Retrieval of chromophore concentration changes in a digital human head model using analytical mean partial pathlengths of photons.

Significance: Continuous-wave functional near-infrared spectroscopy has proved to be a valuable tool for assessing hemodynamic activity in the human brain in a non-invasively and inexpensive way. However, most of the current processing/analysis methods assume the head is a homogeneous medium, and hence do not appropriately correct for the signal coming from the scalp. This effect can be reduced by considering light propagation in a layered model of the human head, being the Monte Carlo (MC) simulations the gold standard to this end. However, this implies large computation times and demanding hardware capabilities. Aim: In this work, we study the feasibility of replacing the homogeneous model and the MC simulations by means of analytical multilayered models, combining in this way, the speed and simplicity of implementation of the former with the robustness and accuracy of the latter. Approach: Oxy- and deoxyhemoglobin (HbO and HbR, respectively) concentration changes were proposed in two different layers of a magnetic resonance imaging (MRI)-based meshed model of the human head, and then these changes were retrieved by means of (i) a typical homogeneous reconstruction and (ii) a theoretical layered reconstruction. Results: Results suggest that the use of analytical models of light propagation in layered models outperforms the results obtained using traditional homogeneous reconstruction algorithms, providing much more accurate results for both, the extra- and the cerebral tissues. We also compare the analytical layered reconstruction with MC-based reconstructions, achieving similar degrees of accuracy, especially in the gray matter layer, but much faster (between 4 and 5 orders of magnitude). Conclusions: We have successfully developed, implemented, and validated a method for retrieving chromophore concentration changes in the human brain, combining the simplicity and speed of the traditional homogeneous reconstruction algorithms with robustness and accuracy much more similar to those provided by MC simulations.

MamoRef: an optical mammography device using whole-field CW diffuse reflectance. Presentation, validation and preliminary clinical results.

Objective.MamoRef is an mammography device that uses near-infrared light, designed to provide clinically relevant information for the screening of diseases of the breast. Using low power continuous wave lasers and a high sensitivity CCD (Charge-coupled device) that captures a diffusely reflected image of the tissue, MamoRef results in a versatile diagnostic tool that aims to fulfill a complementary role in the diagnosis of breast cancer providing information about the relative hemoglobin concentrations as well as oxygen saturation.Approach.We present the design and development of an initial prototype of MamoRef. To ensure its effectiveness, we conducted validation tests on both the theoretical basis of the reconstruction algorithm and the hardware design. Furthermore, we initiated a clinical feasibility study involving patients diagnosed with breast disease, thus evaluating the practical application and potential benefits of MamoRef in a real-world setting.Main results.Our study demonstrates the effectiveness of the reconstruction algorithm in recovering relative concentration differences among various chromophores, as confirmed by Monte Carlo simulations. These simulations show that the recovered data correlates well with the ground truth, with SSIMs of 0.8 or more. Additionally, the phantom experiments validate the hardware implementation. The initial clinical findings exhibit highly promising outcomes regarding MamoRef's ability to differentiate between lesions.Significance.MamoRef aims to be an advancement in the field of breast pathology screening and diagnostics, providing complementary information to standard diagnostic techniques. One of its main advantages is the ability of determining oxy/deoxyhemoglobin concentrations and oxygen saturation; this constitutes valuable complementary information to standard diagnostic techniques. Besides, MamoRef is a portable and relatively inexpensive device, intended to be not only used in specific medical imaging facilities. Finally, its use does not require external compression of the breast. The findings of this study underscore the potential of MamoRef in fulfilling this crucial role.

Reconstruction of light absorption changes in the human head using analytically computed photon partial pathlengths in layered media.

Functional near infrared spectroscopy has been used in recent decades to sense and quantify changes in hemoglobin concentrations in the human brain. This noninvasive technique can deliver useful information concerning brain cortex activation associated with different motor/cognitive tasks or external stimuli. This is usually accomplished by considering the human head as a homogeneous medium; however, this approach does not explicitly take into account the detailed layered structure of the head, and thus, extracerebral signals can mask those arising at the cortex level. This work improves this situation by considering layered models of the human head during reconstruction of the absorption changes in layered media. To this end, analytically calculated mean partial pathlengths of photons are used, which guarantees fast and simple implementation in real-time applications. Results obtained from synthetic data generated by Monte Carlo simulations in two- and four-layered turbid media suggest that a layered description of the human head greatly outperforms typical homogeneous reconstructions, with errors, in the first case, bounded up to ∼20% maximum, while in the second case, the error is usually larger than 75%. Experimental measurements on dynamic phantoms support this conclusion.

Theoretical investigation of photon partial pathlengths in multilayered turbid media.

Functional near infrared spectroscopy (fNIRS) is a valuable tool for assessing oxy- and deoxyhemoglobin concentration changes (Δ[HbO] and Δ[HbR], respectively) in the human brain. To this end, photon pathlengths in tissue are needed to convert from light attenuation to Δ[HbO] and Δ[HbR]. Current techniques describe the human head as a homogeneous medium, in which case these pathlengths are easily computed. However, the head is more appropriately described as a layered medium; hence, the partial pathlengths in each layer are required. The current way to do this is by means of Monte Carlo (MC) simulations, which are time-consuming and computationally expensive. In this work, we introduce an approach to theoretically calculate these partial pathlengths, which are computed several times faster than MC simulations. Comparison of our approach with MC simulations show very good agreement. Results also suggest that these analytical expressions give much more specific information about light absorption in each layer than in the homogeneous case.

A Monte Carlo study of near infrared light propagation in the human head with lesions-a time-resolved approach.

Several clinical conditions leading to traumatic brain injury can cause hematomas or edemas inside the cerebral tissue. If these are not properly treated in time, they are prone to produce long-term neurological disabilities, or even death. Low-cost, portable and easy-to-handle devices are desired for continuous monitoring of these conditions and Near Infrared Spectroscopy (NIRS) techniques represent an appropriate choice. In this work, we use Time-Resolved (TR) Monte Carlo simulations to present a study of NIR light propagation over a digital MRI phantom. Healthy and injured (hematoma/edema) situations are considered. TR Diffuse Reflectance simulations for different lesion volumes and interoptode distances are performed in the frontal area and the left parietal area. Results show that mean partial pathlengths, photon measurement density functions and time dependent contrasts are sensitive to the presence of lesions, allowing their detection mainly for intermediate optodes separations, which proves that these metrics represent robust means of diagnose and monitoring. Conventional Continuous Wave (CW) contrasts are also presented as a particular case of the time dependent ones, but they result less sensitive to the lesions, and have higher associated uncertainties.

A comparison between plausible models in layered turbid media with geometrical variations applying a Bayesian selection criterion.

One possible application of Near Infrared techniques is to analyze human brain metabolic activity. Currently used models take into account the layered structure of the human head but, usually, they do not consider the non-planar surface of some of the boundaries, i.e. gray matter, which results in a much more complex structure, thus leading to more sophisticated models and longer calculation times. The main objective of this work is to determine if it is worth to replace a planar layered structure by a non-planar one. To this end we implement a Bayesian-based quantitative methodology for choosing between two competitive models describing light propagation in layered turbid media. Experiments of time-resolved diffuse reflectance measurements are performed in layered phantoms and complemented with numerical calculations. The resulting Distributions of Time of Flight of both models are compared using Bayesian model selection analysis. The non-planar interface was introduced in the simulations by a simple surface parametrization. Results suggest that, under certain conditions, a multilayer model with planar boundaries is good enough.

Solution of the direct problem in turbid media with inclusions using Monte Carlo simulations implemented in graphics processing units: new criterion for processing transmittance data.

The study of light propagation in diffusive media requires solving the radiative transfer equation, or eventually, the diffusion approximation. Except for some cases involving simple geometries, the problem with immersed inclusions has not been solved. Also, Monte Carlo (MC) calculations have become a gold standard for simulating photon migration in turbid media, although they have the drawback large processing times. The purpose of this work is two-fold: first, we introduce a new processing criterion to retrieve information about the location and shape of absorbing inclusions based on normalization to the background intensity, when no inhomogeneities are present. Second, we demonstrate the feasibility of including inhomogeneities in MC simulations implemented in graphics processing units, achieving large acceleration factors ( approximately 10(3)), thus providing an important tool for iteratively solving the forward problem to retrieve the optical properties of the inclusion. Results using a cw source are compared with MC outcomes showing very good agreement.