### Abstract

To improve the reliability and sensitivity of quantitative analysis in the study and evaluation of brain tumor using Ga-68 EDTA dynamic PET, a linear parametric imaging algorithm was developed in this study for estimation of both distribution volume (DV) and blood brain barrier permeability. F statistics was used for separating tumor from normal tissue. A two-compartmental model was used to describe the tracer kinetics. The operational equations: C_{pet} = (K_{1}+k_{2}V_{p})∫C_{p}ds - k_{2}∫C_{pet}ds V_{p}C_{p} and ∫C_{pet}=(DV+V_{p}) ∫C_{p}ds - (1/k_{2})C_{pet} +(V_{p}/k_{2})C_{p}, were used to estimate K_{1} (permeability) and DV (=K_{1}/k_{2}), respectively. A reliable and robust linear regression with spatial constraint parametric imaging algorithm was developed to generate the K_{1} and DV images. Pixel-wise F statistics with 2 and k-2 degree of freedom was calculated as: F=((k-2)k/(2(k^{2}-1)))D^{2} with D^{2} = (x-μ)′S^{-1}(x-μ), where the sample is from two dimensional sample space {(K_{1}, DV)} of reference regions in normal brain tissue pixels, the sample size k is the number of pixels within the normal reference ROIs, μ and S are, respectively, the sample mean vector (K_{1}, DV) and covariance matrix. By setting critical α values at 0.2, 0.05, and 0.001, statistical significance level images were generated, and its pixel values can be, 0 if F< F_{0.2}, 1 if F_{0.2}=<F< F_{0.05}, 2 if F_{0.05}=<F< F_{0.01}, and 3 if F_{0.01}<=F. The methods were applied to eleven brain tumor Ga-68 EDAT dynamic PET studies. Results shown that the DV, K_{1}, and F images are of good image quality. A highly correlated linear relationship (R^{2}>0.92) was found between the values of K_{1} and DV estimated by model fitting to ROI time activity curve and ones calculated from parametric images. The method for generating K_{1}, DV, F, and significance level images is of high computation efficiency and is easy to be implemented. The statistical model developed in the current study provided a tool to integrate the multi-dimensional physiological information. The normal reference region method and the integration of multi-physiological images may improve the sensitivity and specificity of brain tumor detection and evaluation of treatment.

Original language | English |
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Pages | 1072-1078 |

Number of pages | 7 |

State | Published - Dec 1 2001 |

Externally published | Yes |

Event | 2001 IEEE Nuclear Science Symposium Conference Record - San Diege, CA, United States Duration: Nov 4 2001 → Nov 10 2001 |

### Conference

Conference | 2001 IEEE Nuclear Science Symposium Conference Record |
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Country | United States |

City | San Diege, CA |

Period | 11/4/01 → 11/10/01 |

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## Cite this

*Parametric imaging and statistical mapping of brain tumor in Ga-68 EDTA dynamic PET studies*. 1072-1078. Paper presented at 2001 IEEE Nuclear Science Symposium Conference Record, San Diege, CA, United States.