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CEST data evaluation tool

This tool allows you to evaluate CEST MRI data and create CEST images and ROI evaluations from basic contrasts as well as sophisticated multi-Lorentzian fits

Dowload zipped Matlab implementations here or find the package on


These routines allow you to

  • import raw data
  • Calculate B0 maps from Z-spectra
  • B0 correct Z-spectra
  • investigate CEST spectra for pixels and ROIs
  • calculate contrasts (MTRasym, MTRRex, Lorentzian difference, AREX)
  • fit multi-Lorentzian fits to Z-spectra

MTRRex,AREX: Zaiss et al. NMR Biomed., 27: 240–252. doi: 10.1002/nbm.3054.

Fitting: Windschuh et al. (2015), NMR Biomed., 28(5):529-37. doi: 10.1002/nbm.3283.

WASABI B1/B0 mapping and correction: Schuenke et al. (2016), MRM doi: 10.1002/mrm.26133.

1/2 Basic Z-spectra evaluation

2/2 Lorentzian fitting for isolated CEST evaluation

There are 4 important inputs:

  • M0_stack(x,y,z) the thermal M0 magnetization, or the normalization image w/o saturation
  • Mz_stack(x,y,z,w) the stack of saturated images at frequency w
  • dB0_stack_int(x,y,z) the internal dB0 map in ppm calculated by the minimum of Mz_stack
  • dB0_stack_ext(x,y,z) an external dB0 map in ppm

further we need the frequency offset axis, or the omega-axis (w-axis) of the Z-spectrum. It is saved in the parameter struct P under the sequence parameters P.SEQ

  • P.SEQ.w

To calculate the internal B0 map the function MINFIND_SPLINE_3D is called after that the B0-correction and normalization can be performed and the final stack is

  • Z_corrExt - the B0-corrected and normalized stack of Z-spectra


find the CEST data processing tool of the John Hopkins group here

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cest_eval.txt · Last modified: 2016/02/14 15:35 by mzaiss