NMR in Biomedicine最新文献

Accurate quantification of extracellular volume (ECV) and fractional myocardial blood volume (fMBV) in cardiac magnetic resonance (CMR) relies on precise alignment between precontrast and postcontrast images. Variable image contrast often undermines conventional motion correction, causing misalignment due to respiration or cardiac motion. Herein, we present a registration approach that accounts for varying image contrast levels and cardiac motion to achieve more precise and high-quality quantitative cardiac mapping. Patients with suspected myocardial diseases underwent cardiac MRI with Gadavist (0.1 mmol/kg, n = 11) and ferumoxytol (4.0 mg/kg cumulative, n = 9) enhancement for ECV and fMBV measurements, respectively. T1 maps were generated using the MOLLI sequence. To remove contrast variations across different inversion times and contrast doses, precontrast and postcontrast MOLLI images were grouped and processed using correlation-weighted representations based on the myocardium and blood pool signals. Groupwise registration is performed based on the maximization of mutual information. The image registration accuracy and mapping precision of the proposed method were assessed relative to those of conventional methods. ResultsCompared with the conventional groupwise registration approach, the proposed decontrasted approach showed superior alignment between images of different contrasts, as evidenced by the higher Dice scores (mean 0.77 vs. 0.69, p < 0.001). It also eliminated artifacts commonly observed owing to image misalignment (all 11 cases showed improvement). Improved myocardial mapping precision was observed for both ECV (median coefficient of variation, 0.14 vs. 0.27; p < 0.001) and fMBV (median coefficient of variation, 0.59 vs. 0.71; p < 0.001). It also reduced individual myocardial segmental variations in the ECV (5.8 to 3.58, p < 0.001) and fMBV maps (9.86 to 7.93, p < 0.001). Overall, decontrasted image registration improves the precision of contrast-enhanced myocardial parametric mapping by reducing the misalignment between multicontrast images. This framework may be extended to other postprocessing tasks in cardiac MRI that involve variable image contrasts.

We analyzed the feasibility of using a UTE stack-of-spirals turbo FLASH (STFL) sequence to measure T_1ρ relaxation in the Achilles tendon. Six HS (25-31 years) and five AT patients (32-47 years) participated. The study evaluates the clinical utility of the STFL sequence to generate T_1ρ maps using mono-exponential (ME) and bi-exponential (BE) fitting models. In a phantom experiment, ME-T_1ρ values and SNR estimated from the STFL sequence are compared with those of the Cartesian turbo FLASH (CTFL) sequence. In human subjects, we evaluate differences in estimated ME (ME-T_1ρ) and BE parameters (short T_1ρ, long T_1ρ, and short fraction) between AT and HS groups along with repeatability of STFL. The agarose phantom demonstrates biases of 2.89% (3% agarose), -1.88% (5%), and -0.92% (7%) between ME-T_1ρ values from STFL and CTFL. In the bovine Achilles tendon, STFL shows a large bias of -58.6%, with a lower median ME-T_1ρ (2.9 ms) than CTFL (4.6 ms). SNR is higher in STFL (77.05-80.72 for 3%-7% agarose; 24.43 for bovine tendon) than CTFL (66.73-58.97 for agarose; 3.21 for bovine tendon). ME and BE parameters were averaged over the entire Achilles tendon, and none showed significant group differences (p > 0.05; effect size = 0.05-0.22). Subregional analysis showed that in the mid-Achilles tendon, short and long BE-T_1ρ components were 26% and 37% lower in AT than HS, though not statistically significant. The LDA-combined BE parameter showed significant group separation in the midtendon region (p = 0.016; effect size = 1.53). In HS, the long BE-T_1ρ component showed subregional variation (p = 0.006), increasing 58% from calcaneal to midtendon, and then decreasing 23% toward the intramuscular region. ME and BE fitting showed high repeatability with scan-rescan variations of 2.64% (T_1ρ), 3.38% (short T_1ρ), 3.0% (long T_1ρ), and 0.21% (short fraction). We demonstrated the feasibility of using STFL for T_1ρ quantification in the Achilles tendon.

Magnetic resonance imaging (MRI) applications to the study of gastric function in humans have started to incorporate dynamic volumetric imaging, thus calling for specialized approaches for motion correction. A method for retrospective respiratory motion correction in free-breathing, four-dimensional (4D) abdominal MRI is presented. Our gastric low-rank tensor-based (GLOW) algorithm uses a low-rank tensor (LRT) model to separate the temporal components that correspond to breathing motion from those related to gut motion, which are preserved due to being uncorrelated and spatially localized. As a proof-of-concept, the GLOW algorithm is applied to a human 4D gastric MRI dataset that includes data collected during both a fasted and fed state using a food-based contrast meal. This approach allows for a more robust and accurate assessment of gastric peristalsis. The GLOW algorithm represents an important step toward the effective application of noninvasive, naturalistic approaches to robustly and accurately evaluate gastric function via MRI.

An organism's metabolic profile provides vital information pertaining to its physiology or pathology. To monitor these biochemical changes, Nuclear Magnetic Resonance (NMR) spectroscopy has found success in non-invasively observing metabolite changes within intact samples in an untargeted manner. However, biological samples are chemically complex, comprised of many different constituents (amino acids, carbohydrates, and lipids) at varying concentrations depending on physiological and pathological conditions. Due to the narrow spectral window of proton NMR, compound resonance frequencies can often overlap, making the identification and monitoring of metabolites difficult and time consuming, particularly when dealing with large numbers of samples. Here, we introduce a Python program (ROIAL-NMR) to systematically identify potential metabolites from defined proton NMR spectral regions-of-interest (ROIs), which are identified from complex biological samples (i.e., human serum, saliva, sweat, urine, CSF, and tissues) using the Human Metabolome Database (HMDB) as a reference platform. Briefly, for disease-versus-control studies, the program considers disease types and utilizes study-defined ROIs together with their differing intensity levels, according to sample types, in differentiating disease from control to propose potential metabolites represented by these ROIs in an output table. In this report, we illustrate the utility of the program with one of our recent studies, where we measured proton NMR spectra of serum samples taken from lung cancer (LC) patients, with and without Alzheimer's disease and related dementia (ADRD). The program successfully identified 88 metabolites, with 66 differentiating LC from control patients, and 80 distinguishing LC patients with ADRD from those without ADRD to provide important information regarding pathophysiology in complex biological samples.

∆B₀ shim optimization performed at the beginning of an MR scan is unable to correct for ∆B₀ field inhomogeneities caused by patient motion or hardware instability during scans. Navigator-based methods have been demonstrated previously to be effective for motion and shim correction. The purpose of this work was to accelerate volumetric navigators to allow fast acquisition of the parent navigated sequence with short real-time feedback time and high spatial resolution of the ∆B₀ field mapping. A GRAPPA-accelerated 3D dual-echo EPI vNav was implemented on a 3 T Prisma MRI scanner. Testing was performed on an anthropomorphic head phantom and 11 human participants. vNav-derived ∆B₀ field maps with various spatial resolutions were compared to Cartesian-encoded gold-standard 3D gradient-echo ∆B₀ field mapping. ∆B₀ shimming was evaluated for the scanner's spherical harmonics shims and a custom-made AC/DC RF-receive/∆B₀-shim array. The performance of dual-echo and single-echo accelerated navigators was compared for tracking and updating ∆B₀ field maps during motion. Real-time motion and shim corrections for 2D MRI and 3D MRSI sequences were assessed in vivo with controlled head movement. Up to 8-fold acceleration of volumetric navigators (vNavs) significantly reduced geometric distortions and signal dropouts near air-tissue interfaces and metal implants. Acceleration allowed a flexible tradeoff between spatial resolution (2.5-7.5 mm) and acquisition time (242-1302 ms). Notably, accelerated high-resolution (5 mm) vNav was faster (378 ms) than unaccelerated low-resolution (7.5 mm) vNav (700 ms) and showed better agreement with 3D-GRE ∆B₀ field mapping with 5.5 Hz RMSE, 1 Hz bias, and [-10%, +10%] confidence interval. Accelerated vNavs improved 3D MRSI and 2D MRI in real-time motion and shim correction applications. Advanced shimming with spherical harmonic and shim array showed superior ΔB₀ correction, especially with joint shim optimization. GRAPPA-accelerated vNavs provide fast, robust, and high-quality ∆B₀ field mapping and shimming over the whole-brain. The accelerated vNavs enable rapid correction of ∆B₀ field inhomogeneities and faster acquisition of the navigated parent sequence. This methodology can be used for real-time motion and shim correction to enhance data quality in various MRI applications.

Objectives: Early diagnosis and timely treatment of renal fibrosis can improve the prognosis of patients with nephropathy. We aim to investigate the utility of multi-parametric MRI for evaluating early renal fibrosis and therapeutic efficacy in a rat model.

Methods: Eighty-four male SD rats receiving tail vein injection of adriamycin doxorubicin (ADR) to establish renal fibrosis models were utilized. Twelve rats underwent pilot experiments to identify successful renal fibrosis modeling timepoints. Seventy-two were assigned to treated (AA) and untreated (ADR) groups, which were subdivided into AA-1 and ADR-1 groups (N = 6 each, underwent continuous MRI scanning at 0, 14, 21, 28, 35, 42d), AA-2 and ADR-2 groups (N = 30 each, 6 underwent MRI scanning at 0, 14, 21, 28, 35d). Repeated measures ANOVA was used to evaluate changes in parameters over time within continuous MRI scanning groups (AA-1 and ADR-1). Independent samples t test or Wilcoxon rank sum test were used to compare the differences of parameters among groups and different time points. Pearson's correlation coefficients were used to investigate relationships between renal blood flow (RBF), cortical and medullary T1, mean kurtosis (MK) and mean diffusivity (MD) values and the laboratory results, α-smooth muscle actin (α-SMA), transforming growth factor-β1 (TGF-β1), Smad3, and Smad7.

Results: T1 and MK values increased over time in all groups, while RBF and MD values decreased. Significant differences in all MRI parameters except medullary MK were observed between AA and ADR groups. RBF, MK, MD, and T1 values were significantly correlated with renal interstitial collagen area, α-SMA, TGF-β1, Smad3, and Smad7 (|r| = 0.5882 to 0.9756, p < 0.0001).

Conclusion: Multi-parametric MRI can enable the detection of early microstructural and functional alterations in the kidney associated with renal fibrosis and provides a means to quantify the therapeutic efficacy of interventions.

The choroid plexus (ChP) is critical to the glymphatic system of the human brain through its primary function as the source of cerebrospinal fluid (CSF) production, which plays an important role in brain waste clearance. Developing noninvasive imaging techniques to assess ChP is crucial for studying its function and age-related neurofluid dynamics. In this study, we developed a relaxation-selective intravoxel incoherent motion (IVIM) technique to assess tissue and fluid compartments in the ChP of 83 middle-aged to elderly participants (age: 61.5 ± 17.1 years) and 15 young controls (age: 30.7 ± 2.9 years). Using a 3-T MRI scanner, we implemented T1- and T2-selective IVIM approaches, including Fluid-Attenuated Inversion Recovery IVIM (FLAIR-IVIM), LongTE-IVIM, and Vascular Space Occupancy-LongTE-IVIM (VASO-LongTE-IVIM), to measure diffusivity and volume fractions of fluid compartments in ChP. Our results showed that FLAIR-IVIM identified an additional interstitial fluid (ISF) compartment with free-water-like diffusivity in ChP. We then evaluated the aging effects on microvascular perfusion and ISF in ChP. Compared to younger adults, older adults exhibited increased ChP volume, reduced perfusion, decreased ISF volume fraction, and lower tissue diffusivity. Relaxation-selective IVIM may offer enhanced specificity for characterizing age-related changes in ChP structure and fluid dynamics.

The measurement of cerebral oxygen metabolism is important to understand and treat many disorders. Constrained quantitative BOLD (qBOLD) MRI is a calibration-free method for 3D voxel-wise whole-brain mapping of brain oxygen metabolism. This study aimed to evaluate the agreement between constrained qBOLD and global oximetry methods both at baseline and in response to a caffeine stimulus. Healthy volunteers (N = 10, age 30 ± 8 years) were imaged with constrained qBOLD, MOTIVE (metabolism of oxygen via T₂ and interleaved velocity encoding), dual-slice (DS), and single-slice (SS) OxFlow. Subjects were then given a 200 mg caffeine pill and imaged at 2-s temporal resolution immediately thereafter for 30 min by SS-OxFlow. After 30 min, the baseline protocol was repeated. Constrained qBOLD uses prior constraints to the QSM + qBOLD model to solve for voxel-wise oxygen extraction fraction (OEF). Quantification of cerebral blood flow (CBF) was accomplished for qBOLD from a separate measurement via pseudo-continuous arterial spin labeling (pCASL) to yield CMRO₂. Constrained qBOLD measured OEF (31 ± 5% gray matter [GM], 31 ± 6% white matter [WM] at baseline; 36 ± 7 GM, 35 ± 8 WM post-caffeine) was in good agreement with global oximetry methods DS-OxFlow (30 ± 4, 37 ± 5), SS-OxFlow (31 ± 4, 37 ± 4), and MOTIVE (32 ± 5, 39 ± 5). Temporal data showed a gradual increase in OEF with a commensurate reduction in CBF while the caffeine was taking effect. No significant change in CMRO₂ was noted with any of the techniques. Regional analysis of the basal ganglia, hippocampus, and thalamus found there was a significant increase in OEF post caffeine. The results indicate constrained qBOLD to yield OEF with negligible bias to global oximetry methods, both at baseline and post caffeine. The results also suggest that constrained qBOLD has the sensitivity to detect changes in oxygen metabolism due to a vasoconstrictive stimulus.

To assess lower back pain using quantitative chemical exchange saturation transfer (qCEST) imaging in a porcine model by comparing exchange rate maps obtained from multitasking qCEST with conventional qCEST. Use a permuted random forest (PRF) model trained on CEST-derived magnetization transfer ratio (MTR) and exchange rate (k_sw) features to predict Glasgow pain scores. Six Yucatan minipigs were scanned at baseline and at four post-injury time points (weeks 4, 8, 12, and 16) following intervertebral disc injury. Conventional qCEST imaging was performed at four B1 powers using a two-dimensional reduced field of view turbo spin-echo (TSE) sequence, with a total acquisition time of 24 min per slice. Multitasking steady-state (SS) CEST imaging was performed with pulsed saturation to achieve a steady state, acquiring 32 slices at 59 offsets for 4 B1 powers in 36 min. Exchange rate maps were generated using omega plot analysis, and CEST images were analyzed using a multi-pool fitting model to produce MTR and k_sw maps. Permuted random forest (PRF) model was trained on MTR and k_sw values to predict pain scores. Modic changes were assessed using T2-weighted MR images. The Pearson correlation coefficient between exchange rate maps from multitasking qCEST and conventional qCEST was 0.82, demonstrating strong agreement. The 3D qCEST (SS-CEST) technique effectively differentiated between healthy and injured discs, with injured discs exhibiting significantly higher k_sw values. Using MTR and k_sw, the PRF model achieved 80% accuracy in predicting pain scores disc-by-disc, outperforming the correlation with Modic changes (r = 0.45, p < 0.05); with a Cohen's Kappa of 0.4. 3D steady-state qCEST with whole-spine coverage can be done at 3T within 32 min using MR Multitasking (acceleration factor of 22), and qCEST-derived biomarkers (MTR and k_sw) can predict pain scores with an accuracy of 80%.