On the geometry dependence of differential pathlength factor for near-infrared spectroscopy. I. Steady-state with homogeneous medium

Influence of oversimplifying the head anatomy on cerebral blood flow measurements with diffuse correlation spectroscopy

Significance

Diffuse correlation spectroscopy (DCS) is an emerging optical modality for non-invasive assessment of an index of regional cerebral blood flow. By the nature of this noninvasive measurement, light must pass through extracerebral layers (i.e., skull, scalp, and cerebral spinal fluid) before detection at the tissue surface. To minimize the contribution of these extracerebral layers to the measured signal, an analytical model has been developed that treats the head as a series of three parallel and infinitely extending slabs (mimicking scalp, skull, and brain). The three-layer model has been shown to provide a significant improvement in cerebral blood flow estimation over the typically used model that treats the head as a bulk homogenous medium. However, the three-layer model is still a gross oversimplification of the head geometry that ignores head curvature, the presence of cerebrospinal fluid (CSF), and heterogeneity in layer thickness.

Aim

Determine the influence of oversimplifying the head geometry on cerebral blood flow estimated with the three-layer model.

Approach

Data were simulated with Monte Carlo in a four-layer slab medium and a three-layer sphere medium to isolate the influence of CSF and curvature, respectively. Additionally, simulations were performed on magnetic resonance imaging (MRI) head templates spanning a wide-range of ages. Simulated data were fit to both the homogenous and three-layer model for CBF. Finally, to mitigate the errors in potential CBF estimation due to the difficulty in defining layer thickness, we investigated an approach to identify an equivalent, "optimized" thickness via a pressure modulation.

Results

Both head curvature and failing to account for CSF lead to significant errors in the estimation of CBF. However, the effect of curvature and CSF on relative changes in CBF is minimal. Further, we found that CBF was underestimated in all MRI-templates, although the magnitude of these underestimations was highly influenced by small variations in the source and detector optode positioning. The optimized thickness obtained from pressure modulation did not improve estimation accuracy of CBF, although it did significantly improve the estimation accuracy of relative changes in CBF.

Conclusions

In sum, these findings suggest that the three-layer model holds promise for improving estimation of relative changes in cerebral blood flow; however, estimations of absolute cerebral blood flow with the approach should be viewed with caution given that it is difficult to account for appreciable sources of error, such as curvature and CSF.

Non-Invasive Spectroscopy for Measuring Cerebral Tissue Oxygenation and Metabolism as a Function of Cerebral Perfusion Pressure

Near-infrared spectroscopy (NIRS) and diffuse correlation spectroscopy (DCS) measure cerebral hemodynamics, which in turn can be used to assess the cerebral metabolic rate of oxygen (CMRO₂) and cerebral autoregulation (CA). However, current mathematical models for CMRO₂ estimation make assumptions that break down for cerebral perfusion pressure (CPP)-induced changes in CA. Here, we performed preclinical experiments with controlled changes in CPP while simultaneously measuring NIRS and DCS at rest. We observed changes in arterial oxygen saturation (~10%) and arterial blood volume (~50%) with CPP, two variables often assumed to be constant in CMRO₂ estimations. Hence, we propose a general mathematical model that accounts for these variations when estimating CMRO₂ and validate its use for CA monitoring on our experimental data. We observed significant changes in the various oxygenation parameters, including the coupling ratio (CMRO₂/blood flow) between regions of autoregulation and dysregulation. Our work provides an appropriate model and preliminary experimental evidence for the use of NIRS- and DCS-based tissue oxygenation and metabolism metrics for non-invasive diagnosis of CA health in CPP-altering neuropathologies.

Iterative optical technique for detecting anti-leishmania nanoparticles in mouse lesions

Nanoparticles (NPs) based drugs for topical administration are gaining interest in the biomedical world. However, a study tool of their penetration depth to the different tissue layers without additional markers or contrast agents is required in order to relieve safety concerns. While common diagnostic tools, e.g. X-ray, computed tomography or magnetic resonance imaging, can provide in vivo detection of the metallic NPs, their resolution cannot determine the exact penetration depth to the thin skin layers. In this work, we propose the noninvasive nanophotonics iterative multi-plane optical property extraction (IMOPE) technique for the novel iron-based NPs detection in leishmaniasis lesions. The optical properties of the different tissue layers: epidermis, dermis, subcutaneous fat and muscle, were examined before and after topical drug administration. The potential topical drug was detected in the epidermis (∼13µm) and dermis (∼160µm) layers in mice lesions at different stages of the disease (two or four weeks post infection). The lesion size influence on the detection was also observed, where in larger lesions the IMOPE senses a greater presence of the topical drug.

Effect of adipose tissue thickness and tissue optical properties on the differential pathlength factor estimation for NIRS studies on human skeletal muscle

We propose a quantitative and systematic investigation of the differential pathlength factor (DPF) behavior for skeletal muscles and its dependence on different factors, such as the subcutaneous adipose tissue thickness (ATT), the variations of the tissue absorption (µ_a ) and reduced scattering (µ'_s ) coefficients, and the source-detector distance. A time domain (TD) NIRS simulation study is performed in a two-layer geometry mimicking a human skeletal muscle with an overlying adipose tissue layer. The DPF decreases when µ_a increases, while it increases when µ'_s increases. Moreover, a positive correlation between DPF and ATT is found. These results are supported by an in-vivo TD NIRS study on vastus lateralis and biceps brachii muscles of eleven subjects at rest, showing a high inter-subject and inter-muscle variability.

Exploring the feasibility of wavelength modulated near-infrared spectroscopy

SIGNIFICANCE

The application of near-infrared spectroscopy (NIRS) to determine the concentrations of tissue chromophores has typically relied on three alternative technological approaches: continuous-wave, frequency-domain, and time-domain. It is often the case that uncertain and variable coupling of light into and out of the skin surface renders absolute measurements unreliable, and NIRS methods are mostly used to measure changes of chromophore concentrations and of physiological parameters such as blood volume and oxygenation.

AIM

The aim has been to investigate whether an approach based on a wavelength-modulated source may enable measurements to be acquired, which are independent of surface coupling and may facilitate derivation of absolute values of tissue parameters.

APPROACH

An analysis is performed using the modified Beer-Lambert law.

RESULTS

It is shown that the relative modulation in detected intensity resulting from a wavelength-modulated source could be used to estimate absolute concentrations of chromophores if unknown surface coupling losses and geometrical factors are insensitive to small changes in wavelength.

CONCLUSIONS

Wavelength modulated NIRS could be an effective tool for quantitative in vivo analysis of tissues, although it may be technically challenging.

Media Characterization under Scattering Conditions by Nanophotonics Iterative Multiplane Spectroscopy Measurements

Characterizing materials is preferably done by multiple wavelengths. In opaque materials, the scattering poses a challenge due to the additional complexity to the spectroscopic measurements. We have previously demonstrated an iterative multiplane method for characterizing materials using the reflection from turbid media. Initial studies were performed in the red wavelength regime (632.8 nm) which is optimal for biomedical applications. However, in order to differentiate between materials, it is better to use multiple wavelengths, as spectroscopy may detect the material fingerprint. In this paper, our iterative multiplane optical property extraction (IMOPE) technique is presented in the blue regime (473 nm). Agar-based solid phantom measurements were conducted and compared to our theoretical model. Compatibility between experiments in the red and blue wavelengths shows the robustness of our technique.

Differential pathlength factor in continuous wave functional near-infrared spectroscopy: reducing hemoglobin's cross talk in high-density recordings

Functional near-infrared spectroscopy (fNIRS) estimates the functional oscillations of oxyhemoglobin and deoxyhemoglobin in the cortex through scalp-located multiwavelength recordings. Hemoglobin oscillations are inferred through temporal changes in continuous-wave (CW) light attenuation. However, because of the diffusive multilayered head tissue structures, the photon path is longer than the source-detector separation, complicating hemoglobin evaluation. This aspect is incorporated in the modified Beer-Lambert law where the source-detector distance is multiplied by the differential pathlength factor (DPF). Since DPF estimation requires photons' time-of-flight information, DPF is assumed a priori in CW-fNIRS. Importantly, errors in the DPF spectrum induce hemoglobin cross talk, which is detrimental for fNIRS. We propose to estimate subject-specific DPF spectral dependence relying on multidistance high-density measurements. The procedure estimates the effective attenuation coefficient (EAC), which is proportional to the geometric mean of absorption and reduced scattering. Since DPF depends on the scattering-to-absorption ratio, EAC limits the spectral dependence assumption to scattering. This approach was compared to a standard frequency-domain multidistance procedure. A good association between the two methods ( r 2 = 0.69 ) was obtained. This approach could estimate low-resolution maps of the DPF spectral dependence through large field of view, high-density systems, reducing hemoglobin cross talk, and increasing fNIRS sensitivity and specificity to brain activity without instrumentation modification.

Algorithm for in vivo detection of tissue type from multiple scattering light phase images

In vivo physiological assessments are typically done by either imaging techniques or by sensing changes in the attenuation coefficient. Using visible or near-infrared (NIR), imaging is mainly possible for thin tissues. On the other hand, clinical information can also be detected by examining changes in tissue optical properties. The most challenging aspect in sensing techniques is the spectral dependent scattering, which varies with the physiological state and tissue type. We have previously published our novel noninvasive nanophotonics technique for detecting tissue scattering based on reflectance measurements: the iterative multi-plane optical property extraction (IMOPE). The IMOPE reconstructs the reemitted light phase using an iterative algorithm and extracts the scattering properties based on a theoretical model. This paper presents the in vivo application of distinguishing between different mouse tissue areas. The reconstructed phase images reveal different areas in the inner thigh of a mouse, which are related to the muscle, bone, and skin. The IMOPE uses the reconstructed phases for sensing and detecting unseen components beneath the skin surface. This technique could be further applied to the diagnosis of various physiological states.

Wireless, battery-free optoelectronic systems as subdermal implants for local tissue oximetry

Monitoring regional tissue oxygenation in animal models and potentially in human subjects can yield insights into the underlying mechanisms of local O2-mediated physiological processes and provide diagnostic and therapeutic guidance for relevant disease states. Existing technologies for tissue oxygenation assessments involve some combination of disadvantages in requirements for physical tethers, anesthetics, and special apparatus, often with confounding effects on the natural behaviors of test subjects. This work introduces an entirely wireless and fully implantable platform incorporating (i) microscale optoelectronics for continuous sensing of local hemoglobin dynamics and (ii) advanced designs in continuous, wireless power delivery and data output for tether-free operation. These features support in vivo, highly localized tissue oximetry at sites of interest, including deep brain regions of mice, on untethered, awake animal models. The results create many opportunities for studying various O2-mediated processes in naturally behaving subjects, with implications in biomedical research and clinical practice.

Optical method to extract the reduced scattering coefficient from tissue: theory and experiments

Tissues are considered challenging in terms of structure and composition analysis due to their tendency to multiple scatter the incident light. One of the most common theories for extracting optical properties of tissue is diffusion reflection (DR). In this Letter, we propose a new paradigm for estimating the reduced scattering coefficient of a medium from the reflected light phase. The technique is a modified DR theory wherein the phase is calculated by the product of the wavenumber and the average pathlength. This theory is supported by the reconstructed phase of tissue-like phantom experiments from an iterative algorithm.

Generalized Beer-Lambert model for near-infrared light propagation in thick biological tissues

The attenuation of near-infrared (NIR) light intensity as it propagates in a turbid medium like biological tissue is described by modified the Beer–Lambert law (MBLL). The MBLL is generally used to quantify the changes in tissue chromophore concentrations for NIR spectroscopic data analysis. Even though MBLL is effective in terms of providing qualitative comparison, it suffers from its applicability across tissue types and tissue dimensions. In this work, we introduce Lambert-W function-based modeling for light propagation in biological tissues, which is a generalized version of the Beer–Lambert model. The proposed modeling provides parametrization of tissue properties, which includes two attenuation coefficients μ0 and η. We validated our model against the Monte Carlo simulation, which is the gold standard for modeling NIR light propagation in biological tissue. We included numerous human and animal tissues to validate the proposed empirical model, including an inhomogeneous adult human head model. The proposed model, which has a closed form (analytical), is first of its kind in providing accurate modeling of NIR light propagation in biological tissues.