NMR in Biomedicine最新文献

The use of sequential proton magnetic resonance spectroscopy (MRS) to follow glutamate and gamma-aminobutyric acid (GABA) changes during functional task-based paradigms, functional MRS (fMRS), has increased. This technique has been used to investigate GABA dynamics during both sensory and behavioural tasks, usually with long 'block design' paradigms. Recently, there has been an increase in interest in the use of short stimuli and 'event-related' tasks. While changes in glutamate can be readily followed by collecting multiple individual transients (or shots), measurement of GABA, especially at 3 T, is usually performed using editing techniques like Mescher-Garwood point-resolved spectroscopy (MEGA-PRESS), which by its nature is a dual shot approach. This poses problems when considering an event-related experiment, where it is unclear when GABA may change, or how this may affect the individual subspectra of the MEGA-PRESS acquisition. To address this issue, MEGA-PRESS data were simulated to reflect the effect of a transient change in GABA concentration due to a short event-related stimulus. The change in GABA was simulated for both the ON and OFF subspectra, and the effect of three different conditions (increase only during ON acquisition, increase during OFF acquisition and increase across both) on the corresponding edited GABA spectrum was modelled. Results show that a transient increase in GABA that only occurs during the ON subspectral acquisition, while not changing the results much from when GABA is changed across both conditions, will give a much larger change in the edited GABA spectrum than a transient increase that occurs only during the OFF subspectral acquisition. These results suggest that researchers should think carefully about the design of any event-related fMRS studies using MEGA-PRESS, as well as the analysis of other functional paradigms where transient changes in GABA may be expected. Experimental design considerations are therefore discussed, and suggestions are made.

Early tumor response prediction can help avoid overtreatment with unnecessary chemotherapy sessions. It is important to determine whether multiple apparent diffusion coefficient indices (S index, ADC-diff) are effective in the early prediction of pathological response to neoadjuvant chemotherapy (NAC) in breast cancer (BC). Patients with stage II and III BCs who underwent T₁WI, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced MRI using a 3 T system were included. They were divided into two groups: major histological responders (MHRs, Miller-Payne G4/5) and nonmajor histological responders (nMHRs, Miller-Payne G1-3). Three b values were used for DWI to derive the S index; ADC-diff values were obtained using b = 0 and 1000 s/mm². The different interquartile ranges of percentile S-index and ADC-diff values after treatment were calculated and compared. The assessment was performed at baseline and after two and four NAC cycles. A total of 59 patients were evaluated. There are some correlations of interquartile ranges of S-index parameters and ADC-diff values with histopathological prognostic factors (such as estrogen receptor and human epidermal growth factor receptor 2 expression, all p < 0.05), but no significant differences were found in some other interquartile ranges of S-index parameters or ADC-diff values between progesterone receptor positive and negative or for Ki-67 tumors (all P > 0.05). No differences were found in the dynamic contrast-enhanced MRI characteristics between the two groups. HER-2 expression and kurtosis of the S-index distribution were screened out as independent risk factors for predicting MHR group (p < 0.05, area under the curve (AUC) = 0.811) before NAC. After early NAC (two cycles), only the 10th percentile S index was statistically significant between the two groups (p < 0.05, AUC = 0.714). No significant differences were found in ADC-diff value at any time point of NAC between the two groups (P > 0.1). These findings demonstrate that the S-index value may be used as an early predictor of pathological response to NAC in BC; the value of ADC-diff as an imaging biomarker of NAC needs to be further confirmed by ongoing multicenter prospective trials.

Duchenne muscular dystrophy (DMD) is a progressive X-linked neuromuscular disorder caused by the absence of functional dystrophin protein. In addition to muscle, dystrophin is expressed in the brain in both neurons and glial cells. Previous studies have shown altered white matter microstructure in patients with DMD using diffusion tensor imaging (DTI). However, DTI measures the diffusion properties of water, a ubiquitous molecule, making it difficult to unravel the underlying pathology. Diffusion-weighted spectroscopy (DWS) is a complementary technique which measures diffusion properties of cell-specific intracellular metabolites. Here we performed both DWS and DTI measurements to disentangle intra- and extracellular contributions to white matter changes in patients with DMD. Scans were conducted in patients with DMD (15.5 ± 4.6 y/o) and age- and sex-matched healthy controls (16.3 ± 3.3 y/o). DWS measurements were obtained in a volume of interest (VOI) positioned in the left parietal white matter. Apparent diffusion coefficients (ADCs) were calculated for total N-acetylaspartate (tNAA), choline compounds (tCho), and total creatine (tCr). The tNAA/tCr and tCho/tCr ratios were calculated from the non-diffusion-weighted spectrum. Mean diffusivity (MD), radial diffusivity (RD), axial diffusivity (AD), and fractional anisotropy of water within the VOI were extracted from DTI measurements. DWS and DTI data from patients with DMD (respectively n = 20 and n = 18) and n = 10 healthy controls were included. No differences in metabolite ADC or in concentration ratios were found between patients with DMD and controls. In contrast, water diffusion (MD, t = -2.727, p = 0.011; RD, t = -2.720, p = 0.011; AD, t = -2.715, p = 0.012) within the VOI was significantly higher in patients compared with healthy controls. Taken together, our study illustrates the potential of combining DTI and DWS to gain a better understanding of microstructural changes and their association with disease mechanisms in a clinical setting.

Quantitative muscle magnetic resonance imaging (qMRI) is a valuable methodology for assessing muscular injuries and neuromuscular disorders. Notably, muscle diffusion tensor imaging (DTI) gives insights into muscle microstructural and macrostructural characteristics. However, the long-term reproducibility and robustness of these measurements remain relatively unexplored. The purpose of this prospective longitudinal cohort study was to assess the long-term robustness and range of variation of qMRI parameters, especially DTI metrics, in the lower extremity muscles of healthy controls under real-life conditions. Twelve volunteers (seven females, age 44.1 ± 12.1 years, body mass index 23.3 ± 2.0 kg/m²) underwent five leg muscle MRI sessions every 20 ± 4 weeks over a total period of 1.5 years. A multiecho gradient-echo Dixon-based sequence, a multiecho spin-echo T2-mapping sequence, and a spin-echo echo planar imaging diffusion-weighted sequence were acquired bilaterally with a Philips 3-T Achieva MR System using a 16-channel torso coil. Fifteen leg muscles were segmented in both lower extremities. qMRI parameters, including fat fraction (FF), water T2 relaxation time, and the diffusion metrics fractional anisotropy (FA) and mean diffusivity (MD), were evaluated. Coefficients of variance (wsCV) and intraclass correlation coefficients (ICCs) were calculated to assess the reproducibility of qMRI parameters. The standard error of measurement (SEM) and the minimal detectable change (MDC) were calculated to determine the range of variation. All tests were applied to all muscles and, subsequently, to each muscle separately. wsCV showed good reproducibility (≤ 10%) for all qMRI parameters in all muscles. The ICCs revealed excellent agreement between time points (FF = 0.980, water T2 = 0.941, FA = 0.952, MD = 0.948). Random measurement errors assessed by SEM and the MDC were low (< 12%). In conclusion, in this study, we showed that qMRI parameters in healthy volunteers living normal lives are stable over 18 months, thereby defining a benchmark for the expected range of variation over time.

Currently, brain iron content represents a new neuromarker for understanding the physiopathological mechanisms leading to Parkinson's disease (PD). In vivo quantification of biological iron is possible by reconstructing magnetic susceptibility maps obtained using quantitative susceptibility mapping (QSM). Applying QSM is challenging, as up to now, no standardization of acquisition protocols and phase image processing has emerged from referenced studies. Our objectives were to compare the accuracy and the sensitivity of 10 QSM pipelines built from algorithms from the literature, applied on phantoms data and on brain data. Two phantoms, with known magnetic susceptibility ranges, were created from several solutions of gadolinium chelate. Twenty healthy volunteers from two age groups were included. Phantoms and brain data were acquired at 1.5 and 3 T, respectively. Susceptibility-weighted images were obtained using a 3D multigradient-recalled-echo sequence. For brain data, 3D anatomical T1- and T2-weighted images were also acquired to segment the deep gray nuclei of interest. Concerning in vitro data, the linear dependence of magnetic susceptibility versus gadolinium concentration and deviations from the theoretically expected values were calculated. For brain data, the accuracy and sensitivity of the QSM pipelines were evaluated in comparison with results from the literature and regarding the expected magnetic susceptibility increase with age, respectively. A nonparametric Mann-Whitney U-test was used to compare the magnetic susceptibility quantification in deep gray nuclei between the two age groups. Our methodology enabled quantifying magnetic susceptibility in human brain and the results were consistent with those from the literature. Statistically significant differences were obtained between the two age groups in all cerebral regions of interest. Our results show the importance of optimizing QSM pipelines according to the application and the targeted magnetic susceptibility range, to achieve accurate quantification. We were able to define the optimal QSM pipeline for future applications on patients with PD.

Transmembrane water permeability changes occur after initialization of necrosis and are a mechanism for early detection of cell death. Filter-exchange spectroscopy (FEXSY) is sensitive to transmembrane water permeability and enables its quantification by magnetic resonance via the apparent exchange rate (AXR). In this study, we investigate AXR changes during necrotic cell death. FEXSY measurements of yeast cells in different necrotic stages were performed and compared with established fluorescence cell death markers and pulsed gradient spin echo measurements. Furthermore, the influence of T2 relaxation on AXR was examined in a two-compartment system. The AXR of yeast cells increased slightly after incubation with 20% isopropanol, whereas it peaked sharply after incubation with 25% isopropanol. At this point, almost all the yeast cells were vital but showed compromised membranes. After incubation with 30% isopropanol, AXR measurements showed high variability, at a point corresponding to a majority of the yeast cells being in late-stage necrosis with disrupted cell membranes. Simulations revealed that, for FEXSY measurements in a two-compartment system, a long filter echo time (TE_f), compared with the T2 of the slow-diffusing compartment, filters out a fraction of the slow-diffusing compartment signal and leads to overestimation of apparent diffusion coefficient (ADC) and underestimation of AXR. Our results demonstrate that AXR is sensitive to gradual permeabilization of the cell membrane of living cells in different permeabilization stages without exogenous contrast agents. AXR measurements were sensitive to permeability changes induced by relatively low concentrations of isopropanol, at levels for which no measurable effect was detectable by ADC measurements. TE_f may act as a signal filter that affects the estimated AXR value of a system consisting of a variety of local diffusivities and a range of T2 that includes T2 values shorter or comparable with the TE_f.

For the quantification of rotating frame relaxation times, the T_2ρ relaxation pathway plays an essential role. Nevertheless, T_2ρ imaging has been studied only to a small extent compared with T_1ρ, and preparation techniques for T_2ρ have so far been adapted from T_1ρ methods. In this work, two different preparation concepts are compared specifically for the use of T_2ρ mapping. The first approach involves transferring the balanced spin-locking (B-SL) concept of T_1ρ imaging. The second and newly proposed approach is a continuous-wave Malcolm-Levitt (CW-MLEV) pulse train with zero echo times and was motivated from T₂ preparation strategies. The modules are tested in Bloch simulations for their intrinsic sensitivity to field inhomogeneities and validated in phantom experiments. In addition, myocardial T_2ρ mapping was performed in mice as an exemplary application. Our results demonstrate that the CW-MLEV approach provides superior robustness and thus suggest that established methods of T_1ρ imaging are not best suited for T_2ρ experiments. In the presence of field inhomogeneities, the simulations indicated an increased banding compensation by a factor of 4.1 compared with B-SL. Quantification of left ventricular T_2ρ time in mice yielded more consistent results, and values in the range of 59.2-61.1 ms (R² = 0.986-0.992) were observed at 7 T.

Diffusion-tensor (DT)-MRI tractography provides information about properties relevant to muscle health and function, including estimates of architectural properties such as fascicle length, pennation angle, and curvature and diffusion properties such as mean diffusivity (MD) and fractional anisotropy (FA). Tractography settings, including integration algorithms, thresholds for early tract termination, and tract smoothing approaches, impact the accuracy of the muscle property estimates. However, muscle DT-MRI tractography is performed using a variety of these settings, complicating comparisons between different studies. The effects of different tractography settings on muscle architecture estimates have not been fully explored, and optimized settings for muscle tractography have not yet been determined. We examined the influence of integration algorithm and termination check settings combined with a range of step sizes, termination criteria, and smoothing polynomial orders on tract characteristics, completion/reason for termination, and goodness of fit between fiber tracts and smoothing polynomials using 3-T DT-MR images of the lower leg muscles of seven healthy adults. We found that tract length and completion were highly sensitive to strict FA and intersegment angle thresholds (25%-69% reduction in complete fiber tracts from lowest to highest minimum FA threshold and 11%-36% reduction from highest to lowest intersegment angle threshold). Higher order polynomials (third and fourth order vs. second order) better fit the muscle fiber trajectories, but curvature estimates were highly sensitive to smoothing polynomial order (3.9-6.6 m^-1 increase for second- vs. fourth-order fitting polynomials). Step size impacted curvature estimates, albeit to a lesser degree. Integration algorithm had little impact, and mean pennation angle, and tract-based FA and MD, were relatively insensitive to all parameters. The results demonstrate which muscle diffusion measures and architectural estimates are most sensitive to varying tractography settings and support the need for consistent reporting of tractography details to aid interpretation and comparison of results between studies.

Phosphorus (³¹P) magnetic resonance spectroscopic imaging (MRSI) can serve as a critical tool for more direct quantification of brain energy metabolism, tissue pH, and cell membrane turnover. However, the low concentration of ³¹P metabolites in biological tissue may result in low signal-to-noise ratio (SNR) in ³¹P MRS images. In this work, we present an innovative design and construction of a ³¹P radiofrequency coil for whole-brain MRSI at 7 T. Our coil builds on current literature in ultra-high field ³¹P coil design and offers complete coverage of the brain, including the cerebellum and brainstem. The coil consists of an actively detunable volume transmit (Tx) resonator and a custom 24-channel receive (Rx) array. The volume Tx resonator is a 16-rung high-pass birdcage coil. The Rx coil consists of a 24-element phased array composed of catered loop shapes and sizes built onto a custom, close-fitting, head-shaped housing. The Rx array was designed to provide complete coverage of the head, while minimizing mutual coupling. The Rx configuration had a mean $S_{11}$ reflection coefficient better than -20 decibels (dB) when the coil was loaded with a human head. The mean mutual coupling ( $S_{21}$ ) among Rx elements, when loaded with a human head, was -16 dB. In phantom imaging, the phased array produced a central SNR that was 4.4-fold higher than the corresponding central SNR when operating the ³¹P birdcage as a transceiver. The peripheral SNR was 12-fold higher when applying the optimized phased array. In vivo 3D ³¹P MRSI experiments produced high-quality spectra in the cerebrum gray and white matter, as well as in the cerebellum. Characteristic phosphorus metabolites related to adenosine triphosphate metabolism and cell membrane turnover were distinguishable across all brain regions. In summary, our results demonstrate the potential of our novel coil for accurate, whole-brain ³¹P metabolite quantification.

The increasing signal-to-noise ratio (SNR) is the main reason to use ultrahigh field MRI. Here, we investigate the dependence of the SNR on the magnetic field strength, especially for small animal applications, where small surface coils are used and coil noise cannot be ignored. Measurements were performed at five field strengths from 3 to 14.1 T, using 2.2-cm surface coils with an identical coil design for transmit and receive on two water samples with and without salt. SNR was measured in a series of spoiled gradient echo images with varying flip angle and corrected for saturation based on a series of flip angle and T₁ measurements. Furthermore, the noise figure of the receive chain was determined and eliminated to remove instrument dependence. Finally, the coil sensitivity was determined based on the principle of reciprocity to obtain a measure for ultimate SNR. Before coil sensitivity correction, the SNR increase in nonconductive samples is highly supralinear with B₀ ^1.6-2.7, depending on distance to the coil, while in the conductive sample, the growth is smaller, being around linear close to the surface coil and increasing up to a B₀ ^2.0 dependence when moving away from the coil. After sensitivity correction, the SNR increase is independent of loading with B₀ ^2.1. This study confirms the supralinear increase of SNR with increasing field strengths. Compared with most human measurements with larger coil sizes, smaller surface coils, as mainly used in animal studies, have a higher contribution of coil noise and thus a different behavior of SNR at high fields.