Abstract
Adequate modeling of light propagation in the head is important to predict the sensitivity of NIRS signal and the spatial sensitivity profile of source-detector pairs. The 3D realistic head models of which the geometry is based upon the anatomical images acquired by magnetic resonance imaging and x-ray computed tomography are constructed to investigate the influence of the frontal sinus on the NIRS signal and spatial sensitivity. Light propagation in the head is strongly affected by the presence of the frontal sinus. The light tends to propagate around the frontal sinus. The influence of the frontal sinus on the sensitivity of the NIRS signal to the brain activation is not consistent and depends on the depth of the frontal sinus, the optical properties of the superficial tissues and the relative position between the source-detector pair and the frontal sinus. The frontal sinus located in the shallow region of the skull tends to reduce the sensitivity of the NIRS signal while the deep frontal sinus can increase the sensitivity of the NIRS signal.
Highlights
Near-infrared spectroscopy (NIRS) and optical imaging have been used to non-invasively measure cerebral oxygenation and hemodynamic changes associated with brain activation [1,2]
The time-resolved photon fluence maps in the head models with the whole frontal sinus (FS) and without the FS shown in Figs. 3(a) and 3(b), respectively, were predicted in order to evaluate the influence of the FS on light propagation in the head
0.404 broadened toward the lower side in the model with the deep FS. These results indicate that the increase in photon fluence around the FS affects the spatial sensitivity profile of the NIRS measurements
Summary
Near-infrared spectroscopy (NIRS) and optical imaging have been used to non-invasively measure cerebral oxygenation and hemodynamic changes associated with brain activation [1,2]. The geometry of the tissue boundaries is important for adequate modeling of light propagation in the head. The realistic head models, the structures of which are based upon magnetic resonance (MR) head images has been used to predict light propagation in the head for NIRS and optical imaging [17,18,19,20] These head models basically consisted of five types of tissues that imitate the scalp, skull, CSF, gray matter and white matter. A more sophisticated model, for instance, which includes the extra-cerebral vasculature, has been constructed to investigate the influence of the large pial vessels, such as sagittal sinus, on the diffuse optical imaging [21]
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