An 8-channel receive array for improved 31 P MRSI of the whole brain at 3T.

PURPOSE: To demonstrate a 1 H/31 P whole human brain volume coil configuration for 3 Tesla with separate 31 P transmit and receive components that maintains 1 H MRS performance and delivers optimal 31 P MRSI with 1 H decoupling. METHODS: We developed an 8-channel 31 P receive array coil covering the head to be used as an insert for a commercial double-tuned 1 H/31 P birdcage transmit-receive coil. This retains the possibility of using low-power rectangular pulses for 1 H-decoupled 3D 31 P MRSI (nominal resolution 17.6 cm3 ; acquisition duration 13 min) but increases the SNR with the receive sensitivity of 31 P surface coils. The performance of the combined coil setup was evaluated by measuring 1 H and 31 P SNR with and without the 31 P receive array and by assessing the effect of the receive array on the transmit efficiencies of the birdcage coil. RESULTS: Compared to the birdcage coil alone, the 31 P insert in combination with the birdcage achieved an average 31 P SNR gain of 1.4 ± 0.4 in a center partition of the brain. The insert did not cause losses in 1 H MRS performance and transmit efficiency, whereas for 31 P approximately 20% more power was needed to achieve the same γB1. CONCLUSION: The new coil configuration allows 1 H MRSI and optimal 1 H-decoupled 3D 31 P MRSI, with increased SNR of the human brain without patient repositioning, for clinical and research purposes at 3 Tesla.C. Rodgers is funded by the Wellcome Trust and the Royal Society (Grant Number 098436/Z/12/Z)

Multi-component quantitative magnetic resonance imaging by phasor representation

Quantitative magnetic resonance imaging (qMRI) is a versatile, non-destructive and non-invasive tool in life, material, and medical sciences. When multiple components contribute to the signal in a single pixel, however, it is difficult to quantify their individual contributions and characteristic parameters. Here we introduce the concept of phasor representation to qMRI to disentangle the signals from multiple components in imaging data. Plotting the phasors allowed for decomposition, unmixing, segmentation and quantification of our in vivo data from a plant stem, a human and mouse brain and a human prostate. In human brain images, we could identify 3 main T 2 components and 3 apparent diffusion coefficients; in human prostate 5 main contributing spectral shapes were distinguished. The presented phasor analysis is model-free, fast and accurate. Moreover, we also show that it works for undersampled data

High field imaging of large-scale neurotransmitter networks:proof of concept and initial application to epilepsy

\u3cp\u3eThe brain can be considered a network, existing of multiple interconnected areas with various functions. MRI provides opportunities to map the large-scale network organization of the brain. We tap into the neurobiochemical dimension of these networks, as neuronal functioning and signal trafficking across distributed brain regions relies on the release and presence of neurotransmitters. Using high-field MR spectroscopic imaging at 7.0 T, we obtained a non-invasive snapshot of the spatial distribution of the neurotransmitters GABA and glutamate, and investigated interregional associations of these neurotransmitters. We demonstrate that interregional correlations of glutamate and GABA concentrations can be conceptualized as networks. Furthermore, patients with epilepsy display an increased number of glutamate and GABA connections and increased average strength of the GABA network. The increased glutamate and GABA connectivity in epilepsy might indicate a disrupted neurotransmitter balance. In addition to epilepsy, the ‘neurotransmitter networks’ concept might also provide new insights for other neurological diseases.\u3c/p\u3

A Single-Arm, Multicenter Validation Study of Prostate Cancer Localization and Aggressiveness With a Quantitative Multiparametric Magnetic Resonance Imaging Approach.

Objectives: The aims of this study were to assess the discriminative performance of quantitative multiparametric magnetic resonance imaging (mpMRI) between prostate cancer and noncancer tissues and between tumor grade groups (GGs) in a multicenter, single-vendor study, and to investigate to what extent site-specific differences affect variations in mpMRI parameters. Materials and Methods: Fifty patients with biopsy-proven prostate cancer from 5 institutions underwent a standardized preoperative mpMRI protocol. Based on the evaluation of whole-mount histopathology sections, regions of interest were placed on axial T2-weighed MRI scans in cancer and noncancer peripheral zone (PZ) and transition zone (TZ) tissue. Regions of interest were transferred to functional parameter maps, and quantitative parameters were extracted. Across-center variations in noncancer tissues, differences between tissues, and the relation to cancer grade groups were assessed using linear mixed-effects models and receiver operating characteristic analyses. Results: Variations in quantitative parameters were low across institutes (mean [maximum] proportion of total variance in PZ and TZ, 4% [14%] and 8% [46%], respectively). Cancer and noncancer tissues were best separated using the diffusion-weighted imaging-derived apparent diffusion coefficient, both in PZ and TZ (mean [95% confidence interval] areas under the receiver operating characteristic curve [AUCs]; 0.93 [0.89–0.96] and 0.86 [0.75–0.94]), followed by MR spectroscopic imaging and dynamic contrast-enhanced-derived parameters. Parameters from all imaging methods correlated significantly with tumor grade group in PZ tumors. In discriminating GG1 PZ tumors from higher GGs, the highest AUC was obtained with apparent diffusion coefficient (0.74 [0.57–0.90], P < 0.001). The best separation of GG1–2 from GG3–5 PZ tumors was with a logistic regression model of a combination of functional parameters (mean AUC, 0.89 [0.78–0.98]). Conclusions: Standardized data acquisition and postprocessing protocols in prostate mpMRI at 3 T produce equivalent quantitative results across patients from multiple institutions and achieve similar discrimination between cancer and noncancer tissues and cancer grade groups as in previously reported singlecenter studies

Methodological consensus on clinical proton MRS of the brain: Review and recommendations.

Proton MRS (1 H 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