ArticleCancer imaging : the official publication of the International Cancer Imaging Society2025
Histopathologic deep learning model for predicting tumor response to hepatic arterial infusion chemotherapy plus TKIs and ICIs in large hepatocellular carcinoma.
Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- A simplified MRI‑based risk score and nomogram to predict initial objective response in unresectable hepatocellular carcinoma treated with HAIC, targeted therapy, and immunotherapy: a multicenter study.Abdominal radiology (New York) · 2026Article
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10 authors.
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Abstract
backgroundWhile triplet therapy (HTI), which combines hepatic arterial infusion chemotherapy (HAIC) with tyrosine kinase inhibitors and immune checkpoint inhibitors, is widely used in the treatment of large hepatocellular carcinoma (HCC), there are few reports about its efficacy versus HAIC, and no reliable methods are available for promptly predicting HTI response.
methodsThis study included treatment-naïve patients with large HCCs (> 5 cm in diameter) from two centers between January 2017 and December 2022. Objective response rate (ORR), progression-free survival (PFS), and overall survival (OS) were compared between the HTI and HAIC groups. To efficiently predict HTI response, available pre-treatment H&E-stained biopsy slides of HCC patients were collected to develop deep-learning models.
resultsCompared to group HAIC (n = 97), group HTI (n = 281) showed an ORR (54.45% vs. 21.65%), PFS (median, 10.9 vs. 4.9 months), and OS (median, 25.0 vs. 12.0 months). No significant differences in ORR were observed within the HTI group across different BCLC stages. A deep learning model, termed the Hepatocellular Carcinoma Artificial Intelligence Prediction Model (HAIM), was developed using pathological slides of HTI-treated patients (n = 194). HAIM achieved AUC scores of 0.778 (entire testing set), 0.735 (internal testing set), and 0.853 (external testing set).
conclusionsIntegrating TKIs and ICIs with HAIC significantly improved ORR, PFS, and OS in all stages of large HCCs. HAIM, derived from histopathological images of the biopsy, showed potential clinical aid for predicting HTI response, providing a novel tool for personalized management of HCC.
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