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A quantitative biomarker for myelination, such as myelin water fraction (MWF), would boost the understanding of normative and pathological neurodevelopment, improving patients' diagnosis and follow‐up. We quantified the fraction of a rapidly relaxing pool identified as MW using multicomponent three‐dimensional (3D) magnetic resonance fingerprinting (MRF) to evaluate white matter (WM) maturation in typically developing (TD) children and alterations in leukodystrophies (LDs). We acquired DTI and 3D MRF‐based R1, R2 and MWF data of 15 TD children and 17 LD patients (9 months–12.5 years old) at 1.5 T. We computed normative maturation curves in corpus callosum and corona radiata and performed WM tract profile analysis, comparing MWF with R1, R2 and fractional anisotropy (FA). Normative maturation curves demonstrated a steep increase for all tissue parameters in the first 3 years of age, followed by slower growth for MWF while R1, R2R2 and FA reached a plateau. Unlike FA, MWF values were similar for regions of interest (ROIs) with different degrees of axonal packing, suggesting independence from fiber bundle macro‐organization and higher myelin specificity. Tract profile analysis indicated a specific spatial pattern of myelination in the major fiber bundles, consistent across subjects. LD were better distinguished from TD by MWF rather than FA, showing reduced MWF with respect to age‐matched controls in both ROI‐based and tract analysis. In conclusion, MRF‐based MWF provides myelin‐specific WM maturation curves and is sensitive to alteration due to LDs, suggesting its potential as a biomarker for WM disorders. As MRF allows fast simultaneous acquisition of relaxometry and MWF, it can represent a valuable diagnostic tool to study and follow up developmental WM disorders in children. [ABSTRACT FROM AUTHOR]

In the past decades, new methods for tumor staging, restaging, treatment response monitoring, and recurrence detection of a variety of cancers have emerged in conjunction with the state-of-the-art positron emission tomography with 18F-fluorodeoxyglucose ([18F]-FDG PET). 13C magnetic resonance spectroscopic imaging (13CMRSI) is a minimally invasive imaging method that enables the monitoring of metabolism in vivo and in real time. As with any other method based on 13C nuclear magnetic resonance (NMR), it faces the challenge of low thermal polarization and a subsequent low signal-to-noise ratio due to the relatively low gyromagnetic ratio of 13C and its low natural abundance in biological samples. By overcoming these limitations, dynamic nuclear polarization (DNP) with subsequent sample dissolution has recently enabled commonly used NMR and magnetic resonance imaging (MRI) systems to measure, study, and image key metabolic pathways in various biological systems. A particularly interesting and promising molecule used in 13CMRSI is [1-13C]pyruvate, which, in the last ten years, has been widely used for in vitro, preclinical, and, more recently, clinical studies to investigate the cellular energy metabolism in cancer and other diseases. In this article, we outline the technique of dissolution DNP using a 3.35 T preclinical DNP hyperpolarizer and demonstrate its usage in in vitro studies. A similar protocol for hyperpolarization may be applied for the most part in in vivo studies as well. To do so, we used lactate dehydrogenase (LDH) and catalyzed the metabolic reaction of [1-13C]pyruvate to [1-13C]lactate in a prostate carcinoma cell line, PC3, in vitro using 13CMRSI.

Hyperpolarized (13)C imaging allows real-time in vivo measurements of metabolite levels. Quantification of metabolite conversion between [1-(13)C]pyruvate and downstream metabolites [1-(13)C]alanine, [1-(13)C]lactate, and [(13)C]bicarbonate can be achieved through kinetic modeling. Since pyruvate interacts dynamically and simultaneously with its downstream metabolites, the purpose of this work is the determination of parameter values through a multisite, dynamic model involving possible biochemical pathways present in MR spectroscopy. Kinetic modeling parameters were determined by fitting the multisite model to time-domain dynamic metabolite data. The results for different pyruvate doses were compared with those of different two-site models to evaluate the hypothesis that for identical data the uncertainty of a model and the signal-to-noise ratio determine the sensitivity in detecting small physiological differences in the target metabolism. In comparison to the two-site exchange models, the multisite model yielded metabolic conversion rates with smaller bias and smaller standard deviation, as demonstrated in simulations with different signal-to-noise ratio. Pyruvate dose effects observed previously were confirmed and quantified through metabolic conversion rate values. Parameter interdependency allowed an accurate quantification and can therefore be useful for monitoring metabolic activity in different tissues.

Hyperpolarized (13)C imaging allows real-time in vivo measurements of metabolite levels. Quantification of metabolite conversion between [1-(13)C]pyruvate and downstream metabolites [1-(13)C]alanine, [1-(13)C]lactate, and [(13)C]bicarbonate can be achieved through kinetic modeling. Since pyruvate interacts dynamically and simultaneously with its downstream metabolites, the purpose of this work is the determination of parameter values through a multisite, dynamic model involving possible biochemical pathways present in MR spectroscopy. Kinetic modeling parameters were determined by fitting the multisite model to time-domain dynamic metabolite data. The results for different pyruvate doses were compared with those of different two-site models to evaluate the hypothesis that for identical data the uncertainty of a model and the signal-to-noise ratio determine the sensitivity in detecting small physiological differences in the target metabolism. In comparison to the two-site exchange models, the multisite model yielded metabolic conversion rates with smaller bias and smaller standard deviation, as demonstrated in simulations with different signal-to-noise ratio. Pyruvate dose effects observed previously were confirmed and quantified through metabolic conversion rate values. Parameter interdependency allowed an accurate quantification and can therefore be useful for monitoring metabolic activity in different tissues.

Background: MRI can provide information on kidney structure, perfusion, and oxygenation. Furthermore, it allows for the assessment of kidney sodium concentrations and handling, allowing multiparametric evaluation of kidney physiology. Multiparametric MRI is promising for establishing prognosis and monitoring treatment responses in kidney diseases, but its intraindividual variation during the day is unresolved. Purpose: To investigate the variation in multiparametric MRI measurements from the morning to the evening. Study Type: Prospective. Population: Ten healthy volunteers, aged 29 ± 5 without history of kidney disease. Field Strength/Sequence: 3 T/T1 mapping, blood‐oxygen level dependent imaging, arterial spin labeling perfusion imaging, diffusion weighted imaging, and sodium imaging. Assessment: A multiparametric MRI protocol, yielding T1, R2*, ADC, renal blood flow and renal sodium levels, was acquired in the morning, noon, and evening. The participants were fasting prior to the first examination. Urine biochemical analyses were performed to complement MRI data. The cortex and medulla were analyzed separately in a semi‐automatic fashion, and gradients of total sodium concentration (TSC) and R2* gradients were calculated from outer cortex to inner medulla. Statistical Test: Analyses of variance and mixed‐effects models to estimate differences from time of day. Coefficients of variation to assess variability within and between participants. A P‐value <0.05 was considered statistically significant. Results: The coefficients of variation varied from 5% to 18% for proton‐based parametric sequences, while it was 38% for TSC over a day. Data Conclusion: Multiparametric MRI is stable over the day. The coefficients of variation over a day were lower for proton multiparametric MRI, but higher for sodium MRI. Evidence Level: 2 Technical Efficacy: Stage 2 [ABSTRACT FROM AUTHOR]

In this study, we aimed to develop a fast and robust high‐resolution technique for clinically feasible electrical properties tomography based on water content maps (wEPT) using Quantitative Transient‐state Imaging (QTI), a multiparametric transient state‐based method that is similar to MR fingerprinting. Compared with the original wEPT implementation based on standard spin‐echo acquisition, QTI provides robust electrical properties quantification towards B1+ inhomogeneities and full quantitative relaxometry data. To validate the proposed approach, 3D QTI data of 12 healthy volunteers were acquired on a 1.5 T scanner. QTI‐provided T1 maps were used to compute water content maps of the tissues using an empirical relationship based on literature ex‐vivo measurements. Assuming that electrical properties are modulated mainly by tissue water content, the water content maps were used to derive electrical conductivity and relative permittivity maps. The proposed technique was compared with a conventional phase‐only Helmholtz EPT (HH‐EPT) acquisition both within whole white matter, gray matter, and cerebrospinal fluid masks, and within different white and gray matter subregions. In addition, QTI‐based wEPT was retrospectively applied to four multiple sclerosis adolescent and adult patients, compared with conventional contrast‐weighted imaging in terms of lesion delineation, and quantitatively assessed by measuring the variation of electrical properties in lesions. Results obtained with the proposed approach agreed well with theoretical predictions and previous in vivo findings in both white and gray matter. The reconstructed maps showed greater anatomical detail and lower variability compared with standard phase‐only HH‐EPT. The technique can potentially improve delineation of pathology when compared with conventional contrast‐weighted imaging and was able to detect significant variations in lesions with respect to normal‐appearing tissues. In conclusion, QTI can reliably measure conductivity and relative permittivity of brain tissues within a short scan time, opening the way to the study of electric properties in clinical settings. [ABSTRACT FROM AUTHOR]

Purpose: The underlying functional and microstructural lung disease in neonates who are born preterm (bronchopulmonary dysplasia, BPD) remains poorly characterized. Moreover, there is a lack of suitable techniques to reliably assess lung function in this population. Here, we report our preliminary experience with hyperpolarized 129Xe MRI in neonates with BPD. Methods: Neonatal intensive care patients with established BPD were recruited (N = 9) and imaged at a corrected gestational age of median:40.7 (range:37.1, 44.4) wk using a 1.5T neonatal scanner. 2D 129Xe ventilation and diffusion‐weighted images and dissolved phase spectroscopy were acquired, alongside 1H 3D radial UTE. 129Xe images were acquired during a series of short apneic breath‐holds (˜3 s). 1H UTE images were acquired during tidal breathing. Ventilation defects were manually identified and qualitatively compared to lung structures on UTE. ADCs were calculated on a voxel‐wise basis. The signal ratio of the 129Xe red blood cell (RBC) and tissue membrane (M) resonances from spectroscopy was determined. Results: Spiral‐based 129Xe ventilation imaging showed good image quality and sufficient sensitivity to detect mild ventilation abnormalities in patients with BPD. 129Xe ADC values were elevated above that expected given healthy data in older children and adults (median:0.046 [range:0.041, 0.064] cm2s−1); the highest value obtained from an extremely pre‐term patient. 129Xe spectroscopy revealed a low RBC/M ratio (0.14 [0.06, 0.21]). Conclusion: We have demonstrated initial feasibility of 129Xe lung MRI in neonates. With further data, the technique may help guide management of infant lung diseases in the neonatal period and beyond. [ABSTRACT FROM AUTHOR]

Commercial human MR scanners are optimised for proton imaging, containing sophisticated prescan algorithms with setting parameters such as RF transmit gain and power. These are not optimal for X-nuclear application and are challenging to apply to hyperpolarised experiments, where the non-renewable magnetisation signal changes during the experiment. We hypothesised that, despite the complex and inherently nonlinear electrodynamic physics underlying coil loading and spatial variation, simple linear regression would be sufficient to accurately predict X-nuclear transmit gain based on concomitantly acquired data from the proton body coil. We collected data across 156 scan visits at two sites as part of ongoing studies investigating sodium, hyperpolarised carbon, and hyperpolarised xenon. We demonstrate that simple linear regression is able to accurately predict sodium, carbon, or xenon transmit gain as a function of position and proton gain, with variation that is less than the intrasubject variability. In conclusion, sites running multinuclear studies may be able to remove the time-consuming need to separately acquire X-nuclear reference power calibration, inferring it from the proton instead. [ABSTRACT FROM AUTHOR]