feng_1tc_tac: Feng input model convolved with a 1TC IRF

In mathesong/kinfitr: Kinetic Modelling of PET Time Activity Curves

Feng input model convolved with a 1TC IRF

Description

This function is intended for describing a TAC, such as the reference region TAC. The parameters are not meant to be interpreted as true values, but merely as a guide for interpolating the measured curve through a parametric description. For this reason, there are no upper and lower limits, because completely incorrect values can be helpful for interpolating our measured TACs more closely.

Usage

feng_1tc_tac(
  t_tac,
  tac,
  weights = NULL,
  fit_t0 = TRUE,
  frameStartEnd = NULL,
  multstart_iter = 500
)

Arguments

t_tac	Numeric vector of times for each frame in minutes. We use the time halfway through the frame as well as a zero. If a time zero frame is not included, it will be added.
tac	Numeric vector of radioactivity concentrations in the tissue for each frame. We include zero at time zero: if not included, it is added.
weights	Optional. Numeric vector of the weights assigned to each frame in the fitting. We include zero at time zero: if not included, it is added. If not specified, uniform weights will be used.
fit_t0	Should a time zero point be fitted? If TRUE, the model can accommodate zero values in the TAC before rising. If FALSE, the TAC must rise at time = 0.
frameStartEnd	Optional. This allows one to specify the beginning and final frame to use for modelling, e.g. c(1,20).
multstart_iter	Number of iterations for starting parameters. Default is 500. For more information, see nls_multstart.

Value

A list with a data frame of the fitted parameters out$par, their percentage standard errors out$par.se, the model fit object out$fit, the model weights out$weights, and a dataframe containing the TACs both of the data and the fitted values out$tacs.

Author(s)

Granville J Matheson, [e-mail]

References

Jiao, J. et al, 2023. NiftyPAD-Novel Python Package for Quantitative Analysis of Dynamic PET Data. Neuroinformatics, pp.1-12. Matheson, G.J & Ogden, R.T., in preparation. SiMBA for Reference Tissue Models.

Examples

data(simref)

t_tac <- simref$tacs[[2]]$Times
tac <- simref$tacs[[2]]$Reference
weights <- simref$tacs[[2]]$Weights

fit <- feng_1tc_tac(t_tac, tac, weights)

mathesong/kinfitr documentation built on Jan. 15, 2024, 11:07 p.m.