Optical tomographic brain imaging with diffusion and transport-theory-based algorithms

There has been considerable discussion concerning the effects of the cerebrospinal fluid on measurements of blood-related parameters in the human brain, and if diffusion-theory-based image reconstruction algorithms can accurately account for the light propagation in the head. All of these studies have been performed either with synthetic data generate from numerical models or from phantom studies. We present here the first comparative study that involves clinical data from optical tomographic measurements. Data obtained from the human forehead during a Valsalva maneuver were input to two different model-based iterative image reconstruction algorithms recently developed in our laboratories. One code is based on the equation of radiative transfer, while the other algorithm uses a diffusion model to describe the light propagation in the head. Both codes use finite-element formulations of the respective theories and were used to obtain three-dimensional volumetric images of oxy, dexoy and total hemoglobin. The reconstructed overall spatial heterogeneity in changes of these parameters is similar using both algorithms. The two codes differ mostly in the amplitude of the observed changes. In general the transport based codes reconstructs changes 10-40% stronger than the diffusion code.