MSE-MRI sequence optimisation for measurement of bi- and tri-exponential T2 relaxation in a phantom and fruit

Quantitative MRI post-processing algorithm and visualization research based on moisture status detection of winter jujube

Quantitative Magnetic Resonance Imaging (qMRI) offers precise measurements of the relaxation characteristics of microstructures, representing a cutting-edge method in non-destructive fruit analysis. This study aims to visualize information on changes in moisture status and distribution at the subcellular level of winter jujube. The 0.5 T nuclear magnetic imaging equipment was utilized to rapidly, non-invasively, and accurately capture the internal relaxation status of the sample with multiple-echo-imaging. By examining the signal and noise data, a simulated dataset was developed to tackle the optimization challenge of estimating parameters for the discrete relaxation model from the multiple-echo-imaging data, especially under conditions of low signal-to-noise ratio (SNR) and in the context of heteroscedastic noise. An optimal weighting factor and the T2NR truncation model have been identified to establish an effective experimental inversion strategy. Subsequently, multiple-echo-imaging can rapidly and stably yielded voxel-level maps under conditions of low signal-to-noise ratio. Utilizing this experimental approach, data from winter jujube was collected and analyzed, facilitating an exploration of water activity (T2 mapping) and associated water content (A2 mapping). Through analyzing winter jujube fruits across two maturity stages, this study elucidates the role of precise quantification and voxel-wise visualization in moisture status detection. The methodology presents an innovative approach for assessing internal moisture distribution in fruits.

Quantitative magnetic resonance imaging of in vitro gastrointestinal digestion of a bread and cheese meal

The monitoring of food degradation during gastrointestinal digestion is essential in understanding food structure impacts on the bioaccessibility and bioavailability of nutrients. Magnetic Resonance Imaging (MRI) has the unique ability to access information on changes in multi-scale structural features of foods in a spatially resolved and non-destructive way. Our objective was to exploit various opportunities offered by MRI for monitoring starch, lipid and protein hydrolysis, as well as food particle breakdown during the semi-dynamic in vitro gastrointestinal digestion of complex foods combined in a meal. The meal consisted of French bread, hard cheese and water (drink), with a realistic distribution of bolus particle sizes. The MRI approach was reinforced by parallel chemical analysis of all macronutrients in the supernatant. By combining different imaging protocols, quantitative MRI provided insights into a number of phenomena at the level of the cheese and bread particles and within the liquid phase that are hard to access through conventional approaches. MRI thus revealed the progressive ingress of fluids into the bread crust and the release of the gas trapped in the crumb, the erosion of cheese particles, the creaming of fat, the disappearance of small food particles and changes in liquid phase composition. Excellent agreement was obtained between the quantitative parameters extracted from the MRI images and the results of the chemical analysis, demonstrating the strong potential of MRI for the monitoring of in vitro gastrointestinal digestion. The present study proposes further improvements to fully exploit the capabilities of MRI and constitutes an important step towards the extension of quantitative MRI to in vivo studies.

Characterization of Potato Tuber Tissues Using Spatialized MRI T2 Relaxometry

Magnetic Resonance Imaging is a powerful non-destructive tool in the study of plant tissues. For potato tubers, it greatly assists the study of tissue defects and tissue evolution during storage. This paper describes the MRI analysis of potato tubers with internal defects in their flesh tissue at eight sampling dates from 14 to 33 weeks after harvest. Spatialized multi-exponential T2 relaxometry was used to generate bi-exponential T2 maps, coupled with a classification scheme to identify the different T2 homogeneous zones within the tubers. Six classes with statistically different relaxation parameters were identified at each sampling date, allowing the defects and the pith and cortex tissues to be detected. A further distinction could be made between three constitutive elements within the flesh, revealing the heterogeneity of this particular tissue. Relaxation parameters for each class and their evolution during storage were successfully analyzed. The work demonstrated the value of MRI for detailed non-invasive plant tissue characterization.

Characterization of the Water Shortage Effects on Potato Tuber Tissues during Growth Using MRI Relaxometry and Biochemical Parameters

The potato is one of the most cultivated crops worldwide, providing an important source of food. The quality of potato tubers relates to their size and dry matter composition and to the absence of physiological defects. It depends on the spatial and temporal coordination of growth and metabolic processes in the major tuber tissues: the cortex, flesh and pith. In the present study, variations in the biochemical traits of each of these tissues were investigated during tuber growth under optimal and water-deficit conditions. MRI relaxometry was used as a non-invasive and quantitative method to access information on cellular water status. The presence of slight but significant variations in organic compound contents quantified in the cortex and flesh revealed a tissue-dependent metabolic pattern. The T₂ and relative I₀ of the bi-exponential relaxation signal allowed a distinction to be made between the pith and the cortex, whereas the flesh could be differentiated from these tissues only through its relative I₀. T₂ values did not vary significantly during tuber development, in accordance with the typical growth pattern of tubers, but were shown to be sensitive to water stress. The interpretation of the multi-exponential transverse relaxation times is discussed and could be further developed via microscopic analysis.

New strategies on the application of artificial intelligence in the field of phytoremediation

Artificial Intelligence (AI) is expected to play a crucial role in the field of phytoremediation and its effective management in monitoring the growth of the plant in different contaminated soils and their phenotype characteristic such as the biomass of plants. This review focuses on recent applications of various AI techniques and remote sensing approaches in the field of phytoremediation to monitor plant growth with relevant morphological parameters using novel sensors, cameras, and associated modern technologies. Novel sensing and various measurement techniques are highlighted. Input parameters are used to develop futuristic models utilizing AI and statistical approaches. Additionally, a brief discussion has been presented on the use of AI techniques to detect metal hyperaccumulation in all parts of the plant, carbon capture, and sequestration along with its effect on food production to ensure food safety and security. This article highlights the application, limitation, and future perspectives of phytoremediation in monitoring the mobility, bioavailability, seasonal variation, effect of temperature on plant growth, and plant response to the heavy metals in soil by using the AI technique. Suggestions are made for future research in this area to analyze which would help to enhance plant growth and improve food security in long run.

Quantitative MRI analysis of structural changes in tomato tissues resulting from dehydration

A quantitative magnetic resonance imaging (MRI) analysis at 1.5T of the effects of different dehydration regimes on transverse relaxation parameters measured in tomato tissue is presented. Multi-exponential T₂ maps have been estimated for the first time, providing access to spatialized microstructural information at voxel scale. The objective was to provide a better understanding of the changes in the multi-exponential transverse relaxation parameters induced by dehydration in tomato tissues and to unravel the effects of microstructure and composition on relaxation parameters. The results led to the hypothesis that the multi-exponential relaxation signal reflects cell compartmentation and tissue heterogeneity, even at the voxel scale. Multi-exponential relaxation times provided information about water loss from specific cell compartments and seem to indicate that the dehydration process mainly affects large cells. By contrast, total signal intensity showed no sensitivity to variations in water content in the range investigated in the present study (between 95% [fresh tissue] and 90% [after dehydration]). The variation in relaxation times resulting from water loss was due to both changes in solute concentration and compartment size. The comparative analysis of the two contrasted tissues in terms of microporosity demonstrated that magnetic susceptibility effects, caused by the presence of air in the placenta tissue, significantly impact the effective relaxation and might be the dominant effect in the variations observed in relaxation times in this tissue.

A Weighted Stochastic Conjugate Direction Algorithm for Quantitative Magnetic Resonance Images—A Pattern in Ruptured Achilles Tendon T2-Mapping Assessment

This study presents an accurate biexponential weighted stochastic conjugate direction (WSCD) method for the quantitative T2-mapping reconstruction of magnetic resonance images (MRIs), and this approach was compared with the non-negative-least-squares Gauss–Newton (GN) numerical optimization method in terms of accuracy and goodness of fit of the reconstructed images from simulated data and ruptured Achilles tendon (AT) MRIs. Reconstructions with WSCD and GN were obtained from data simulating the signal intensity from biexponential decay and from 58 MR studies of postrupture, surgically repaired ATs. Both methods were assessed in terms of accuracy (closeness of the means of calculated and true simulated T2 values) and goodness of fit (magnitude of mean squared error (MSE)). The lack of significant deviation in correct T2 values for the WSCD method was demonstrated for SNR ≥ 20 and for GN–SNR ≥ 380. The MSEs for WSCD and GN were 287.52 ± 224.11 and 2553.91 ± 1932.31, respectively. The WSCD reconstruction method was better than the GN method in terms of accuracy and goodness of fit.

Multi-exponential MRI T2 maps: A tool to classify and characterize fruit tissues

The estimation of multi-exponential relaxation time T₂ and their associated amplitudes A₀ at the voxel level has been made possible by recent developments in the field of image processing. These data are of great interest for the characterization of biological tissues, such as fruit tissues. However, they represent a high number of information, not easily interpretable. Moreover, the non-uniformity of the MRI images, which mainly directly impacts A₀, could induce interpretation errors. In this paper, we propose a post-processing scheme that clusters similar voxels according to the multi-exponential relaxation parameters in order to reduce the complexity of the information while avoiding the problems associated with intensity non-uniformity. We also suggest a data representation suitable for the visualization of the multi-T₂ distribution within each tissue. We illustrate this work with results for different fruits, demonstrating the great potential of multi-T₂ information to shed new light on fruit characterization.

Impact of chemical exchange on transverse relaxation at low and moderate magnetic field strengths for sugar solutions representative of fruit tissues analyzed by simulation and MRI experiments

Proton exchange effects on transverse relaxation rate were studied at low and moderate magnetic fields. Analysis was conducted on low-concentrate simple sugar (fructose and glucose) solutions modeling the vacuolar liquid in fruits. Simulated data obtained from Carver and Richards equations were used to analyze the effects of temperature and pH on parameters involved in the chemical exchange mechanisms. The results have highlighted that measurement conditions and tissue characteristics (echo time, magnetic field strength, temperature, pH, etc.) significantly impact the transverse relaxation rate via chemical exchange, even for low and mid magnetic fields and the narrow echo time ranges of TD-NMR and MRI measurements. This explains some of the divergent relaxation data from plant tissue NMR measurements reported in the literature and emphasizes the importance of taking experimental conditions and tissue characteristics into account when interpreting results. It also clearly demonstrates that the appropriate choice of experimental conditions can emphasize the effects of sugar concentration or pH variations on transverse relaxation in vacuolar liquids, making it possible to monitor these parameters accurately via transverse relaxation measurements. The impact of concentration, solute type, pH and temperature on transverse relaxation of sugar solutions were demonstrated experimentally at 1.5 T with an MRI scanner. These data were interpreted using the Carver-Richards model which was effective in estimating parameters involved in chemical exchange mechanism in the imaging experiment.

Spatial and temporal evolution of quantitative magnetic resonance imaging parameters of peach and apple fruit - relationship with biophysical and metabolic traits

Fruits are complex organs that are spatially regulated during development. Limited phenotyping capacity at cell and tissue levels is one of the main obstacles to our understanding of the coordinated regulation of the processes involved in fruit growth and quality. In this study, the spatial evolution of biophysical and metabolic traits of peach and apple fruit was investigated during fruit development. In parallel, the multi-exponential relaxation times and apparent microporosity were assessed by quantitative magnetic resonance imaging (MRI). The aim was to identify the possible relationships between MRI parameters and variations in the structure and composition of fruit tissues during development so that transverse relaxation could be proposed as a biomarker for the assessment of the structural and functional evolution of fruit tissues during growth. The study provides species-specific data on developmental and spatial variations in density, cell number and size distribution, insoluble and soluble compound accumulation and osmotic and water potential in the fruit mesocarp. Magnetic resonance imaging was able to capture tissue evolution and the development of pericarp heterogeneity by accessing information on cell expansion, water status and distribution at cell level, and microporosity. Changes in vacuole-related transverse relaxation rates were mostly explained by cell/vacuole size. The impact of cell solute composition, microporosity and membrane permeability on relaxation times is also discussed. The results demonstrate the usefulness of MRI as a tool to phenotype fruits and to access important physiological data during development, including information on spatial variability.

Multi-exponential Transverse Relaxation Times Estimation from Magnetic Resonance Images under Rician Noise and Spatial Regularization

Relaxation signal inside each voxel of magnetic resonance images (MRI) is commonly fitted by a multi-exponential decay curve. The estimation of a discrete multi-component relaxation model parameters from magnitude MRI data is a challenging nonlinear inverse problem since it should be conducted on the entire image voxels under non-Gaussian noise statistics. This paper proposes an efficient algorithm allowing the joint estimation of relaxation time values and their amplitudes using different criteria taking into account a Rician noise model, combined with a spatial regularization accounting for low spatial variability of relaxation time constants and amplitudes between neighboring voxels. The Rician noise hypothesis is accounted for either by an adapted nonlinear least squares algorithm applied to a corrected least squares criterion or by a majorization-minimization approach applied to the maximum likelihood criterion. In order to solve the resulting large-scale non-negativity constrained optimization problem with a reduced numerical complexity and computing time, an optimization algorithm based on a majorization approach ensuring separability of variables between voxels is proposed. The minimization is carried out iteratively using an adapted Levenberg-Marquardt algorithm that ensures convergence by imposing a sufficient decrease of the objective function and the non-negativity of the parameters. The importance of the regularization alongside the Rician noise incorporation is shown both visually and numerically on a simulated phantom and on magnitude MRI images acquired on fruit samples.

The application of Magnetic Resonance Imaging (mri) to the examination of plant tissues and water barriers

The aim of the present study is to extend the applicability of MRI measurements similar to those used in human diagnostics to the examination of water barriers in living plants, thus broadening their use in natural sciences. The cucumber, Cucumis sativus, and Phillyrea angustifolia, or false olive, were chosen as test plants. The MRI measurements were carried out on three samples of each plant in the same position vis-a-vis the MRI apparatus using a Siemens Avanto MRI scanner. Two different relaxation times were employed, T₁, capable of histological mapping, and T₂, used for the examination of water content. In the course of the analysis, it was found that certain histological formations and branching cause modifications to the intensity detected with relaxation time T₂. Furthermore, these positions can also be found in T1 measurements. A monotonic correlation (cucumber: ρ = 0.829; false olive: ρ = -0.84) was observed between the T₁ and T₂ measurements. In the course of the statistical analysis of the signal intensities of the xylems it was concluded that they cannot be regarded as independent in a statistical sense; these changes rather depend on the anatomic structure of the plant, as the intensity profile is modified by nodes, leaves and branches. This serves as a demonstration of the applicability of MRI to the measurement of well know plant physiological processes. The special parametrization required for this equipment, which is usually used in human diagnostics, is also documented in the present study.

Multicomponent T2 relaxation studies of the avian egg

PURPOSE

To investigate the tissue-like multiexponential T2 signal decays in avian eggs.

METHODS

Transverse relaxation studies of raw, soft-boiled and hard-boiled eggs were performed at 3 Tesla using a three-dimensional Carr-Purcell-Meiboom-Gill imaging sequence. Signal decays over a TE range of 11 to 354 ms were fitted assuming single- and multicomponent signal decays with up to three separately decaying components. Fat saturation was used to facilitate spectral assignment of observed decay components.

RESULTS

Egg white, yolk and the centrally located latebra all demonstrate nonmonoexponential T2 decays. Specifically, egg white exhibits two-component decays with intermediate and long T2 times. Meanwhile, yolk and latebra are generally best characterized with triexponential decays, with short, intermediate and very long T2 decay times. Fat saturation revealed that the intermediate component of yolk could be attributed to lipids. Cooking of the egg profoundly altered the decay curves.

CONCLUSION

Avian egg T2 decay curves cover a wide range of decay times. Observed T2 components in yolk and latebra as short as 10 ms, may prove valuable for testing clinical sequences designed to measure short T2 components, such as myelin-associated water in the brain. Thus we propose that the egg can be a versatile and widely available MR transverse relaxation phantom.