This study is a multicenter retrospective clinical research, led by the First Affiliated Hospital of Wenzhou Medical University, and jointly conducted by other sub-centers. The aim is to develop an non-invasive artificial intelligence system for predicting the response and clinical outcomes of patients with unresectable hepatocellular carcinoma (uHCC) to the treatment with atezolizumab combined with bevacizumab (T+A). In response to the clinical situation where approximately half of uHCC patients do not respond to the standard T+A therapy and traditional invasive biopsy is unable to fully reflect the heterogeneity of the tumor microenvironment, this study plans to retrospectively collect the data of 400 patients who met the inclusion and exclusion criteria from January 2020 to November 2025. The study will systematically summarize multi-dimensional data such as enhanced CT images within one month before treatment, baseline characteristics, serum markers, liver disease factors, and tumor stage. By integrating these clinical features with deep learning imageomics features extracted from images, the research team is dedicated to constructing and validating a safe, non-invasive, and reproducible prediction model, with the aim of achieving precise identification of the benefit population before implementing immunotherapy combined with anti-angiogenic treatment, and providing a powerful intelligent tool support for optimizing clinical treatment decisions and improving patient survival prognosis.

Inclusion Criteria:

• (i) Clinical or pathological diagnosis of HCC;
• (ii) Administration of atezolizumab-bevacizumab treatment;
• (iii) At least 18 years old.

Exclusion Criteria:

• (i) Lack of key clinical data (laboratory test results), or lack of enhanced CT images taken within one month before treatment;
• (ii) Comorbid with other malignant tumors;
• (iii) PS score > 2 or Child-Pugh score > 7;
• (iv) Unable to evaluate tumor response;
• (v) Loss to follow-up.

unresectable HCC patients