Dynamic adaptive microscopy for label-free multi-parametric imaging in biology and medicine

ended

Optical microscopy constitutes one of the most fundamental paradigms in biological and medical imaging. However, significant challenges remain in regard to the application of optical microscopy to in vivo interrogations. First, the diffusing nature of light propagation in tissue due to random variations of the refractive index, limits in vivo microscopy to superficial depths; within only a few mean free paths (<1mm). Second the invasive nature of fluorescent proteins and probes, allows monitoring of only 1-5 events by spectrally multiplexing different fluorochromes; i.e. performance that is highly incompatible with the targets of functional genomics and proteomics. This proposal aims to develop the next step in optical visualization by addressing these two fundamental limitations of optical imaging, i.e. Depth and Contrast. To achieve this, DynAMic proposes a radically new concept for optical imaging of tissue based on ❶ developing real-time wavefront-shaping adaptive optics for making the performance of any optical system ideal and for the first time in Raman microscopy ❷ reaching tenfold deeper in tissue than conventional optical microscopy by compensating for the refractive index variations using phase and polarization retrieval for inversing light diffusion and ❸ utilize advance image formation to improve the sensitivity and utilization of stimulated Raman scattering for multi-parametric label-free contrast that radically expands at least tenfold the number of labels concurrently retrieved from living systems, linking optical observation to functional proteomic requirements. The new optical imaging ability delivered in DynAMic will be applied to a first target application of ophthalmic imaging, also used as a window to the brain and devastating nervous disease detection, defining the next generation ophthalmology and neurology sensing, disrupting the modus operandi of retinal imaging without disturbing the modus agendi of the end users.