In vivo quantitative 1H MRS of cerebellum and evaluation of quantitation reproducibility by simulation of different levels of noise and spectral resolution

Macrì, Monica; Garreffa, Girolamo; Giove, Federico; Guardati, Manuela; Ambrosini, Anna; Colonnese, Claudio; Maraviglia, B.

doi:10.1016/j.mri.2004.10.021

Cited by 24 publications

(34 citation statements)

References 19 publications

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“…Furthermore, at 1.5 T, marked SNR reduction and linewidth broadening either did not affect estimated tNAA or generated only 4% increases in tNAA and mI estimations. 35,36 While the earliest HD neuropathologic changes occur in caudate and putamen, 37 the putamen was selected to avoid averaging CSF into the brain parenchymal compartment. CSF partial volume effects may generate spurious metabolite measurements 5 and is a risk with caudate voxel placement.…”

Section: Huntington Disease (Hd)mentioning

confidence: 99%

Magnetic resonance spectroscopy biomarkers in premanifest and early Huntington disease

Sturrock¹,

Laule²,

Decolongon³

et al. 2010

Neurology

105

102

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Objectives: To evaluate in vivo brain metabolite differences in control subjects, individuals with premanifest Huntington disease (pre-HD), and individuals with early HD using 1 H magnetic resonance spectroscopy (MRS) and to assess their relationship with motor performance.Methods: Eighty-five participants (30 controls, 25 pre-HD, and 30 early HD) were recruited as part of the TRACK-HD study. Eighty-four were scanned at 3 T with single-voxel spectroscopy in the left putamen. Disease burden score was Ͼ220 among pre-HD individuals. Subjects underwent TRACK-HD motor assessment including Unified Huntington's Disease Rating Scale (UHDRS) motor scoring and a novel quantitative motor battery. Statistical analyses included linear regression and one-way analysis of variance. Results:Total N-acetylaspartate (tNAA), a neuronal integrity marker, was lower in early HD (ϳ15%) vs controls (p Ͻ 0.001). N-acetylaspartate (NAA), a constituent of tNAA, was lower in pre-HD (ϳ8%) and early HD (ϳ17%) vs controls (p Ͻ 0.05). The glial cell marker, myo-inositol (mI), was 50% higher in early HD vs pre-HD (p Ͻ 0.01). In early HD, mI correlated with UHDRS motor score (R 2 ϭ 0.23, p Ͻ 0.05). Across pre-HD and early HD, tNAA correlated with performance on a tongue pressure task (R 2 ϭ 0.30, p Ͻ 0.0001) and with disease burden score (R 2 ϭ 0.17, p Ͻ 0.005). Conclusions:We demonstrate lower putaminal tNAA in early HD compared to controls in a crosssection of subjects. A novel biomarker role for mI in early HD was also identified. These findings resolve disagreement in the literature about the role of MRS as an HD biomarker. We conclude that putaminal MRS measurements of NAA and mI are promising potential biomarkers of HD onset and progression. Neurology ® 2010;75:1702-1710 GLOSSARY AD ϭ Alzheimer disease; Cr ϭ creatine; DBS ϭ disease burden score; Glu ϭ glutamate; GPC ϭ glycerophosphocholine; HD ϭ Huntington disease; mI ϭ myo-inositol; MR ϭ magnetic resonance; MRS ϭ 1 H magnetic resonance spectroscopy; NAA ϭ N-acetylaspartate; NAAG ϭ N-acetylaspartylglutamate; PC ϭ phosphocholine; PCr ϭ phosphocreatine; pre-HD ϭ premanifest Huntington disease; SNR ϭ signal-to-noise ratio; tCho ϭ total choline; tCr ϭ total creatine; TE ϭ echo time; tNAA ϭ total N-acetylaspartate; TR ϭ repetition time; UBC ϭ University of British Columbia; UHDRS ϭ Unified Huntington's Disease Rating Scale; VBM ϭ voxel-based morphometry.The eventual development of Huntington disease (HD) symptoms can be predicted through detection of CAG trinucleotide repeat expansion in the HTT gene 1 in premanifest gene carriers. However, definitive HD biomarkers, able to objectively identify disease onset and progression, are lacking. Evaluation of potential biomarkers are the focus of longitudinal studies such as TRACK-HD 2 and PREDICT-HD. H magnetic resonance spectroscopy (MRS) has previously been evaluated as a biomarker modality in premanifest and early HD. [4][5][6][7][8][9][10][11] However, the literature is conflicted with regard to the utility of metabolites such as total N-ac...

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Section: Huntington Disease (Hd)mentioning

confidence: 99%

Magnetic resonance spectroscopy biomarkers in premanifest and early Huntington disease

Sturrock¹,

Laule²,

Decolongon³

et al. 2010

Neurology

105

102

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“…More recently, Venkatraman et al 124 compared the precision (reproducibility) and variability of singlevoxel PRESS data collected from the anterior cingulate and hippocampus at 4.0 T with reproducibility (single subject scanned multiple times) [125][126][127][128][129][130][131][132][133] and variability studies (many subjects scanned at least once) 109,115,120,128 -130,134 -144 from the literature (many different regions of the brain). The motivation for the Venkatraman study was the review of Steen et al, 145 who found an average coefficient of variation (CV, % ϭ SD/mean ϫ 100) for NAA by Steen et al 145 in the frontal lobe in healthy controls of 13.7% at 1.5 T (from 16 published studies).…”

Section: Reproducibility Of Mrs Studies Of Normal Controlsmentioning

confidence: 99%

Recent Advances in Magnetic Resonance Neurospectroscopy

Rosen

Lenkinski

2007

Neurotherapeutics

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Summary:Over the past two decades, proton magnetic resonance spectroscopy (proton MRS) of the brain has made the transition from research tool to a clinically useful modality. In this review, we first describe the localization methods currently used in MRS studies of the brain and discuss the technical and practical factors that determine the applicability of the methods to particular clinical studies. We also describe each of the resonances detected by localized solvent-suppressed proton MRS of the brain and discuss the metabolic and biochemical information that can be derived from an analysis of their concentrations. We discuss spectral quantitation and summarize the reproducibility of both single-voxel and multivoxel methods at 1.5 and 3-4 T. We have selected three clinical neurologic applications in which there has been a consensus as to the diagnostic value of MRS and summarize the information relevant to clinical applications. Finally, we speculate about some of the potential technical developments, either in progress or in the future, that may lead to improvements in the performance of proton MRS.

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“…The measurement of metabolite concentrations from short echo-time (TE) 1 H-MRS is sensitive to spectral quality [lineshape, motion artifacts, signalto-noise ratio (SNR), and linewidth] (7)(8)(9)(10)(11)(12)(13)(14) and the completeness of the prior-knowledge basis set used for linear combination fitting (15)(16)(17)(18). Linear combination fitting yields relative concentrations of individual metabolites that can be converted into absolute units by appropriate referencing (19).…”

Section: Introductionmentioning

confidence: 99%

“…The macromolecule contribution to the spectrum (20,21) must also be modeled (22,23) or removed (24) during the fitting process, as failure to do so will result in overestimation of metabolite concentrations. Macromolecule signals may be included as prior-knowledge on the basis of parameterized estimates of the macromolecule spectrum (22), estimated by regularized baseline fitting together with linear combination fitting (13,14,25), or measured directly by inversion nulling and removed (24) before linear combination fitting. Such methods presumably increase the precision of metabolite measurements, including those metabolites with significant J-coupling modulation (e.g.…”

Section: Introductionmentioning

confidence: 99%

“…glutamate, glutamine, myo-inositol) which overlap significantly with macromolecule resonances in the spectrum. However, even when the macromolecule contribution has been correctly modeled/removed, metabolite quantification from in vivo short echo-time spectra may remain sensitive to spectral linewidth (9,26,27) and SNR (11,13,14,24,27) because of the complicated overlap of metabolite resonances.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Effect of signal‐to‐noise ratio and spectral linewidth on metabolite quantification at 4 T

Bartha

2007

NMR in Biomedicine

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The accuracy and precision of measurements of metabolite concentrations from short echo-time spectra has previously been characterized at l.5 T as a function of signal-to-noise ratio (SNR) and peak linewidth. The purpose of this study was to characterize the systematic error in quantification of metabolite concentrations associated with linewidth and SNR for the major metabolites of interest in the short echo-time 1H-MR spectrum at 4 T. Simulated 4 T LASER localized spectra (TE = 46 ms) were generated with full width at half maximum (FWHM) over the range 4-14 Hz, and SNR over the range 5-500 by adding 100 Gaussian-distributed noise realizations at each combination of SNR and linewidth. Linewidth and SNR were treated as independent parameters, and therefore an increase in linewidth at a constant SNR resulted in increased metabolite areas. All spectra were fitted in the time domain using identical prior-knowledge and relative parameter starting values. Six metabolites (N-acetylaspartate, glutamate, creatine, myo-inositol, glycerophosphocholine, phosphocholine) were quantified with >90% accuracy and <10% standard deviation at SNR = 10 for linewidths ranging from 8 to 14 Hz FWHM. These simulations did not consider additional sources of variation, including eddy current artifacts, incomplete macromolecule baseline removal, and incomplete water suppression. Regardless, the results show that metabolite quantification from 4 T short echo-time 1H-MRS is sensitive to SNR and linewidth.

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In vivo quantitative 1H MRS of cerebellum and evaluation of quantitation reproducibility by simulation of different levels of noise and spectral resolution

Cited by 24 publications

References 19 publications

Magnetic resonance spectroscopy biomarkers in premanifest and early Huntington disease

Magnetic resonance spectroscopy biomarkers in premanifest and early Huntington disease

Recent Advances in Magnetic Resonance Neurospectroscopy

Effect of signal‐to‐noise ratio and spectral linewidth on metabolite quantification at 4 T

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