Analysis of magnetization transfer (MT) influence on quantitative mapping of T2 relaxation time

A comprehensive protocol for quantitative magnetic resonance imaging of the brain at 3 Tesla

Quantitative MRI (qMRI) has been shown to be clinically useful for numerous applications in the brain and body. The development of rapid, accurate, and reproducible qMRI techniques offers access to new multiparametric data, which can provide a comprehensive view of tissue pathology. This work introduces a multiparametric qMRI protocol along with full postprocessing pipelines, optimized for brain imaging at 3 Tesla and using state-of-the-art qMRI tools. The total scan time is under 50 minutes and includes eight pulse-sequences, which produce range of quantitative maps including T1, T2, and T2* relaxation times, magnetic susceptibility, water and macromolecular tissue fractions, mean diffusivity and fractional anisotropy, magnetization transfer ratio (MTR), and inhomogeneous MTR. Practical tips and limitations of using the protocol are also provided and discussed. Application of the protocol is presented on a cohort of 28 healthy volunteers and 12 brain regions-of-interest (ROIs). Quantitative values agreed with previously reported values. Statistical analysis revealed low variability of qMRI parameters across subjects, which, compared to intra-ROI variability, was x4.1 ± 0.9 times higher on average. Significant and positive linear relationship was found between right and left hemispheres' values for all parameters and ROIs with Pearson correlation coefficients of r>0.89 (P<0.001), and mean slope of 0.95 ± 0.04. Finally, scan-rescan stability demonstrated high reproducibility of the measured parameters across ROIs and volunteers, with close-to-zero mean difference and without correlation between the mean and difference values (across map types, mean P value was 0.48 ± 0.27). The entire quantitative data and postprocessing scripts described in the manuscript are publicly available under dedicated GitHub and Figshare repositories. The quantitative maps produced by the presented protocol can promote longitudinal and multi-center studies, and improve the biological interpretability of qMRI by integrating multiple metrics that can reveal information, which is not apparent when examined using only a single contrast mechanism.

Ultrahigh field diffusion magnetic resonance imaging uncovers intriguing microstructural changes in the adult zebrafish brain caused by Toll-like receptor 2 genomic deletion

Toll-like receptor 2 (TLR2) belongs to the TLR protein family that plays an important role in the immune and inflammation response system. While TLR2 is predominantly expressed in immune cells, its expression has also been detected in the brain, specifically in microglia and astrocytes. Recent studies indicate that genomic deletion of TLR2 can result in impaired neurobehavioural function. It is currently not clear if the genomic deletion of TLR2 leads to any alterations in the microstructural features of the brain. In the current study, we noninvasively assess microstructural changes in the brain of TLR2-deficient (tlr2-/-) zebrafish using state-of-the art magnetic resonance imaging (MRI) methods at ultrahigh magnetic field strength (17.6 T). A significant increase in cortical thickness and an overall trend towards increased brain volumes were observed in young tlr2-/- zebrafish. An elevated T2 relaxation time and significantly reduced apparent diffusion coefficient (ADC) unveil brain-wide microstructural alterations, potentially indicative of cytotoxic oedema and astrogliosis in the tlr2-/- zebrafish. Multicomponent analysis of the ADC diffusivity signal by the phasor approach shows an increase in the slow ADC component associated with restricted diffusion. Diffusion tensor imaging and diffusion kurtosis imaging analysis revealed diminished diffusivity and enhanced kurtosis in various white matter tracks in tlr2-/- compared with control zebrafish, identifying the microstructural underpinnings associated with compromised white matter integrity and axonal degeneration. Taken together, our findings demonstrate that the genomic deletion of TLR2 results in severe alterations to the microstructural features of the zebrafish brain. This study also highlights the potential of ultrahigh field diffusion MRI techniques in discerning exceptionally fine microstructural details within the small zebrafish brain, offering potential for investigating microstructural changes in zebrafish models of various brain diseases.

Mitigating slice cross-talk in multi-slice multi-echo spin echo T2 mapping

PURPOSE

To investigate whether a T2 inter-slice variation could occur when a multi-slice multi-echo spin echo (MESE) sequence is used for image acquisition and to propose an enhanced method for reconstructing T2 maps that can effectively address and correct these variations.

METHODS

Bloch simulations were performed accounting for the direct saturation effect to evaluate magnetization changes in multi-slice 2D MESE sequence. Experimental phantom scans were performed to validate these simulations. An improved version of the dictionary-based reconstruction approach was proposed, enabling the creation of a multi-slice dictionary of echo modulation curves (EMC). The corresponding method has been assayed considering inter-slice T2 variation with phantoms and in lower leg.

RESULTS

Experimental and numerical study illustrate that direct saturation leads to a bias of EMCs. This bias during the T2 maps reconstructions using original single-slice EMC-dictionary method led to inter-slice T2 variation of 2.03% in average coefficient of variation (CV) in agarose phantoms, and up to 2.8% in vivo (for TR = 2 s, slice gap = 0%). A reduction of CV was observed when increasing the gap up to 100% (0.36% in phantoms, and up to 1.5% in vivo) or increasing TR up to 4 s (0.76% in phantoms, and up to 1.9% in vivo). Matching the multi-slice experimental data with multi-slice dictionaries provided a reduced CV of 0.54% in phantoms and up to 2.3% in vivo.

CONCLUSION

T2 values quantified from multi-slice MESE images using single-slice dictionaries are biased. A dedicated multi-slice EMC method providing the appropriate dictionaries can reduce the inter-slice T2 variation.

Probing muscle recovery following downhill running using precise mapping of MRI T2 relaxation times

PURPOSE

Postexercise recovery rate is a vital component of designing personalized training protocols and rehabilitation plans. Tracking exercise-induced muscle damage and recovery requires sensitive tools that can probe the muscles' state and composition noninvasively.

METHODS

Twenty-four physically active males completed a running protocol consisting of a 60-min downhill run on a treadmill at -10% incline and 65% of maximal heart rate. Quantitative mapping of MRI T2 was performed using the echo-modulation-curve algorithm before exercise, and at two time points: 1 h and 48 h after exercise.

RESULTS

T2 values increased by 2%-4% following exercise in the primary mover muscles and exhibited further elevation of 1% after 48 h. For the antagonist muscles, T2 values increased only at the 48-h time point (2%-3%). Statistically significant decrease in the SD of T2 values was found following exercise for all tested muscles after 1 h (16%-21%), indicating a short-term decrease in the heterogeneity of the muscle tissue.

CONCLUSION

MRI T2 relaxation time constitutes a useful quantitative marker for microstructural muscle damage, enabling region-specific identification for short-term and long-term systemic processes, and sensitive assessment of muscle recovery following exercise-induced muscle damage. The variability in T2 changes across different muscle groups can be attributed to their different role during downhill running, with immediate T2 elevation occurring in primary movers, followed by delayed elevation in both primary and antagonist muscle groups, presumably due to secondary damage caused by systemic processes.

Evaluating T1, T2 Relaxation, and Proton Density in Normal Brain Using Synthetic MRI with Fast Imaging Protocol

Synthetic MRI is being increasingly used for the quantification of brain longitudinal relaxation time (T1), transverse relaxation time (T2), and proton density (PD) values. However, the effect of fast imaging protocols on these quantitative values has not been fully estimated. The purpose of this study was to investigate the effect of fast scan parameters on T1, T2, and PD measured with a multi-dynamic multi-echo (MDME) sequence of normal brain at 3.0T. Thirty-four volunteers were scanned using 3 MDME sequences with different scan times (named Fast, 2 min, 29 sec; Routine, 4 min, 07 sec; and Research, 7 min, 46 sec, respectively). The measured T1, T2, and PD in 18 volumes of interest (VOI) of brain were compared between the 3 sequences using rank sum test, t test, coefficients of variation (CVs) analysis, correlation analysis, and Bland-Altman analysis. We found that even though T1, T2, and PD were significantly different between the 3 sequences in most of the brain regions, the intersequence CVs were relatively low and linear correlation were high. Bland-Altman plots showed that most of the values fall within the 95% prediction limits. We concluded that fast imaging protocols of MDME sequence used in our study can potentially be used for quantitative evaluation of brain tissues. Since changing scan parameters can affect the measured T1, T2, and PD values, it is necessary to use consistent scan parameter for comparing or following up cases quantitatively.

Fast and accurate T2 mapping using Bloch simulations and low-rank plus sparse matrix decomposition

PURPOSE

MRI's T2 relaxation time is one of the key contrast mechanisms for clinical diagnosis and prognosis of pathologies. Mapping this relaxation time, however, involves extensive scan times, which are needed to collect quantitative data, thereby impeding its integration into clinical routine. This study employs a low-rank plus sparse (L + S) signal decomposition approach in order to reconstruct accurate T2-maps from highly undersampled multi-echo spin-echo (MESE) MRI data.

METHODS

Two new algorithms are presented: the first uses standard L + S approach, where both L and S are iteratively updated. The second technique, dubbed SPArse and fixed RanK (SPARK), uses a fixed-rank L, under the assumption that most MESE information is found in the L component and that this rank can be pre-calculated. The utility of these new techniques is demonstrated on in vivo brain and calf data at x2 to x6 acceleration factors.

RESULTS

Accelerated T2 maps showed improved accuracy compared to fully sampled ground truth maps, when using L + S and SPARK techniques vis-à-vis standard GRAPPA acceleration.

CONCLUSION

SPARK provides accurate T2 maps with increased robustness to the selection of reconstruction parameters making it suitable to a wide range of applications and facilitating the use of quantitative T2 information in clinical settings.

Estimation of subvoxel fat infiltration in neurodegenerative muscle disorders using quantitative multi-T2 analysis

MRI's T₂ relaxation time is a valuable biomarker for neuromuscular disorders and muscle dystrophies. One of the hallmarks of these pathologies is the infiltration of adipose tissue and a loss of muscle volume. This leads to a mixture of two signal components, from fat and from water, to appear in each imaged voxel, each having a specific T₂ relaxation time. In this proof-of-concept work, we present a technique that can separate the signals from water and from fat within each voxel, measure their separate T₂ values, and calculate their relative fractions. The echo modulation curve (EMC) algorithm is a dictionary-based technique that offers accurate and reproducible mapping of T₂ relaxation times. We present an extension of the EMC algorithm for estimating subvoxel fat and water fractions, alongside the T₂ and proton-density values of each component. To facilitate data processing, calf and thigh anatomy were automatically segmented using a fully convolutional neural network and FSLeyes software. The preprocessing included creating two signal dictionaries, for water and for fat, using Bloch simulations of the prospective protocol. Postprocessing included voxelwise fitting for two components, by matching the experimental decay curve to a linear combination of the two simulated dictionaries. Subvoxel fat and water fractions and relaxation times were generated and used to calculate a new quantitative biomarker, termed viable muscle index, and reflecting disease severity. This biomarker indicates the fraction of remaining muscle out of the entire muscle region. The results were compared with those using the conventional Dixon technique, showing high agreement (R = 0.98, p < 0.001). It was concluded that the new extension of the EMC algorithm can be used to quantify abnormal fat infiltration as well as identify early inflammatory processes corresponding to elevation in the T₂ value of the water (muscle) component. This new ability may improve the diagnostic accuracy of neuromuscular diseases, help stratification of patients according to disease severity, and offer an efficient tool for tracking disease progression.

Three-dimensional high-resolution T1 and T2 mapping of whole macaque brain at 9.4 T using magnetic resonance fingerprinting

PURPOSE

Quantitative T₁ and T₂ mapping in non-human primates with whole-brain coverage is challenged by the requirement of sub-millimeter resolution and the inhomogeneity of the transmit magnetic field (B₁ ⁺ ) covering a large field of view. The goal of the current study is to develop a magnetic resonance fingerprinting (MRF) method for simultaneous T₁ and T₂ mapping of the entire macaque brain within feasible scan time.

METHODS

A three-dimensional (3D) MRF sequence with both inversion- and T₂ -preparation modules was developed and evaluated on a 9.4 T preclinical scanner. Data acquisition used a 3D stack-of-spirals trajectory, with undersampling along both the in-plane and the through-plane directions. The effect of B₁ ⁺ inhomogeneity was accounted for by matching the acquired fingerprint to a dictionary simulated with the B₁ ⁺ factors measured from a separate scan. In vitro and ex vivo studies were performed to evaluate the accuracy and the undersampling capacity of the MRF method. The application of the MRF method for in vivo, brain-wide T₁ and T₂ mapping was demonstrated on macaques at 4, 6, and 12 years of age.

RESULTS

The MRF method enabled highly repeatable T₁ and T₂ mapping at high spatial resolution (0.35 × 0.35 × 1 mm³ ) with an acceleration factor of 24. In vivo studies showed significant age-related T₂ reduction in deep gray nuclei including the globus pallidus, the putamen, and the caudate nucleus.

CONCLUSIONS

This study demonstrates the first MRF study for brain-wide, multi-parametric quantification in non-human primates with sub-millimeter resolution.

Accelerated reconstruction of dictionary-based T2 relaxation maps based on dictionary compression and gradient descent search algorithms

Background Quantitative T₂-relaxation-based contrast maps have shown to be highly beneficial for clinical diagnosis and follow-up. The generation of quantitative maps, however, is impaired by long acquisition times, and time-consuming post-processing schemes. The EMC platform is a dictionary-based technique, which involves simulating theoretical signal curves for different physical and experimental values, followed by matching the experimentally acquired signals to the set simulated ones. Purpose Although the EMC technique has shown to produce accurate T₂ maps, it involves computationally intensive post-processing procedures. In this work we present an approach for accelerating the reconstruction of T₂ relaxation maps. Methods This work presents two alternative post-processing approaches for accelerating the reconstruction of EMC-based T₂ relaxation maps. These are (a) Dictionary compression using principal component analysis (PCA) and (b) gradient-descent search algorithm. Additional acceleration was achieved by finding the optimal MATLAB C++ compiler. The utility of the two suggested approaches was examined by calculating the relative error, produced by each technique. Results Gradient descent method was in perfect agreement with the ground truth exhaustive search matching process. PCA based acceleration produced root mean square error (RMSE) of up to 4% compared to exhaustive matching process. Overall acceleration of x16 was achieved using gradient descent in addition to x7 acceleration by choosing the optimal MATLAB C++ compiler. Conclusions Postprocessing of EMC-based T₂ relaxation maps can be accelerated without impairing the accuracy of the ensuing T₂ values.

Quantitative platform for accurate and reproducible assessment of transverse (T2 ) relaxation time

MRI's transverse relaxation time (T₂ ) is sensitive to tissues' composition and pathological state. While variations in T₂ values can be used as clinical biomarkers, it is challenging to quantify this parameter in vivo due to the complexity of the MRI signal model, differences in protocol implementations, and hardware imperfections. Herein, we provide a detailed analysis of the echo modulation curve (EMC) platform, offering accurate and reproducible mapping of T₂ values, from 2D multi-slice multi-echo spin-echo (MESE) protocols. Computer simulations of the full Bloch equations are used to generate an advanced signal model, which accounts for stimulated echoes and transmit field (B₁⁺ ) inhomogeneities. In addition to quantifying T₂ values, the EMC platform also provides proton density (PD) maps, and fat-water fraction maps. The algorithm's accuracy, reproducibility, and insensitivity to T₁ values are validated on a phantom constructed by the National Institute of Standards and Technology and on in vivo human brains. EMC-derived T₂ maps show excellent agreement with ground truth values for both in vitro and in vivo models. Quantitative values are accurate and stable across scan settings and for the physiological range of T₂ values, while showing robustness to main field (B₀ ) inhomogeneities, to variations in T₁ relaxation time, and to magnetization transfer. Extension of the algorithm to two-component fitting yields accurate fat and water T₂ maps along with their relative fractions, similar to a reference three-point Dixon technique. Overall, the EMC platform allows to generate accurate and stable T₂ maps, with a full brain coverage using a standard MESE protocol and at feasible scan times. The utility of EMC-based T₂ maps was demonstrated on several clinical applications, showing robustness to variations in other magnetic properties. The algorithm is available online as a full stand-alone package, including an intuitive graphical user interface.

Quantitative muscle MRI as a sensitive marker of early muscle pathology in myotonic dystrophy type 1

BACKGROUND

Quantitative muscle MRI as a sensitive marker of early muscle pathology and disease progression in adult-onset myotonic dystrophy type 1. The utility of muscle MRI as a marker of muscle pathology and disease progression in adult-onset myotonic dystrophy type 1 (DM1) was evaluated.

METHODS

This prospective, longitudinal study included 67 observations from 36 DM1 patients (50% female), and 92 observations from 49 healthy adults (49% female). Lower-leg 3T magnetic resonance imaging (MRI) scans were acquired. Volume and fat fraction (FF) were estimated using a three-point Dixon method, and T2-relaxometry was determined using a multi-echo spin-echo sequence. Muscles were segmented automatically. Mixed linear models were conducted to determine group differences across muscles and image modality, accounting for age, sex, and repeated observations. Differences in rate of change in volume, T2-relaxometry, and FF were also determined with mixed linear regression that included a group by elapsed time interaction.

RESULTS

Compared with healthy adults, DM1 patients exhibited reduced volume of the tibialis anterior, soleus, and gastrocnemius (GAS) (all, P < .05). T2-relaxometry and FF were increased across all calf muscles in DM1 compared to controls. (all, P < .01). Signs of muscle pathology, including reduced volume, and increased T2-relaxometry and FF were already noted in DM1 patients who did not exhibit clinical motor symptoms of DM1. As a group, DM1 patients exhibited a more rapid change than did controls in tibialis posterior volume (P = .05) and GAS T2-relaxometry (P = .03) and FF (P = .06).

CONCLUSIONS

Muscle MRI renders sensitive, early markers of muscle pathology and disease progression in DM1. T2 relaxometry may be particularly sensitive to early muscle changes related to DM1.

Fast Open-Source Toolkit for Water T2 Mapping in the Presence of Fat From Multi-Echo Spin-Echo Acquisitions for Muscle MRI

Imaging has become a valuable tool in the assessment of neuromuscular diseases, and, specifically, quantitative MR imaging provides robust biomarkers for the monitoring of disease progression. Quantitative evaluation of fat infiltration and quantification of the T2 values of the muscular tissue's water component (wT2) are two of the most essential indicators currently used. As each voxel of the image can contain both water and fat, a two-component model for the estimation of wT2 must be used. In this work, we present a fast method for reconstructing wT2 maps obtained from conventional multi-echo spin-echo (MESE) acquisitions and released as Free Open Source Software. The proposed software is capable of fast reconstruction thanks to extended phase graphs (EPG) simulations and dictionary matching implemented on a general-purpose graphic processing unit. The program can also perform more conventional biexponential least-squares fitting of the data and incorporate information from an external water-fat acquisition to increase the accuracy of the results. The method was applied to the scans of four healthy volunteers and five subjects suffering from facioscapulohumeral muscular dystrophy (FSHD). Conventional multi-slice MESE acquisitions were performed with 17 echoes, and additionally, a 6-echo multi-echo gradient-echo (MEGE) sequence was used for an independent fat fraction calculation. The proposed reconstruction software was applied on the full datasets, and additionally to reduced number of echoes, respectively, to 8, 5, and 3, using EPG and biexponential least-squares fitting, with and without incorporating information from the MEGE acquisition. The incorporation of external fat fraction maps increased the robustness of the fitting with a reduced number of echoes per datasets, whereas with unconstrained fitting, the total of 17 echoes was necessary to retain an independence of wT2 from the level of fat infiltration. In conclusion, the proposed software can successfully be used to calculate wT2 maps from conventional MESE acquisition, allowing the usage of an optimized protocol with similar precision and accuracy as a 17-echo acquisition. As it is freely released to the community, it can be used as a reference for more extensive cohort studies.

Exercise-induced muscle damage: mechanism, assessment and nutritional factors to accelerate recovery

There have been a multitude of reviews written on exercise-induced muscle damage (EIMD) and recovery. EIMD is a complex area of study as there are a host of factors such as sex, age, nutrition, fitness level, genetics and familiarity with exercise task, which influence the magnitude of performance decrement and the time course of recovery following EIMD. In addition, many reviews on recovery from exercise have ranged from the impact of nutritional strategies and recovery modalities, to complex mechanistic examination of various immune and endocrine signaling molecules. No one review can adequately address this broad array of study. Thus, in this present review, we aim to examine EIMD emanating from both endurance exercise and resistance exercise training in recreational and competitive athletes and shed light on nutritional strategies that can enhance and accelerate recovery following EIMD. In addition, the evaluation of EIMD and recovery from exercise is often complicated and conclusions often depend of the specific mode of assessment. As such, the focus of this review is also directed at the available techniques used to assess EIMD.

Fast T2 mapping using multi-echo spin-echo MRI: A linear order approach

PURPOSE

Multi-echo spin-echo sequence is commonly used for T2 mapping. The estimated values using conventional exponential fit, however, are hampered by stimulated and indirect echoes leading to overestimation of T2 . Here, we present fast analysis of multi-echo spin-echo (FAMESE) as a novel approach to decrease the complexity of the search space, which leads to accelerated measurement of T2 .

METHODS

We developed FAMESE based on mathematical analysis of the Bloch equations in which the search space dimension decreased to only one. Then, we tested it in both phantom and human brain. Bland-Altman plot was used to assess the agreement between the estimated T2 values from FAMESE and the ones estimated from single-echo spin-echo sequence. The reliability of FAMESE was assessed by intraclass correlation coefficients. In addition, we investigated the noise stability of the method in synthetic and experimental data.

RESULTS

In both phantom and healthy participants, FAMESE provided accelerated and SNR-resistant T2 maps. The FAMESE had a very good agreement with the single-echo spin echo for the whole range of T2 values. The intraclass correlation coefficient values for FAMESE were excellent (ie, 0.9998 and 0.9860 < intraclass correlation coefficient < 0.9942 for the phantom and humans, respectively).

CONCLUSION

Our developed method FAMESE could be considered as a candidate for rapid T2 mapping with a clinically feasible scan time.

Three-dimensional whole-brain simultaneous T1, T2, and T1ρ quantification using MR Multitasking: Method and initial clinical experience in tissue characterization of multiple sclerosis

PURPOSE

To develop a 3D whole-brain simultaneous T1/T2/T1ρ quantification method with MR Multitasking that provides high quality, co-registered multiparametric maps in 9 min.

METHODS

MR Multitasking conceptualizes T1/T2/T1ρ relaxations as different time dimensions, simultaneously resolving all three dimensions with a low-rank tensor image model. The proposed method was validated on a phantom and in healthy volunteers, comparing quantitative measurements against corresponding reference methods and evaluating the scan-rescan repeatability. Initial clinical validation was performed in age-matched relapsing-remitting multiple sclerosis (RRMS) patients to examine the feasibility of quantitative tissue characterization and to compare with the healthy control cohort. The feasibility of synthesizing six contrast-weighted images was also examined.

RESULTS

Our framework produced high quality, co-registered T1/T2/T1ρ maps that closely resemble the reference maps. Multitasking T1/T2/T1ρ measurements showed substantial agreement with reference measurements on the phantom and in healthy controls. Bland-Altman analysis indicated good in vivo repeatability of all three parameters. In RRMS patients, lesions were conspicuously delineated on all three maps and on four synthetic weighted images (T2-weighted, T2-FLAIR, double inversion recovery, and a novel "T1ρ-FLAIR" contrast). T1 and T2 showed significant differences for normal appearing white matter between patients and controls, while T1ρ showed significant differences for normal appearing white matter, cortical gray matter, and deep gray matter. The combination of three parameters significantly improved the differentiation between RRMS patients and healthy controls, compared to using any single parameter alone.

CONCLUSION

MR Multitasking simultaneously quantifies whole-brain T1/T2/T1ρ and is clinically promising for quantitative tissue characterization of neurological diseases, such as MS.

Magnetization transfer in magnetic resonance fingerprinting

PURPOSE

To study the effects of magnetization transfer (MT, in which a semi-solid spin pool interacts with the free pool), in the context of magnetic resonance fingerprinting (MRF).

METHODS

Simulations and phantom experiments were performed to study the impact of MT on the MRF signal and its potential influence on T1 and T2 estimation. Subsequently, an MRF sequence implementing off-resonance MT pulses and a dictionary with an MT dimension, generated by incorporating a two-pool model, were used to estimate the fractional pool size in addition to the B 1 + , T1 , and T2 values. The proposed method was evaluated in the human brain.

RESULTS

Simulations and phantom experiments showed that an MRF signal obtained from a cross-linked bovine serum sample is influenced by MT. Using a dictionary based on an MT model, a better match between simulations and acquired MR signals can be obtained (NRMSE 1.3% vs. 4.7%). Adding off-resonance MT pulses can improve the differentiation of MT from T1 and T2 . In vivo results showed that MT affects the MRF signals from white matter (fractional pool-size ~16%) and gray matter (fractional pool-size ~10%). Furthermore, longer T1 (~1060 ms vs. ~860 ms) and T2 values (~47 ms vs. ~35 ms) can be observed in white matter if MT is accounted for.

CONCLUSION

Our experiments demonstrated a potential influence of MT on the quantification of T1 and T2 with MRF. A model that encompasses MT effects can improve the accuracy of estimated relaxation parameters and allows quantification of the fractional pool size.

Dehydration assessment via a portable, single sided magnetic resonance sensor

PURPOSE

Undiagnosed dehydration compromises health outcomes across many populations. Existing dehydration diagnostics require invasive bodily fluid sampling or are easily confounded by fluid and electrolyte intake, environment, and physical activity limiting widespread adoption. We present a portable MR sensor designed to measure intramuscular fluid shifts to identify volume depletion.

METHODS

Fluid loss is induced via a mouse model of thermal dehydration (37°C; 15-20% relative humidity). We demonstrate quantification of fluid loss induced by hyperosmotic dehydration with multicomponent T2 relaxometry using both a benchtop NMR system and MRI localized to skeletal muscle tissue. We then describe a miniaturized (~1000 cm³ ) portable (~4 kg) MR sensor (0.28 T) designed to identify dehydration-induced fluid loss. T2 relaxometry measurements were performed using a Carr-Purcell-Meiboom-Gill pulse sequence in ~4 min.

RESULTS

T2 values from the portable MR sensor exhibited strong (R² = 0.996) agreement with benchtop NMR spectrometer. Thermal dehydration induced weight loss of 4 to 11% over 5 to 10 h. Fluid loss induced by thermal dehydration was accurately identified via whole-animal NMR and skeletal muscle. The portable MR sensor accurately identified dehydration via multicomponent T2 relaxometry.

CONCLUSION

Performing multicomponent T2 relaxometry localized to the skeletal muscle with a miniaturized MR sensor provides a noninvasive, physiologically relevant measure of dehydration induced fluid loss in a mouse model. This approach offers sensor portability, reduced system complexity, fully automated operation, and low cost compared with MRI. This approach may serve as a versatile and portable point of care technique for dehydration monitoring.