Macromolecules

It is recommended to use empirically derived macromolecular basis spectra for the fitting step. A measured MM spectrum described in JSON format can be added to the basis spectra by following the instructions on the basis spectra simulation page.

A collection of MM basis spectra is available for a variety of field strengths, species and anatomies at MRSHub.

In situations where an empirically measured macromolecular spectrum is not available FSL-MRS includes methods for quickly generating synthetic MM basis spectra. For details see Synthetic MM. Both methods should not be used simultaneously.

For an in depth discussion of the effects of MM basis spectra choice on fitting performance see [CUDA12] and [GIAP19].

Synthetic MM

Syntheic MM basis spectra may be added using the --add_MM flag with fsl_mrs or fsl_mrsi. In the interactive environment the same can be achieved by calling the method add_MM_peaks of fsl_mrs.core.MRS.

By default this option will add the following basis spectra (in separate metabolite groups) to the basis sets.

Peak name

Peak location(s) (ppm)

Peak relative amplitude(s)

Peak broadening (gamma/sigma)

MM09

0.9

3

10/20

MM12

1.2

2

10/20

MM14

1.4

2

10/20

MM17

1.7

2

10/20

MM21

2.08, 2.25, 1.95, 3.0

1.33, 0.22, 0.33, 0.4

10/20

Additional peaks may be added int he interactive environment by calling add_MM_peaks with optional arguments to override the defaults.

References

CUDA12

Cudalbu C, Mlynárik V, Gruetter R. Handling Macromolecule Signals in the Quantification of the Neurochemical Profile. Journal of Alzheimer’s Disease 2012;31:S101–S115 doi: 10.3233/JAD-2012-120100.

GIAP19

Giapitzakis I-A, Borbath T, Murali‐Manohar S, Avdievich N, Henning A. Investigation of the influence of macromolecules and spline baseline in the fitting model of human brain spectra at 9.4T. Magnetic Resonance in Medicine 2019;81:746–758 doi: 10.1002/mrm.27467.