Optimization of source-detector separation for non-invasive regional cerebral blood flow sensing

Autor: Hao Feng, Guang Han, Qianbei Guo, Huiquan Wang, Siqi Chen
Rok vydání: 2021
Předmět:
Zdroj: Infrared Physics & Technology. 117:103843
ISSN: 1350-4495
DOI: 10.1016/j.infrared.2021.103843
Popis: The detection of cerebral blood flow (CBF) has important clinical value for the diagnosis and treatment of ischemic cerebrovascular disease. The chronic changes of regional cerebral blood flow (rCBF) need long-term detection in specific cerebrovascular diseases such as Alzheimer's disease. In this paper, the optimal source-detector separation (SDS) in optical heterodyne detection combined with interferometric diffusing wave spectroscopy (OHD-iDWS) was studied. Changing the thickness of the skull and the absorption coefficient of the scalp layer, the Polarized Monte Carlo (PMC) method was used to analyze the influence of the average penetration depth and the number of polarized photons on SDS. In addition, the dynamic phantom experiments were used to evaluate the performance of the OHD-iDWS system. In this study, the system further explored the optimal SDS by distinguishing different flow rates, which provided an optimal method for SDS within 20 mm. Using PMC simulation and dynamic phantom experiments to find out the optimal SDS of rCBF sensing, it provides a theoretical basis for more effective detection of rCBF.
Databáze: OpenAIRE