NMR in Biomedicine最新文献

Existing techniques for the non-invasive in vivo study of dynamic changes in skeletal muscle metabolism are subject to several limitations, for example, poor signal-to-noise ratios which result in long scan times and low temporal resolution. Hyperpolarized [1-¹³C]pyruvate magnetic resonance spectroscopy (HP-MRS) allows the real-time visualization of in vivo metabolic processes and has been used extensively to study cardiac metabolism, but has not resolved oxidative phosphorylation in contracting skeletal muscle. Combining HP-MRS with an in vivo muscle hindlimb electrical stimulation protocol that modelled voluntary exercise to exhaustion allows the simultaneous real-time assessment of both metabolism and function. The aim of this work was to validate the sensitivity of the method by assessing pyruvate dehydrogenase (PDH) flux in resting vs. working muscle: measuring the production of bicarbonate (H¹³CO₃ ^-), a byproduct of the PDH-catalysed conversion of [1-¹³C]pyruvate to acetyl-CoA. Mice (n = 6) underwent two hyperpolarized [1-¹³C]pyruvate injections with ¹³C MR spectra obtained from the gastrocnemius muscle to measure conversion of pyruvate to lactate and bicarbonate, one before the stimulation protocol with the muscle in a resting state and one during the stimulation protocol. The muscle force generated during stimulation was also measured, and ¹³C MRS undertaken at a point of ~50% fatigue. We observed an increase in the bicarbonate/pyruvate ratio by a factor of ~1.5×, in the lactate/pyruvate ratio of ~2.7×, together with an increase in total carbon (~1.5×) that we attribute to perfusion. This demonstrates profound differences in metabolism between the resting and exercising states. These data therefore serve as preliminary evidence that hyperpolarized ¹³C MRS is an effective in vivo probe of PDH flux in exercising skeletal muscle and could be used in future studies to examine changes in muscle metabolism in states of disease and altered nutrition.

X-nuclei magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) are powerful tools for the in vivo investigation of metabolism. Most nuclei require a dedicated radio frequency (RF) coil for signal detection; however, RF coils are often expensive. Coupled with the need for experts to create RF coils, X-nuclei MR measurements are often inaccessible to the general user. In this paper, we present cost-efficient and easy to assemble ⁷Li RF coils that achieved comparable signal-to-noise ratios (SNRs) to their commercial counterpart. Our ⁷Li RF coils were built as single resonance, transmit-receive (Tx/Rx) coils with sufficient design flexibility to allow for future implementations for other nuclei. We found that for a mouse surface coil the optimal number of segmentation capacitors was two. In vitro ⁷Li MRS yielded a 75% SNR increase and in vivo ⁷Li MRS yielded a 42% SNR increase compared with a commercial dual-tuned surface coil. Finally, we demonstrated that in vivo ⁷Li MRI of lithium-fed mice is possible with a custom-built, 2-segment surface coil.

In vivo proton magnetic resonance spectroscopy (¹H-MRS) data often exhibit baselines or low-amplitude signal variations resulting from residual water, imperfectly suppressed lipids, low-amplitude metabolites not considered for fitting, and other features not represented in a basis set. While multitudinous approaches exist to model these baselines in ¹H-MR spectral analysis, many continue to lack systematic validation against varied and realistic ground-truth standards. Here, we compare the accuracy (error mean) and precision (error standard deviation) of metabolite scaling estimates by linear combination modeling (LCM) spectral fitting accounting for spectral baselines via smoothed cubic splines at 50 different combinations of fixed knot interval and smoothing weight, either with or without additionally simulated Gaussian basis signals to separately model spectral macromolecules. Synthesized in-vivo-like metabolite brain spectra incorporating macromolecule signals measured using double-inversion-recovery-prepared sLASER (T_E 20.1 ms; T_R 2 s; T_I1 920 ms; T_I2 330 ms) at 3 T from single voxels in the frontal and occipital cortex of 10 healthy volunteers (five female; 23 ± 5 y.o.) provided both in vivo realism and a standard ground truth for error calculation. Optimal baseline flexibility differed both by definition of "optimum" as either accuracy or precision and by metabolite. Regardless of definition or metabolite, optimal models were not those yielding the smallest fit residuals. Optimized spline baseline definitions yielded high accuracies (lowest mean error -0.003 ± 2.1% for total N-acetyl aspartate and highest mean error 10.1 ± 19.2% for glutamate + glutamine within fits including macromolecule bases) as well as comparable precision for most metabolites to fits achieved in LCModel; inclusion of simulated macromolecules in baseline models improved maximum fit precision but not accuracy. Taken together, these data illustrate that optimized spline baseline model flexibility exhibits metabolite-specific relationships with ¹H-MR spectral quantification accuracy or precision not readily predicted by visual inspection of associated fit residuals and not necessarily improved by adaptive relative to absolute constraints.

Combined ²³Na/³⁹K MRI at 7 T can highlight ion disturbances in skeletal muscle tissue. In this work, we investigated if the apparent tissue potassium concentration (aTPC) can be determined in fatty replaced muscles of patients with facio-scapulo-humeral muscular dystrophy (FSHD) and if it can provide additional information to the fat replacement and the apparent tissue sodium concentration (aTSC). The lower leg of 14 patients (six females, eight males; mean age 47.7 ± 14.0 years) with genetically confirmed FSHD and 11 healthy controls (four females, seven males; mean age 47.0 ± 14.0 years) was examined at a 7-T MR system using a dual-tuned ²³Na/³⁹K birdcage RF coil. In addition, qualitative and quantitative ¹H MR measurements were performed at 7 T to assess the fat replacement and water accumulation. The aTPC and aTSC were determined in seven different muscle regions based on five external references phantoms and corrected for partial volume effects, relaxation biases, and reduced ion concentrations in fat. Results are expressed as median (interquartile range). The measured aTPC was strongly reduced in fat-replaced muscles and was close to zero in totally fat replaced muscles (aTPC = 4.3 mM [2.7 mM] for FF > 80%). After correction of aTPC values for reduced potassium concentration in fat, aTPC_fc values of patients in muscles with low or moderate fat fraction (FF < 30%) were similar to values of healthy subjects (patients: aTPC_fc = 85.6 mM [21.7 mM]; controls: aTPC_fc = 83.2 mM [22.3 mM]). However, muscles with FF > 30% showed reduced aTPC_fc and increased aTSC_fc compared with healthy controls (aTPC_fc = 28.9 mM [46.2 mM], aTSC_fc = 42.3 mM [17.6 mM]; controls: aTSC_fc = 15.0 mM [4.6 mM], aTPC_fc = 83.2 mM [22.3 mM]). No correlations were observed between the aTPC_fc and aTSC_fc, or between aTPC_fc and water T₂. We showed that a determination of the aTPC in dystrophic skeletal muscles is feasible using ³⁹K MRI at 7 T. Measured changes in aTPC_fc were greater than sole fat replacement and might therefore be used as an additional quantitative measure for dystrophic muscle tissue.

Diffusion MRI (dMRI) is widely used as a non-invasive means of detecting changes in brain tissue microstructure. In our previous studies, we demonstrated the sensitivity of dMRI to capture brain microstructural alterations in the triple transgenic (3xTg-AD) mice, particularly brain morphological abnormalities in 2-month-old mice, where dMRI was sensitive to myelin abnormalities, to microglia proliferation/activation, and to the larger number of basal forebrain cholinergic neurons previously described in this model at this young age. In this study, we extend our prior work by establishing the dMRI profile of several brain regions relevant to AD pathology in 2-month-old 3xTg-AD and age-matched controls (NC) and by investigating the effectiveness of these dMRI metrics in predicting group genotype using elastic net (EN) logistic regression modeling. EN has been shown to be a high-performance and stable machine learning model for neuroimaging data. Our results demonstrated significant group differences in several ROIs, particularly in the corpus callosum (CC) where fractional anisotropy (FA) (p < 0.0001; d = -1.87), radial diffusivity (D_┴) (p < 0.0001; d = -1.33), and radial kurtosis (K_┴) (p < 0.0001; d = -1.34) were statistically significant and the most sensitive dMRI metrics to differentiate between the two groups, with large effect sizes (Cohen's d) values. Moreover, FA in the ventral hippocampus (VH) (p < 0.0001; d = 1.13) and fimbria (Fi) (p < 0.0001; d = -1.04) as well as mean diffusivity (MD) (p < 0.0001; d = 1.10) and D_┴ in the subiculum (Sub) (p < 0.0001; d = 1.12) were also statistically significant and able to clearly distinguish the two groups. Additionally, our results from the trained EN model indicate that FA in the VH, CC, and cingulate cortex (Ctx-Cg) were the three best dMRI metrics to classify the 3xTg-AD mice with an accuracy of 0.95. Sensitivity and specificity were also calculated to assess the goodness of prediction, resulting in 0.96 and 0.94, respectively.

The goal of the present study was to investigate the effect of positioning a soft flexible tube-based actuator parallel or orthogonal to the principle muscle fibre direction, on measurements of the stiffness of upper trapezius (UT) muscle obtained using magnetic resonance elastography (MRE). The effects of using three different vibration frequencies (60 Hz, 80 Hz and 100 Hz) and studying left and right sides of the body were also investigated. The relevant MRE datasets were acquired on a 1.5 T MRI system using a 2D gradient-echo (GRE) MRE sequence, and corresponding wave images produced using multimodel direct inversion (MMDI) were analysed by two observers using the manual caliper technique. Except for two of the 108 individual datasets, when the agreement was moderate, there was substantial to perfect agreement between wave quality scores obtained by the two observers, with an identical mean value. Similarly, and again with only two exceptions, there was good to excellent agreement between the measurements of UT stiffness obtained by the two observers. UT stiffness values obtained when the acoustic waves were propagating along the principle muscle fibre direction were significantly higher than when the waves were propagating orthogonal to the principle muscle fibre direction at all vibration frequencies (p < 0.005), and only for the former was a significant dispersion effect observed whereby stiffness increased as frequency increased (p < 0.05). No significant asymmetry was observed in measurements of UT stiffness obtained for the left and right sides of the body (p = 0.29). In conclusion, the new soft and flexible tube-based actuator is comfortable and produced very good wave propagation in UT when positioned in either orientation. However, it is recommended for wave propagation to be induced in the principle fibre direction and there was found to be no advantage in using a vibration frequency above 60 Hz.

We demonstrate that quasi-diffusion imaging (QDI) is a signal representation that extends towards the negative power law regime. We evaluate QDI for in vivo human and ex vivo fixed rat brain tissue across $b$ -value ranges from 0 to 25,000 s mm^-2, determine whether accurate parameter estimates can be acquired from clinically feasible scan times and investigate their diffusion time-dependence. Several mathematical properties of the QDI representation are presented. QDI describes diffusion magnetic resonance imaging (dMRI) signal attenuation by two fitting parameters within a Mittag-Leffler function (MLF). We present its asymptotic properties at low and high $b$ -values and define the inflection point (IP) above which the signal tends to a negative power law. To show that QDI provides an accurate representation of dMRI signal, we apply it to two human brain datasets (Dataset 1: $0\le b\le \mathrm{15,000}$ s mm^-2; Dataset 2: $0\le b\le \mathrm{17,800}$  s mm^-2) and an ex vivo fixed rat brain (Dataset 3: $0\le b\le \mathrm{25,000}$  s mm^-2, diffusion times $17.5\le ∆\le 200$  ms). A clinically feasible 4 $b$ -value subset of Dataset 1 ( $0\le b\le \mathrm{15,000}$  s mm^-2) is also analysed (acquisition time 6 min and 16 s). QDI showed excellent fits to observed signal attenuation, identified signal IPs and provided an apparent negative power law. Stable parameter estimates were identified upon increasing the maximum $b$ -value of the fitting range to near and above signal IPs, suggesting QDI is a valid signal representation within in vivo and ex vivo brain tissue across large $b$ -value ranges with multiple diffusion times. QDI parameters were accurately estimated from clinically feasible shorter data acquisition, and time-dependence was observed with parameters appr

Recent advancements in magnetic resonance imaging (MRI) techniques are promising for the detection of fetal abnormalities, and MRI may supplement or replace prenatal ultrasound scans in the future. In particular, the interest of scientific and medical communities in high-field (3T) MRI continues to grow due to its improved contrast-to-noise and signal-to-noise ratios compared to clinical MRI of lower field strength (1.5T). However, 3T MRI shows more prominent dielectric artifacts due to constructive and destructive interference of standing waves inside the body at these frequencies. Here, we present a concept of passive radiofrequency shimming using metasurface-based pads to improve image quality in fetal MRI at 3T. The proposed metasurface increases the efficiency and homogeneity of the radiofrequency magnetic field, reducing dielectric artifacts in the fetal body and brain images. We offer an ultralight and compact passive way to improve 3T imaging of fetal brain and body structures, simplifying clinical workflows and decreasing the procedure time.

Hepatic de novo lipogenesis (DNL) plays a key role in the pathogenesis of several metabolic diseases that affect the liver. In humans, the detection of deuterium (²H) in triglycerides from very low density lipoprotein collected from blood after administration of deuterated water (D₂O) is commonly used as an indirect estimate of hepatic DNL. Here, we tested in rats (1) the feasibility to detect ²H-labeling directly in liver lipids in vivo by using noninvasive ²H MRS and (2) to what extent these results correlated with the gold standard measurement of DNL in excised liver tissue. To increase hepatic DNL, half of the animals (n = 4) underwent a 7-week dietary intervention in which fructose was provided in drinking water. Deuterium MRS data were acquired from a single voxel placed in the liver. In vivo ²H MRS data showed ²H-labeling in the combined peak of methyl and methylene resonances after 1 week of administrati NBM_70014 on of 5% D₂O as drinking water. DNL was calculated using ¹H and ²H NMR data acquired from extracted lipids of excised liver tissue. The ²H lipid level measured in vivo correlated with the ex vivo estimates of hepatic DNL (r = 0.81, p = 0.016). These results demonstrate the feasibility of direct detection of deuterium labeling in liver lipids using localized ²H MRS in vivo and indicate the potential of this approach to measure hepatic DNL. These initial observations provide a basis for the method to be translated and to develop noninvasive, quantitative measurements of hepatic DNL in humans.