Reducing the noise effects in Logan graphic analysis for PET receptor measurements

Hongbin Guo, Kewei Chen, Rosemary Renaut, Eric M. Reiman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Logan's graphical analysis (LGA) is a widely-used approach for quantification of biochemical and physiological processes from Positron emission tomography (PET) image data. A well-noted problem associated with the LGA method is the bias in the estimated parameters. We recently systematically evaluated the bias associated with the linear model approximation and developed an alternative to minimize the bias due to model error. In this study, we examined the noise structure in the equations defining linear quantification methods, including LGA. The noise structure conflicts with the conditions given by the Gauss-Markov theorem for the least squares (LS) solution to generate the best linear unbiased estimator. By carefully taking care of the data error structure, we propose to use structured total least squares (STLS) to obtain the solution using a one-dimensional optimization problem. Simulations of PET data for [11C] benzothiazole-aniline (Pittsburgh Compound-B [PIB]) show that the proposed method significantly reduces the bias. We conclude that the bias associated with noise is primarily due to the unusual structure of he correlated noise and it can be reduced with the proposed STLS method.

Original languageEnglish (US)
Title of host publication2009 ICME International Conference on Complex Medical Engineering, CME 2009
DOIs
StatePublished - 2009
Event2009 ICME International Conference on Complex Medical Engineering, CME 2009 - Tempe, AZ, United States
Duration: Apr 9 2009Apr 11 2009

Other

Other2009 ICME International Conference on Complex Medical Engineering, CME 2009
CountryUnited States
CityTempe, AZ
Period4/9/094/11/09

Fingerprint

Positron emission tomography
Positron-Emission Tomography
Noise
Least-Squares Analysis
Aniline
Linear equations
Aniline Compounds
Biochemical Phenomena
Physiological Phenomena
Linear Models

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics

Cite this

Guo, H., Chen, K., Renaut, R., & Reiman, E. M. (2009). Reducing the noise effects in Logan graphic analysis for PET receptor measurements. In 2009 ICME International Conference on Complex Medical Engineering, CME 2009 [4906641] https://doi.org/10.1109/ICCME.2009.4906641

Reducing the noise effects in Logan graphic analysis for PET receptor measurements. / Guo, Hongbin; Chen, Kewei; Renaut, Rosemary; Reiman, Eric M.

2009 ICME International Conference on Complex Medical Engineering, CME 2009. 2009. 4906641.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Guo, H, Chen, K, Renaut, R & Reiman, EM 2009, Reducing the noise effects in Logan graphic analysis for PET receptor measurements. in 2009 ICME International Conference on Complex Medical Engineering, CME 2009., 4906641, 2009 ICME International Conference on Complex Medical Engineering, CME 2009, Tempe, AZ, United States, 4/9/09. https://doi.org/10.1109/ICCME.2009.4906641
Guo H, Chen K, Renaut R, Reiman EM. Reducing the noise effects in Logan graphic analysis for PET receptor measurements. In 2009 ICME International Conference on Complex Medical Engineering, CME 2009. 2009. 4906641 https://doi.org/10.1109/ICCME.2009.4906641
Guo, Hongbin ; Chen, Kewei ; Renaut, Rosemary ; Reiman, Eric M. / Reducing the noise effects in Logan graphic analysis for PET receptor measurements. 2009 ICME International Conference on Complex Medical Engineering, CME 2009. 2009.
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