Estimation of metabolite T1 relaxation times using tissue specific analysis, signal averaging and bootstrapping from magnetic resonance spectroscopic imaging data.
ABSTRACT A novel method of estimating metabolite T1 relaxation times using MR spectroscopic imaging (MRSI) is proposed. As opposed to conventional single-voxel metabolite T1 estimation methods, this method investigates regional and gray matter (GM)/white matter (WM) differences in metabolite T1 by taking advantage of the spatial distribution information provided by MRSI.
The method, validated by Monte Carlo studies, involves a voxel averaging to preserve the GM/WM distribution, a non-linear least squares fit of the metabolite T1 and an estimation of its standard error by bootstrapping. It was applied in vivo to estimate the T1 of N-acetyl compounds (NAA), choline, creatine and myo-inositol in eight normal volunteers, at 1.5 T, using a short echo time 2D-MRSI slice located above the ventricles.
WM-T 1,NAA was significantly (P < 0.05) longer in anterior regions compared to posterior regions of the brain. The anterior region showed a trend of a longer WM T1 compared to GM for NAA, creatine and myo-Inositol. Lastly, accounting for the bootstrapped standard error estimate in a group mean T1 calculation yielded a more accurate T1 estimation.
The method successfully measured in vivo metabolite T1 using MRSI and can now be applied to diseased brain.
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ABSTRACT: IMPORTANCE Predicting disease evolution is becoming essential for optimizing treatment decision making in multiple sclerosis (MS). Multiple sclerosis pathologic damage typically includes demyelination, neuro-axonal loss, and astrogliosis. OBJECTIVE To evaluate the potential of magnetic resonance markers of central nervous system injury to predict brain-volume loss and clinical disability in multiple sclerosis. DESIGN, SETTING, AND PARTICIPANTS Participants were selected from the Multiple Sclerosis Center at the University of California-San Francisco. The preliminary data set included 59 patients with MS and 43 healthy control individuals. The confirmatory data set included 220 patients from an independent, large genotype-phenotype research project. MAIN OUTCOMES AND MEASURES Baseline N-acetylaspartate (NAA) level, myo-inositol (mI) in normal-appearing white and gray matter, myelin water fraction in normal-appearing white matter, markers of axonal damage, astrogliosis, and demyelination were evaluated as predictors in a preliminary data set. Potential predictors were subsequently tested for replication in a confirmatory data set. Clinical scores and percentage of brain-volume change were obtained annually over 4 years as outcomes. Predictors of outcomes were assessed using linear models, linear mixed-effects models, and logistic regression. RESULTS N-acetylaspartate and mI both had statistically significant effects on brain volume, prompting the use of the mI:NAA ratio in normal-appearing white matter as a predictor. The ratio was a predictor of brain-volume change in both cohorts (annual slope in the percentage of brain-volume change/unit of increase in the ratio: -1.68; 95% CI, -3.05 to -0.30; P = .02 in the preliminary study cohort and -1.08; 95% CI, -1.95 to -0.20; P = .02 in the confirmatory study cohort). Furthermore, the mI:NAA ratio predicted clinical disability (Multiple Sclerosis Functional Composite evolution: -0.52 points annually, P < .001; Multiple Sclerosis Functional Composite sustained progression: odds ratio, 2.76/SD increase in the ratio; 95% CI, 1.32 to 6.47; P = .01) in the preliminary data set and predicted Multiple Sclerosis Functional Composite evolution (-0.23 points annually; P = .01), Expanded Disability Status Scale evolution (0.57 points annually; P = .04), and Expanded Disability Status Scale sustained progression (odds ratio, 1.46; 95% CI, 1.10 to 1.94; P = .009) in the confirmatory data set. Myelin water fraction did not show predictive value. CONCLUSIONS AND RELEVANCE The mI:NAA ratio in normal-appearing white matter has consistent predictive power on brain atrophy and neurological disability evolution. The combined presence of astrogliosis and axonal damage in white matter has cardinal importance in disease severity.JAMA Neurology 05/2014; 71(7). DOI:10.1001/jamaneurol.2014.895 · 7.01 Impact Factor
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ABSTRACT: The phase III, multicenter, randomized, placebo-controlled PreCISe trial assessed glatiramer acetate (GA) effects in patients with clinically isolated syndromes (CIS) suggestive of multiple sclerosis (MS). To assess the neuroprotective effect of GA in a subset of patients in the PreCISe trial, we used proton magnetic resonance spectroscopy (MRS) to measure N-acetylaspartate (NAA), a marker of neuronal integrity, in a large central volume of brain. Thirty-four CIS patients randomized to GA 20 mg/day (n = 19) SC or placebo (n = 15) were included. Patients who relapsed (developed clinically definite MS [CDMS]) were removed from the substudy. NAA/creatine (NAA/Cr) ratios were compared between GA-treated and placebo-treated patients. Twenty patients with CIS had not converted to CDMS and were still in the double-blind phase of the trial at 12 months of follow-up. Paired changes in NAA/Cr differed significantly in patients treated with GA (+0.14, n = 11) compared with patients receiving placebo (-0.33, n = 9, p = 0.03) at 12 months, consistent with a neuroprotective effect of GA in vivo. Patients with CIS who received GA showed improvement in brain neuroaxonal integrity, as indicated by increased NAA/Cr, relative to comparable patients treated with placebo, who showed a decline in NAA/Cr consistent with findings from natural history studies.Journal of Neurology 04/2013; 260(7). DOI:10.1007/s00415-013-6903-5 · 3.84 Impact Factor
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ABSTRACT: Mapping the longitudinal relaxation time (T(1)) of brain tissue is of great interest for both clinical research and MRI sequence development. For an unambiguous interpretation of in vivo variations in T(1) images, it is important to understand the degree of variability that is associated with the quantitative T(1) parameter. This paper presents a general framework for estimating the uncertainty in quantitative T(1) mapping by combining a slice-shifted multi-slice inversion recovery EPI technique with the statistical wild-bootstrap approach. Both simulations and experimental analyses were performed to validate this novel approach and to evaluate the estimated T(1) uncertainty in several brain regions across four healthy volunteers. By estimating the T(1) uncertainty, it is shown that the variation in T(1) within anatomic regions for similar tissue types is larger than the uncertainty in the measurement. This indicates that heterogeneity of the inspected tissue and/or partial volume effects can be the main determinants for the observed variability in the estimated T(1) values. The proposed approach to estimate T(1) and its uncertainty without the need for repeated measurements may also prove to be useful for calculating effect sizes that are deemed significant when comparing group differences.Journal of Magnetic Resonance 09/2012; 224:53-60. DOI:10.1016/j.jmr.2012.08.017 · 2.32 Impact Factor