Paper
2 July 2001 Near-infrared spectroscopic approach to assess tissue viability following a thermal injury
Lorenzo Leonardi, Michael G. Sowa, Jeri R. Payette, Mark D. Hewko, Bernhard J. Schattka, Anna Matas, Henry H. Mantsch
Author Affiliations +
Abstract
A recurrent problem in the assessment of thermal injuries is the ability to accurately identify the depth and extent of injury. Generally, the depth of a burn injury determines and is inversely related to the ability of the skin to restore and regenerate itself. Burns involve damage to the dermis in varying amounts, reducing the dermal blood supply and altering the skin hemodynamics. Near infrared spectroscopic imaging was used to non-invasively assess the changes that occur in the early (1-3 h) post-burn period. The study used an accurate porcine model to investigate the potential of near infrared spectroscopic imaging to accurately distinguish between burns of varying severity. Data analysis was carried out using a two-way and three-way data decompositions techniques to investigate the spectral changes related to burns. Burn injuries drastically alter the physical and optical properties of the tissue. Thermal destruction of cutaneous vasculature disrupts perfusion and oxygen delivery to the affected tissue. The results demonstrated that near infrared spectroscopic imaging might provide a new tool for an objective clinical assessment of burn injuries.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Lorenzo Leonardi, Michael G. Sowa, Jeri R. Payette, Mark D. Hewko, Bernhard J. Schattka, Anna Matas, and Henry H. Mantsch "Near-infrared spectroscopic approach to assess tissue viability following a thermal injury", Proc. SPIE 4259, Biomarkers and Biological Spectral Imaging, (2 July 2001); https://doi.org/10.1117/12.432478
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Cited by 1 scholarly publication.
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KEYWORDS
Injuries

Spectroscopy

Imaging spectroscopy

Near infrared

Tissues

Near infrared spectroscopy

Principal component analysis

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