A cautionary note on the use of positivity constrained reconstructions for quantification of regional PET imaging data


Conference Paper

Positively constrained maximum likelihood (ML) reconstructions in PET eliminate the negative values associated with unconstrained least squares (LS) - more commonly known as filtered back-projection (FBP). This is desirable for certain qualitative imaging tasks, however, it is not clear if there is a significant benefit for quantitative analysis of dynamic data. We consider a situation where the goal is to quantify the mean uptake in a tissue region of interest using data reconstructed with or without positivity constraints. A theoretical analysis is used to show that averaging unconstrained data is a sufficient statistic for estimation of the regional mean. This calculation casts some doubt over averaging constrained data. We use simulation sto investigate the effect of positivity constraint on mixture model analysis of dynamic data. The results show that the positivity constraint may cause bias in estimation of physiological parameters. © 2013 IEEE.

Full Text

Duke Authors

Cited Authors

  • Huang, J; Wolsztynski, E; Hawe, D; Kim, KM; Roy Choudhury, K; O'Sullivan, F

Published Date

  • January 1, 2013

Published In

International Standard Serial Number (ISSN)

  • 1095-7863

International Standard Book Number 13 (ISBN-13)

  • 9781479905348

Digital Object Identifier (DOI)

  • 10.1109/NSSMIC.2013.6829380

Citation Source

  • Scopus