blmod_feng: Blood Model: Feng

blmod_fengR Documentation

Blood Model: Feng

Description

Fit a Feng model to AIF data. This model fits the conventional Feng model to AIF data. Note: this model is pretty terrible for just about all tracers except for FDG. The convolved Feng model, fengconv is usually much more effective.

Usage

blmod_feng(
  time,
  activity,
  Method = NULL,
  weights = NULL,
  fit_t0 = TRUE,
  lower = NULL,
  upper = NULL,
  start = NULL,
  multstart_lower = NULL,
  multstart_upper = NULL,
  multstart_iter = 100,
  taper_weights = TRUE,
  check_startpars = FALSE,
  expdecay_props = c(1/60, 0.1)
)

Arguments

time

The time of each measurement in seconds

activity

The radioactivity of each measurement

Method

Optional. The method of collection, i.e. "Discrete" or "Continuous"

weights

Optional. Weights of each measurement.

fit_t0

Should time point zero be fitted? If not, it is set to 0. Default is TRUE.

lower

Optional. The lower limits of the fit. If left as NULL, they will be given reasonable defaults (mostly 10% of the starting parameters).

upper

Optional. The upper limits of the fit. If left as NULL, they will be given reasonable defaults (mostly 150% of the starting parameters).

start

Optional. The starting parameters for the fit. If left as NULL, they will be selected using blmod_exp_startpars.

multstart_lower

Optional. The lower limits of the starting parameters.

multstart_upper

Optional. The upper limits of the starting parameters.

multstart_iter

The number of fits to perform with different starting parameters. If set to 1, then the starting parameters will be used for a single fit.

taper_weights

Should the weights be tapered to gradually trade off between the continuous and discrete samples after the peak?

check_startpars

Optional. Return only the starting parameters. Useful for debugging fits which do not work.

expdecay_props

What proportions of the decay should be used for choosing starting parameters for the exponential decay. Defaults to 0 and 0.5, i.e. the latter two exponentials, B, C, beta, gamma are estimated using halfway to the end of the decay, and the beginning to halfway through the decay. The first parameters, A and alpha, are estimated from the ascent.

Value

A model fit including all of the individual parameters, fit details, and model fit object of class blood_feng.

References

Wang, Xinmin, and Dagan Feng. "A study on physiological parameter estimation accuracy for tracer kinetic modeling with positron emission tomography (pet)." 1992 American Control Conference. IEEE, 1992. Feng, D., Z. Wang, and S. C. Huang. "Tracer plasma time-activity curves in circulatory system for positron emission tomography kinetic modeling studies." IFAC Proceedings Volumes 26.2 (1993): 175-178.

Examples

blooddata <- pbr28$blooddata[[1]]
blooddata <- bd_blood_dispcor(blooddata)
aif <- bd_extract(blooddata, output = "AIF")
blood_fit <- blmod_feng(aif$time,
                           aif$aif,
                           Method = aif$Method, multstart_iter = 1)

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