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Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging
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Quantitative active super-resolution thermal imaging: The melanoma case study.

Mario Marini1, Margaux Bouzin1, Riccardo Scodellaro1

  • 1Physics Department, Università degli Studi di Milano-Bicocca, Piazza Della Scienza 3, 20126, Milano, Italy.

Biomolecular Concepts
|April 21, 2022
PubMed
Summary
This summary is machine-generated.

Super-resolution thermal imaging quantifies photo-thermal biomarkers in biological tissues. This method maps melanin concentration in melanoma biopsies with high resolution, aiding histopathological analysis.

Keywords:
hematoxylin-and-eosin staininfrared thermographyk-means clusteringmelanomasuper-resolution imaging

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Area of Science:

  • Biomedical Optics
  • Thermal Imaging
  • Super-resolution Microscopy

Background:

  • Photo-activated far-infrared thermal imaging offers advanced characterization of biological tissues.
  • Super-resolution techniques enable sub-diffraction localization of temperature variations.
  • This allows reconstruction of photo-thermal biomarker distribution at tunable resolutions (∼10-50 μm).

Purpose of the Study:

  • To develop theoretical models for laser-primed temperature variations.
  • To provide guidelines for converting super-resolved thermal images into quantitative concentration maps of photo-thermal probes.
  • To apply and validate the developed data-analysis protocol on biological samples.

Main Methods:

  • Utilized camera-based temperature detection based on Stefan-Boltzmann's law.
  • Investigated the influence of camera point-spread-function, sensor size, and excitation beam waist on temperature measurements.
  • Employed numerical solutions of the 3D heat equation for modulated laser illumination, considering thermal properties and probe concentration.

Main Results:

  • Developed a protocol to convert super-resolved thermal images into quantitative molar concentration maps.
  • Successfully mapped and quantified melanin in murine B16 melanoma biopsies at 40 μm resolution in a label-free manner.
  • Validated results using unsupervised machine learning analysis of standard histopathological images.

Conclusions:

  • Super-resolved thermography provides a quantitative method for analyzing photo-thermal biomarkers.
  • The technique enables label-free mapping and quantification of melanin in melanoma.
  • This approach shows potential to complement conventional histopathological analyses of melanocytic lesions.