### Abstract

Conventional semi-infinite solution for extracting blood flow index (BFI) from diffuse correlation spectroscopy (DCS) measurements may cause errors in estimation of BFI (αD_{B}) in tissues with small volume and large curvature. We proposed an algorithm integrating Nth-order linear model of autocorrelation function with the Monte Carlo simulation of photon migrations in tissue for the extraction of αD_{B}. The volume and geometry of the measured tissue were incorporated in the Monte Carlo simulation, which overcome the semi-infinite restrictions. The algorithm was tested using computer simulations on four tissue models with varied volumes/geometries and applied on an in vivo stroke model of mouse. Computer simulations shows that the high-order (N¥ 5) linear algorithm was more accurate in extracting αD_{B} (errors < ±2%) from the noise-free DCS data than the semi-infinite solution (errors: -5.3% to -18.0%) for different tissue models. Although adding random noises to DCS data resulted in αD _{B} variations, the mean values of errors in extracting αD _{B} were similar to those reconstructed from the noise-free DCS data. In addition, the errors in extracting the relative changes of αD _{B} using both linear algorithm and semi-infinite solution were fairly small (errors < ±2.0%) and did not rely on the tissue volume/geometry. The experimental results from the in vivo stroke mice agreed with those in simulations, demonstrating the robustness of the linear algorithm. DCS with the high-order linear algorithm shows the potential for the inter-subject comparison and longitudinal monitoring of absolute BFI in a variety of tissues/organs with different volumes/geometries.

Original language | English |
---|---|

Article number | 193703 |

Journal | Applied Physics Letters |

Volume | 104 |

Issue number | 19 |

DOIs | |

State | Published - May 12 2014 |

### Fingerprint

### ASJC Scopus subject areas

- Physics and Astronomy (miscellaneous)

### Cite this

*Applied Physics Letters*,

*104*(19), [193703]. https://doi.org/10.1063/1.4876216

**Extraction of diffuse correlation spectroscopy flow index by integration of N th-order linear model with Monte Carlo simulation.** / Shang, Yu; Li, Ting; Chen, Lei; Lin, Yu; Toborek, Michal J; Yu, Guoqiang.

Research output: Contribution to journal › Article

*Applied Physics Letters*, vol. 104, no. 19, 193703. https://doi.org/10.1063/1.4876216

}

TY - JOUR

T1 - Extraction of diffuse correlation spectroscopy flow index by integration of N th-order linear model with Monte Carlo simulation

AU - Shang, Yu

AU - Li, Ting

AU - Chen, Lei

AU - Lin, Yu

AU - Toborek, Michal J

AU - Yu, Guoqiang

PY - 2014/5/12

Y1 - 2014/5/12

N2 - Conventional semi-infinite solution for extracting blood flow index (BFI) from diffuse correlation spectroscopy (DCS) measurements may cause errors in estimation of BFI (αDB) in tissues with small volume and large curvature. We proposed an algorithm integrating Nth-order linear model of autocorrelation function with the Monte Carlo simulation of photon migrations in tissue for the extraction of αDB. The volume and geometry of the measured tissue were incorporated in the Monte Carlo simulation, which overcome the semi-infinite restrictions. The algorithm was tested using computer simulations on four tissue models with varied volumes/geometries and applied on an in vivo stroke model of mouse. Computer simulations shows that the high-order (N¥ 5) linear algorithm was more accurate in extracting αDB (errors < ±2%) from the noise-free DCS data than the semi-infinite solution (errors: -5.3% to -18.0%) for different tissue models. Although adding random noises to DCS data resulted in αD B variations, the mean values of errors in extracting αD B were similar to those reconstructed from the noise-free DCS data. In addition, the errors in extracting the relative changes of αD B using both linear algorithm and semi-infinite solution were fairly small (errors < ±2.0%) and did not rely on the tissue volume/geometry. The experimental results from the in vivo stroke mice agreed with those in simulations, demonstrating the robustness of the linear algorithm. DCS with the high-order linear algorithm shows the potential for the inter-subject comparison and longitudinal monitoring of absolute BFI in a variety of tissues/organs with different volumes/geometries.

AB - Conventional semi-infinite solution for extracting blood flow index (BFI) from diffuse correlation spectroscopy (DCS) measurements may cause errors in estimation of BFI (αDB) in tissues with small volume and large curvature. We proposed an algorithm integrating Nth-order linear model of autocorrelation function with the Monte Carlo simulation of photon migrations in tissue for the extraction of αDB. The volume and geometry of the measured tissue were incorporated in the Monte Carlo simulation, which overcome the semi-infinite restrictions. The algorithm was tested using computer simulations on four tissue models with varied volumes/geometries and applied on an in vivo stroke model of mouse. Computer simulations shows that the high-order (N¥ 5) linear algorithm was more accurate in extracting αDB (errors < ±2%) from the noise-free DCS data than the semi-infinite solution (errors: -5.3% to -18.0%) for different tissue models. Although adding random noises to DCS data resulted in αD B variations, the mean values of errors in extracting αD B were similar to those reconstructed from the noise-free DCS data. In addition, the errors in extracting the relative changes of αD B using both linear algorithm and semi-infinite solution were fairly small (errors < ±2.0%) and did not rely on the tissue volume/geometry. The experimental results from the in vivo stroke mice agreed with those in simulations, demonstrating the robustness of the linear algorithm. DCS with the high-order linear algorithm shows the potential for the inter-subject comparison and longitudinal monitoring of absolute BFI in a variety of tissues/organs with different volumes/geometries.

UR - http://www.scopus.com/inward/record.url?scp=84900849618&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84900849618&partnerID=8YFLogxK

U2 - 10.1063/1.4876216

DO - 10.1063/1.4876216

M3 - Article

AN - SCOPUS:84900849618

VL - 104

JO - Applied Physics Letters

JF - Applied Physics Letters

SN - 0003-6951

IS - 19

M1 - 193703

ER -