Quantitative active super-resolution thermal imaging: The melanoma case study.

Super-resolution image acquisition has turned photo-activated far-infrared thermal imaging into a promising tool for the characterization of biological tissues. By the sub-diffraction localization of sparse temperature increments primed by the sample absorption of modulated focused laser light, the distribution of (endogenous or exogenous) photo-thermal biomarkers can be reconstructed at tunable ∼10-50 µm resolution. We focus here on the theoretical modeling of laser-primed temperature variations and provide the guidelines to convert super-resolved temperature-based images into quantitative maps of the absolute molar concentration of photo-thermal probes. We start from camera-based temperature detection via Stefan-Boltzmann's law, and elucidate the interplay of the camera point-spread-function and pixelated sensor size with the excitation beam waist in defining the amplitude of the measured temperature variations. This can be accomplished by the numerical solution of the three-dimensional heat equation in the presence of modulated laser illumination on the sample, which is characterized in terms of thermal diffusivity, conductivity, thickness, and concentration of photo-thermal species. We apply our data-analysis protocol to murine B16 melanoma biopsies, where melanin is mapped and quantified in label-free configuration at sub-diffraction 40 µm resolution. Our results, validated by an unsupervised machine-learning analysis of hematoxylin-and-eosin images of the same sections, suggest potential impact of super-resolved thermography in complementing standard histopathological analyses of melanocytic lesions.

Multiphoton Laser Fabrication of Hybrid Photo-Activable Biomaterials.

The possibility to shape stimulus-responsive optical polymers, especially hydrogels, by means of laser 3D printing and ablation is fostering a new concept of "smart" micro-devices that can be used for imaging, thermal stimulation, energy transducing and sensing. The composition of these polymeric blends is an essential parameter to tune their properties as actuators and/or sensing platforms and to determine the elasto-mechanical characteristics of the printed hydrogel. In light of the increasing demand for micro-devices for nanomedicine and personalized medicine, interest is growing in the combination of composite and hybrid photo-responsive materials and digital micro-/nano-manufacturing. Existing works have exploited multiphoton laser photo-polymerization to obtain fine 3D microstructures in hydrogels in an additive manufacturing approach or exploited laser ablation of preformed hydrogels to carve 3D cavities. Less often, the two approaches have been combined and active nanomaterials have been embedded in the microstructures. The aim of this review is to give a short overview of the most recent and prominent results in the field of multiphoton laser direct writing of biocompatible hydrogels that embed active nanomaterials not interfering with the writing process and endowing the biocompatible microstructures with physically or chemically activable features such as photothermal activity, chemical swelling and chemical sensing.

Whole-Section Tumor Micro-Architecture Analysis by a Two-Dimensional Phasor-Based Approach Applied to Polarization-Dependent Second Harmonic Imaging.

Second Harmonic Generation (SHG) microscopy has gained much interest in the histopathology field since it allows label-free imaging of tissues simultaneously providing information on their morphology and on the collagen microarchitecture, thereby highlighting the onset of pathologies and diseases. A wide request of image analysis tools is growing, with the aim to increase the reliability of the analysis of the huge amount of acquired data and to assist pathologists in a user-independent way during their diagnosis. In this light, we exploit here a set of phasor-parameters that, coupled to a 2-dimensional phasor-based approach (µMAPPS, Microscopic Multiparametric Analysis by Phasor projection of Polarization-dependent SHG signal) and a clustering algorithm, allow to automatically recover different collagen microarchitectures in the tissues extracellular matrix. The collagen fibrils microscopic parameters (orientation and anisotropy) are analyzed at a mesoscopic level by quantifying their local spatial heterogeneity in histopathology sections (few mm in size) from two cancer xenografts in mice, in order to maximally discriminate different collagen organizations, allowing in this case to identify the tumor area with respect to the surrounding skin tissue. We show that the "fibril entropy" parameter, which describes the tissue order on a selected spatial scale, is the most effective in enlightening the tumor edges, opening the possibility of their automatic segmentation. Our method, therefore, combined with tissue morphology information, has the potential to become a support to standard histopathology in diseases diagnosis.