Scalp and skull influence on near infrared photon propagation in the Colin27 brain template.

TitleScalp and skull influence on near infrared photon propagation in the Colin27 brain template.
Publication TypeJournal Article
Year of Publication2014
AuthorsStrangman GE, Zhang Q, Li Z
JournalNeuroImage
Volume85 Pt 1
Pagination136-49
Date Published2014 Jan 15
Abstract

Near-infrared neuromonitoring (NIN) is based on near-infrared spectroscopy (NIRS) measurements performed through the intact scalp and skull. Despite the important effects of overlying tissue layers on the measurement of brain hemodynamics, the influence of scalp and skull on NIN sensitivity are not well characterized. Using 3555 Monte Carlo simulations, we estimated the sensitivity of individual continuous-wave NIRS measurements to brain activity over the entire adult human head by introducing a small absorption perturbation to brain gray matter and quantifying the influence of scalp and skull thickness on this sensitivity. After segmenting the Colin27 template into five tissue types (scalp, skull, cerebrospinal fluid, gray matter and white matter), the average scalp thickness was 6.9±3.6mm (range: 3.6-11.2mm), while the average skull thickness was 6.0±1.9mm (range: 2.5-10.5mm). Mean NIN sensitivity - defined as the partial path length through gray matter divided by the total photon path length - ranged from 0.06 (i.e., 6% of total path length) at a 20mm source-detector separation, to over 0.19 at 50mm separations. NIN sensitivity varied substantially around the head, with occipital pole exhibiting the highest NIRS sensitivity to gray matter, whereas inferior frontal regions had the lowest sensitivity. Increased scalp and skull thickness were strongly associated with decreased sensitivity to brain tissue. Scalp thickness always exhibited a slightly larger effect on sensitivity than skull thickness, but the effect of both varied with SD separation. We quantitatively characterize sensitivity around the head as well as the effects of scalp and skull, which can be used to interpret NIN brain activation studies as well as guide the design, development and optimization of NIRS devices and sensors.

DOI10.1155/2013/638582
Alternate JournalNeuroimage