Non-invasive and rapid determination of plant biomass would be beneficial for a number of research aims. Here, we present a novel device to non-invasively determine plant water content as a proxy for ...plant biomass. It is based on changes of dielectric properties inside a microwave cavity resonator induced by inserted plant material. The water content of inserted shoots leads to a discrete shift in the centre frequency of the resonator. Calibration measurements with pure water showed good spatial homogeneity in the detection volume of the microwave resonators and clear correlations between water content and centre frequency shift. For cut tomato and tobacco shoots, linear correlations between fresh weight and centre frequency shift were established. These correlations were used to continuously monitor diel growth patterns of intact plants and to determine biomass increase over several days. Interferences from soil and root water were excluded by shielding pots with copper. The presented proof of principle shows that microwave resonators are promising tools to quantitatively detect the water content of plants and to determine plant biomass. As the method is non-invasive, integrative and fast, it provides the opportunity for detailed, dynamic analyses of plant growth, water status and phenotype.
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
F-fluorodeoxyglucose (
F-FDG PET).
C magnetic resonance spectroscopic imaging (
CMRSI) 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
C 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
C 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
CMRSI is 1-
Cpyruvate, 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-
Cpyruvate to 1-
Clactate in a prostate carcinoma cell line, PC3, in vitro using
CMRSI.
In the metabolism of acetate several enzymes are involved, which play an important role in free fatty acid oxidation. Fatty acid metabolism is altered in diabetes patients and therefore acetate might ...serve as a marker for pathological changes in the fuel selection of cells, as these changes occur in diabetes patients. Acetylcarnitine is a metabolic product of acetate, which enables its transport into the mitochondria for energy production. This study investigates whether the ratio of acetylcarnitine to acetate, measured by noninvasive hyperpolarized 1‐13Cacetate magnetic resonance spectroscopy, could serve as a marker for myocardial, hepatic, and renal metabolic changes in rats with Streptozotocin (STZ)‐induced diabetes in vivo. We demonstrate that the conversion of acetate to acetylcarnitine could be detected and quantified in all three organs of interest. More interestingly, we found that the hyperpolarized acetylcarnitine to acetate ratio was independent of blood glucose levels and prolonged hyperglycemia following diabetes induction in a type‐1 diabetes model.
This study investigates whether the ratio of acetylcarnitine to acetate, measured with noninvasive hyperpolarized 1‐13Cacetate magnetic resonance spectroscopy, could serve as a marker for myocardial, hepatic and renal metabolic changes in rats with Streptozotocin (STZ) induced diabetes in vivo.
Hyperpolarized (13)C imaging allows real-time in vivo measurements of metabolite levels. Quantification of metabolite conversion between 1-(13)Cpyruvate and downstream metabolites 1-(13)Calanine, ...1-(13)Clactate, and (13)Cbicarbonate 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.
High-Dimensional Confidence Regions in Sparse MRI Hoppe, Frederik; Krahmer, Felix; Mayrink Verdun, Claudio ...
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),
2023-June-4
Conference Proceeding
Odprti dostop
One of the most promising solutions for uncertainty quantification in high-dimensional statistics is the debiased LASSO that relies on unconstrained ℓ 1 -minimization. The initial works focused on ...real Gaussian designs as a toy model for this problem. However, in medical imaging applications, such as compressive sensing for MRI, the measurement system is represented by a (subsampled) complex Fourier matrix. The purpose of this work is to extend the method to the MRI case in order to construct confidence intervals for each pixel of an MR image. We show that a sufficient amount of data is n \gtrsim \max \left\{ {{s_0}{{\log }^2}{s_0}\log p,{s_0}{{\log }^2}p} \right\}.
Dear Editor, Indeed acetate trafficking matters, however, hyperpolarized 13C‐acetate‐to‐acetylcarnitine is unable to detect any significant alterations between healthy controls and type‐1 diabetic ...rat heart, liver, and kidney, respectively in the fed state, with the current clinical setting hyperpolarized methodology. The use of the short‐chain fatty acid acetate as an imaging biomarker has on the other hand shown success in PET, where acetate turnover is associated with oxygen consumption in both heart and kidney (Shreve et al. ; Juillard et al. ). ...we examined if the metabolic imbalance between the glucose utilization and fatty acid oxidation seen in diabetes would be observable in the diabetic rat in heart, liver, and kidneys by hyperpolarized 13C‐acetate‐to‐acetylcarnitine conversion. Acetyl‐CoA synthetase substrate imbalance has been associated with hypoxia, myocardial disease, fatty acid oxidation disorders, and diabetes (Rebouche and Paulson ; Jensen et al. ).
Current state-of-the-art reconstruction for quantitative tissue maps from fast, compressive, Magnetic Resonance Fingerprinting (MRF), use supervised deep learning, with the drawback of requiring ...high-fidelity ground truth tissue map training data which is limited. This paper proposes NonLinear Equivariant Imaging for MRF (NLEIMRF), a self-supervised learning approach to eliminate the need for ground truth for deep MRF image reconstruction. NLEI-MRF extends the recent Equivariant Imaging framework to the MRF nonlinear inverse problem. Only compressed-sampled MRF scans are used for training. NLEI-MRF learns tissue mapping using spatiotemporal priors: spatial priors are obtained from the invariance of MRF data to a group of geometric image transformations, while temporal priors are obtained from a nonlinear Bloch response model approximated by a pre-trained neural network. Tested retrospectively on two acquisition settings, we observe that NLEI-MRF closely approaches the performance of supervised learning.
Hyperpolarized 13C imaging allows real-time in vivo measurements of metabolite levels. Quantification of metabolite conversion between 1-13Cpyruvate and downstream metabolites 1-13Calanine, ...1-13Clactate, and 13Cbicarbonate 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.
Diffusion tensor magnetic resonance imaging (DT-MRI) is a non-invasive imaging technique allowing to estimate the molecular self-diffusion tensors of water within surrounding tissue. Due to the low ...signal-to-noise ratio of magnetic resonance images, reconstructed tensor images usually require some sort of regularization in a post-processing step. Previous approaches are either suboptimal with respect to the reconstructing or regularization step. This paper presents a Bayesian approach for simultaneous reconstructing and regularization of DT-MR images that allows to resolve the disadvantages of previous approaches. To this end, estimation theoretical concepts are generalized to tensor valued images that are considered as Riemannian manifolds. Doing so allows us to derive a maximum a posterior estimator of the tensor image that considers both the statistical characteristics of the Rician noise occurring in MR images as well as the nonlinear structure of tensor valued images. Experiments on synthetic data as well as real DT-MRI data validate the advantage of considering both statistical as well as geometrical characteristics of DT-MRI.
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