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Quantitative active super-resolution thermal imaging: The melanoma case study
- Source :
- Biomolecular Concepts, Vol 13, Iss 1, Pp 242-255 (2022)
- Publication Year :
- 2022
- Publisher :
- De Gruyter, 2022.
-
Abstract
- 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.
Details
- Language :
- English
- ISSN :
- 1868503X
- Volume :
- 13
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Biomolecular Concepts
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.11ac34e73e0f4786bc9079914addf063
- Document Type :
- article
- Full Text :
- https://doi.org/10.1515/bmc-2022-0015