A Nth-order linear algorithm for extracting diffuse correlation spectroscopy blood flow indices in heterogeneous tissues

Journal Article · Mon Sep 29 00:00:00 EDT 2014 · Applied Physics Letters

DOI:https://doi.org/10.1063/1.4896992· OSTI ID:22350833

Shang, Yu; Yu, Guoqiang ^[1]

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1. Department of Biomedical Engineering, University of Kentucky, Lexington, Kentucky 40506 (United States)

Conventional semi-infinite analytical solutions of correlation diffusion equation may lead to errors when calculating blood flow index (BFI) from diffuse correlation spectroscopy (DCS) measurements in tissues with irregular geometries. Very recently, we created an algorithm integrating a Nth-order linear model of autocorrelation function with the Monte Carlo simulation of photon migrations in homogenous tissues with arbitrary geometries for extraction of BFI (i.e., αD{sub B}). The purpose of this study is to extend the capability of the Nth-order linear algorithm for extracting BFI in heterogeneous tissues with arbitrary geometries. The previous linear algorithm was modified to extract BFIs in different types of tissues simultaneously through utilizing DCS data at multiple source-detector separations. We compared the proposed linear algorithm with the semi-infinite homogenous solution in a computer model of adult head with heterogeneous tissue layers of scalp, skull, cerebrospinal fluid, and brain. To test the capability of the linear algorithm for extracting relative changes of cerebral blood flow (rCBF) in deep brain, we assigned ten levels of αD{sub B} in the brain layer with a step decrement of 10% while maintaining αD{sub B} values constant in other layers. Simulation results demonstrate the accuracy (errors < 3%) of high-order (N ≥ 5) linear algorithm in extracting BFIs in different tissue layers and rCBF in deep brain. By contrast, the semi-infinite homogenous solution resulted in substantial errors in rCBF (34.5% ≤ errors ≤ 60.2%) and BFIs in different layers. The Nth-order linear model simplifies data analysis, thus allowing for online data processing and displaying. Future study will test this linear algorithm in heterogeneous tissues with different levels of blood flow variations and noises.

• OSTI ID: 22350833
• Journal Information: Applied Physics Letters, Vol. 105, Issue 13; Other Information: (c) 2014 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA); ISSN 0003-6951
• Country of Publication: United States
• Language: English

Related Subjects

75 CONDENSED MATTER PHYSICS
SUPERCONDUCTIVITY AND SUPERFLUIDITY
ACCURACY
ALGORITHMS
ANALYTICAL SOLUTION
ANIMAL TISSUES
BLOOD FLOW
BRAIN
CEREBROSPINAL FLUID
COMPUTERIZED SIMULATION
CORRELATIONS
DATA ANALYSIS
DATA PROCESSING
DIFFUSION EQUATIONS
EXTRACTION
LAYERS
MIGRATION
MONTE CARLO METHOD
NOISE
SPECTROSCOPY