TY - JOUR T1 - Plasma metabolite correction: Improvements of current parent plasma models JF - Journal of Nuclear Medicine JO - J Nucl Med SP - 43 LP - 43 VL - 54 IS - supplement 2 AU - Matteo Tonietto AU - Gaia Rizzo AU - Mattia Veronese AU - Paolo Zanotti-Fregonara AU - Talakad Lohith AU - Masahiro Fujita AU - Sami Zoghbi AU - Robert Innis AU - Alessandra Bertoldo Y1 - 2013/05/01 UR - http://jnm.snmjournals.org/content/54/supplement_2/43.abstract N2 - 43 Objectives Quantitative PET studies using an arterial input function often require the correction of the measured total plasma activity for the presence of radiometabolites. This is achieved by fitting a Parent Plasma fraction (PPf) model to discrete HPLC measurements. This study aims to improve PPf model description by taking into account the duration of tracer injection. Methods PPf models are categorized into three classes: power, Hill and exponential type [1]. These models were modified by taking into account the tracer injection time (convoluted models) and then compared to their relative unmodified models using two datasets, [11C]NOP-1A (n=18)and [11C](R)-rolipram (n=20) both with an injection time of 1 min. Model parameter estimates were obtained by using nonlinear maximum likelihood estimator with a relative weighting scheme based on HPLC measurements. Weighted Residuals Sum of Squares (WRSS), parameters precision and weighted residuals analysis were used as performance indices. Results The convoluted models always reached lower WRSS (up to 32%) than the corresponding unmodified models. A Hill type convoluted model was selected for both data sets, showing a very low estimation error for all the parameters and weighted residuals in agreement with the statistical assumptions, i.e. mean = 0, variance = 1, uncorrelated. The other models led to low parameter precision (power type convoluted) or poor data fits (exponential type convoluted). Conclusions Taking into account the duration of tracer injection improves the description of the PPf data modeling without introducing any new parameter. This may have an impact on the quantification of physiological parameters. [1] Oikonen, 2003 (Turku PET Centre Modelling report) ER -