Abstract

Laser Scanning Microscopy (LSM) techniques play in current days a key role in imaging and characterizing biological tissues. Among these, Multiphoton Microscopy (MPM), with its two main variants: Two-Photon Excitation Fluorescence (TPEF) and Second Harmonic Generation (SHG), has emerged as a powerful tool to investigate unprocessed tissues with resolution and detail comparable to standard histology. This is achieved by exploiting endogenous optical signals generated by the tissues upon interaction with a femtosecond laser beam used as excitation. The main optical signals that can be probed by MPM for in-vivo/ex-vivo characterization and diagnostics tasks are autofluorescence generated by endogenous chromophores, such as the enzyme cofactors nicotinamide adenine dinucleotide or flavin adenine dinucleotide and harmonic generations originated from non-centro-symmetric molecules present in the biological tissues, such as myosin, tubulin or collagen. These optical signals can provide valuable information over aspects such as abnormal cell morphology, size variation of cell nuclei, or modifications in the architecture of the extracellular matrix, all of these being important indicators for a wide range of pathologies, including cancers or neurodegenerative diseases. Currently, the lateral resolution that can be achieved by using such LSM techniques is limited by diffraction, which impedes an exact understanding of many fundamental structures and processes at cellular and sub-cellular levels. Apertureless Scanning Near-Field Optical microscopy (ASNOM) holds significant potential for resolving cellular and tissular features of physiological and pathological relevance at optical resolutions lying at nano-scale. However, due to the limited body of work performed so far in the ASNOM bioimaging area, the interpretation of near-field data sets collected using variants such as scattering-type SNOM or Second Harmonic Generation SNOM can be very cumbersome in the absence of supporting information. On the other hand, collecting supporting information with separate systems is not always easy. Investigating corresponding sample regions using systems that are based on different contrast mechanisms is often a difficult task (and sometimes impossible). Moreover, identifying sample regions of interest after switching between imaging systems working at different resolution scales is usually time demanding

© 2017 IEEE