Atezolizumab-Bevacizumab is recommended as first-line treatment for advanced/unresectable hepatocellular carcinoma (HCC). However, validated clinical or radiological systems able to predict early treatment response or identify non- responsive patients at risk of early therapeutic failure are currently lacking. We developed a multimodal AI model to predict 6-month progression-free survival (PFS)
Celsa, C., Contino, S., Cannella, R., Ciccia, R., Crescimanno, G., Cruciata, L., et al. (2025). 354P A multimodal deep learning model for prediction of early progression in patients with advanced hepatocellular carcinoma treated with atezolizumab-bevacizumab. In Abstract Book of the ESMO AI & Digital Oncology Congress 2025, 12-14 November 2025 [10.1016/j.esmorw.2025.100550].
354P A multimodal deep learning model for prediction of early progression in patients with advanced hepatocellular carcinoma treated with atezolizumab-bevacizumab
Celsa, C.
;Contino, S.
;Cannella, R.;Ciccia, R.;Crescimanno, G.;Cruciata, L.;Restuccia, S.;Giusino, G.;Calascibetta, S.;Cusimano, G.;Quartararo, A.;Cabibbo, G.;Cirrincione, G.;Pirrone, R.;
2025-11-01
Abstract
Atezolizumab-Bevacizumab is recommended as first-line treatment for advanced/unresectable hepatocellular carcinoma (HCC). However, validated clinical or radiological systems able to predict early treatment response or identify non- responsive patients at risk of early therapeutic failure are currently lacking. We developed a multimodal AI model to predict 6-month progression-free survival (PFS)
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