Practice guidelines for the pathological diagnosis of primary liver cancer: 2015 update

Histopathological diagnosis of microvascular invasion in hepatocellular carcinoma: Is it reliable?

BACKGROUND

Microvascular invasion (MVI) is a critical prognostic factor for postoperative hepatocellular carcinoma recurrence, but the reliability of its current pathological diagnosis remains uncertain.

AIM

To evaluate the accuracy of current 7-point sampling methods and propose an optimal pathological protocol using whole-mount slide imaging (WSI) for better MVI detection.

METHODS

We utilized 40 New Zealand white rabbits to establish VX2 liver tumor models. The entire tumor-containing liver lobe was subsequently obtained, following which five different sampling protocols (A-E) were employed to evaluate the detection rate, accuracy, quantity, and distribution of MVI, with the aim of identifying the optimal sampling method.

RESULTS

VX2 liver tumor models were successfully established in 37 rabbits, with an incidence of MVI of 81.1% (30/37). The detection rates [27% (10/37), 43% (16/37), 62% (23/37), 68% (25/37), and 93% (14/15)] and quantity (15, 36, 107, 125, and 395) of MVI increased significantly from protocols A to E. The distribution of MVI showed fewer MVIs farther away from the tumor, but the percentage of MVI detected quantity gradually increased from 6.7% to 48.3% in the distant nonneoplastic liver tissue from protocols A to E. Protocol C was identified as the optimal sampling method by comparing them in sequence. The sampling protocol of three consecutive interval WSIs at the tumor center (WSI₃) was further screened to determine the optimal number of WSIs. Protocol A (7-point sampling method) exhibited only 46% accuracy and a high false-negative rate of 67%. Notably, the WSI₃ protocol improved the accuracy to 78% and decreased the false-negative rate to 27%.

CONCLUSION

The current 7-point sampling method has a high false-negative rate in MVI detection. In contrast, the WSI₃ protocol provides a practical and effective approach to improve MVI diagnostic accuracy, which is crucial for hepatocellular carcinoma diagnosis and treatment planning.

Association Between MRI-Based Radiomics Features and Regional Lymph Node Metastasis in Intrahepatic Cholangiocarcinoma and Its Clinical Outcome

BACKGROUND

Regional lymph node metastasis (LNM) assessment is crucial for predicting intrahepatic cholangiocarcinoma (iCCA) prognosis. However, imaging assessment has limitations for identifying LNM.

PURPOSE

To investigate the association between MRI radiomics features, regional LNM status, and prognosis in iCCA.

STUDY TYPE

Retrospective.

SUBJECTS

Two hundred ninety-six patients (male = 197) with surgically confirmed iCCA.

FIELD STRENGTH/SEQUENCE

1.5 T and 3.0 T. DWI, T2WI, and contrast-enhanced T1WI.

ASSESSMENT

Clinical information, radiologic, and MRI-based radiomics features associated with LNM status were collected to establish models. Performance of MRI, PET/CT, and the combined LNM models were compared in training (N = 207) and test (N = 89) datasets. Overall survival (OS) was compared based on LNM status.

STATISTICAL TESTS

The independent features were selected by 5-fold cross-validation. The performance of MRI, PET/CT, and the models was evaluated using the area under receiver operating characteristic curve (AUC). Univariable and multivariable Cox regression were used to identify independent variables for OS. Kaplan-Meier curves were compared with the log-rank test between LNM positive and negative groups. P < 0.05 was considered statistically significant.

RESULTS

Intrahepatic duct dilatation, enhancement pattern, and CA19-9 were independent clinicoradiologic features. The radiomics model was constructed by the independent radiomics features extracted from T2WI and delay phase T1WI. The combined LNM model showed AUC of 0.888, 0.884, and 0.811 in training, validation, and test cohorts with a positive net benefit. PET/CT exhibited similar sensitivity to the combined LNM model (0.750 vs. 0.733, P > 0.999) while the combined LNM model showed higher specificity (0.703 vs. 0.630, P = 0.039) in the test cohort. High risk of regional LNM was significantly associated with worse OS (median: 24 months) than low risk (median: 30 months, P < 0.0001).

DATA CONCLUSIONS

The combined LNM model has the strongest correlation with LNM status for mass-forming iCCA patients.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 2.

Correlation Between Dynamic Contrast-Enhanced CT Imaging Signs and Differentiation Grade and Microvascular Invasion of Hepatocellular Carcinoma

Objective

This study aimed to investigate how dynamic contrast-enhanced CT imaging signs correlate with the differentiation grade and microvascular invasion (MVI) of hepatocellular carcinoma (HCC), and to assess their predictive value for MVI when combined with clinical characteristics.

Methods

We conducted a retrospective analysis of clinical data from 232 patients diagnosed with HCC at our hospital between 2021 and 2022. All patients underwent preoperative enhanced CT scans, laboratory tests, and postoperative pathological examinations. Among the 232 patients, 89 were identified as MVI-positive and 143 as MVI-negative. Regarding tumor differentiation, 56 patients were well-differentiated, 145 moderately, and 31 poorly. Multivariate logistic regression analysis was employed to establish a prediction model for variables showing significant differences. Additionally, the diagnostic performance of various indicators were evaluated using ROC analysis.

Results

Among the qualitative data, significant differences (P<0.05) were observed between the MVI-positive and MVI-negative groups in 5 items such as peritumoral enhancement. In terms of quantitative data, the MVI-positive group exhibited higher maximum tumor length, AST, ALT, AFP levels and the ALBI score (P<0.05). Conversely, CT values in the arterial phase (AP), portal venous phase (PVP), and PT levels were lower in the MVI-positive group (P<0.05). Multivariate Logistic regression analysis identified ALBI score, PT level, CT value in PVP, and tumor capsule as independent risk factors for MVI occurrence (AUC: 0.71, 0.58, 0.66, and 0.60). The combined diagnostic AUC value was 0.82 (95% CI: 0.76-0.87). Significant differences were found among different differentiation grade groups in 10 items such as non-smooth tumor margin (P<0.05).

Conclusion

Preoperative dynamic contrast-enhanced CT examination in patients with HCC can be utilized to predict the presence of MVI. When combined with clinical characteristics, these imaging signs demonstrate good predictive performance for MVI status. Furthermore, this approach has significant implications for determining the differentiation grade of tumors.

Significance of anatomical resection and wide surgical margin for HCC patients with MVI undergoing laparoscopic hepatectomy: A multicenter study

OBJECTIVE

To investigate the impact of surgical resection margin and hepatic resection type on prognosis and compare their prognostic significance on patients with hepatocellular carcinoma (HCC) with or without microvascular invasion (MVI) who underwent laparoscopic liver resection (LLR).

METHODS

A retrospective analysis was conducted on 320 patients with HCC who underwent LLR. According to the grading of MVI, patients were classified as M0, M1 and M2. Patients were divided into the anatomical resection (AR) and nonanatomical resection (NAR) groups according to the hepatic resection type. Survival and Cox regression analyses were performed to explore the effects of AR and NAR, wide and narrow resection margin on overall survival (OS) and time to recurrence (TTR).

RESULTS

In the whole cohort, narrow resection margin was an independent risk factor for OS and TTR, whereas NAR was not. Subgroup analysis showed that narrow resection margin and NAR were both independent risk factors for OS and TTR in HCC patients with MVI. The 5-year OS and TTR rates of the two groups (NAR-wide resection margin and AR-narrow resection margin) with M1 were 85.3 % versus 62 % and 34.4 % versus 60.2 %. Similarly, the 5-year OS and TTR rates of the two groups (NAR-wide resection margin and AR-narrow resection margin) with M2 were 80.2 % versus 47.9 % and 30.8 % versus 64.8 %.

CONCLUSIONS

Anatomical hepatectomy and wide resection margin were independent protective factors for HCC patients with MVI receiving LLR. Nonetheless, wide resection margin had a greater impact on prognosis than anatomical hepatectomy.

An MRI-Based Radiomics Model for Preoperative Prediction of Microvascular Invasion and Outcome in Intrahepatic Cholangiocarcinoma

PURPOSE

Microvascular invasion (MVI) serves as a significant predictor of poor prognosis in intrahepatic cholangiocarcinoma (ICC). This study aims to establish a comprehensive model utilizing MR radiomics for preoperative MVI status stratification and outcome prediction in ICC patients.

MATERIALS AND METHODS

A total of 249 ICC patients were randomly assigned to training and validation cohorts (174:75), along with a time-independent test cohort consisting of 47 ICC patients. Independent clinical and imaging predictors were identified by univariate and multivariate logistic regression analyses. The radiomic model was developed based on robust radiomic features extracted using a logistic regression classifier. The predictive efficacy of the models was evaluated by receiver operating characteristic curves, calibration curves and decision curves. Multivariate Cox analysis identified the independent risk factors for recurrence-free survival and overall survival, Kaplan-Meier curves were plotted, and a nomogram was used to visualize the predictive model.

RESULTS

The imaging model included tumor size and intrahepatic duct dilatation. The radiomics model comprised 25 stable radiomics features. The Imaging-Radiomics (IR) model, which integrates independent predictors and robust radiomics features, demonstrates desirable performance for MVI (AUCtraining= 0.890, AUCvalidation= 0.885 and AUCtest= 0.815). The calibration curve and decision curve validate the clinical utility. Preoperative MVI prediction based on IR model demonstrated comparable accuracy in MVI stratification and outcome prediction when compared to histological MVI.

CONCLUSION

The IR model and the nomogram based on IR model-predicted MVI status may serve as potential tools for MVI status stratification and outcome prediction in ICC patients preoperatively.

Evaluating microvascular invasion in hepatitis B virus-related hepatocellular carcinoma based on contrast-enhanced computed tomography radiomics and clinicoradiological factors

BACKGROUND

Microvascular invasion (MVI) is a significant indicator of the aggressive behavior of hepatocellular carcinoma (HCC). Expanding the surgical resection margin and performing anatomical liver resection may improve outcomes in patients with MVI. However, no reliable preoperative method currently exists to predict MVI status or to identify patients at high-risk group (M2).

AIM

To develop and validate models based on contrast-enhanced computed tomography (CECT) radiomics and clinicoradiological factors to predict MVI and identify M2 among patients with hepatitis B virus-related HCC (HBV-HCC). The ultimate goal of the study was to guide surgical decision-making.

METHODS

A total of 270 patients who underwent surgical resection were retrospectively analyzed. The cohort was divided into a training dataset (189 patients) and a validation dataset (81) with a 7:3 ratio. Radiomics features were selected using intra-class correlation coefficient analysis, Pearson or Spearman's correlation analysis, and the least absolute shrinkage and selection operator algorithm, leading to the construction of radscores from CECT images. Univariate and multivariate analyses identified significant clinicoradiological factors and radscores associated with MVI and M2, which were subsequently incorporated into predictive models. The models' performance was evaluated using calibration, discrimination, and clinical utility analysis.

RESULTS

Independent risk factors for MVI included non-smooth tumor margins, absence of a peritumoral hypointensity ring, and a high radscore based on delayed-phase CECT images. The MVI prediction model incorporating these factors achieved an area under the curve (AUC) of 0.841 in the training dataset and 0.768 in the validation dataset. The M2 prediction model, which integrated the radscore from the 5 mm peritumoral area in the CECT arterial phase, α-fetoprotein level, enhancing capsule, and aspartate aminotransferase level achieved an AUC of 0.865 in the training dataset and 0.798 in the validation dataset. Calibration and decision curve analyses confirmed the models' good fit and clinical utility.

CONCLUSION

Multivariable models were constructed by combining clinicoradiological risk factors and radscores to preoperatively predict MVI and identify M2 among patients with HBV-HCC. Further studies are needed to evaluate the practical application of these models in clinical settings.

Three-Dimensional Multifrequency MR Elastography for Microvascular Invasion and Prognosis Assessment in Hepatocellular Carcinoma

BACKGROUND

Pretreatment identification of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) is important when selecting treatment strategies.

PURPOSE

To improve models for predicting MVI and recurrence-free survival (RFS) by developing nomograms containing thre