Standard SVS 1H brain analysis pipeline.

Note this function is still under development and liable to changes.

svs_1h_brain_analysis_dev(
  metab,
  w_ref = NULL,
  output_dir = NULL,
  basis = NULL,
  p_vols = NULL,
  append_basis = NULL,
  remove_basis = NULL,
  dfp_corr = FALSE,
  omit_bad_dynamics = FALSE,
  te = NULL,
  tr = NULL,
  output_ratio = "tCr",
  ecc = FALSE,
  abfit_opts = NULL,
  verbose = FALSE
)

Arguments

metab

filepath or mrs_data object containing MRS metabolite data.

w_ref

filepath or mrs_data object containing MRS water reference data.

output_dir

directory path to output fitting results.

basis

precompiled basis set object to use for analysis.

p_vols

a numeric vector of partial volumes expressed as percentages. Defaults to 100% white matter. A voxel containing 100% gray matter tissue would use : p_vols = c(WM = 0, GM = 100, CSF = 0).

append_basis

names of extra signals to add to the default basis. Eg append_basis = c("peth", "cit"). Cannot be used with precompiled basis sets.

remove_basis

names of signals to remove from the basis. Cannot be used with precompiled basis sets.

dfp_corr

perform dynamic frequency and phase correction using the RATS method.

omit_bad_dynamics

detect and remove bad dynamics.

te

metabolite mrs data echo time in seconds. If not supplied this will be guessed from the metab data file.

tr

metabolite mrs data repetition time in seconds. If not supplied this will be guessed from the metab data file.

output_ratio

optional string to specify a metabolite ratio to output. Defaults to "tCr" and multiple metabolites may be specified for multiple outputs. Set as NULL to omit.

ecc

option to perform water reference based eddy current correction, defaults to FALSE.

abfit_opts

options to pass to ABfit.

verbose

output potentially useful information.

Examples

metab <- system.file("extdata", "philips_spar_sdat_WS.SDAT",
                     package = "spant")
w_ref <- system.file("extdata", "philips_spar_sdat_W.SDAT",
                     package = "spant")
if (FALSE) {
fit_result <- svs_1h_brain_analysis(metab, w_ref, "fit_res_dir")
}