Application limits of the scaling relations for Monte Carlo simulations in diffuse optics. Part 1: theory.

Monte Carlo (MC) is a powerful tool to study photon migration in scattering media, yet quite time-consuming to solve inverse problems. To speed up MC-simulations, scaling relations can be applied to an existing initial MC-simulation to generate a new data-set with different optical properties. We named this approach trajectory-based since it uses the knowledge of the detected photon trajectories of the initial MC-simulation, in opposition to the slower photon-based approach, where a novel MC-simulation is rerun with new optical properties. We investigated the convergence and applicability limits of the scaling relations, both related to the likelihood that the sample of trajectories considered is representative also for the new optical properties. For absorption, the scaling relation contains smoothly converging Lambert-Beer factors, whereas for scattering it is the product of two quickly diverging factors, whose ratio, for NIRS cases, can easily reach ten orders of magnitude. We investigated such instability by studying the probability-distribution for the number of scattering events in trajectories of given length. We propose a convergence test of the scattering scaling relation based on the minimum-maximum number of scattering events in recorded trajectories. We also studied the dependence of MC-simulations on optical properties, most critical in inverse problems, finding that scattering derivatives are ascribed to small deviations in the distribution of scattering events from a Poisson distribution. This paper, which can also serve as a tutorial, helps to understand the physics of the scaling relations with the causes of their limitations and devise new strategies to deal with them.

Detectability of hemodynamic oscillations in cerebral cortex through functional near-infrared spectroscopy: a simulation study.

Significance: We explore the feasibility of using time-domain (TD) and continuous-wave (CW) functional near-infrared spectroscopy (fNIRS) to monitor brain hemodynamic oscillations during resting-state activity in humans, a phenomenon that is of increasing interest in the scientific and medical community and appears to be crucial to advancing the understanding of both healthy and pathological brain functioning. Aim: Our general object is to maximize fNIRS sensitivity to brain resting-state oscillations. More specifically, we aim to define comprehensive guidelines for optimizing main operational parameters in fNIRS measurements [average photon count rate, measurement length, sampling frequency, and source-detector distance (SSD)]. In addition, we compare TD and CW fNIRS performance for the detection and localization of oscillations. Approach: A series of synthetic TD and CW fNIRS signals were generated by exploiting the solution of the diffusion equation for two different geometries of the probed medium: a homogeneous medium and a bilayer medium. Known and periodical perturbations of the concentrations of oxy- and deoxy-hemoglobin were imposed in the medium, determining changes in its optical properties. The homogeneous slab model was used to determine the effect of multiple measurement parameters on fNIRS sensitivity to oscillatory phenomena, and the bilayer model was used to evaluate and compare the abilities of TD and CW fNIRS in detecting and isolating oscillations occurring at different depths. For TD fNIRS, two approaches to enhance depth-selectivity were evaluated: first, a time-windowing of the photon distribution of time-of-flight was performed, and then, the time-dependent mean partial pathlength (TMPP) method was used to retrieve the hemoglobin concentrations in the medium. Results: In the homogeneous medium case, the sensitivity of TD and CW fNIRS to periodical perturbations of the optical properties increases proportionally with the average photon count rate, the measurement length, and the sampling frequency and approximatively with the square of the SSD. In the bilayer medium case, the time-windowing method can detect and correctly localize the presence of oscillatory components in the TD fNIRS signal, even in the presence of very low photon count rates. The TMPP method demonstrates how to correctly retrieve the periodical variation of hemoglobin at different depths from the TD fNIRS signal acquired at a single SSD. For CW fNIRS, measurements taken at typical SSDs used for short-separation channel regression show notable sensitivity to oscillations occurring in the deep layer, challenging the assumptions underlying this correction method when the focus is on analyzing oscillatory phenomena. Conclusions: We demonstrated that the TD fNIRS technique allows for the detection and depth-localization of periodical fluctuations of the hemoglobin concentrations within the probed medium using an acquisition at a single SSD, offering an alternative to multi-distance CW fNIRS setups. Moreover, we offered some valuable guidelines that can assist researchers in defining optimal experimental protocols for fNIRS studies.

Statistics of maximum photon penetration depth in a two-layer diffusive medium.

We present numerical results for the probability density function f(z) and for the mean value of photon maximum penetration depth zmax> in a two-layer diffusive medium. Both time domain and continuous wave regime are considered with several combinations of the optical properties (absorption coefficient, reduced scattering coefficient) of the two layers, and with different geometrical configurations (source detector distance, thickness of the upper layer). Practical considerations on the design of time domain and continuous wave systems are derived. The methods and the results are of interest for many research fields such as biomedical optics and advanced microscopy.

Erratum: Assessment of power spectral density of microvascular hemodynamics in skeletal muscles at very low and low-frequency via near-infrared diffuse optical spectroscopies: erratum.

[This corrects the article on p. 5994 in vol. 14, PMID: 38021143.].

Non-Invasive Monitoring of Microvascular Oxygenation and Reactive Hyperemia using Hybrid, Near-Infrared Diffuse Optical Spectroscopy for Critical Care.

The detection of levels of impairment in microvascular oxygen consumption and reactive hyperemia is vital in critical care. However, there are no practical means for a robust and quantitative evaluation. This paper describes a protocol to evaluate these impairments using a hybrid near-infrared diffuse optical device. The device contains modules for near-infrared time-resolved and diffuse correlation spectroscopies and pulse-oximetry. These modules allow the non-invasive, continuous, and real-time measurement of the absolute, microvascular blood/tissue oxygen saturation (StO2) and the blood flow index (BFI) along with the peripheral arterial oxygen saturation (SpO2). This device uses an integrated, computer-controlled tourniquet system to execute a standardized protocol with optical data acquisition from the brachioradialis muscle. The standardized vascular occlusion test (VOT) takes care of the variations in the occlusion duration and pressure reported in the literature, while the automation minimizes inter-operator differences. The protocol we describe focuses on a 3-min occlusion period but the details described in this paper can readily be adapted to other durations and cuff pressures, as well as other muscles. The inclusion of an extended baseline and post-occlusion recovery period measurement allows the quantification of the baseline values for all the parameters and the blood/tissue deoxygenation rate that corresponds to the metabolic rate of oxygen consumption. Once the cuff is released, we characterize the tissue reoxygenation rate, magnitude, and duration of the hyperemic response in BFI and StO2. These latter parameters correspond to the quantification of the reactive hyperemia, which provides information about the endothelial function. Furthermore, the above-mentioned measurements of the absolute concentration of oxygenated and deoxygenated hemoglobin, BFI, the derived metabolic rate of oxygen consumption, StO2, and SpO2 provide a yet-to-be-explored rich data set that can exhibit disease severity, personalized therapeutics, and management interventions.