Phased spectroscopic images: Application to the characterization of the <sup>1</sup>H 1.3‐ppm resonance in intracerbral tumors in the rat

Fur, Yann Le; Ziegler, Anne; Bourgeois, Dominique; Décorps, M.; Rémy, Chantal

doi:10.1002/mrm.1910290402

Cited by 13 publications

(3 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For each MRSI voxel, the local frequency shift due to macroscopic B 0 inhomogeneities was calculated by maximizing the cross‐correlation between the real component of s̃ M ( r i ,ω) and an “ideal” spectrum as a function of frequency and phase (9) variation: where Δω i is the estimated frequency shift at location r i . The “ideal” spectrum consisted of the singlet resonances of NAA, Cr, Cho, and mI, with frequencies at 2.01, 3.01, 3.24, and 3.53 ppm, respectively, using prior knowledge about the spectral pattern obtained by in vitro NMR experiments (10) with a line‐broadening of 5 Hz and no zero‐ or first‐order phase.…”

Section: Methodsmentioning

confidence: 99%

Robust analysis of short echo time ¹H MRSI of human brain

Zhu

Young

Ebel

et al. 2006

Magnetic Resonance in Med

View full text Add to dashboard Cite

Short echo time proton MR Spectroscopic Imaging (MRSI) suffers from low signal-to-noise ratio (SNR), limiting accuracy to estimate metabolite intensities. A method to coherently sum spectra in a region of interest of the human brain by appropriate peak alignment was developed to yield a mean spectrum with increased SNR. Furthermore, principal component (PC) spectra were calculated to estimate the variance of the mean spectrum. The mean or alternatively the first PC (PC 1 ) spectrum from the same region can be used for quantitation of peak areas of metabolites in the human brain at increased SNR. Monte Carlo simulations showed that both mean and PC 1 spectra were more accurate in estimating regional metabolite concentrations than solutions that regress individual spectra against the tissue compositions of MRSI voxels. Back-to-back MRSI studies on 10 healthy volunteers showed that mean spectra markedly improved reliability of brain metabolite measurements, most notably for myo-inositol, as compared to regression methods. Both single voxel MR spectroscopy (MRS) and MR spectroscopic imaging (MRSI) methods have been used to measure metabolite changes in various neurodegenerative diseases, such as Alzheimer's disease, epilepsy, and amyotrophic lateral sclerosis (1). While MRSI is more efficient in assessing regional distributions of cerebral metabolites than MRS, it is technically more challenging. When using short echo time (TE) acquisitions, resonances from scalp lipids and residual water can severely contaminate metabolite spectra because of "voxel bleeding." Using a combination of lipid nulling and k-space extrapolation (2), we previously achieved substantial reduction of lipid contaminations in proton ( 1 H) MRSI spectra for echo times as short as 25 ms. Although we were able to measure regional distribution of N-acetylaspartate (NAA, a marker of neuronal integrity), choline (Cho), and creatine (Cr) containing compounds with high reliability (3), measurements of myo-inositol (mI, a proposed glial marker) (4) were less reliable (3). We attributed the high variability of mI measurements to a combination of a low signal to noise ratio (SNR) of the mI multiplet peaks and baseline fluctuations resulting from the close spectral proximity of mI and water, in addition to instrumental and biologic variability.To reduce problems from low SNR and baseline fluctuations, we have developed a new approach for data analysis of MRSI. To increase SNR, we averaged spectra from a particular tissue type, e.g., cortical gray matter, within a particular anatomic structure in the brain, e.g., frontal lobe. Aligning the spectral peaks and phasing the data in each individual spectrum before summation maximized the gain in averaged SNR, yielding what we term a regional coherently averaged mean spectrum (RCMS). Under the assumption that baseline fluctuations and instrumental noise are random, an SNR gain of ͌ N can theoretically be achieved for metabolites using RCMS, where N is the number of averaged spectra.We previously demonstrated anot...

show abstract

Section: Methodsmentioning

confidence: 99%

Robust analysis of short echo time ¹H MRSI of human brain

Zhu

Young

Ebel

et al. 2006

Magnetic Resonance in Med

View full text Add to dashboard Cite

show abstract

“…The sum of these 16 transients is then subtracted from 16 transients acquired with the same pulse sequence except the frequency of the selective inversion pulse is shifted symmetrically about the lactate methyl protons at 1.3 ppm. Unfortunately, when this latter approach is combined with other pulse sequences ( e g , ISIS (40)) and other phase cycling schemes ( e g , Exorcycle (41)), the large number of required transients places severe limitations on the temporal resolution achievable with this approach.…”

Section: Homonuclear Editing With Adiabatic Pulsesmentioning

confidence: 99%

“…Proton MRS studies of tumors requires the use of spectral editing to resolve the lactate signals from overlapping lipid resonances which are also known to occur in brain tumors (14)(15)(16). The necessity for spectral editing to identify and quantify lactate, combined with the relative complexity of editing pulse sequences, have contributed to the lack of edited 'H MRS studies of glucose metabolism in brain tumors.…”

Section: Introductionmentioning

confidence: 97%

Localized detection of glioma glycolysis using edited ¹H MRS

Schupp

Merkle

Ellermann

et al. 1993

Magnetic Resonance in Med

View full text Add to dashboard Cite

In vivo 1H MRS can be used to detect and quantify the lactate resonance at 1.3 ppm provided that overlapping lipid resonances are eliminated. A homonuclear spectral editing method was developed to acquire uncontaminated 1H spectra of lactate with adiabatic pulses. An advantage of the adiabatic pulse sequence is the ability to induce uniform flip angles and to maximize sensitivity in applications employing surface coil transmitters which produce highly inhomogeneous B1. Glycolytic activity in an intracerebral C6 glioma in rats was monitored by using adiabatic editing sequences to observe [3-13C]lactate produced from infused [1-13C]glucose. Acute hyperglycemia (serum glucose > 22 mM, n = 10) had no significant effect (P = 0.08) on the total ([12C] + [13C]) tumor lactate signal intensity.

show abstract