Influence of the Signal-To-Noise Ratio on Variance of Chromophore Concentration Quantification in Broadband Near-Infrared Spectroscopy

Abstract

This study presented a theoretical or analytical approach to quantify how the signal-to-noise ratio (SNR) of a near infrared spectroscopy (NIRS) device influences the accuracy on calculated changes of oxy-hemoglobin (Δ[HbO]), deoxy-hemoglobin (Δ[HHb]), and oxidized cytochrome c oxidase (Δ[oxCCO]). In theory, all NIRS experimental measurements include variations due to thermal or electrical noise, drifts, and disturbance of the device. Since the computed concentration results are highly associated with device-driven variations, in this study, we applied the error propagation analysis to compute the variability or variance of Δ[HbO], Δ[HHb], and Δ[oxCCO] depending on the system SNR. The quantitative expressions of variance or standard deviations of changes in chromophore concentrations were derived based on the error propagation analysis and the modified Beer-Lambert law. In order to compare and confirm the derived variances versus those from the actual measurements, we conducted two sets of broadband NIRS (bbNIRS) measurements using a solid tissue phantom and the human forearm. A Monte Carlo framework was also executed to simulate the bbNIRS data under two physiological conditions for further confirmation of the theoretical analysis. Finally, the confirmed expression for error propagation was utilized for quantitative analyses to guide optimal selections of wavelength ranges and different wavelength combinations for minimal variances of Δ[HbO], Δ[HHb], and Δ[oxCCO] in actual experiments.

Prefrontal cortical connectivity and coupling of infraslow oscillation in the resting human brain: a 2-channel broadband NIRS study

“…After repeating the concentration quantification at all recorded time points, we obtained a time series of Δ[HbO] and Δ[CCO] for the 7-min resting-state period at a sampling frequency of 0.67 Hz. The spectral range of 780–900 nm estimates the chromophore concentration with a low level of error propagated from noise ( Truong et al. 2022 ).…”

Review of measurements and imaging of cytochrome-c-oxidase in humans using near-infrared spectroscopy: an update

“…Establishing a consensus on suitable measurement wavelengths, initial testing protocols, and standardization methods for each system is imperative. While efforts have been made to determine optimal measurement wavelengths [ 32 , 76 ] and SNR [ 77 ], further investigations are needed to understand the combined influence of wavelength choice, system design, layout, and processing methods on the acquired oxCCO signal. To serve as an initial proof-of-concept test, measurements of oxCCO should ideally be performed using reproducible dynamic liquid phantoms, as demonstrated in recent studies [ 78 ] and currently under investigation by our research group in Cambridge.…”

Unilateral Mitochondrial-Hemodynamic Coupling and Bilateral Connectivity in the Younger and Older Prefrontal Cortex of Healthy Adults

“…Step 2: Conversion of OD(t, ) to [HbO](t, ) and [CCO](t, ) over 7-min resting state With a sample rate of 0.67 Hz, 7-min bbNIRS data collection provided a set of 280 spectra for either eyes-open or eyes-closed session. The recorded spectrum was in the wavelength range of 740 to 1100 nm, but a spectral band of 780 to 900 nm was sufficient for our need [36]. According to the modified Beer-Lambert law, we converted OD(t, ) to [HbO](t, ) and [CCO](t, ) [37][38][39] for each time point over the 7-min measurement window for both lateral sides of the measurements [8,11,19].…”