Practical Trade-Offs in 3D Cancer Imaging.

Abstract

Three-dimensional (3D) imaging is increasingly shaping cancer research. This piece highlights key technical considerations when adopting 3D over traditional two-dimensional (2D) imaging methods, emphasizing its unique ability to capture complex and heterogeneous tumor architecture. We also discuss the importance of multiomics integration and how virtual staining workflows can address scalability issues. Finally, we propose hybrid strategies that balance 2D and 3D imaging for a well-rounded understanding of inter- and intratumoral heterogeneity, underscoring the complementary value of both modalities in advancing cancer research. This article is part of a special series: Driving Cancer Discoveries with Computational Research, Data Science, and Machine Learning/AI .