Arterial Input Functions {dcemri} | R Documentation |
Parametric models for arterial input functions (AIFs) that are compatible with single compartment models for dynamic contrast-enhanced MRI (DCE-MRI).
aif.orton.exp(tt, AB, muB, AG, muG) model.orton.exp(tt, aparams, kparams) orton.exp.lm(tt, aif, guess=c(100,10,1,0.1), nprint=0)
tt |
is a vector of acquisition times (in minutes) relative to injection of the contrast agent. Negative values should be used prior to the injection. |
AB,muB,AG,muG |
are parameters of the double exponential function that describe the AIF. |
aparams |
is the vector of parameters (A_B, μ_B, A_G, μ_G) associated with the AIF. |
kparams |
is the vector of parameters (v_p, K^{trans}, k_{ep}) associated with the “extended Kety model” for contrast agent concentration. |
aif |
is the vector of observed contrast agent concentrations (data) used to estimate the parametric model. |
guess |
Initial parameter values for the nonlinear optimization. |
nprint |
is an integer, that enables controlled printing of
iterates if it is positive. In this case, estimates of par
are printed at the beginning of the first iteration and every
nprint iterations thereafter and immediately prior to return.
If nprint is not positive, no tracing information on the
progress of the optimization is produced. |
aif.orton.exp
displays the exponential AIF from Orton et
al. (2008) for a known set of AIF parameter values.
model.orton.exp
displays the exponential AIF from Orton
et al. (2008) for a known set of AIF and compartmental model
parameter values. orton.exp.lm
estimates the AIF parameters,
using nonlinear optimization, using a vector of observed contrast
agent concentrations.
aif.orton.exp
and model.orton.exp
return the AIF
associated with the pre-specified parameter values.
orton.exp.lm
returns a list structure with
AB |
The amplitude of the first exponential function. |
muB |
The decay rate of the first exponential function. |
AG |
The amplitude of the second exponential function. |
muG |
The decay rate of the second exponential function. |
info |
The success (or failure) code from the Levenburg-Marquardt
algorithm nls.lm . |
message |
The text message associated with the info
paramters. |
Brandon Whitcher
Orton, M.R., Collins, D.J., Walker-Samuel, S., d'Arcy, J.A., Hawkes, D.J., Atkinson, D. and Leach, M.O. (2007) Bayesian estimation of pharmacokinetic parameters for DCE-MRI with a robust treatment of enhancement onset time, Physics in Medicine and Biology 52, 2393-2408.
Orton, M.R., d'Arcy, J.A., Walker-Samuel, S., Hawkes, D.J., Atkinson, D., Collins, D.J. and Leach, M.O. (2008) Computationally efficient vascular input function models for quantitative kinetic modelling using DCE-MRI, Physics in Medicine and Biology 53, 1225-1239.
dcemri.lm
, extract.aif
,
nls.lm
data("buckley") ## Generate AIF params using the orton.exp function from Buckley's AIF xi <- seq(5, 300, by=5) time <- buckley$time.min[xi] aif <- buckley$input[xi] aifparams <- orton.exp.lm(time, aif) aifparams$D <- 1 unlist(aifparams[1:4]) aoe <- aif.orton.exp(time, aifparams$AB, aifparams$muB, aifparams$AG, aifparams$muG) with(buckley, plot(time.min, input, type="l", lwd=2)) lines(time, aoe, lwd=2, col=2) legend("right", c("Buckley's AIF", "Our approximation"), lty=1, lwd=2, col=1:2) cbind(time, aif, aoe)[1:10,]