Light and metabolism: label-free optical imaging of metabolic activities in biological systems [Invited].

Metabolic imaging is critical for understanding cellular functions beyond morphology, offering significant insights into various biological processes and disease states. Label-free optical imaging techniques stand out by providing high-resolution, molecularly specific, and/or non-invasive assessments of metabolic activity without relying on exogenous contrast agents. This review discusses the key photon-tissue interactions-absorption, emission, and scattering-that underpin label-free optical imaging modalities for interrogating tissue's metabolic activities at various scales. Specifically, photoacoustic imaging (PAI) leverages absorption-based contrasts such as hemoglobin oxygenation and glucose concentrations to quantify metabolic dynamics. Emission-based techniques, including two-photon fluorescence (TPF) and fluorescence lifetime imaging microscopy (FLIM), exploit intrinsic fluorophores like nicotinamide adenine dinucleotide (NADH) and flavin adenine dinucleotide (FAD) to assess cellular energy metabolism. Interferometric methods, particularly optical coherence tomography (OCT), provide insights into tissue morphological changes. Second harmonic generation (SHG) detects extracellular matrix components such as the collagen network. Molecular vibrational imaging methods, such as stimulated Raman scattering (SRS) microscopy, visualizes spatial heterogeneity of molecular compositions. Recent clinical translations of these methods highlight their growing roles in oncology, neurology, and dermatology, underscoring their potential in early disease diagnosis and monitoring therapeutic responses. Despite challenges such as depth limitations, advancements like wavefront engineering and optical clearing techniques promise to enhance imaging penetration and clinical applicability, paving the way for broader adoption of label-free optical metabolic imaging in both research and clinical settings.

Duke Scholars

Author Junjie Yao Biomedical Engineering