The simplified reference tissue model (SRTM) estimates the binding potential from an observed time activity curve without the need for aterial sampling. It assumes a one-tissue compartment model to describe the influx and efflux in the tissue region of interest and the reference region.
simplifiedReferenceTissueModel(
tac,
ref,
time,
SRTM2 = TRUE,
k2prime = NULL,
guess = c(R1 = 0.5, k2 = 0.01),
control = minpack.lm::nls.lm.control()
)Binding potential
Ratio of the volumes of distrubution for the tissue and reference region
Clearance rate constant from the tissue to plasma
Approximate standard error of the binding potential
Approximate standard error for the ratio
Approximate standard error for k2
a vector corresponding to the time activity curve from the tissue (in Bq/mL).
a vector corresponding to the time activity curve from the reference region (in Bq/mL).
a vector of average frame times (in minutes).
a logical value that selects the three-parameter model (SRTM) or the two-parameter model (SRTM2), where k2prime is fixed.
the value of k2prime that has been fixed.
values for the inital parameter estimates for R1 and k2.
a list of parameters used by nls.lm.control that are
set by default, but may be customized by the user.
Brandon Whitcher b.whitcher@gmail.com
See the references.
The model has been parameterized in the manner of Wu and Carson (2002). That is, the nonlinear regression estimates R1, k2 and k'2 for the three-parameter model (SRTM) and R1 and k2 for the two-parameter model (SRTM2).
The convolution is performed after interpolating the time activity curves, both for the tissue and the reference region, to one-second resolution then downsampling them back to the original sampling rate.
Lammertsma, A.A. and Hume, S.P. (1996) Simplified reference tissue model for PET receptor studies, NeuroImage, 4, 153-158.
Wu, Y. and Carson, R.E. (2002) Noise reduction in the simplified reference tissue model for neuroreceptor functional imaging, Journal of Cerebral Blood Flow & Metabolism, 22, 1440-1452.
deltamethod, expConv,
nls.lm