PET kinetic analysis: Error consideration of quantitative analysis in dynamic studies

Yoko Ikoma; Hiroshi Watabe; Miho Shidahara; Mika Naganawa; Yuichi Kimura

doi:10.1007/s12149-007-0083-2

PET kinetic analysis: Error consideration of quantitative analysis in dynamic studies

Yoko Ikoma, Hiroshi Watabe, Miho Shidahara, Mika Naganawa, Yuichi Kimura

Research output: Contribution to journal › Review article › peer-review

20 Citations (Scopus)

Abstract

Positron emission tomography dynamic studies have been performed to quantify several biomedical functions. In a quantitative analysis of these studies, kinetic parameters were estimated by mathematical methods, such as a nonlinear least-squares algorithm with compartmental model and graphical analysis. In this estimation, the uncertainty in the estimated kinetic parameters depends on the signal-to-noise ratio and quantitative analysis method. This review describes the reliability of parameter estimates for various analysis methods in reversible and irreversible models.

Original language	English
Pages (from-to)	1-11
Number of pages	11
Journal	Annals of Nuclear Medicine
Volume	22
Issue number	1
DOIs	https://doi.org/10.1007/s12149-007-0083-2
Publication status	Published - 2008 Jan 1
Externally published	Yes

Keywords

Compartmental model
Error analysis
PET

ASJC Scopus subject areas

Radiology Nuclear Medicine and imaging

Access to Document

10.1007/s12149-007-0083-2

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AU - Watabe, Hiroshi

AU - Shidahara, Miho

AU - Naganawa, Mika

AU - Kimura, Yuichi

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AB - Positron emission tomography dynamic studies have been performed to quantify several biomedical functions. In a quantitative analysis of these studies, kinetic parameters were estimated by mathematical methods, such as a nonlinear least-squares algorithm with compartmental model and graphical analysis. In this estimation, the uncertainty in the estimated kinetic parameters depends on the signal-to-noise ratio and quantitative analysis method. This review describes the reliability of parameter estimates for various analysis methods in reversible and irreversible models.

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