lin2tcm: Linear Two Tissue Compartment Model

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

Linear Two Tissue Compartment Model

Description

Function to fit the linearised 2TCM function.

Usage

lin2tcm(
  t_tac,
  tac,
  input,
  weights = NULL,
  inpshift = 0,
  vB = NULL,
  dur = NULL,
  frameStartEnd = NULL
)

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 target tissue for each frame. We include zero at time zero: if not included, it is added.
input	Data frame containing the blood, plasma, and parent fraction concentrations over time. This can be generated using the blood_interp function.
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.
inpshift	Optional. The number of minutes by which to shift the timing of the input data frame forwards or backwards. If not specified, this will be set to 0. This can be fitted using 1TCM or 2TCM.
vB	Optional. The blood volume fraction. If not specified, this will be fitted. If specified as a number (e.g. 0.05 for 5 will be used.
dur	Optional. Numeric vector of the time durations of the frames. If not included, the integrals will be calculated using trapezoidal integration.
frameStartEnd	Optional: This allows one to specify the beginning and final frame to use for modelling, e.g. c(1,20). This is to assess time stability.

Value

A list with a data frame of the fitted parameters out$par, the model fit object out$fit, a dataframe containing the TACs of the data out$tacs, a dataframe containing the fitted values out$fitvals, the blood input data frame after time shifting input, a vector of the weights out$weights, the inpshift value used inpshift and the specified vB value out$vB.

Author(s)

Granville J Matheson, [e-mail]

References

Oikonen, V (2003). Multilinear solution for 4-compartment model: I. Tissue compartments in series. Gjedde A, Wong DF 1990. Modeling neuroreceptor binding of radioligands in vivo. In: Quantitative imaging: neuroreceptors, neurotransmitters, and enzymes. (Eds. Frost JJ, Wagner HM Jr). Raven Press, 51-79.

Examples

data(pbr28)

t_tac <- pbr28$tacs[[2]]$Times / 60
tac <- pbr28$tacs[[2]]$FC
weights <- pbr28$tacs[[2]]$Weights
dur <- pbr28$tacs[[2]]$Duration/60

input <- blood_interp(
  pbr28$procblood[[2]]$Time / 60, pbr28$procblood[[2]]$Cbl_dispcorr,
  pbr28$procblood[[2]]$Time / 60, pbr28$procblood[[2]]$Cpl_metabcorr,
  t_parentfrac = 1, parentfrac = 1
)

fit1 <- lin2tcm(t_tac, tac, input, weights, inpshift=0.1)
fit2 <- lin2tcm(t_tac, tac, input, weights, inpshift = 0.1, vB=0.05)
fit3 <- lin2tcm(t_tac, tac, input, weights, inpshift = 0.1, vB=0.05, dur = dur)
fit4 <- lin2tcm(t_tac, tac, input, weights, inpshift = 0.1, dur = dur)

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