Preoperative PET-CT is useful for predicting recurrent extrahepatic metastasis of hepatocellular carcinoma after resection

Radiomics and machine learning based on preoperative MRI for predicting extrahepatic metastasis in hepatocellular carcinoma patients treated with transarterial chemoembolization

Purpose

To develop and validate a radiomics machine learning (Rad-ML) model based on preoperative MRI to predict extrahepatic metastasis (EHM) in hepatocellular carcinoma (HCC) patients receiving transarterial chemoembolization (TACE) treatment.

Methods

A total of 355 HCC patients who received multiple TACE procedures were split at random into a training set and a test set at a 7:3 ratio. Radiomic features were calculated from tumor and peritumor in arterial phase and portal venous phase, and were identified using intraclass correlation coefficient, maximal relevance and minimum redundancy, and least absolute shrinkage and selection operator techniques. Cox regression analysis was employed to determine the clinical model. The best-performing algorithm among eight machine learning methods was used to construct the Rad-ML model. A nomogram combining clinical and Rad-ML parameters was used to develop a combined model. Model performance was evaluated using C-index, decision curve analysis, calibration plot, and survival analysis.

Results

In clinical model, elevated neutrophil to lymphocyte ratio and alpha-fetoprotein were associated with faster EHM. The XGBoost-based Rad-ML model demonstrated the best predictive performance for EHM. When compared to the clinical model, both the Rad-ML model and the combination model performed better (C-indexes of 0.61, 0.85, and 0.86 in the training set, and 0.62, 0.82, and 0.83 in the test set, respectively). However, the combined model's and the Rad-ML model's prediction performance did not differ significantly. The most influential feature was peritumoral waveletHLL_firstorder_Minimum in AP, which exhibited an inverse relationship with EHM risk.

Conclusions

Our study suggests that the preoperative MRI-based Rad-ML model is a valuable tool to predict EHM in HCC patients treated with TACE.

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

Introduction

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

Methods

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

Results

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

Conclusion

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

Advances in Immunotherapy for Hepatocellular Carcinoma

Immune checkpoint inhibitors (ICIs) aim to induce immune responses against tumors and are less likely to develop drug resistance than molecularly targeted drugs. In addition, they are characterized by a long-lasting antitumor effect. However, since its effectiveness depends on the tumor’s immune environment, it is essential to understand the immune environment of hepatocellular carcinoma to select ICI therapeutic indications and develop biomarkers. A network of diverse cellular and humoral factors establishes cancer immunity. By analyzing individual cases and classifying them from the viewpoint of tumor immunity, attempts have been made to select the optimal therapeutic drug for immunotherapy, including ICIs. ICI treatment is discussed from the viewpoints of immune subclass of HCC, Wnt/β-catenin mutation, immunotherapy in NASH-related HCC, the mechanism of HPD onset, and HBV reactivation.

Pre-operative MRI features predict early post-operative recurrence of hepatocellular carcinoma with different degrees of pathological differentiation

PURPOSE

To investigate the value of pre-operative gadoxetate disodium (Gd-EOB-DTPA) enhanced MRI predicting early post-operative recurrence (< 2 years) of hepatocellular carcinoma (HCC) with different degrees of pathological differentiation.

METHODS

Retrospective analysis of pre-operative MR imaging features of 177 patients diagnosed as suffering from HCC and that underwent radical resection. Multivariate logistic regression assessment was adopted to assess predictors for HCC recurrence with different degrees of pathological differentiation. The area under the curve (AUC) of receiver operating characteristics (ROC) was utilized to assess the diagnostic efficacy of the predictors.

RESULTS

Among the 177 patients, 155 (87.5%) were males, 22 (12.5%) were females; the mean age was 49.97 ± 10.71 years. Among the predictors of early post-operative recurrence of highly-differentiated HCC were an unsmooth tumor margin and an incomplete/without tumor capsule (p = 0.037 and 0.033, respectively) whereas those of early post-operative recurrence of moderately-differentiated HCC were incomplete/without tumor capsule, peritumoral enhancement along with peritumoral hypointensity (p = 0.006, 0.046 and 0.004, respectively). The predictors of early post-operative recurrence of poorly-differentiated HCC were peritumoral enhancement, peritumoral hypointensity, and tumor thrombosis (p = 0.033, 0.006 and 0.021, respectively). The AUCs of the multi-predictor diagnosis of early post-operative recurrence of highly-, moderately-, and poorly-differentiated HCC were 0.841, 0.873, and 0.875, respectively. The AUCs of the multi-predictor diagnosis were each higher than for those predicted separately.

CONCLUSIONS

The imaging parameters for predicting early post-operative recurrence of HCC with different degrees of pathological differentiation were different and combining these predictors can improve the diagnostic efficacy of early post-operative HCC recurrence.

Value of 18F-FDG PET/MRI in the early evaluation of treatment response following radiofrequency ablation of liver cancer in a rabbit model

PURPOSE

To test the hypothesis that ¹⁸F-fluorodeoxyglucose positron emission tomography and MRI (18F-FDG PET/MRI) can detect early residual tumor following radiofrequency ablation (RFA) of liver cancer using a VX2 tumor model.

METHODS

Twenty-four rabbits with VX2 liver tumors were randomly divided into three groups (n = 8/group): group 1 without RFA treatment, group 2 with complete ablation, and group 3 with partial ablation. ¹⁸F-FDG PET/MRI scan was obtained in three animal groups within 2 hours post-RFA. The maximum standardized uptake value (SUVmax) of non-treated liver tumor, benign peri-ablational enhancement (BPE), residual tumor, ablated tumor, adjacent liver parenchyma, and mean SUV of normal liver were measured, respectively. The ratios of SUVmax for these targets to mean SUV of normal liver (TNR) were calculated and statistically compared.

RESULTS

The mean TNR of non-treated liver tumors in group 1 was significantly greater than that of adjacent liver parenchyma (8.68 ± 0.71 vs 1.89 ± 0.26, p < 0.001). In group 2, the mean TNR of BPE was significantly greater than that of adjacent liver parenchyma (2.85 ± 0.20 vs 1.86 ± 0.25, p < 0.001). In group 3, the mean TNR of residual tumor was significantly greater than that of BPE (8.64 ± 0.59 vs 2.78 ± 0.23, p < 0.001), which was significantly greater than that of completely ablated tumor (2.78 ± 0.23 vs 0.50 ± 0.06, p < 0.001).

CONCLUSION

¹⁸F-FDG PET/MRI may serve as a promising imaging tool for early detection of viable residual tumors due to incomplete tumor ablation.

Novel model combining contrast-enhanced ultrasound with serology predicts hepatocellular carcinoma recurrence after hepatectomy

BACKGROUND

Surgery is the primary curative option in patients with hepatocellular carcinoma (HCC). However, recurrence within 2 years is observed in 30%–50% of patients, being a major cause of mortality.

AIM

To construct and verify a non-invasive prediction model combining contrast-enhanced ultrasound (CEUS) with serology biomarkers to predict the early recurrence of HCC.

METHODS

Records of 744 consecutive patients undergoing first-line curative surgery for HCC in one institution from 2016–2018 were reviewed, and 292 local patients were selected for analysis. General characteristics including gender and age, CEUS liver imaging reporting and data system (LIRADS) parameters including wash-in time, wash-in type, wash-out time, and wash-out type, and serology biomarkers including alanine aminotransferase, aspartate aminotransferase, platelets, and alpha-fetoprotein (AFP) were collected. Univariate analysis and multivariate Cox proportional hazards regression model were used to evaluate the independent prognostic factors for tumor recurrence. Then a nomogram called CEUS model was constructed. The CEUS model was then used to predict recurrence at 6 mo, 12 mo, and 24 mo, the cut-off value was calculate by X-tile, and each C-index was calculated. Then Kaplan-Meier curve was compared by log-rank test. The calibration curves of each time were depicted.

RESULTS

A nomogram predicting early recurrence (ER), named CEUS model, was formulated based on the results of the multivariate Cox regression analysis. This nomogram incorporated tumor diameter, preoperative AFP level, and LIRADS, and the hazard ratio was 1.123 (95% confidence interval [CI]: 1.041-1.211), 1.547 (95%CI: 1.245-1.922), and 1.428 (95%CI: 1.059-1.925), respectively. The cut-off value at 6 mo, 12 mo, and 24 mo was 100, 80, and 50, and the C-index was 0.748 (95%CI: 0.683-0.813), 0.762 (95%CI: 0.704-0.820), and 0.762 (95%CI: 0.706-0.819), respectively. The model showed satisfactory results, and the calibration at 6 mo was desirable; however, the calibration at 12 and 24 mo should be improved.

CONCLUSION

The CEUS model enables the well-calibrated individualized prediction of ER before surgery and may represent a novel tool for biomarker research and individual counseling.

HCC: role of pre- and post-treatment tumor biology in driving adverse outcomes and rare responses to therapy

Liver cancer is the fastest-growing cause of cancer deaths in the United States and is a complex disease. The response of hepatocellular carcinoma (HCC) to treatment can be variable. Predicting response to determine the most effective therapy is an active area of research. Our understanding of underlying factors which drive response to therapy is continually increasing. As more therapies for the treatment of this disease evolve, it is crucial to identify and match the ideal therapy for a particular tumor and patient. The potential predicative imaging features of tumor behavior, while of research interest, have not been validated for clinical use and do not currently inform treatment planning. If further validated though, prognostic features may be used in the future to personalize treatment plans according to individual patients and tumors. Unexpected post-treatment responses such as potential tumor biology changes and abscopal effect which are important to be aware of. This review is intended for radiologists who routinely interpret post treatment HCC imaging and is designed to increase their cognizance about how HCC tumor biology drives response to therapy and explore rare responses to therapy.