The application and progress of AI-based image analysis in tumor organoid research.

The development of preclinical models that recapitulate the physiological and pathological features of human tumors remains a central challenge in cancer research. Advances in cell biology have enabled the generation of three-dimensional tumor organoids, which closely mirror patient-specific therapeutic responses and facilitate the study of disease mechanisms. However, the trend of these models necessitates a shift from traditional, invasive analytical methods toward non-invasive, high-throughput imaging approaches. Here, we review the current state of tumor organoid culture and the emerging application of artificial intelligence (AI) in their evaluation. We discuss how AI-driven technologies are revolutionizing the analysis of fluorescence imaging, viability assessments, and dynamic cell tracking, thereby overcoming the limitations of manual interpretation. Finally, we provide a perspective on how integrating deep learning with organoid technology will enhance the precision and efficiency of drug discovery and personalized oncology.

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Authors

Xu Y; Fan S; Chen Y; Xu W; Lu H; Zhou Y; Liu Y; Du Q; Wang W; Yu T; Dong L

Published

Jan 1, 2026

Journal or venue

iScience

DOI

10.1016/j.isci.2026.116756

Paper type

journal article

Source

Pubmed