We present an overview of the wide range of potential applications of optical methods for monitoring traumatic brain injury. The MEDLINE database was electronically searched with the following search terms: “traumatic brain injury,” “head injury,” or “head trauma,” and “optical methods,” “NIRS,” “near-infrared spectroscopy,” “cerebral oxygenation,” or “cerebral oximetry.” Original reports concerning human subjects published from January 1980 to June 2015 in English were analyzed. Fifty-four studies met our inclusion criteria. Optical methods have been tested for detection of intracranial lesions, monitoring brain oxygenation, assessment of brain perfusion, and evaluation of cerebral autoregulation or intracellular metabolic processes in the brain. Some studies have also examined the applicability of optical methods during the recovery phase of traumatic brain injury . The limitations of currently available optical methods and promising directions of future development are described in this review. Considering the outstanding technical challenges, the limited number of patients studied, and the mixed results and opinions gathered from other reviews on this subject, we believe that optical methods must remain primarily research tools for the present. More studies are needed to gain confidence in the use of these techniques for neuromonitoring of traumatic brain injury patients.

Parameter recovery in diffuse optical tomography is a computationally expensive algorithm, especially when used for large and complex volumes, as in the case of human brain functional imaging. The modeling of light propagation, also known as the forward problem, is the computational bottleneck of the recovery algorithm, whereby the lack of a real-time solution is impeding practical and clinical applications. The objective of this work is the acceleration of the forward model, within a diffusion approximation-based finite-element modeling framework, employing parallelization to expedite the calculation of light propagation in realistic adult head models. The proposed methodology is applicable for modeling both continuous wave and frequency-domain systems with the results demonstrating a 10-fold speed increase when GPU architectures are available, while maintaining high accuracy. It is shown that, for a very high-resolution finite-element model of the adult human head with ∼600,000 nodes, consisting of heterogeneous layers, light propagation can be calculated at ∼0.25  s/excitation source.

Recently, a method for the estimation of speed distribution of particles moving in an optically turbid medium has been proposed. The method allows potentially absolute measurement of speed of the particles and can be applied in laser-Doppler perfusion measurements. However, the decomposition technique was limited to short source-detector separations for which the assumption that one photon is Doppler scattered not more than once is fulfilled. In the present paper we show a generalized decomposition technique in which photons can be scattered more than once. We show the theoretical background for decomposition in such a case. We apply a decomposition method for the analysis of laser-Doppler spectra obtained by Monte Carlo simulations. This analysis allows showing noise limits in which the technique can be effectively applied in analysis of measured spectra. We propose an approximated scattering model based on the assumption that for one photon consecutive Doppler scattering events occur on particles moving with the same speed, and we show that this approximation does not influence significantly the uncertainty of the resulting speed distribution. The proposed decomposition procedure is validated in measurements on a physical flow model. The decomposition procedure is also validated by analysis of spectra measured on a physical phantom using laser-Doppler flow meter (Oxford Optronix, UK). A diluted solution of milk was pumped through a tube fixed in an optically turbid material with speed varying from 0 mm s(-1) to 4 mm s(-1). We observed a linear relation between actual speed of milk solution and speed estimated from results of spectra decomposition.

Time-domain optical brain imaging techniques introduce a number of different measurands for analyzing absorption changes located deep in the tissue, complicated by superficial absorption changes and noise. We implement a method that allows analysis, quantitative comparison and performance ranking of measurands under various conditions – including different values of reduced scattering coefficient, thickness of the superficial layer, and source-detector separation. Liquid phantom measurements and Monte Carlo simulations were carried out in two-layered geometry to acquire distributions of times of flight of photons and to calculate the total photon count, mean time of flight, variance, photon counts in time windows and ratios of photon counts in different time windows. Quantitative comparison of performance was based on objective metrics: relative contrast, contrast-to-noise ratio (CNR) and depth selectivity. Moreover, the product of CNR and depth selectivity was used to rank the overall performance and to determine the optimal source-detector separation for each measurand. Variance ranks the highest under all considered conditions.