In neuroconductor-devel-releases/spant: MR Spectroscopy Analysis Tools

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.width = 6,
  fig.height = 5
)

Reading raw data and plotting

Load the spant package:

library(spant)

Get the path to a data file included with spant:

fname <- system.file("extdata", "philips_spar_sdat_WS.SDAT", package = "spant")

Read the file and save to the workspace as mrs_data:

mrs_data <- read_mrs(fname, format = "spar_sdat")

Output some basic information about the data:

print(mrs_data)

Plot the spectral region between 5 and 0.5 ppm:

plot(mrs_data, xlim = c(5, 0.5))

Basic preprocessing

Apply a HSVD filter to the residual water region and align the spectrum to the tNAA resonance at 2.01 ppm:

mrs_proc <- hsvd_filt(mrs_data)
mrs_proc <- align(mrs_proc, 2.01)
plot(mrs_proc, xlim = c(5, 0.5))

Basis simulation

Simulate a typical basis set for short TE brain analysis, print some basic information and plot:

basis <- sim_basis_1h_brain_press(mrs_proc)
print(basis)
stackplot(basis, xlim = c(4, 0.5), labels = basis$names, y_offset = 5)

Perform ABfit analysis of the processed data (mrs_proc):

fit_res <- fit_mrs(mrs_proc, basis)

Plot the fit result:

plot(fit_res)

Extract the estimated amplitudes from fit_res and print as a ratio to total-creatine in column format:

amps <- fit_amps(fit_res)
print(t(amps / amps$tCr))

neuroconductor-devel-releases/spant documentation built on May 6, 2020, 4:29 p.m.