A comparison between simulated and experimental basis sets for assessing short-TE in vivo ¹H MRS data at 1.5 T.
A number of algorithms designed to determine metabolite concentrations from in vivo (1)H MRS require a collection of single metabolite spectra, known as a basis set, which can be obtained experimentally or by simulation. It has been assumed that basis sets can be used interchangeably, but no systematic study has investigated the effects of small variations in basis functions on the metabolite values obtained. The aim of this study was to compare the results of simulated with experimental basis sets when used to fit short-TE (1)H MRS data of variable quality at 1.5 T. Two hundred and twelve paediatric brain tumour spectra were included in the analysis, and each was analysed twice with LCModel™ using a simulated and experimental basis set. To determine the influence of data quality on quantification, each spectrum was assessed and 152 were classified as being of 'good' quality. Bland-Altman statistics were used to measure the agreement between the two basis sets for all available spectra and only 'good'-quality spectra. Monte-Carlo simulations were performed to investigate the influence of minor shifts in metabolite frequencies on metabolite concentration estimates. All metabolites showed good agreement between the two basis sets, and the average metabolite limits of agreement were approximately ±3.84 mM for all available data and ±0.99 mM for good-quality data. Errors obtained from the Monte-Carlo analysis were found to be more accurate than the Cramer-Rao lower bounds (CRLB) for 12 of 15 metabolites when metabolite frequency shifting was considered. For the majority of purposes, a level of agreement of ±0.99 mM between simulated and experimental basis sets is sufficiently small for them to be used interchangeably. Multiple analyses using slightly modified basis sets may be useful in estimating fitting errors, which are not predicted by CRLBs.
Cancer Sciences, University of Birmingham, UK.
Martin
M
Wilson
Nigel P
NP
Davies
Yu
Y
Sun
Kal
K
Natarajan
Theodoros N
TN
Arvanitis
Risto A
RA
Kauppinen
Andrew C
AC
Peet
D002648:Child; D003198:Computer Simulation; D003401:Creatine / Q000378:metabolism; D006801:Humans; D009010:Monte Carlo Method; D019906:Nuclear Magnetic Resonance, Biomolecular / Q000379:methods*; D011522:Protons
D011522:Protons; D003401:Creatine