Optical imaging has revolutionized biomedical research and clinical diagnostics by enabling non-invasive visualization of biological structures and dynamic processes. However, its utility in deep-tissue applications remains constrained by photon scattering, absorption, and refractive index heterogeneity. This comprehensive review systematically examines multidisciplinary innovations across physical, chemical, and computational domains to overcome these barriers. Physically, coherence-gated techniques (e.g., optical coherence tomography, multiphoton microscopy) and diffuse light methodologies (e.g., near-infrared-II fluorescence, photoacoustic imaging) enhance resolution and depth. Chemically, tissue optical clearing agents and advanced contrast agents improve optical accessibility and specificity. Computationally, adaptive optics and artificial intelligence (AI) paradigms correct distortions and enable real-time image reconstruction. We highlight transformative clinical applications in neuroscience, oncology, and surgery, such as neural activity mapping, tumor margin delineation, and intraoperative guidance. Critical challenges—including phototoxicity, nanoparticle biocompatibility, and clinical standardization—are addressed, underscoring the need for scalable protocols and translational frameworks. Emerging trends, such as AI-driven theranostics, minimally invasive fiber-based probes, and multimodal systems, are poised to redefine precision medicine. By synthesizing state-of-the-art technologies and envisioning future innovations, this review emphasizes the convergence of optics, materials science, and computational biology to unlock new frontiers in deep-tissue imaging and therapeutic interventions.
Pang et al. (Thu,) studied this question.