光谱学与光谱分析 |
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Estimation of Tissue’s Blood Oxygen Parameters from Visible Absorption Spectrum of Tissues by Artificial Neural Network |
DAI Li-juan1,WANG Hui-nan1,QIAN Zhi-yu1,YU Guo-qiang2 |
1. Department of Biomedical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China 2. College of Medicine, East South University, Nanjing 210009, China |
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Abstract Total hemoglobin concentration (THC) and hemoglobin oxygen saturation (SO2) are essential parameters to doctors who wonder patients’ hematogenous conditions and oxygen supplies and consumptions. Instruments presently used for measuring these parameters have big size of detecting probes that limit their applications to inner bodies. An optical probe involving two fibers with source-detector separations of one hundred micrometers was developed in the present study for purpose of minimally invasive inner detecting, which uses steady-state, broadband (300-1 000 nm) light source. The source light is delivered to targets through one fiber and the reflected light from the targets is collected and transferred to a spectrometer through the other fiber. Reflectance spectrum is obtained from the spectrometer. The method of reading THC and SO2 from the reflectance spectrum was developed using liquid-tissue phantoms containing intralipid and blood. Firstly, reflex spectrum of intralipid was recorded before mixtures of intralipid and blood with different THC were made as tissue phantoms. Then the fiber optical spectrometer was used to obtain reflex spectra as the phantoms’ SO2 changed; simultaneously their corresponding THC and SO2 were recorded as the scale values by an oximeter. Differences of reflex spectra in 520-590 nm between intralipid and tissue models were proved reliably. Secondly, after data collections of absorption spectra and scale values were finished, two artificial neural networks (ANN) were build to model the relationship between scale values and absorption spectra. After being trained, the ANNs could output THC and SO2 correctly when an absorption spectrum was input. The ANNs produced errors of less than 4 μmol·L-1 for THC and 5% for SO2. In vivo and minimally invasive measurements of THC and SO2 of brain tissues in different depth were finished on 30 rats by this specific system with the ANNs. The probe was inserted stereotactically to a depth of 6 mm with measurements obtained every 0.2 mm. SO2 of gray mater and white mater of rats was respectively obtained as 0.60-0.70 and 0.45-0.55. The highest THC, 110 μmol·L-1 was measured around rat cortex. THC of brain tissue in other depth is 70-90 μmol·L-1. These values agree well with reported data. This simple, inexpensive method deserves further study to establish its efficacy for THC and SO2 measurements of inner body.
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Received: 2007-02-13
Accepted: 2007-05-18
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Corresponding Authors:
DAI Li-juan
E-mail: viviantea@tom.com
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[1] Sogandares F M,Fry E S. Appl. Opt.,1997, 36: 8699. [2] Buiteveld H, Hakvoort J M H, Donze M. SPIE Proceedings on Ocean Ⅻ, 1994, 2258: 174. [3] Prahl Scott. Optical Absorption of Hemoglobin, Oregon. Medical Laser Center Webpage[EB/OL]. http://omlc.ogi.edu./spectra/hemoglobin/index.html. [4] Takatani S,Graham M D. IEEE Trans. Biomed. Eng., 1987, 34: 656. [5] Tachtsidis I, Elwell CE, Leung TS, et al. Physiological Measurement, 2004, 25(2): 437. [6] Ohmae E, Ouchi Y, Oda M, et al. NeuroImage, 2006, 29(3): 697. [7] Plesnila N, Putz C, Rinecker M, et. al. Journal of Neuroscience Method, 2002, 114(1):107. [8] Mcleod AD, Igielman F, Elwell C, et al. Anaesthesia and Analgesia, 2003, 97(3):851. [9] LI Yue, DING Hai-shu, HUANG Lan, et al(李 岳,丁海曙,黄 岚,等). Spectroscopy and Spectral Analysis(光谱学与光谱分析),2005,25(3):377. [10] Strangman G, Boas D A, Sutton J P. Biological Phychiotry, 2002, 52(7):679. [11] Cheong W F, Prahl S A, Welch A J. IEEE J. Quantum Electron, 1990, 26(12):2166. [12] Johns M, Giller C A, Liu H. Appl. Spectroscopy, 2001, 55(12):1686. |
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