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Nuclear Magnetic Resonance (NMR) provides a highly flexible platform for non invasive analysis and imaging biological samples, since the manipulation of nuclear spin allows the tailoring of experiments to maximize the informativeness of the data. MRI is capable of visualizing a holistic picture of the lipid storage in living plant/seed. This review has sought to explain how the technology can be used to acquire functional and physiological data from plant samples, and how to exploit it to characterize lipid deposition in vivo. At the same time, we have referred to the current limitations of NMR technology as applied to plants, and in particular of the difficulty of transferring methodologies optimized for animal/medical subjects to plant ones. A forward look into likely developments in the field is included, anticipating its key future role in the study of living plant.
Purpose
To test quantitative functional lung MRI techniques in young adults with cystic fibrosis (CF) compared to healthy volunteers and to monitor immediate treatment effects of a single inhalation of hypertonic saline in comparison to clinical routine pulmonary function tests.
Materials and methods
Sixteen clinically stable CF patients and 12 healthy volunteers prospectively underwent two functional lung MRI scans and pulmonary function tests before and 2h after a single treatment of inhaled hypertonic saline or without any treatment. MRI-derived oxygen enhanced T1 relaxation measurements, fractional ventilation, first-pass perfusion parameters and a morpho-functional CF-MRI score were acquired.
Results
Compared to healthy controls functional lung MRI detected and quantified significantly increased ventilation heterogeneity in CF patients. Regional functional lung MRI measures of ventilation and perfusion as well as the CF-MRI score and pulmonary function tests could not detect a significant treatment effect two hours after a single treatment with hypertonic saline in young adults with CF (p>0.05).
Conclusion
This study shows the feasibility of functional lung MRI as a non-invasive, radiation-free tool for monitoring patients with CF.
Diabetic neuropathy (DPN) is one of the most severe and yet most poorly understood complications of diabetes mellitus. In vivo imaging of dorsal root ganglia (DRG), a key structure for the understanding of DPN, has been restricted to animal studies. These have shown a correlation of decreased DRG volume with neuropathic symptom severity. Our objective was to investigate correlations of DRG morphology and signal characteristics at 3 Tesla (3T) magnetic resonance neurography (MRN) with clinical and serological data in diabetic patients with and without DPN. In this cross-sectional study, participants underwent 3T MRN of both L5 DRG using an isotropic 3D T2-weighted, fat-suppressed sequence with subsequent segmentation of DRG volume and analysis of normalized signal properties. Overall, 55 diabetes patients (66 ± 9 years; 32 men; 30 with DPN) took part in this study. DRG volume was smaller in patients with severe DPN when compared to patients with mild or moderate DPN (134.7 ± 21.86 vs 170.1 ± 49.22; p = 0.040). In DPN patients, DRG volume was negatively correlated with the neuropathy disability score (r = −0.43; 95%CI = −0.66 to −0.14; p = 0.02), a measure of neuropathy severity. DRG volume showed negative correlations with triglycerides (r = −0.40; 95%CI = −0.57 to −0.19; p = 0.006), and LDL cholesterol (r = −0.33; 95%CI = −0.51 to −0.11; p = 0.04). There was a strong positive correlation of normalized MR signal intensity (SI) with the neuropathy symptom score in the subgroup of patients with painful DPN (r = 0.80; 95%CI = 0.46 to 0.93; p = 0.005). DRG SI was positively correlated with HbA1c levels (r = 0.30; 95%CI = 0.09 to 0.50; p = 0.03) and the triglyceride/HDL ratio (r = 0.40; 95%CI = 0.19 to 0.57; p = 0.007). In this first in vivo study, we found DRG morphological degeneration and signal increase in correlation with neuropathy severity. This elucidates the potential importance of MR-based DRG assessments in studying structural and functional changes in DPN.
Increased aortic stiffness is known to be associated with atherosclerosis and has a predictive value for cardiovascular events. This study aims to investigate the local distribution of early arterial stiffening due to initial atherosclerotic lesions. Therefore, global and local pulse wave velocity (PWV) were measured in ApoE\(^{-/-}\) and wild type (WT) mice using ultrahigh field MRI. For quantification of global aortic stiffness, a new multi-point transit-time (TT) method was implemented and validated to determine the global PWV in the murine aorta. Local aortic stiffness was measured by assessing the local PWV in the upper abdominal aorta, using the flow/area (QA) method. Significant differences between age matched ApoE\(^{-/-}\) and WT mice were determined for global and local PWV measurements (global PWV: ApoE\(^{-/-}\): 2.7 ±0.2m/s vs WT: 2.1±0.2m/s, P<0.03; local PWV: ApoE\(^{-/-}\): 2.9±0.2m/s vs WT: 2.2±0.2m/s, P<0.03). Within the WT mouse group, the global PWV correlated well with the local PWV in the upper abdominal aorta (R\(^2\) = 0.75, P<0.01), implying a widely uniform arterial elasticity.
In ApoE\(^{-/-}\) animals, however, no significant correlation between individual local and global PWV was present (R\(^2\) = 0.07, P = 0.53), implying a heterogeneous distribution of vascular stiffening in early atherosclerosis. The assessment of global PWV using the new multi-point TT measurement technique was validated against a pressure wire measurement in a vessel
phantom and showed excellent agreement. The experimental results demonstrate that vascular stiffening caused by early atherosclerosis is unequally distributed over the length of large vessels. This finding implies that assessing heterogeneity of arterial stiffness by multiple local measurements of PWV might be more sensitive than global PWV to identify early atherosclerotic lesions.
To evaluate an iterative learning approach for enhanced performance of robust artificial‐neural‐networks for k‐space interpolation (RAKI), when only a limited amount of training data (auto‐calibration signals [ACS]) are available for accelerated standard 2D imaging.
Methods
In a first step, the RAKI model was tailored for the case of limited training data amount. In the iterative learning approach (termed iterative RAKI [iRAKI]), the tailored RAKI model is initially trained using original and augmented ACS obtained from a linear parallel imaging reconstruction. Subsequently, the RAKI convolution filters are refined iteratively using original and augmented ACS extracted from the previous RAKI reconstruction. Evaluation was carried out on 200 retrospectively undersampled in vivo datasets from the fastMRI neuro database with different contrast settings.
Results
For limited training data (18 and 22 ACS lines for R = 4 and R = 5, respectively), iRAKI outperforms standard RAKI by reducing residual artifacts and yields better noise suppression when compared to standard parallel imaging, underlined by quantitative reconstruction quality metrics. Additionally, iRAKI shows better performance than both GRAPPA and standard RAKI in case of pre‐scan calibration with varying contrast between training‐ and undersampled data.
Conclusion
RAKI benefits from the iterative learning approach, which preserves the noise suppression feature, but requires less original training data for the accurate reconstruction of standard 2D images thereby improving net acceleration.
Background: Cystic fibrosis (CF) patients would benefit from a safe and effective tool to detect early-stage, regional lung disease to allow for early intervention. Magnetic Resonance Imaging (MRI) is a safe, non-invasive procedure capable of providing quantitative assessments of disease without ionizing radiation. We developed a rapid normalized T1 MRI technique to detect regional lung disease in early-stage CF patients.
Materials and Methods: Conventional multislice, pulmonary T1 relaxation time maps were obtained for 10 adult CF patients with normal spirometry and 5 healthy non-CF control subjects using a rapid Look-Locker MRI acquisition (5 seconds/imaging slice). Each lung absolute T1 map was separated into six regions of interest (ROI) by manually selecting upper, central, and lower lung regions in the left and right lungs. In order to reduce the effects of subject-to-subject variation, normalized T1 maps were calculated by dividing each pixel in the absolute T1 maps by the mean T1 time in the central lung region. The primary outcome was the differences in mean normalized T1 values in the upper lung regions between CF patients with normal spirometry and healthy volunteers.
Results: Normalized T1 (nT1) maps showed visibly reduced subject-to-subject variation in comparison to conventional absolute T1 maps for healthy volunteers. An ROI analysis showed that the variation in the nT1 values in all regions was <= 2% of the mean. The primary outcome, the mean (SD) of the normalized T1 values in the upper right lung regions, was significantly lower in the CF subjects [.914 (.037)] compared to the upper right lung regions of the healthy subjects [.983 (.003)] [difference of .069 (95% confidence interval .032-.105); p=.001). Similar results were seen in the upper left lung region.
Conclusion: Rapid normalized T1 MRI relaxometry obtained in 5 seconds/imaging slice may be used to detect regional early-stage lung disease in CF patients.
Purpose: To compare a novel combined acquisition technique (CAT) of turbo-spin-echo (TSE) and echo-planar-imaging (EPI) with conventional TSE. CAT reduces the electromagnetic energy load transmitted for spin excitation. This radiofrequency (RF) burden is limited by the specific absorption rate (SAR) for patient safety. SAR limits restrict high-field MRI applications, in particular.
Material and Methods: The study was approved by the local Medical Ethics Committee. Written informed consent was obtained from all participants. T2- and PD-weighted brain images of n = 40 Multiple Sclerosis (MS) patients were acquired by CAT and TSE at 3 Tesla. Lesions were recorded by two blinded, board-certificated neuroradiologists. Diagnostic equivalence of CAT and TSE to detect MS lesions was evaluated along with their SAR, sound pressure level (SPL) and sensations of acoustic noise, heating, vibration and peripheral nerve stimulation.
Results: Every MS lesion revealed on TSE was detected by CAT according to both raters (Cohen's kappa of within-rater/across-CAT/TSE lesion detection kappa(CAT) = 1.00, at an inter-rater lesion detection agreement of kappa(LES) = 0.82). CAT reduced the SAR burden significantly compared to TSE (p<0.001). Mean SAR differences between TSE and CAT were 29.0 (+/- 5.7) % for the T2-contrast and 32.7 (+/- 21.9) % for the PD-contrast (expressed as percentages of the effective SAR limit of 3.2 W/kg for head examinations). Average SPL of CAT was no louder than during TSE. Sensations of CAT-vs. TSE-induced heating, noise and scanning vibrations did not differ.
Conclusion: T2-/PD-CAT is diagnostically equivalent to TSE for MS lesion detection yet substantially reduces the RF exposure. Such SAR reduction facilitates high-field MRI applications at 3 Tesla or above and corresponding protocol standardizations but CAT can also be used to scan faster, at higher resolution or with more slices. According to our data, CAT is no more uncomfortable than TSE scanning.