseases. However, its role in hepatocellular carcinoma (HCC) remains unclear. In this study, we investigated the expression of key genes involved in the arachidonic acid metabolism pathway in HCC using a combination of bioinformatics, proteomics and immunohistochemistry analyses. Through a comprehensive analysis of publicly available datasets, clinical HCC tissues, and tissue microarrays, we compared the expression of hepatic arachidonic acid metabolic genes. We observed significant downregulation of cytochrome P450 (CYP450) pathway genes at both the messenger RNA and protein levels in HCC tissues compared to normal liver tissues. Furthermore, we observed a strong correlation between the deregulation of the arachidonic acid metabolism CYP450 pathway and the pathological features and prognosis of HCC. Specifically, the expression of CYP2C8/9/18/19 was significantly correlated with pathological grade (r = -.484, p < .0001), vascular invasion (r = -.402, p < .0001), aspartate transaminase (r = -.246, p = .025), gamma-glutamyl transpeptidase (r = -.252, p = .022), alkaline phosphatase (r = -.342, p = .002), alpha-fetoprotein (r = -.311, p = .004) and carbohydrate antigen 19-9 (r = -.227, p = .047). Moreover, we discovered a significant association between CYP450 pathway activity and vascular invasion in HCC. Collectively, these data indicate that arachidonic acid CYP450 metabolic pathway deregulation is implicated in HCC progression and may be a potential predictive factor for early recurrence in patients with HCC.

Noninvasive urinary protein signatures combined clinical information associated with microvascular invasion risk in HCC patients

BACKGROUND

Microvascular invasion (MVI) is the main factor affecting the prognosis of patients with hepatocellular carcinoma (HCC). The aim of this study was to identify accurate diagnostic biomarkers from urinary protein signatures for preoperative prediction.

METHODS

We conducted label-free quantitative proteomic studies on urine samples of 91 HCC patients and 22 healthy controls. We identified candidate biomarkers capable of predicting MVI status and combined them with patient clinical information to perform a preoperative nomogram for predicting MVI status in the training cohort. Then, the nomogram was validated in the testing cohort (n = 23). Expression levels of biomarkers were further confirmed by enzyme-linked immunosorbent assay (ELISA) in an independent validation HCC cohort (n = 57).

RESULTS

Urinary proteomic features of healthy controls are mainly characterized by active metabolic processes. Cell adhesion and cell proliferation-related pathways were highly defined in the HCC group, such as extracellular matrix organization, cell-cell adhesion, and cell-cell junction organization, which confirms the malignant phenotype of HCC patients. Based on the expression levels of four proteins: CETP, HGFL, L1CAM, and LAIR2, combined with tumor diameter, serum AFP, and GGT concentrations to establish a preoperative MVI status prediction model for HCC patients. The nomogram achieved good concordance indexes of 0.809 and 0.783 in predicting MVI in the training and testing cohorts.

CONCLUSIONS

The four-protein-related nomogram in urine samples is a promising preoperative prediction model for the MVI status of HCC patients. Using the model, the risk for an individual patient to harbor MVI can be determined.

Radiomics nomogram for the prediction of microvascular invasion of HCC and patients' benefit from postoperative adjuvant TACE: a multi-center study

OBJECTIVES

To evaluate the performance of a radiomics nomogram developed based on gadolinium-ethoxybenzyl-diethylenetriamine penta-acetic acid (Gd-EOB-DTPA) MRI for preoperative prediction of microvascular invasion (MVI) of hepatocellular carcinoma (HCC), and to identify patients who may benefit from the postoperative adjuvant transarterial chemoembolization (PA-TACE).

METHODS

A total of 260 eligible patients were retrospectively enrolled from three hospitals (140, 65, and 55 in training, standardized external, and non-standardized external validation cohort). Radiomics features and image characteristics were extracted from Gd-EOB-DTPA MRI image before hepatectomy for each lesion. In the training cohort, a radiomics nomogram which incorporated the radiomics signature and radiological predictors was developed. The performance of the radiomics nomogram was assessed with respect to discrimination calibration, and clinical usefulness with external validation. A score (m-score) was constructed to stratify the patients and explored whether it could accurately predict patient who benefit from PA-TACE.

RESULTS

A radiomics nomogram integrated with the radiomics signature, max-D(iameter)  > 5.1 cm, peritumoral low intensity (PTLI), incomplete capsule, and irregular morphology had favorable discrimination in the training cohort (AUC = 0.982), the standardized external validation cohort (AUC = 0.969), and the non-standardized external validation cohort (AUC = 0.981). Decision curve analysis confirmed the clinical usefulness of the novel radiomics nomogram. The log-rank test revealed that PA-TACE significantly decreased the early recurrence in the high-risk group (p = 0.006) with no significant effect in the low-risk group (p = 0.270).

CONCLUSIONS

The novel radiomics nomogram combining the radiomics signature and clinical radiological features achieved preoperative non-invasive MVI risk prediction and patient benefit assessment after PA-TACE, which may help clinicians implement more appropriate interventions.

CLINICAL RELEVANCE STATEMENT

Our radiomics nomogram could represent a novel biomarker to identify patients who may benefit from the postoperative adjuvant transarterial chemoembolization, which may help clinicians to implement more appropriate interventions and perform individualized precision therapies.

KEY POINTS

• The novel radiomics nomogram developed based on Gd-EOB-DTPA MRI achieved preoperative non-invasive MVI risk prediction. • An m-score based on the radiomics nomogram could stratify HCC patients and further identify individuals who may benefit from the PA-TACE. • The radiomics nomogram could help clinicians to implement more appropriate interventions and perform individualized precision therapies.

Roles and Molecular Mechanisms of Biomarkers in Hepatocellular Carcinoma with Microvascular Invasion: A Review

Hepatocellular carcinoma (HCC) being a leading cause of cancer-related death, has high associated mortality and recurrence rates. It has been of great necessity and urgency to find effective HCC diagnosis and treatment measures. Studies have shown that microvascular invasion (MVI) is an independent risk factor for poor prognosis after hepatectomy. The abnormal expression of biomacromolecules such as circ-RNAs, lncRNAs, STIP1, and PD-L1 in HCC patients is strongly correlated with MVI. Deregulation of several markers mentioned in this review affects the proliferation, invasion, metastasis, EMT, and anti-apoptotic processes of HCC cells through multiple complex mechanisms. Therefore, these biomarkers may have an important clinical role and serve as promising interventional targets for HCC. In this review, we provide a comprehensive overview on the functions and regulatory mechanisms of MVI-related biomarkers in HCC.

Establishment and Clinical Application of the Nomogram Related to Risk or Prognosis of Hepatocellular Carcinoma: A Review

Hepatocellular carcinoma (HCC) is the most prevalent primary liver malignancy, accounting for approximately 90% of all primary liver cancers, with high mortality and a poor prognosis. A large number of predictive models have been applied that integrate multiple clinical factors and biomarkers to predict the prognosis of HCC. Nomograms, as easy-to-use prognostic predictive models, are widely used to predict the probability of clinical outcomes. We searched PubMed with the keywords "hepatocellular carcinoma" and "nomogram", and 974 relative literatures were retrieved. According to the construction methodology and the real validity of the nomograms, in this study, 97 nomograms for HCC were selected in 77 publications. These 97 nomograms were established based on more than 100,000 patients, covering seven main prognostic outcomes. The research data of 56 articles are from hospital-based HCC patients, and 13 articles provided external validation results of the nomogram. In addition to AFP, tumor size, tumor number, stage, vascular invasion, age, and other common prognostic risk factors are included in the HCC-related nomogram, more and more biomarkers, including gene mRNA expression, gene polymorphisms, and gene signature, etc. were also included in the nomograms. The establishment, assessment and validation of these nomograms are also discussed in depth. This study would help clinicians construct and select appropriate nomograms to guide precise judgment and appropriate treatments.

A novel nomogram predicting the early recurrence of hepatocellular carcinoma patients after R0 resection

Background

Early tumor recurrence is one of the most significant poor prognostic factors for patients with HCC after R0 resection. The aim of this study is to identify risk factors of early recurrence, in addition, to develop a nomogram model predicting early recurrence of HCC patients.

Methods

A total of 481 HCC patients after R0 resection were enrolled and divided into a training cohort (n = 337) and a validation cohort (n = 144). Risk factors for early recurrence were determined based on Cox regression analysis in the training cohort. A nomogram incorporating independent risk predictors was established and validated.

Results

Early recurrence occurred in 37.8% of the 481 patients who underwent curative liver resection of HCC. AFP ≥ 400 ng/mL (HR: 1.662; P = 0.008), VEGF-A among 127.8 to 240.3 pg/mL (HR: 1.781, P = 0.012), VEGF-A > 240.3 pg/mL (HR: 2.552, P < 0.001), M1 subgroup of MVI (HR: 2.221, P = 0.002), M2 subgroup of MVI (HR: 3.120, P < 0.001), intratumor necrosis (HR: 1.666, P = 0.011), surgical margin among 5.0 to 10.0 mm (HR: 1.601, P = 0.043) and surgical margin < 5.0 mm (HR: 1.790, P = 0.012) were found to be independent risk factors for recurrence-free survival in the training cohort and were used for constructing the nomogram. The nomogram indicated good predictive performance with an AUC of 0.781 (95% CI: 0.729-0.832) and 0.808 (95% CI: 0.731-0.886) in the training and validation cohorts, respectively.

Conclusions

Elevated serum concentrations of AFP and VEGF-A, microvascular invasion, intratumor necrosis, surgical margin were independent risk factors of early intrahepatic recurrence. A reliable nomogram model which incorporated blood biomarkers and pathological variables was established and validated. The nomogram achieved desirable effectiveness in predicting early recurrence in HCC patients.

Preoperative MRI features for characterization of vessels encapsulating tumor clusters and microvascular invasion in hepatocellular carcinoma

PURPOSE

This study aimed to analyze imaging features based on preoperative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for the identification of vessels encapsulating tumor clusters (VETC)-microvascular invasion (MVI) in hepatocellular carcinoma (HCC), VM-HCC pattern.

METHODS

Patients who underwent hepatectomy and preoperative DCE-MRI between January 2015 and March 2021 were retrospectively analyzed. Clinical and imaging features related to VM-HCC (VETC + /MVI-, VETC-/MVI +, VETC + /MVI +) and Non-VM-HCC (VETC-/MVI-) were determined by multivariable logistic regression analyses. Early and overall recurrence were determined using the Kaplan-Meier survival curve. Indicators of early and overall recurrence were identified using the Cox proportional hazard regression model.

RESULTS

In total, 221 patients (177 men, 44 women; median age, 60 years; interquartile range, 52-66 years) were evaluated. The multivariable logistic regression analyses revealed fetoprotein > 400 ng/mL (odds ratio [OR] = 2.17, 95% confidence interval [CI] 1.07, 4.41, p = 0.033), intratumor vascularity (OR 2.15, 95% CI 1.07, 4.31, p = 0.031), and enhancement pattern (OR 2.71, 95% CI 1.17, 6.03, p = 0.019) as independent predictors of VM-HCC. In Kaplan-Meier survival analysis, intratumor vascularity was associated with early and overall recurrence (p < 0.05).

CONCLUSION

Based on DCE-MRI, intratumor vascularity can be used to characterize VM-HCC and is of prognostic significance for recurrence in patients with HCC.

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.

Analysis of Related Risk Factors of Microvascular Invasion in Hepatocellular Carcinoma

Objective

To forecast the onset of microvascular invasion (MVI) in patients with hepatoma by evaluating the preoperative aspartate aminotransferase-to-platelet ratio index (APRI), alpha-fetoprotein (AFP), neutrophil-to-lymphocyte ratio (NLR), and other clinicopathological data.

Methods

In this study, we retrospectively analysed the clinical data of 62 patients who received radical surgery for hepa toma from 2019 to 2021. Patients were separated into the MVI-negative group and the MVI-positive group according to the postoperative pathological diagnosis. The relationships between MVI and NLR, APRI, AFP, tumor size, and other clinical data were assessed using the univariate analysis, receiver operating characteristic (ROC) curve, least absolute shrinkage and selection operator (LASSO) analysis, and logistic analysis.

Results

The ROC curve determined that the cutoff values of NLR, platelet-to-lymphocyte ratio (PLR), and APRI were 1.520, 98, and 0.275, respectively. The univariate analysis showed that the MVI-positive result was associated with five factors: tumor size (χ² = 10.620, p = 0.001), AFP (χ² = 10.524, p = 0.001), Edmondson grade (χ² = 20.736, p < 0.001), NLR (χ² = 8.744, p = 0.003), and APRI (χ² = 4.849, p = 0.028). The LASSO analysis indicated that the risk factors were the number of tumors, PLR, APRI, NLR, AFP, Edmondson grade, and tumor size. The multivariate logistic regression analysis showed that NLR ≥ 1.520 (OR 11.119, p = 0.006), APRI ≥ 0.275 (OR 12.515, p = 0.009), AFP ≥ 200 μg/mL (OR 7.823, p = 0.016), and tumor size > 3 cm (OR 7.689, p = 0.022) were independent risk factors for MVI in patients with hepatoma.

Conclusion

Preoperative NLR, APRI, AFP, and tumor size are reliable indicators for predicting the appearance of MVI in patients with hepatoma and are of great value in making detailed and reliable treatment protocols for these patients before surgery.

Prognostic Analysis of Postoperative Survival for Ruptured Hepatocellular Carcinoma with or without Cirrhosis

Background and Aims

Conflicting results are often observed in the prognosis of patients with ruptured hepatocellular carcinoma (rHCC), and there are currently very few studies on the long-term postoperative outcomes of ruptured hepatocellular carcinoma patients. This study aimed to distinguish between the postoperative prognosis of rHCC patients with cirrhosis (rHCC-C) and those without cirrhosis (rHCC-NC) using some serum markers.

Methods

We collected the data of 151 rHCC patients treated at our centers from January 2010 to March 2021. 62 had no cirrhosis, and 89 had cirrhosis. The prognosis of rHCC-C and rHCC-NC groups was compared using the Kaplan-Meier method. We used multivariate Cox regression to analyze prognostic factors in rHCC patients, and subgroup analysis was performed on the two groups of patients.

Results

The long-term prognosis of rHCC-NC patients was better than that of rHCC-C patients. Tumor diameter, Barcelona clinic liver cancer (BCLC) stage, HBsAg, positive Hepatitis C virus (HCV) antibodies, elevated creatinine, and elevated T-bilirubin were prognostic factors for overall survival (OS) in rHCC-C patients. However, only alpha-fetoprotein (AFP) > 92 ng/mL was a prognostic factor for OS in rHCC-NC patients. In noncirrhotic patients, HBsAg positivity was only associated with OS. Similarly, the presence or absence of microvascular invasion (MVI) also had different results in the two groups.

Conclusions

There are differences in serum alpha-fetoprotein (AFP) levels, the presence of microvascular invasion (MVI), and HBsAg positivity between rHCC-C and rHCC-NC patients, indicating that the analysis of these prognostic factors may help improve the management of rHCC patients and provide a direction for future treatment options.