Effect of head model on Monte Carlo modeling of spatial sensitivity distribution for functional near-infrared spectroscopy

Ting Li,Liyuan Peng,Yan Li,Yunlong Sun,Meixue Duan

doi:10.1142/s1793545815500248

Abstract

Modeling Light propagation within human head to deduce spatial sensitivity distribution (SSD) is important for Near-infrared spectroscopy (NIRS)/imaging (NIRI) and diffuse correlation tomography. Lots of head models have been used on this issue, including layered head model, artificial simplified head model, MRI slices described head model, and visible human head model. Hereinto, visible Chinese human (VCH) head model is considered to be a most faithful presentation of anatomical structure, and has been highlighted to be employed in modeling light propagation. However, it is not practical for all researchers to use VCH head models and actually increasing number of people are using magnet resonance imaging (MRI) head models. Here, all the above head models were simulated and compared, and we focused on the effect of using different head models on predictions of SSD. Our results were in line with the previous reports on the effect of cerebral cortex folding geometry. Moreover, the influence on SSD increases with the fidelity of head models. And surprisingly, the SSD percentages in scalp and gray matter (region of interest) in MRI head model were found to be 80% and 125% higher than in VCH head model. MRI head models induced nonignorable discrepancy in SSD estimation when compared with VCH head model. This study, as we believe, is the first to focus on comparison among full serials of head model on estimating SSD, and provided quantitative evidence for MRI head model users to calibrate their SSD estimation.

Highlights

Characterization of human tissue blood oxygenation, blood volume, and blood °ow in brain is important for diagnosis and therapeutic assessment of brain function and vascular/cellular diseases.[1,2,3,4] Near-infrared spectroscopy (NIRS) and imaging (NIRI) have been applied to measure changes of blood oxygenation and volume of the brain tissue, which are caused by functional brain activity.[1,2,5] These traditional NIRS has been already widely accepted by research and clinics as a simple, fast, portable, low-cost, and nonionizing technique for noninvasive quantication of blood oxygenation-represented brain functional activities
The light propagation in a layered head model, an articial head model with sulci slots, Zubal MRI head model, and visible chinese human (VCH) head model was computed by Monte Carlo method, thedelity of which increased successively
We observed that the distortion of the brain structure enhanced with thedelity of the head model while the spatial sensitivity prole in VCH head model showed strong e®ects on the complex brain structure

Summary

Introduction

Characterization of human tissue blood oxygenation, blood volume, and blood °ow in brain is important for diagnosis and therapeutic assessment of brain function and vascular/cellular diseases.[1,2,3,4] Near-infrared spectroscopy (NIRS) and imaging (NIRI) have been applied to measure changes of blood oxygenation and volume of the brain tissue, which are caused by functional brain activity.[1,2,5] These traditional NIRS has been already widely accepted by research and clinics as a simple, fast, portable, low-cost, and nonionizing technique for noninvasive quantication of blood oxygenation-represented brain functional activities. An emerging dynamic NIR methodology, di®use correlation spectroscopy (DCS),[3,4] has been developed to measure blood °ow in brain microvasculature. DCS has been combined with NIRS in hybrid instruments and truly portable models.[4] Challenge remains for all these techniques in the precision or spatial resolution. Precise modeling of light propagation in the head to deduce the spatial sensitivity prole is crucial to improve precision/spatial resolution of all the above NIR technologies.[3,4,6,7]

Methods

Results

Conclusion