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使用三层分析模型时脑血流扩散相关光谱测量的准确性

Accuracy of diffuse correlation spectroscopy measurements of cerebral blood flow when using a three-layer analytical model.

作者信息

Zhao Hongting, Sathialingam Eashani, Buckley Erin M

机构信息

Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, 1760 Haygood Dr. NE, Atlanta, GA 30322, USA.

Department of Pediatrics, Emory University School of Medicine, 2015 Uppergate Dr., Atlanta, GA 30322, USA.

出版信息

Biomed Opt Express. 2021 Oct 27;12(11):7149-7161. doi: 10.1364/BOE.438303. eCollection 2021 Nov 1.

Abstract

Diffuse correlation spectroscopy (DCS) is a non-invasive optical technology for the assessment of an index of cerebral blood flow (CBFi). Analytical methods that model the head as a three-layered medium (i.e., scalp, skull, brain) are becoming more commonly used to minimize the contribution of extracerebral layers to the measured DCS signal in adult cerebral blood flow studies. However, these models rely on knowledge of layer optical properties and thicknesses. Errors in these values can lead to errors in the estimation of CBFi, although the magnitude of this influence has not been rigorously characterized. Herein, we investigate the accuracy of measuring cerebral blood flow with a three-layer model when errors in layer optical properties or thicknesses are present. Through a series of experiments, we demonstrate that CBFi is highly sensitive to errors in brain optical properties and skull and scalp thicknesses. Relative changes in CBFi are less sensitive to optical properties but are influenced by errors in layer thickness. Thus, when using the three-layer model, accurate estimation of scalp and skull thickness are required for reliable results.

摘要

扩散相关光谱学(DCS)是一种用于评估脑血流指数(CBFi)的非侵入性光学技术。在成人大脑血流研究中,将头部建模为三层介质(即头皮、颅骨、大脑)的分析方法越来越普遍地被用于最小化脑外层对测量的DCS信号的贡献。然而,这些模型依赖于层光学特性和厚度的知识。尽管这种影响的程度尚未得到严格表征,但这些值的误差可能导致CBFi估计中的误差。在此,我们研究当层光学特性或厚度存在误差时,使用三层模型测量脑血流的准确性。通过一系列实验,我们证明CBFi对脑光学特性以及颅骨和头皮厚度的误差高度敏感。CBFi的相对变化对光学特性不太敏感,但受层厚度误差的影响。因此,使用三层模型时,为获得可靠结果需要准确估计头皮和颅骨厚度。

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