A novel test procedure for evaluation of MRS quantitation
methods
F. Schubert, F. Seifert, C. Elster, A. Link, M. Walzel, H. Rinneberg
Physikalisch-Technische Bundesanstalt
Medical Physics and Metrological Information Technology Division, IO587 Berlin
INTRODUCTION
Quantitative MRS requires reliable methods of data analysis.
This holds particularly for short echo time spectra, which contain
a wealth of information, but are complicated by overlapping
background features.
For evaluation of time domain (TD), frequency domain (FD)
and combined (TDFD) methods of analysis of MR spectra both
simulated and measured MRS data have been employed. The
former approach is not directly transferable to real world
applications where model assumptions might not be valid; the
latter suffers from the true metabolite concentrations not being
known, making exact quantitative assessment of a method’s
accuracy impossible.
This study presents a novel simulation technique to evaluate
and compare methods for quantitative MRS. Test problems are
constructed as linear combination of measured and pretreated
brain proton spectra with simulated, i.e. exactly known, MRS
data. The generated test sets were employed to compare a TD
with a TDFD method.
MATERIALS
e 50. TD method
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AND METHODS
MR spectroscopy
The brain spectra used for constructing the test problems were
obtained by proton MRS on 5 healthy volunteers and 5 patients
having multiple sclerosis (MS). Measurements were carried out
at 3 T on a MEDSPEC 30/100 scanner (Bruker Medical,
Ettlingen, Germany). Voxels of 2 x 2 x 2 cm3 were centered on a
MS lesion in the patients and in parietal white matter in the
controls. Water suppressed spectra were acquired with PRESS
(Ta = 3 s, TE = 30 ms, n = 128). In a sixth control, 10 spectra
were acquired on 10 occasions within a period of 3 weeks.
After Fourier transformation of the in vivo data the 3 methyl
resonances of NAA, creatine + phosphocreatine (tCr), and
choline containing compounds (tCho) were removed by using
three different methods. A: the spectral ranges [-380 Hz, -290
Hz], [-240 Hz, -170 Hz] were replaced by values of a median
filter; B, C: the resonances were approximated using Prony’s
method (1) in the ranges [-380 Hz, -280 Hz], [-250 Hz, -160 Hz]
(B) and [-350 Hz, -310 Hz], [-220 Hz, -170 Hz] (C), and the
approximations were then subtracted. To these pretreated data a
simulated MRS signal consisting of 3 corresponding resonances
of known parameters (amplitudes, equal linewidths and equal
phases) was added, resulting in 3 sets of 10 test problems each.
Data analysis
For TD analysis AMARES (2) was applied with appropriate
prior knowledge. Broad baseline parts in the region of interest
were included in the model. Model parameters belonging to
simulated and original resonances were varied independently
from each other. The used TDFD method (3) utilizes TD models
whose parameters were determined by fitting a selected part of
the discrete Fourier transform of the TD model to that of the test
data. The background signal was approximated by wavelets (4).
Here, as prior knowledge equal linewidth and equal phase for the
three desired (simulated) signals was imposed.
RESULTS AND CONCLUSIONS
With both the TD and the TDFD method best recovery of the
simulated signals was obtained for test set B, where the
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:
TDFD method
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NAA
tCr
tCho
NAA
tCr
tCho
Figure: Deviations from simulated signal amplitudes, test set C
Table: Metabolite amplitudes and relative standard deviations
(RSD) for analysis of 10 spectra of a healthy volunteer.
Method
Construction of test problems
Proc. Intl. Sot. Mag. Reson. Med. 8 (2000)
background in the region around the resonances of interest had
been almost completely removed before adding the resonances.
The two methods performed equally well. For test sets A and C,
which reflect realistic situations better since background features
are still present around the resonances of interest, the TDFD
method performed better than the TD method (Figure).
Consequently, these test problems permit to distinguish between
the two quantitation methods regarding their performance.
For 10 spectra measured in the brain of a healthy volunteer
(Table) no significant differences between the mean metabolite
values as analyzed by TD and TDFD could be detected. The
TDFD method, however, led to results with smaller variability.
TD
TDFD
RSD, %
Resonance
Mean amplitude, a.u.
NAA
tCr
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13917
11.7
tCho
11786
9.3
NAA
tCr
21958
6.3
14658
7.6
tCho
12118
8.4
10
The proposed test approach permits a quantitative assessment
of results of analysis of MR spectra due to the simulated part of
the data and, at the same time, includes real world problems, like
overlapping background features, contained in the measured part
of the data. Thus, results on the test problems give insight into
the accuracy achievable for real spectra. In some cases the TDFD
method performed better due to the sophisticated background
treatment involved.
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