Influence of extracerebral layers on estimates of optical properties with continuous wave near infrared spectroscopy: analysis based on multi-layered brain tissue architecture and Monte Carlo simulation. (1st October 2019)

• Record Type: Journal Article
• Authors: Zhang, Yan; Liu, Xin; Wang, Qisong; Liu, Dan; Yang, Chunling; Sun, Jinwei
• Is Part Of: Computer assisted surgery. Volume 24(2019)Supplement 1
• Page Start: 144
• Page End: 150
• Publication Date: 2019-10-01
• Subjects: Near infrared spectroscopy -- Monte Carlo -- mean optical pathlength -- partial optical pathlength; Computer-assisted surgery -- Periodicals
• DOI: 10.1080/24699322.2018.1557902
• Languages: English
• ISSNs: 2469-9322

Abstract

Abstract: Continuous wave near-infrared spectroscopy (CW-NIRS) can be used to measure cerebral activity because it is noninvasive, simple and portable. However, the performance of the continuous wave near-infrared spectroscopy is distorted by the presence of extracerebral layer. Change of optical parameters in gray matter layer will then be inappropriately converted into the brain activity response. In the current study, a five-layer structure model constitute of scalp, skull, cerebrospinal fluid, gray matter and white matter, have been applied to fabricate human brain tissue. The phantom is made by the mixture of the Intralipid, India ink and agar. The optical parameters of gray matter layer can be flexibly adjusted to simulate the change of the deep brain tissue. The near infrared optical measurement system was designed to detect the changes in the absorption coefficients of the gray matter and quantitative analyze the influence of the extracerebral layers. Monte Carlo technique for the equivalent multi-layered brain tissue models is then performed to compensate partial volume effect introduced by the extracerebral layers. The results of the experiments suggested that the extracerebral layers influence the measurement and the influence of the extracerebral layers can be suppressed by correcting partial volume effect using Monte Carlo simulations.