Öz, Gülin

Proton MRS (1H MRS) provides noninvasive, quantitative metabolite profiles of tissue and has been shown to aid the clinical management of several brain diseases. Although most modern clinical MR scanners support MRS capabilities, routine use is largely restricted to specialized centers with good access to MR research support. Widespread adoption has been slow for several reasons, and technical challenges toward obtaining reliable good‐quality results have been identified as a contributing factor. Considerable progress has been made by the research community to address many of these challenges, and in this paper a consensus is presented on deficiencies in widely available MRS methodology and validated improvements that are currently in routine use at several clinical research institutions. In particular, the localization error for the PRESS localization sequence was found to be unacceptably high at 3 T, and use of the semi‐adiabatic localization by adiabatic selective refocusing sequence is a recommended solution. Incorporation of simulated metabolite basis sets into analysis routines is recommended for reliably capturing the full spectral detail available from short TE acquisitions. In addition, the importance of achieving a highly homogenous static magnetic field (B0) in the acquisition region is emphasized, and the limitations of current methods and hardware are discussed. Most recommendations require only software improvements, greatly enhancing the capabilities of clinical MRS on existing hardware. Implementation of these recommendations should strengthen current clinical applications and advance progress toward developing and validating new MRS biomarkers for clinical use.

PurposeTo develop a fast and automated volume‐of‐interest (VOI) prescription pipeline (AutoVOI) for single‐voxel MRS that removes the need for manual VOI placement, allows flexible VOI planning in any brain region, and enables high inter‐ and intra‐subject consistency of VOI prescription.MethodsAutoVOI was designed to transfer pre‐defined VOIs from an atlas to the 3D anatomical data of the subject during the scan. The AutoVOI pipeline was optimized for consistency in VOI placement (precision), enhanced coverage of the targeted tissue (accuracy), and fast computation speed. The tool was evaluated against manual VOI placement using existing T1‐weighted data sets and corresponding VOI prescriptions. Finally, it was implemented on 2 scanner platforms to acquire MRS data from clinically relevant VOIs that span the cerebrum, cerebellum, and the brainstem.ResultsThe AutoVOI pipeline includes skull stripping, non‐linear registration of the atlas to the subject's brain, and computation of the VOI coordinates and angulations using a minimum oriented bounding box algorithm. When compared against manual prescription, AutoVOI showed higher intra‐ and inter‐subject spatial consistency, as quantified by generalized Dice coefficients (GDC), lower intra‐ and inter‐subject variability in tissue composition (gray matter, white matter, and cerebrospinal fluid) and higher or equal accuracy, as quantified by GDC of prescribed VOI with targeted tissues. High quality spectra were obtained on Siemens and Philips 3T systems from 6 automatically prescribed VOIs by the tool.ConclusionRobust automatic VOI prescription is feasible and can help facilitate clinical adoption of MRS by avoiding operator dependence of manual selection.

ABSTRACTBACKGROUND AND PURPOSEGlutamate levels may be informative about the declining neuronal health in the central nervous system. We used an advanced proton MR spectroscopy (1H‐MRS) protocol composed of semi‐localization by adiabatic selective refocusing (sLASER) localization and FAST(EST)MAP shimming for detection of alterations in brain glutamate concentrations in patients with amnestic mild cognitive impairment.METHODSParticipants with amnestic mild cognitive impairment (n= 14; median age = 80) and age‐ and sex‐matched clinically normal controls (n= 32; median age = 79) from the population‐based Mayo Clinic Study of Aging were recruited prospectively to the 3T single‐voxel1H‐MRS study that examined metabolite changes in the posterior cingulate gyri. To be included, controls had to have low β‐amyloid load on [11C] Pittsburgh Compound B (PiB)‐PET (standard uptake value ratio; SUVr < 1.42) and patients with amnestic mild cognitive impairment had to have high β‐amyloid load (SUVr ≥ 1.42).RESULTSGlutamate concentration and the glutamate/myo‐inositol ratio were lower in patients with amnestic mild cognitive impairment than clinically normal controls (P< .05). Higher global cortical PiB‐PET SUVr correlated with lower glutamate/myo‐inositol (r= –.3,P= .04).CONCLUSIONSThe advanced sLASER with FAST(EST)MAP shimming is a promising protocol for identifying glutamate alterations. Advanced1H‐MRS protocols may add to the understanding of early Alzheimer's disease pathophysiology through detection of glutamate concentration in posterior cingulate gyri of individuals with amnestic mild cognitive impairment.

PurposeTo investigate the utility of an advanced magnetic resonance spectroscopy (MRS) protocol in the clinical setting, and to compare the localization accuracy, spectral quality, and quantification repeatability between this advanced and the conventional vendor‐provided MRS protocol on a clinical 3T platform.MethodsProton spectra were measured from the posterior cingulate cortices in 30 healthy elderly subjects by clinical MR technologists using a vendor‐provided (point resolved spectroscopy with advanced 3D gradient‐echo B0 shimming) and an advanced (semi‐LASER with FAST(EST)MAP shimming) protocol, in random order. Spectra were quantified with LCModel using standard pipelines for the clinical and research settings, respectively.ResultsThe advanced protocol outperformed the vendor‐provided protocol in localization accuracy (chemical‐shift‐displacement error: 2.0%/ppm, semi‐LASER versus 11.6%/ppm, point resolved spectroscopy), spectral quality (water linewidth: 6.1 ± 1.8 Hz, FAST(EST)MAP versus 10.5 ± 3.7 Hz, 3D gradient echo; P < 7e‐6; residual water: 0.08 ± 0.12%, VAPOR versus 0.45 ± 0.50%, WET; P < 2e‐5) and within‐session repeatability of metabolite concentrations, particularly of low signal‐to‐noise ratio data with two to eight averages (test‐retest coefficients of variance of metabolite concentrations, P < 0.01). Concentrations of J‐coupled metabolites such as γ‐aminobutyric acid and glutamate were biased when using the default pipeline with simulated macromolecules.ConclusionsThe quality of MRS data can be improved using advanced acquisition and analysis protocols on standard 3T hardware in the clinical setting, which can facilitate robust applications in central nervous system diseases. Magn Reson Med 79:1241–1250, 2018. © 2017 International Society for Magnetic Resonance in Medicine.