Guro Fannelb Giskedegrd1, Tom Bloemberg2,
Lutgarde Buydens2, Geert Postma2, Ingrid Susanne
Gribbestad1, Tone Frost Bathen1
1Dept. of Circulation and Medical
Imaging, Norwegian University of Science and Technology (NTNU), Trondheim,
Norway; 2Dept. of Analytical Chemistry, Radboud University
Nijmegen, Nijmegen, Netherlands
Correction
of misaligned peaks is an important part of multivariate preprocessing of MR
spectra. In this study, three different peak alignment algorithms were tested
on HR MAS MRS data from breast cancer tissue. The datasets were used to
predict the prognostic factor ER status, which is shown to be related to
metabolic profile. Correlation
optimized warping (COW) and peak alignment by genetic algorithm (PAGA)
resulted in greatly improved PLS-DA classification of ER status compared to
unaligned data. Parametric time warping (PTW) did not improve the
classification error, indicating that PTW may not be as suitable for
metabolomic MR data.