### Abstract

Logan's graphical model is a robust estimation of the total distribution volume (DVt) of reversibly bound radio-pharmaceuticals, but the resulting DVt values decrease with increasing noise. The authors hypothesized that the noise dependence can be reduced by a linear regression model that minimizes the sum of squared perpendicular rather than vertical (y) distances between the data points and fitted straight line. To test the new method, 15 levels of simulated noise (repeated 2,000 times) were added to synthetic tissue activity curves, calculated from two different sets of kinetic parameters. Contrary to the traditional method, there was no (P > 0.05) or dramatically decreased noise dependence with the perpendicular model. Real dynamic ^{11}C (+) McN5652 serotonin transporter binding data were processed either by applying Logan analysis to average counts of large areas or by averaging the Logan slopes of individual-voxel data. There were no significant differences between the parameters when the perpendicular regression method was used with both approaches. The presented experiments show that the DVt calculated from the Logan plot is much less noise dependent if the linear regression model accounts for errors in both the x and y variables, allowing fast creation of unbiased parametric images from dynamic positron-emission tomography studies.

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

Pages (from-to) | 240-244 |

Number of pages | 5 |

Journal | Journal of Cerebral Blood Flow and Metabolism |

Volume | 22 |

Issue number | 2 |

Publication status | Published - 2002 |

### Fingerprint

### Keywords

- Graphical analysis
- Logan plot
- Positron emission tomography

### ASJC Scopus subject areas

- Endocrinology
- Neuroscience(all)
- Endocrinology, Diabetes and Metabolism

### Cite this

*Journal of Cerebral Blood Flow and Metabolism*,

*22*(2), 240-244.

**Modified regression model for the Logan plot.** / Varga, J.; Szabo, Zsolt.

Research output: Contribution to journal › Article

*Journal of Cerebral Blood Flow and Metabolism*, vol. 22, no. 2, pp. 240-244.

}

TY - JOUR

T1 - Modified regression model for the Logan plot

AU - Varga, J.

AU - Szabo, Zsolt

PY - 2002

Y1 - 2002

N2 - Logan's graphical model is a robust estimation of the total distribution volume (DVt) of reversibly bound radio-pharmaceuticals, but the resulting DVt values decrease with increasing noise. The authors hypothesized that the noise dependence can be reduced by a linear regression model that minimizes the sum of squared perpendicular rather than vertical (y) distances between the data points and fitted straight line. To test the new method, 15 levels of simulated noise (repeated 2,000 times) were added to synthetic tissue activity curves, calculated from two different sets of kinetic parameters. Contrary to the traditional method, there was no (P > 0.05) or dramatically decreased noise dependence with the perpendicular model. Real dynamic 11C (+) McN5652 serotonin transporter binding data were processed either by applying Logan analysis to average counts of large areas or by averaging the Logan slopes of individual-voxel data. There were no significant differences between the parameters when the perpendicular regression method was used with both approaches. The presented experiments show that the DVt calculated from the Logan plot is much less noise dependent if the linear regression model accounts for errors in both the x and y variables, allowing fast creation of unbiased parametric images from dynamic positron-emission tomography studies.

AB - Logan's graphical model is a robust estimation of the total distribution volume (DVt) of reversibly bound radio-pharmaceuticals, but the resulting DVt values decrease with increasing noise. The authors hypothesized that the noise dependence can be reduced by a linear regression model that minimizes the sum of squared perpendicular rather than vertical (y) distances between the data points and fitted straight line. To test the new method, 15 levels of simulated noise (repeated 2,000 times) were added to synthetic tissue activity curves, calculated from two different sets of kinetic parameters. Contrary to the traditional method, there was no (P > 0.05) or dramatically decreased noise dependence with the perpendicular model. Real dynamic 11C (+) McN5652 serotonin transporter binding data were processed either by applying Logan analysis to average counts of large areas or by averaging the Logan slopes of individual-voxel data. There were no significant differences between the parameters when the perpendicular regression method was used with both approaches. The presented experiments show that the DVt calculated from the Logan plot is much less noise dependent if the linear regression model accounts for errors in both the x and y variables, allowing fast creation of unbiased parametric images from dynamic positron-emission tomography studies.

KW - Graphical analysis

KW - Logan plot

KW - Positron emission tomography

UR - http://www.scopus.com/inward/record.url?scp=0036168351&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0036168351&partnerID=8YFLogxK

M3 - Article

C2 - 11823722

AN - SCOPUS:0036168351

VL - 22

SP - 240

EP - 244

JO - Journal of Cerebral Blood Flow and Metabolism

JF - Journal of Cerebral Blood Flow and Metabolism

SN - 0271-678X

IS - 2

ER -