Protocol for AI-assisted quantitative analysis and setup of tumor spheroid invasion into tissue
Recent work has revealed an active mechanical role for the tissue barrier in collective invasion, offering a new perspective on tissue invasion and morphogenesis. Here, we present a protocol for AI-assisted quantitative analysis and setup of tumor spheroid invasion into mesothelial tissue. We describe steps for co-culture setup, time-lapse imaging, AI training, and segmentation. We then detail procedures for cell tracking and quantitative analysis to study the fracturing process of the mesothelium. For complete details on the use and execution of this protocol, please refer to Wu et al.<sup>1</sup>.
Authors
- Jennifer L. Young (ORCID: https://orcid.org/0000-0002-5229-5168)
- Shu Chian Tay
- Selwin K. Wu (ORCID: https://orcid.org/0000-0002-5185-8467)
- Ivan Yow (ORCID: https://orcid.org/0000-0002-5561-5411)
- Boon Chuan Low (ORCID: https://orcid.org/0000-0003-0756-096X)
- K. Lee
- Phoebe Lim
- Christina Bao-Xian Huang
- Eileen Poon (ORCID: https://orcid.org/0000-0001-9452-3408)
- Celestine Z. Ho
- Daniella B Lawther
- Sriram Bharathkumar
- Shi Wei Beh
- Carla Felisha
Institutions
- National University of Singapore (SG)
Publication Details
- Journal
- STAR Protocols
- Published
- 2025-10-11
- DOI
- https://doi.org/10.1016/j.xpro.2025.104140
- Citations
- 3
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 4.08