blmod_exp: Blood Model: Exponential
In mathesong/kinfitr: Kinetic Modelling of PET Time Activity Curves

blmod_exp

R Documentation

Blood Model: Exponential

Description

Fit an exponential model to AIF data with the ability to model the peak. In other words, this model fits a single NLS model which describes the rise and the fall of the AIF. This approach is more flexible, but also more sensitive to fitting failures.

Usage

blmod_exp(
  time,
  activity,
  Method = NULL,
  weights = NULL,
  fit_t0 = TRUE,
  fit_exp3 = TRUE,
  fit_peaktime = FALSE,
  fit_peakval = FALSE,
  peaktime_val = NULL,
  peakval_set = 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.
`fit_exp3`	Should the third exponential be fitted, or should a bi-exponential model be used? Default is TRUE for a tri-exponential model.
`fit_peaktime`	Should the time of the peak be fitted? Default is FALSE. This is potentially useful for data where sampling frequency was low around the peak.
`fit_peakval`	Should the value of the peak be fitted? Default is FALSE. This is potentially useful for data where sampling frequency was low around the peak.
`peaktime_val`	Optional. If `fit_peaktime` is FALSE, then this parameter will define the peaktime. If `fit_peaktime` is FALSE and this parameter is left as NULL, then the empirical measured peaktime will be used.
`peakval_set`	Optional. If `fit_peakval` is FALSE, then this parameter defines the peakval as either the empirical measured peakval (TRUE), or the combination of A+B+c (FALSE).
`lower`	Optional. The lower limits of the fit. If left as NULL, they will be given reasonable defaults (mostly 50% 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 1/60 and 1/10, i.e. start to 1/60, 1/60 to 1/10 and 1/10 to end. If fitting only two exponentials, the second value will be used.

Details

This model fits a bi- or tri-exponential model to AIF data. This model can be specified in a fairly large number of ways, depending primarily on the quality of the input data. Reasonably conservative defaults are provided.

The model can fit the time zero point (fit_t0), otherwise the rise starts at time point zero. It can fit two or three exponentials to the curve after the peak (fit_exp0). When it comes to fitting the peak itself, the time of the peak can be fit or set (fit_peaktime). When the peaktime is set, it is either set to the time point of the maximal measured value, or it can be set to another value using peaktime_val. For fitting the peak value, it can be fit as a unique parameter or set using fit_peakval. If it is set, then it can either be set to the largest measured value, or it can be set to the fitted combination of A+B+C, i.e. the initial part of the decay after the peak.

Value

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

Examples

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

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