Hyperspectral imaging of Kaposi's Sarcoma for disease assessment and treatment monitoring

David Hattery, Moinuddin Hassan, Stavros Demos, Amir Gandjbakhche

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations


Light spectroscopic methods are critical to advances in molecular characterization of disease processes. However, these methods have been limited to in-vitro or cell culture studies. In fact, strong scattering in almost all tissue types causes dispersion of the photons paths which results in poor localization and resolution. Hence, quantitative analysis of spectral data obtained from structures below the tissue surface requires accounting for scattering which affects both the penetration of the photons and the path length over which the photons will be subject to molecularly specific absorption. The goal of much current research is to non-invasively obtain diagnostically useful molecular information from embedded sites. We have designed and built a six-band multi-spectral NIR imaging system which we have used on patients with highly vascularized tumors in the skin called Kaposi's Sarcoma. The imaged lesions are undergoing treatment with experimental anti-angiogenesis drugs that are designed to reduce bloodflow and hence growth of the tumors. The NIR data is combined with both 3-5 micron and 8-12 micron infrared images, obtained of the same tumors, which are used to identify thermal signatures of blood volume, as well as three-band visible wavelength data which show the visible extent of the lesions. We have developed a layered model of the skin in which specific analytes exist in specific layers. The spectral signatures of analytes such as oxy- and deoxy-hemoglobin are known. To obtain information on the concentration of those analytes in the tissue, however, the diffuse reflectance NIR images from the patients must be corrected for scattering. The scattering is modeled using analytical solutions developed from a random walk model of photon migration in turbid media. When the hyperspectral patient data is fit to the model, physiologically related parameters, such as to blood volume and oxygenation, are obtained. This provides clinically important data that may be used by the physician for evaluations of drug effectiveness, disease assessment and patient treatment monitoring.

Original languageEnglish (US)
Title of host publicationProceedings - Applied Imagery Pattern Recognition Workshop
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages7
ISBN (Print)076951863X
StatePublished - 2002
Externally publishedYes
Event31st Applied Imagery Pattern Recognition Workshop, AIPR 2002 - Washington, United States
Duration: Oct 16 2002Oct 18 2002


Other31st Applied Imagery Pattern Recognition Workshop, AIPR 2002
Country/TerritoryUnited States


  • Diseases
  • Drugs
  • Hyperspectral imaging
  • Lesions
  • Light scattering
  • Monitoring
  • Neoplasms
  • Particle scattering
  • Skin
  • Spectral analysis

ASJC Scopus subject areas

  • Engineering(all)


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