Evaluation and Prediction of Treatment Response for Hepatocellular Carcinoma

Deep learning of pretreatment multiphase CT images for predicting response to lenvatinib and immune checkpoint inhibitors in unresectable hepatocellular carcinoma

Objectives

Combination therapy of lenvatinib and immune checkpoint inhibitors (CLICI) has emerged as a promising approach for managing unresectable hepatocellular carcinoma (HCC). However, the response to such treatment is observed in only a subset of patients, underscoring the pressing need for reliable methods to identify potential responders.

Materials & methods

This was a retrospective analysis involving 120 patients with unresectable HCC. They were divided into training (n = 72) and validation (n = 48) cohorts. We developed an interpretable deep learning model using multiphase computed tomography (CT) images to predict whether patients will respond or not to CLICI treatment, based on the Response Evaluation Criteria in Solid Tumors, version 1.1 (RECIST v1.1). We evaluated the models' performance and analyzed the impact of each CT phase. Critical regions influencing predictions were identified and visualized through heatmaps.

Results

The multiphase model outperformed the best biphase and uniphase models, achieving an area under the curve (AUC) of 0.802 (95% CI = 0.780-0.824). The portal phase images were found to significantly enhance the model's predictive accuracy. Heatmaps identified six critical features influencing treatment response, offering valuable insights to clinicians. Additionally, we have made this model accessible via a web server at http://uhccnet.com/ for ease of use.

Conclusions

The integration of multiphase CT images with deep learning-generated heatmaps for predicting treatment response provides a robust and practical tool for guiding CLICI therapy in patients with unresectable HCC.

Efficacy of doxorubicin and lipiodol therapy by trans-arterial chemoembolization in hepatocellular carcinoma Egyptian patients and relation to genetic polymorphisms

BACKGROUND

Genetic polymorphisms play a crucial role in predicting treatment efficacy in patients with hepatocellular carcinoma (HCC). This study aims to evaluate the response to Transarterial Chemoembolization (TACE) in relation to the genetic polymorphisms of interleukin 28B (IL28B) and angiopoietin-2 (ANGPT2) in HCC patients.

RESEARCH DESIGN AND METHODS

Prospective cohort study conducted on 104 eligible HCC Egyptian patients who underwent TACE using doxorubicin and lipiodol. Genotyping of the IL28B and ANGPT2 genes was performed with laboratory data analysis.

RESULTS

At baseline IL28B rs12979860 genotypes C/T, C/C and T/T appeared in 43.9%, 34.6% and 21.5% while ANGPT2 rs55633437 genotypes C/C, C/A and A/A found in 71.03%, 28.04% and 0.93% of patients respectively. After one month of therapy, 51.4% of patients achieved a complete response. There was a significant difference in relation to IL28B rs12979860 genotypes (p = 0.017) whereas ANGPT2 rs55633437 genotypes (p = 0.432) showed no significant difference in patient response after one month of TACE.

CONCLUSION

This study demonstrates the effectiveness of TACE in Egyptian HCC patients, as evidenced by low recurrence rates. Furthermore, the IL28B rs12979860 (C/T) gene may be associated with the efficacy and prognosis of TACE treatment in HCC Egyptian patients.

TRIAL REGISTRATION

The trial is registered at ClinicalTrials.gov (CT.gov identifier: NCT05291338).

Hepatocellular Carcinoma: The Evolving Role of Systemic Therapies as a Bridging Treatment to Liver Transplantation

Hepatocellular carcinoma (HCC) is the third most common cause of cancer-related deaths. Classically, liver transplantation (LT) can be curative for HCC tumors within the Milan criteria. Bridging strategies to reduce the dropouts from LT waiting lists and/or to downstage patients who are beyond the Milan criteria are widely utilized. We conducted a literature-based review to evaluate the role of systemic therapies as a bridging treatment to liver transplantation (LT) in HCC patients. Tyrosine kinase inhibitors (TKIs) can be used as a systemic bridging therapy to LT in patients with contraindications for locoregional liver-directed therapies. Immune checkpoint inhibitor (ICI) treatment can be utilized either as a monotherapy or as a combination therapy with bevacizumab or TKIs prior to LT. Acute rejection after liver transplantation is a concern in the context of ICI treatment. Thus, a safe ICI washout period before LT and cautious post-LT immunosuppression strategies are required to reduce post-LT rejections and to optimize clinical outcomes. Nevertheless, prospective clinical trials are needed to establish definitive conclusions about the utility of systemic therapy as a bridging modality prior to LT in HCC patients.

Individual Participant Data Meta-Analysis of LR-5 in LI-RADS Version 2018 versus Revised LI-RADS for Hepatocellular Carcinoma Diagnosis

Background A simplification of the Liver Imaging Reporting and Data System (LI-RADS) version 2018 (v2018), revised LI-RADS (rLI-RADS), has been proposed for imaging-based diagnosis of hepatocellular carcinoma (HCC). Single-site data suggest that rLI-RADS category 5 (rLR-5) improves sensitivity while maintaining positive predictive value (PPV) of the LI-RADS v2018 category 5 (LR-5), which indicates definite HCC. Purpose To compare the diagnostic performance of LI-RADS v2018 and rLI-RADS in a multicenter data set of patients at risk for HCC by performing an individual patient data meta-analysis. Materials and Methods Multiple databases were searched for studies published from January 2014 to January 2022 that evaluated the diagnostic performance of any version of LI-RADS at CT or MRI for diagnosing HCC. An individual patient data meta-analysis method was applied to observations from the identified studies. Quality Assessment of Diagnostic Accuracy Studies version 2 was applied to determine study risk of bias. Observations were categorized according to major features and either LI-RADS v2018 or rLI-RADS assignments. Diagnostic accuracies of category 5 for each system were calculated using generalized linear mixed models and compared using the likelihood ratio test for sensitivity and the Wald test for PPV. Results Twenty-four studies, including 3840 patients and 4727 observations, were analyzed. The median observation size was 19 mm (IQR, 11-30 mm). rLR-5 showed higher sensitivity compared with LR-5 (70.6% [95% CI: 60.7, 78.9] vs 61.3% [95% CI: 45.9, 74.7]; P < .001), with similar PPV (90.7% vs 92.3%; P = .55). In studies with low risk of bias (n = 4; 1031 observations), rLR-5 also achieved a higher sensitivity than LR-5 (72.3% [95% CI: 63.9, 80.1] vs 66.9% [95% CI: 58.2, 74.5]; P = .02), with similar PPV (83.1% vs 88.7%; P = .47). Conclusion rLR-5 achieved a higher sensitivity for identifying HCC than LR-5 while maintaining a comparable PPV at 90% or more, matching the results presented in the original rLI-RADS study. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Sirlin and Chernyak in this issue.