The accuracy of near infrared spectroscopy and imaging during focal changes in cerebral hemodynamics.

Near infrared spectroscopy (NIRS) can detect changes in the concentrations of oxy-hemoglobin ([HbO]) and deoxy-hemoglobin ([Hb]) in tissue based upon differential absorption at multiple wavelengths. The common analysis of NIRS data uses the modified Beer-Lambert law, which is an empirical formulation that assumes global concentration changes. We used simulations to examine the errors that result when this analysis is applied to focal hemodynamic changes, and we performed simultaneous NIRS measurements during a motor task in adult humans and a neonate to evaluate the dependence of the measured changes on detector-probe geometry. For both simulations and in vivo measurements, the wide range of NIRS results was compared to an imaging analysis, diffuse optical tomography (DOT). The results demonstrate that relative changes in [HbO] and [Hb] cannot, in general, be quantified with NIRS. In contrast to that method, DOT analysis was shown to accurately quantify simulated changes in chromophore concentrations. These results and the general principles suggest that DOT can accurately measure changes in [Hb] and [HbO], but NIRS cannot accurately determine even relative focal changes in these chromophore concentrations. For the standard NIRS analysis to become more accurate for focal changes, it must account for the position of the focal change relative to the source and detector as well as the wavelength dependent optical properties of the medium.

Simultaneous imaging and optode calibration with diffuse optical tomography.

In order for diffuse optical tomography to realize its potential of obtaining quantitative images of spatially varying optical properties within random media, several potential experimental systematic errors must be overcome. One of these errors is the calibration of the emitter strength and detector efficiency/gain. While in principle these parameters can be determined accurately prior to an imaging experiment, slight fluctuations will cause significant image artifacts. For this reason, it is necessary to consider including their calibration as part of the inverse problem for image reconstruction. In this paper, we show that this can be done successfully in a linear reconstruction model with simulated continuous-wave data. The technique is general for frequency and time domain data.

A comparison study of linear reconstruction techniques for diffuse optical tomographic imaging of absorption coefficient.

We compare, through simulations, the performance of four linear algorithms for diffuse optical tomographic reconstruction of the three-dimensional distribution of absorption coefficient within a highly scattering medium using the diffuse photon density wave approximation. The simulation geometry consisted of a coplanar array of sources and detectors at the boundary of a half-space medium. The forward solution matrix is both underdetermined, because we estimate many more absorption coefficient voxels than we have measurements, and ill-conditioned, due to the ill-posedness of the inverse problem. We compare two algebraic techniques, ART and SIRT, and two subspace techniques, the truncated SVD and CG algorithms. We compare three-dimensional reconstructions with two-dimensional reconstructions which assume all inhomogeneities are confined to a known horizontal slab, and we consider two 'object-based' error metrics in addition to mean square reconstruction error. We include a comparison using simulated data generated using a different FDFD method with the same inversion algorithms to indicate how our conclusions are affected in a somewhat more realistic scenario. Our results show that the subspace techniques are superior to the algebraic techniques in localization of inhomogeneities and estimation of their amplitude, that two-dimensional reconstructions are sensitive to underestimation of the object depth, and that an error measure based on a location parameter can be a useful complement to mean squared error.

Three-dimensional images generated by quadrature interferometry.

Quadrature detection techniques have been applied to images obtained from a Mach-Zehnder interferometer with differently polarized beams to yield the real and the imaginary parts of the diffracted fields simultaneously. This approach eliminates the need for phase retrieval by providing complete information on the complex amplitude of the diffracted signal. We present results in which we demonstrate our ability to reconstruct two- and three-dimensional microscopic objects from their complex diffraction patterns.