Frequency-domain near-infrared spectroscopy affords quantitative measurements which do account for scattering. Many real-world samples are optically turbid, causing scattering confounds which many commercial spectrometers can not address. Many applications seek to measure the absorption coefficient spectrum to retrieve the chemical makeup a sample. Further work will investigate implementation and reproducibility. We expect that higher error in the absorption coefficient can be alleviated with highly scattering samples and that boundary condition confounds may be suppressed by designing a cuvette with high index of refraction. Noise simulations with 0.1% amplitude and 0.1°=1.7 mrad phase uncertainty find errors in absorption and reduced scattering coefficients of 4% and 1%, respectively. We find: this works best for highly scattering samples (reduced scattering coefficient above 1 mm−1) higher relative error in the absorption coefficient compared to the reduced scattering coefficient accuracy is tied to knowledge of the sample’s index of refraction. Inspired by the self-calibrating method, which removes instrumental confounds, the method uses measurements of the diffuse complex transmittance at two sets of two different source-detector distances. Using diffusion theory and considering absorption and reduced scattering coefficients on the order of 0.01 mm−1 and 1mm−1, respectively, we develop a method which utilizes frequency-domain to measure absolute optical properties of turbid samples in a standard cuvette (45 mm×10 mm×10 mm). Many real-world samples are optically turbid, causing scattering confounds which many commercial spectrometers cannot address. Many applications seek to measure a sample’s absorption coefficient spectrum to retrieve the chemical makeup. This capability can have significant implications for non-invasive optical measurements of the human brain. In-vivo imaging of the human occipital lobe with FD NIRS and a mean distance of 31 mm indicated: (1) greater hemodynamic response to visual stimulation from FD phase versus intensity, and from DS versus single-distance (SD) (2) hemodynamics from FD phase and DS mainly driven by blood flow, and hemodynamics from SD intensity mainly driven by blood volume.ĭS imaging with FD NIRS may suppress confounding contributions from superficial hemodynamics without relying on data at short source-detector distances. The mean distance (between the two source-detector distances needed for DS) is the key factor for depth sensitivity. In-vivo demonstrations of DS imaging of the human brain during visual stimulation and during systemic blood pressure oscillations. Theoretical studies (in-silico) based on diffusion theory in two-layered and in homogeneous scattering media. To identify optimal source-detector distances for dual-slope (DS) measurements in frequency-domain (FD) near-infrared spectroscopy (NIRS) and demonstrate preferential sensitivity of DS imaging to deeper tissue (brain) versus superficial tissue (scalp). This work targets the contamination of optical signals by superficial hemodynamics, which is one of the chief hurdles in non-invasive optical measurements of the human brain. In particular, we present diffusion theory results for a symmetrical linear array of two sources (separated by 55 mm) that sandwich two detectors (separated by 15 mm), for which dual slopes achieve maximal sensitivity at a depth of about 5 mm for direct current (DC) intensity (as measured in continuous-wave spectroscopy) and 11 mm for phase (as measured in frequency-domain spectroscopy) under typical values of the tissue optical properties (absorption coefficient: $\sim\!0.01\,\,$ for the phase). The dual-slope method requires a minimum of two sources and two detectors arranged in specially configured arrays. Using diffusion theory, we show that a dual-slope method is more effective than single-slope methods or single-distance methods at enhancing sensitivity to deeper tissue.
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