Fast high-resolution brain metabolite mapping on a clinical 3T MRI by accelerated 1 H-FID-MRSI and low-rank constrained reconstruction.

PURPOSE: Epitomizing the advantages of ultra short echo time and no chemical shift displacement error, high-resolution-free induction decay magnetic resonance spectroscopic imaging (FID-MRSI) sequences have proven to be highly effective in providing unbiased characterizations of metabolite distributions. However, its merits are often overshadowed in high-resolution settings by reduced signal-to-noise ratios resulting from the smaller voxel volumes procured by extensive phase encoding and the related acquisition times. METHODS: To address these limitations, we here propose an acquisition and reconstruction scheme that offers both implicit dataset denoising and acquisition acceleration. Specifically, a slice selective high-resolution FID-MRSI sequence was implemented. Spectroscopic datasets were processed to remove fat contamination, and then reconstructed using a total generalized variation (TGV) regularized low-rank model. We further measured reconstruction performance for random undersampled data to assess feasibility of a compressed-sensing SENSE acceleration scheme. Performance of the lipid suppression was assessed using an ad hoc phantom, while that of the low-rank TGV reconstruction model was benchmarked using simulated MRSI data. To assess real-world performance, 2D FID-MRSI acquisitions of the brain in healthy volunteers were reconstructed using the proposed framework. RESULTS: Results from the phantom and simulated data demonstrate that skull lipid contamination is effectively removed and that data reconstruction quality is improved with the low-rank TGV model. Also, we demonstrated that the presented acquisition and reconstruction methods are compatible with a compressed-sensing SENSE acceleration scheme. CONCLUSIONS: An original reconstruction pipeline for 2D 1 H-FID-MRSI datasets was presented that places high-resolution metabolite mapping on 3T MR scanners within clinically feasible limits.

3D-printed Shepp-Logan phantom as a real-world benchmark for MRI.

PURPOSE: As prescribed and reliable geometrical entities, phantoms have served as indispensable validation tools in a variety of MR-related topics. Though a number of phantoms have been conceived, certain applications may warrant highly customized geometries. The purpose of this study was to demonstrate the expediency of rapid prototyping for generating a flexible class of MR-compatible phantom designs. METHODS: An incarnation of the three-dimensional Shepp-Logan numerical phantom, amended for use in magnetic resonance spectroscopic imaging, was actualized using rapid prototyping. Each of the comprising compartments was filled with a solution containing prepared concentrations of common (1)H brain metabolites. Analytical Fourier expressions for the phantom class were established in order to generate a set of simulated measurements, which were then contrasted with acquired data. RESULTS: Experimental results for both structural and spectroscopic imaging substantiate the suitability of rapid prototyping for MR phantom applications. The analytically simulated measurements show excellent agreement with the measured data, but also highlight the various consequences effectuated when certain aspects of the acquisition model are disregarded or misrepresented. CONCLUSION: Rapid prototyping offers a novel and versatile framework for MR phantom-based validation studies. Furthermore, the growing accessibility and open-source compatibility may provide an important link between the often disparate numerical and haptic testing.

Neuropsychological dysfunction and neuroimaging abnormalities in neurologically intact adults with sickle cell anemia.

CONTEXT: Sickle cell anemia (SCA) is a chronic illness causing progressive deterioration in quality of life. Brain dysfunction may be the most important and least studied problem affecting individuals with this disease. OBJECTIVE: To measure neurocognitive dysfunction in neurologically asymptomatic adults with SCA vs healthy control individuals. DESIGN, SETTING, AND PARTICIPANTS: Cross-sectional study comparing neuropsychological function and neuroimaging findings in neurologically asymptomatic adults with SCA and controls from 12 SCA centers, conducted between December 2004 and May 2008. Participants were patients with SCA (hemoglobin [Hb] SS and hemoglobin level < or = 10 mg/dL) aged 19 to 55 years and of African descent (n = 149) or community controls (Hb AA and normal hemoglobin level) (n = 47). Participants were stratified on age, sex, and education. MAIN OUTCOME MEASURES: The primary outcome measure was nonverbal function assessed by the Wechsler Adult Intelligence Scale, third edition (WAIS-III) Performance IQ Index. Secondary exploratory outcomes included performance on neurocognitive tests of executive function, memory, attention, and language and magnetic resonance imaging measurement of total intracranial and hippocampal volume, cortical gray and white matter, and lacunae. RESULTS: The mean WAIS-III Performance IQ score of patients with SCA was significantly lower than that of controls (adjusted mean, 86.69 for patients with SCA vs 95.19 for controls [mean difference, -5.50; 95% confidence interval {CI}, -9.55 to -1.44]; P = .008), with 33% performing more than 1 SD (<85) below the population mean. Among secondary measures, differences were observed in adjusted mean values for global cognitive function (full-scale IQ) (90.47 for patients with SCA vs 95.66 for controls [mean difference, -5.19; 95% CI, -9.24 to -1.13]; P = .01), working memory (90.75 vs 95.25 [mean difference, -4.50; 95% CI, -8.55 to -0.45]; P = .03), processing speed (86.50 vs 97.95 [mean difference, -11.46; 95% CI, -15.51 to -7.40]; P < .001), and measures of executive function. Anemia was associated with poorer neurocognitive function in older patients. No differences in total gray matter or hippocampal volume were observed. Lacunae were more frequent in patients with SCA but not independently related to neurocognitive function. CONCLUSION: Compared with healthy controls, adults with SCA had poorer cognitive performance, which was associated with anemia and age.

Magnetic resonance spectroscopic imaging at superresolution: Overview and perspectives.

The notion of non-invasive, high-resolution spatial mapping of metabolite concentrations has long enticed the medical community. While magnetic resonance spectroscopic imaging (MRSI) is capable of achieving the requisite spatio-spectral localization, it has traditionally been encumbered by significant resolution constraints that have thus far undermined its clinical utility. To surpass these obstacles, research efforts have primarily focused on hardware enhancements or the development of accelerated acquisition strategies to improve the experimental sensitivity per unit time. Concomitantly, a number of innovative reconstruction techniques have emerged as alternatives to the standard inverse discrete Fourier transform (DFT). While perhaps lesser known, these latter methods strive to effect commensurate resolution gains by exploiting known properties of the underlying MRSI signal in concert with advanced image and signal processing techniques. This review article aims to aggregate and provide an overview of the past few decades of so-called "superresolution" MRSI reconstruction methodologies, and to introduce readers to current state-of-the-art approaches. A number of perspectives are then offered as to the future of high-resolution MRSI, with a particular focus on translation into clinical settings.

DCD pigs' kidneys analyzed by MRI to assess ex vivo their viability.

BACKGROUND: Magnetic resonance imaging (MRI) gadolinium-perfusion was applied in simulated Donation after Cardiac Death (DCD) in porcine kidneys to measure intrarenal perfusion. Adenosine triphosphate (ATP) resynthesis during oxygenated hypothermic perfusion was compared to evaluate the "ex vivo organ viability". Adenine nucleotide (AN) was measured by P nuclear magnetic resonance (NMR) spectroscopy. Whereas this latter technique requires sophisticated hardware, gadolinium-perfusion can be realized using any standard proton-MRI scanner. The aim of this work was to establish a correlation between the two methods. METHODS: Twenty-two porcine kidneys presenting up to 90 min warm ischemia were perfused with oxygenation at 4 °C using our magnetic resonance-compatible machine. During the perfusion, P NMR spectroscopy and gadolinium-perfusion sequences were performed. Measures obtained from the gadolinium-perfusion were the speed of elimination of the cortical gadolinium and the presence or absence of a corticomedullar shunt. For ATP resynthesis analysis, P chemical shift imaging was acquired and analyzed. All the kidneys have been submitted to histologic examination. RESULTS: ATP resynthesis was observed in all organs presenting a cortical gadolinium elimination slope of (-) 23° or greater. In organs with lower gadolinium elimination, no AN or only precursors were detected. This study reveals a link between the two methods and demonstrates ex vivo viability in 93% of the analyzed kidneys. Benefits and side effects of both methods are discussed. CONCLUSION: Oxygenated hypothermic perfusion enables the evaluation of kidneys in DCD simulated situation; gadolinium-perfusion can be introduced into any center equipped with a proton-MRI scanner allowing results superposable with ATP measurement.

Data-driven MRSI spectral localization via low-rank component analysis.

Magnetic resonance spectroscopic imaging (MRSI) is a powerful tool capable of providing spatially localized maps of metabolite concentrations. Its utility, however, is often depreciated by spectral leakage artifacts resulting from low spatial resolution measurements through an effort to reduce acquisition times. Though model-based techniques can help circumvent these drawbacks, they require strong prior knowledge, and can introduce additional artifacts when the underlying models are inaccurate. We introduce a novel scheme in which a generative model is estimated from the raw MRSI data via a regularized variational framework that minimizes the model approximation error within a measurement-prescribed subspace. As additional a priori information, our approach relies only upon a measured field inhomogeneity map at high spatial resolution. We demonstrate the feasibility of our approach on both synthetic and experimental data.