Modeling of a three-source perfusion and blood oxygenation sensor for transplant monitoring using multilayer Monte Carlo code

Bennett L. Ibey; Seungjoon Lee; M. Nance Ericson; Mark A. Wilson M.D.; Gerard L. Cote

doi:10.1117/12.529444

18 June 2004 Modeling of a three-source perfusion and blood oxygenation sensor for transplant monitoring using multilayer Monte Carlo code

Bennett L. Ibey, Seungjoon Lee, M. Nance Ericson, Mark A. Wilson M.D., Gerard L. Cote

Author Affiliations +

Proceedings Volume 5325, Optical Diagnostics and Sensing IV; (2004) https://doi.org/10.1117/12.529444
Event: Biomedical Optics 2004, 2004, San Jose, CA, United States

Abstract

A Multi-Layer Monte Carlo (MLMC) model was developed to predict the results of in vivo blood perfusion and oxygenation measurement of transplanted organs as measured by an indwelling optical sensor. A sensor has been developed which uses three-source excitation in the red and infrared ranges (660, 810, 940 nm). In vitro data was taken using this sensor by changing the oxygenation state of whole blood and passing it through a single-tube pump system wrapped in bovine liver tissue. The collected data showed that the red signal increased as blood oxygenation increased and infrared signal decreased. The center wavelength of 810 nanometers was shown to be quite indifferent to blood oxygenation change. A model was developed using MLMC code that sampled the wavelength range from 600-1000 nanometers every 6 nanometers. Using scattering and absorption data for blood and liver tissue within this wavelength range, a five-layer model was developed (tissue, clear tubing, blood, clear tubing, tissue). The theoretical data generated from this model was compared to the in vitro data and showed good correlation with changing blood oxygenation.

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Bennett L. Ibey, Seungjoon Lee, M. Nance Ericson, Mark A. Wilson M.D., and Gerard L. Cote "Modeling of a three-source perfusion and blood oxygenation sensor for transplant monitoring using multilayer Monte Carlo code", Proc. SPIE 5325, Optical Diagnostics and Sensing IV, (18 June 2004); https://doi.org/10.1117/12.529444

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