Modeling venous plasma samples in $[^{18}\mathrm{F}]$ FDG PET studies: a nonlinear mixed-effects approach.

The gold-standard approach to quantifying dynamic PET images relies on using invasive measures of the arterial plasma tracer concentration. An attractive alternative is to employ an image-derived input function (IDIF), corrected for spillover effects and rescaled with venous plasma samples. However, venous samples are not always available for every participant. In this work, we used the nonlinear mixed-effects modeling approach to develop a model which infers venous tracer kinetics by using venous samples obtained from a population of healthy individuals and integrating subject-specific covariates. Population parameters (fixed effects), their between-subject variability (random effects), and the effects of covariates were estimated. The selected model will allow to reliably infer venous tracer kinetics in subjects with missing measurements. Clinical relevance - The derived model will be relevant for fully noninvasive dynamic FDG PET quantification using image-derived input functions in both healthy and patient populations when hemodynamics is not impaired.