title: Detection limits of multi-spectral optical imaging under the skin surface.
abstract: The present work shows that the optical/biological information contained in a typical spectral image mainly reflects the properties of a small (conic like) volume of tissue situated vertically under each individual pixel. The objects appearing on a spectral image reasonably reproduce the correct geometrical shape and size (like a non-deformed shadow) of underlying inclusions of pathological tissue. The information contained in a spectral image comes from a depth that does not exceed approximately 2-3 mm. The number of photons that visit a given tissue voxel situated at a depth larger than approximately 2 mm represents less than the 1% of the total number of photons reaching the corresponding detection pixel (forming the image). A pathological inclusion (e.g. a pool of blood or vascular tumor) situated at a depth of approximately 0.5 mm with a thickness of 0.5 mm produces an image intensity contrast of approximately 5% (for images taken at wavelengths in the 600-1000 nm range) when compared to the normal skin background. The same inclusion at a depth of 20 microm provides a contrast decreasing from 55 to 20% with respect to an increase in wavelength. The dermis/hypodermis interface behaves as a partial barrier for the photons, limiting their access to deeper skin regions. The image contrast depends on the depth and the type of chromophore contained in the inclusion. An increase in the concentration of a given molecule may produce different contrast, independently of the depth, depending on the characteristics of the skin layer where this change occurs.
authors.affiliation: Département des Neurosciences Fondamentales, University of Geneva, Switzerland. Tiziano.Binzoni@medecine.unige.ch
authors.forename: T
authors.initials: T
authors.lastname: Binzoni
authors.forename: A
authors.initials: A
authors.lastname: Vogel
authors.forename: A H
authors.initials: AH
authors.lastname: Gandjbakhche
authors.forename: R
authors.initials: R
authors.lastname: Marchesini
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D046169:Dermoscopy / Q000379:methods*; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008954:Models, Biological; D010783:Photometry / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012867:Skin / Q000166:cytology*; D013057:Spectrum Analysis / Q000379:methods*; D041622:Tomography, Optical / Q000379:methods*