Holotomography in 2025: From Morphometric Imaging to AI-Driven Multimodal Phenotyping

Abstract

By 2025, holotomography (HT) has matured from a niche optical modality into a versatile platform for quantitative, label-free imaging in biomedicine. By reconstructing the three-dimensional refractive-index (RI) distribution of cells and tissues, HT enables high-resolution volumetric imaging with low phototoxicity and minimal sample perturbation. This Review surveys recent advances in the field and highlights three emerging directions: (i) the incorporation of deep-learning approaches for virtual staining, phenotypic classification, and automated analysis; (ii) the extension of HT to structurally complex biological systems, including organoids and thick tissue specimens; and (iii) the integration of HT with complementary modalities, such as Raman and polarization-sensitive microscopy, to enhance molecular and biophysical specificity. We summarize current HT applications spanning subcellular phenotyping, metabolic and mechanical profiling, and early-stage clinical studies in areas such as infectious disease and pathology. Finally, we discuss remaining technical and translational challenges and outline a roadmap for the prospective integration of HT into digital pathology and high-throughput screening workflows.