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. 2017 Oct 23;8(11):5151-5159.
doi: 10.1364/BOE.8.005151. eCollection 2017 Nov 1.

Optimal hemoglobin extinction coefficient data set for near-infrared spectroscopy

Affiliations

Optimal hemoglobin extinction coefficient data set for near-infrared spectroscopy

Yue Zhao et al. Biomed Opt Express. .

Abstract

Extinction coefficient (ε) is a critical parameter for quantification of oxy-, deoxy-, and total-hemoglobin concentrations (Δ[HbO2], Δ[Hb], Δ[tHb]) from optical measurements of Near-infrared spectroscopy (NIRS). There are several different ε data sets which were frequently used in NIRS quantification. A previous study reported that even a small variation in ε could cause a significant difference in hemodynamic measurements. Apparently the selection of an optimal ε data set is important for NIRS. We conducted oxygen-state-varied and blood-concentration-varied model experiments with 57 human blood samples to mimic tissue hemodynamic variations. Seven reported ε data sets were evaluated by comparisons between quantifications and assumed values. We found that the Moaveni et al (1970)' ε data set was the optimal one, the NIRS quantification varied significantly among different ε data sets and parameter Δ[tHb] was most sensitive to ε data sets selection.

Keywords: (120.0120) Instrumentation, measurement, and metrology; (170.1470) Blood or tissue constituent monitoring; (170.6510) Spectroscopy.

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Conflict of interest statement

The authors declare that there are no conflicts of interest related to this article.

Figures

Fig. 1
Fig. 1
Absorption spectra of HbO2 and Hb from Moaveni (1970), Tkatani et al (1979), Gratzer et al (1999), Cope et al (1991), Zijlstra et al (1991), Prahl et al (1998) and Wray et al (1988).
Fig. 2
Fig. 2
Experimental setup, including a tissue-like liquid phantom, a NIRS probe (a source and a detector), a functional module and a computer.
Fig. 3
Fig. 3
(a) An example of time-related ΔOD trace during the whole experiment process. The icon of 0.5ml  blood denotes every blood addition; O2 bubbling denotes the start of pump oxygen and O2 stopped is stopping the oxygen gas. (b) The sample-averaged ΔOD with error bar on both full-oxygenated and deoxygenated states for measured wavelengths.
Fig. 4
Fig. 4
The deviation evaluation of Δ[HbO2], Δ[Hb] and Δ[tHb] caused by using 7 different ε data sets during each state. Odd states represent fully-oxygenated states and even states are fully-deoxygenated states.
Fig. 5
Fig. 5
Sample-averaged assumed and measured hemodynamics for every state by using 7 different ε data sets, respectively. Odd-order state represents fully-oxygenated state and even-order state is fully-deoxygenated state. The standard deviation (SD) values were marked in red.
Fig. 6
Fig. 6
Time responses of assumed and measured Δ[tHb] variations.

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References

    1. Murkin J. M., Arango M., “Near-infrared spectroscopy as an index of brain and tissue oxygenation,” Br. J. Anaesth. 103(Suppl 1), i3–i13 (2009). - PubMed
    1. Colak S. B., Van der Mark M. B., Hooft G. W., Hoogenraad J. H., Van der Linden E. S., Kuijpers F. A., “Clinical optical tomography and NIR spectroscopy for breast cancer detection,” IEEE J. Sel. Top. Quantum Electron. 5(4), 1143–1158 (1999).
    1. Delpy D. T., Cope M., “Quantification in tissue near-infrared spectroscopy,” Phil. Trans. Biol. Sci. 352(1354), 649–659 (2002).
    1. Jöbsis F. F., “Noninvasive, infrared monitoring of cerebral and myocardial oxygen sufficiency and circulatory parameters,” Science 198(4323), 1264–1267 (1977). - PubMed
    1. Strangman G., Franceschini M. A., Boas D. A., “Factors affecting the accuracy of near-infrared spectroscopy concentration calculations for focal changes in oxygenation parameters,” Neuroimage 18(4), 865–879 (2003). - PubMed