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Noninvasive estimation of the input function for dynamic mouse 18F-FDG MicroPET studies

  • Wei Mu
  • , Zhe Chen
  • , Xiaoqian Dai
  • , Jie Tian*
  • *Corresponding author for this work
  • CAS - Institute of Automation

Research output: Contribution to journalArticlepeer-review

Abstract

A new noninvasive estimation method for the plasma time-activity curve, i.e., input function (IF) of the tracer kinetic model in dynamic 18F-FDG microPET mouse studies, is proposed and validated. This estimation method comprises of four steps. First, a novel constraint nonnegative matrix factorization segmentation algorithm was applied to extract the left ventricle (Lv) and myocardium (Myo) time activity curves (TACs). Second, we modeled the IF as a seven-parameter mathematical equation and constructed a dual-output model of the real TAC in Lv and Myo accounting for the partial-volume and spillover effects. Then, we fit the image-derived Lv and Myo TACs to the dual-output model to estimate the parameters of the IF. Finally, the IF was validated by comparing it to the gold standard IF while considering the delay and dispersion effects. Our method was verified based on 20 mice datasets from the Mouse Quantitation Program database, provided by UCLA. The error of the areas under the curves between the delayed and dispersed estimated IF and the gold standard IF was 7.237% ± 6.742% (r = 0.969), and the error of the 18 F-FDG influx constant Ki of the Myo was 4.910% ± 6.810% (r = 0.992). The results demonstrated the effectiveness of the proposed method.

Original languageEnglish
Article number6544251
Pages (from-to)3103-3112
Number of pages10
JournalIEEE Transactions on Biomedical Engineering
Volume60
Issue number11
DOIs
StatePublished - 2013
Externally publishedYes

Keywords

  • Bayesian penalty term
  • constraint nonnegative matrix factorization (CNMF)
  • delay and dispersion effects
  • input function
  • partial-volume and spillover effects

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