Quantitative MRI imaging of parenchyma and venation networks in Brassica napus leaves: effects of development and dehydration.

BACKGROUND: Characterisation of the structure and water status of leaf tissues is essential to the understanding of leaf hydraulic functioning under optimal and stressed conditions. Magnetic Resonance Imaging is unique in its capacity to access this information in a spatially resolved, non-invasive and non-destructive way. The purpose of this study was to develop an original approach based on transverse relaxation mapping by Magnetic Resonance Imaging for the detection of changes in water status and distribution at cell and tissue levels in Brassica napus leaves during blade development and dehydration. RESULTS: By combining transverse relaxation maps with a classification scheme, we were able to distinguish specific zones of areoles and veins. The tissue heterogeneity observed in young leaves still occurred in mature and senescent leaves, but with different distributions of T2 values in accordance with the basipetal progression of leaf blade development, revealing changes in tissue structure. When subjected to severe water stress, all blade zones showed similar behaviours. CONCLUSION: This study demonstrates the great potential of Magnetic Resonance Imaging in assessing information on the structure and water status of leaves. The feasibility of in planta leaf measurements was demonstrated, opening up many opportunities for the investigation of leaf structure and hydraulic functioning during development and/or in response to abiotic stresses.

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.

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.

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.

Genetic Parameters and Genome-Wide Association Studies of Quality Traits Characterised Using Imaging Technologies in Rainbow Trout, Oncorhynchus mykiss.

One of the top priorities of the aquaculture industry is the genetic improvement of economically important traits in fish, such as those related to processing and quality. However, the accuracy of genetic evaluations has been hindered by a lack of data on such traits from a sufficiently large population of animals. The objectives of this study were thus threefold: (i) to estimate genetic parameters of growth-, yield-, and quality-related traits in rainbow trout (Oncorhynchus mykiss) using three different phenotyping technologies [invasive and non-invasive: microwave-based, digital image analysis, and magnetic resonance imaging (MRI)], (ii) to detect quantitative trait loci (QTLs) associated with these traits, and (iii) to identify candidate genes present within these QTL regions. Our study collected data from 1,379 fish on growth, yield-related traits (body weight, condition coefficient, head yield, carcass yield, headless gutted carcass yield), and quality-related traits (total fat, percentage of fat in subcutaneous adipose tissue, percentage of fat in flesh, flesh colour); genotypic data were then obtained for all fish using the 57K SNP Axiom® Trout Genotyping array. Heritability estimates for most of the 14 traits examined were moderate to strong, varying from 0.12 to 0.67. Most traits were clearly polygenic, but our genome-wide association studies (GWASs) identified two genomic regions on chromosome 8 that explained up to 10% of the genetic variance (cumulative effects of two QTLs) for several traits (weight, condition coefficient, subcutaneous and total fat content, carcass and headless gutted carcass yields). For flesh colour traits, six QTLs explained 1-4% of the genetic variance. Within these regions, we identified several genes (htr1, gnpat, ephx1, bcmo1, and cyp2x) that have been implicated in adipogenesis or carotenoid metabolism, and thus represent good candidates for further functional validation. Finally, of the three techniques used for phenotyping, MRI demonstrated particular promise for measurements of fat content and distribution, while the digital image analysis-based approach was very useful in quantifying colour-related traits. This work provides new insights that may aid the development of commercial breeding programmes in rainbow trout, specifically with regard to the genetic improvement of yield and flesh-quality traits as well as the use of invasive and/or non-invasive technologies to predict such traits.

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.

Multi-tissue partial volume quantification in multi-contrast MRI using an optimised spectral unmixing approach.

Multi-tissue partial volume estimation in MRI images is investigated with a viewpoint related to spectral unmixing as used in hyperspectral imaging. The main contribution of this paper is twofold. It firstly proposes a theoretical analysis of the statistical optimality conditions of the proportion estimation problem, which in the context of multi-contrast MRI data acquisition allows to appropriately set the imaging sequence parameters. Secondly, an efficient proportion quantification algorithm based on the minimisation of a penalised least-square criterion incorporating a regularity constraint on the spatial distribution of the proportions is proposed. Furthermore, the resulting developments are discussed using empirical simulations. The practical usefulness of the spectral unmixing approach for partial volume quantification in MRI is illustrated through an application to food analysis on the proving of a Danish pastry.

Quantification of mass fat fraction in fish using water-fat separation MRI.

Selection of fish with appropriate fat content and anatomic distribution is searched in fish industry. This necessitates fast and accurate measurements of mass fat fraction maps on a large number of fish. The objective of this work is to assess the relevance of MRI water-fat separation for this purpose. For the separation of the water and fat images we rely on a single T2(⁎) and a multiple peak fat spectrum model, the parameters of which are estimated using the "Varpro" method. The difference of proton density between fat and water and the lack of the signal from the macromolecules are taken into account to convert the obtained proton density fat fraction into mass fat fraction. We used 0.23T NMR to validate the method on 30 salmon steaks. The fat fraction values were in the range of 5% to 25%. Very good accordance was found between 1.5T MRI and NMR although MRI slightly overestimated the mass fat fraction. The R(2) of the linear regression was equal to 0.96 (P<10(-5)), the slope to 1.12 (CI.95=0.03). These results demonstrate that a good accuracy can be achieved. We also show that high throughput can be achieved since the measurements do not depend on the position and we conclude that, for example, it is feasible to quantify the mass fat fraction in fish steaks within about one minute per sample.

Rapid quantification of muscle fat content and subcutaneous adipose tissue in fish using MRI.

The potentiality of MRI to quantify fat content in flesh and subcutaneous fat in fish cutlets was investigated. Low measurement time was aimed at in a view to handling large number of samples needed in selective breeding programs for example. Results on fresh and frozen-thawed cutlets were compared to assess this way of conservation. As MRI generates unwanted spatial variations of the signal, a correction method was developed enabling the measurement on several cutlets simultaneously in less than 3 min per sample. For subcutaneous fat, the results were compared with vision measurements. High correlations between both techniques were found (R(2)=0.77 and 0.87 for the ventral and dorsal part). Fat in flesh was validated vs NMR measurements. No statistical difference was found between fresh and frozen-thawed cutlets. RMSE was respectively 0.8% and 0.89%. These results confirmed the potentiality of MRI for fat measurement in fish particularly for a large number of samples.

Muscle and fat quantification in MRI gradient echo images using a partial volume detection method. Application to the characterization of pig belly tissue.

Complete dissection is the current reference method to quantify muscle and fat tissue on pig carcasses. Magnetic resonance imaging (MRI) is an appropriate nondestructive alternative method that can provide reliable and quantitative information on pig carcass composition without losing the spatial information. We have developed a method to quantify the amount of fat tissue and muscle in gradient echo MR images. This method is based on the method proposed by Shattuck et al. [12]. It provides segmentation of pure tissue and partial volume voxels, which allows separation of muscle and fat tissue including the fine insertions of intermuscular fat. Partial volume voxel signal is expected to be proportional to the signals of pure tissue constituting them or at least to vary monotonously with the proportion of each tissue. However, it is not always the case with gradient echo sequence due to the chemical shift effect. We studied this effect on a fat tissue/muscle interface model with variable proportion of water in the fat tissue and variable TE. We found that at TE=8 ms, for a 0.2-T MRI system, the requirement of Shattuck's method were filled thanks to the presence of water in fat tissue. Moreover, we extended the segmentation method with a simple correction scheme to compute more accurately the proportions of each tissue in partial volume voxels. We used this method to evaluate the fat tissue and muscle on 24 pig bellies using a gradient echo sequence (TR 700 ms, TE 8 ms, slice thickness 8 mm, number of averages 8, flip angle 90 degrees , FOV 512 mm, matrix 512*512, Rect. FOV 4/8, 19 slices, space between slices 2 mm). The image analysis results were compared with dissection results giving a prediction error of the muscle content (mean=2.7 kg) of 88.9 g and of the fat content (mean=2.7 kg) of 115.8 g without correction of the chemical shift effect in the computation of partial volume fat content. The correction scheme improved these results to, respectively, 81.5 and 107.1 g.