NMR in Biomedicine

Free carnitine is essential to mitochondrial health by buffering the free acetyl-CoA pool and thereby maintaining energy production. It is also responsible for transporting long-chain fatty acids into the mitochondria for oxidation. Almost all the body's carnitine is in muscle, and plasma concentrations do not reflect tissue content, but there are as yet no non-invasive techniques to assess muscle total or free carnitine. Here we describe a novel non-invasive postprocessing method, using standard 1H magnetic resonance spectroscopy data, for quantifying muscle total and free carnitine concentrations, which includes an orientation- visibility and spectral fitting component, and consideration of interfering metabolites. We demonstrate the importance of the orientation correction even within one muscle group (accounting for up to 1.9-fold difference within one muscle group and 2.9-fold difference in signal between muscles), show its good reproducibility (CoV 8-12%), and validate the results with mass spectrometry measurements in muscle biopsy samples. We apply this method in a group of patients with genetic mitochondrial disease, to investigate the relationship between mitochondrial dysfunction and muscle lipid accumulation. As predicted muscle total and free carnitine were lower in patients with disease and correlated with the degree of mitochondrial dysfunction and lipid accumulation. Further, robust spatial correlations of total carnitine and muscle lipid imply heterogeneity in mitochondrial function. Our findings suggest that increasing muscle carnitine stores could ameliorate the metabolic effects of and disorders related to mitochondrial dysfunction. Furthermore, it has not usually been known in supplementation studies whether l-carnitine actually reached the target tissue. We suggest that this novel method has significant potential for informing on physiology and pathophysiology, and as a biomarker in monitoring treatment response, investigative drug discovery, and personalised medicine.

Magnetic resonance imaging (MRI) is the imaging modality of choice for the diagnosis, characterization, and monitoring of multiple sclerosis (MS). Nevertheless, the contrasts manifested by MS lesions often overlap with those of other pathological conditions, highlighting the need for additional disease biomarkers. In addition, while saturation transfer (ST) MRI provides molecular information associated with myelin, protein, and lipids, quantifying the underlying proton exchange parameters remains challenging. Here, we describe a strategy that extends and modifies AI-boosted ST magnetic resonance fingerprinting (MRF) imaging at 7T. This approach was used to quantify the dynamics of the semisolid magnetization transfer (MT) and the aliphatic relayed nuclear Overhauser effect (rNOE at -3.5 ppm and -1.6 ppm relative to water) in a longitudinal cuprizone MS mouse model (n=12). In lipid phantoms, the reconstructed proton volume fractions were strongly correlated with known lipid concentrations across all three proton pools (r>0.96, p<0.001). In vivo, semisolid MT and rNOE proton volume fractions in the corpus callosum demonstrated a significant decrease (p<0.01) as early as week 4 of cuprizone feeding, preceding changes detected by conventional water relaxometry. ST-MRF based biomarkers were in agreement with histological findings. Overall, our results demonstrate the feasibility of rapid, multi-pool ST-MRF quantification for MS characterization.

Background Mitochondrial dysfunction and abnormal cerebral energy metabolism are implicated in many neuropsychiatric and neurodegenerative disorders. 13C magnetic resonance spectroscopy (MRS), combined with 13C-labeled substrate infusion, offers a non-ionizing, minimally invasive method for assessing fluxes through the main cerebral energy metabolism pathways. However, its human application at 7 T has not been fully established, especially within the frontal lobe. Purpose To explore a clinically translatable interleaved 1H/13C MRS protocol for quantification of cerebral glucose uptake and downstream metabolism at 7 T, and to estimate the tricarboxylic acid (TCA) cycle flux (VTCA) for validation. Study Type Prospective. Population Three young healthy volunteers. Field Strength/Sequence 7T; ACE-STEAM (indirect 1H-[13C]) and ISIS-DEPT (direct 13C-[1H]). Assessment ACE-STEAM and ISIS-DEPT were applied to acquire the time-resolved spectra in the frontal lobe. 13C-labeled glucose, glutamate, and glutamine fractional enrichment time courses were quantified to estimate VTCA through the one-compartment model. Statistical Tests The relative estimated fitting uncertainties (EFUs) were reported for the processed spectra. Nonlinear least squares minimization was used for flux fitting of 13C traces. Uncertainty of the estimated metabolic fluxes was evaluated using Monte-Carlo simulations. Results [1-13C]-glucose (GlcC1) was detected immediately on 13C MR spectra, followed by 13C-labeled GluH4 and GlnH4 and then GlxH3 can be quantified on 1H MR spectra. End-of-infusion mean enrichments were 17% (GluH4), 13% (GlnH4), and 7% (GlxH3). Brain glucose concentration ranged 1.86-2.94 mM, with 61% of the mean enrichment in C1. Group-average VTCA was 0.66 {+/-} 0.07 mol/g/min. Data Conclusion This interleaved 1H/13C MRS protocol enables minimally invasive quantification of cerebral metabolic fluxes, may provide a useful framework for investigating neuropsychiatric and neurodegenerative diseases at 7 T. Evidence Level 1. Technical Efficacy Stage 1.

PurposeBreast microcalcifications trigger 70-80% of unnecessary biopsies because current imaging cannot distinguish malignancy-associated hydroxyapatite (HA) from benign-associated calcium oxalate (CaOx). Quantitative susceptibility mapping (QSM) could exploit the susceptibility contrast between these minerals (HA: {Delta}{chi} {approx} -7 ppm; CaOx: {Delta}{chi} {approx} -1 ppm relative to water), but no study has demonstrated compositional differentiation at clinical field strength. This work assessed susceptibility and R2* relaxation rate maps for microcalcification differentiation at 3 T using tissue-mimicking phantoms. MethodsA phantom comprising 12 tubes, each containing co-embedded HA and CaOx particles in BaCl2-crosslinked alginate gels (pure alginate, adipose-mimicking, and fibroglandular tissue-mimicking relaxation properties; n = 4 per type), were scanned at 0.70 mm and 0.86 mm isotropic resolution using a multi-echo gradient echo sequence. A consensus-aligned QSM pipeline and mono-exponential R2* fitting was developed. A digital twin phantom simulation quantified the contributions of partial volume effects and Total Variation (TV) regularisation to susceptibility underestimation. ResultsQSM detected HA in 18/24 measurements ({Delta}{chi}peak = -0.37 {+/-} 0.07 ppm in alginate at 0.70 mm) and CaOx in 0/24. R2* mapping detected HA in 23/24 and CaOx in 22/24. The digital twin identified TV regularisation as the dominant signal loss mechanism (57.5% loss), exceeding partial volume effects (24.3% loss). Combined parameters yielded three classification categories: QSM-positive with elevated R2* (HA), QSM-negative with moderate R2* (CaOx), and neither elevated (no calcification). ConclusionQSM at 3 T enables categorical HA detection while R2* provides complementary CaOx sensitivity, together enabling two-parameter microcalcification classification from a single multi-echo acquisition.

BackgroundMethylmalonic acidemia (MMAemia) is a genetic metabolic disorder characterized by an accumulation of methylmalonic acid (MMA) and impaired energy metabolism leading to increased lactate (Lac). The signals of MMA (1.23 ppm) and Lac (1.33 ppm) overlap, making their separation using conventional MRS challenging. An MRS method to differentiate the two metabolites could enhance pathophysiological understanding and improve treatment monitoring - Hadamard-edited MRS has the potential to achieve this. PurposeTo develop a Hadamard-encoded J-difference editing approach for independent detection of MMA and Lac at 3T. MethodsA novel Hadamard-encoded editing scheme was implemented and evaluated with density-matrix simulations, phantom and in vivo experiments. The new four-step scheme uses frequency-selective editing pulses, applied at 3.2 ppm and 4.1 ppm to modulate the J-coupled methyl resonances of MMA and Lac, respectively. Hadamard combinations of the four sub-experiments yield the separate difference-edited spectra for each target metabolite. ResultsSimulations and phantom experiments clearly illustrate the separated signals of MMA and Lac. In vivo validation experiments show a Lac signal (but no MMA) in a healthy infant, and both Lac and MMA (separated into their respective Hadamard-combination spectra) in a patient with MMAemia. ConclusionHadamard-encoded editing at 3T can separate MMA and Lac signals and shows promise for studying altered metabolism in patients with MMAemia.

Purpose: {beta}-hydroxybutyrate (BHB), a ketone body and alternative cerebral energy substrate, can be measured in vivo using J-difference edited proton magnetic resonance spectroscopy (1H-MRS). Oral ketone supplementation with substrates such as the ketone monoester (R)-3-hydroxybutyl-(R)-3-hydroxybutyrate (KME) and 1,3-butanediol (BD) have gained attention as a mechanism to elevate circulating BHB and induce ketosis without dietary restrictions. Elevated brain ketone availability is of growing therapeutic interest as a strategy to support neuronal energetics in conditions such as epilepsy, neurodegenerative disease, and alcohol use disorder (AUD). However, both pathways introduce BD into the bloodstream, which crosses the blood-brain barrier. Critically, BD exhibits a spectral signature that closely resembles the prominent BHB peak in JDE-MR spectroscopic imaging (MRSI), identified in a pilot AUD study. Methods: Two separate JDE-MRSI acquisitions tailored for BHB and BD editing were implemented, exploiting frequency separation between the BHB (4.14ppm) and BD (3.95ppm) coupling partners of the observed 1.2ppm resonance to independently quantify each metabolite. Results: Brain BD concentrations (0.25-0.58mM) were comparable to or exceeded corresponding BHB concentrations (0.20-0.27mM) in all volunteers after consumption of a single dose of the KME, indicating that BD constitutes a major fraction of the signal conventionally attributed to BHB. Combined BHB+BD concentrations (~0.45-0.85mM) were consistent with brain BHB values reported in prior studies employing similar doses of the KME, indicating that those measurements likely reflect a combined BHB+BD signal. Conclusions: Separate quantification of the two metabolites is important for interpreting brain ketone studies and for understanding the full pharmacology of KME supplementation.

Chemical exchange saturation transfer (CEST) has become an indispensable NMR method to characterize slow exchange affecting biomacromolecules, especially for cases involving exchange between a major state and a minor state, the latter of which is often invisible in the spectrum. The CEST method is based on successive irradiation of selective regions of the NMR spectrum using a weak radiofrequency field, B1, while observing the effect on the visible major state when the B1 field saturates the invisible minor state. The need for selective saturation of narrow spectral regions has to date required acquisition of many tens of two-dimensional CEST spectra to sample the entire spectrum with sufficient resolution. Here we present the ACCEST method which measures an entire CEST profile from a single two-dimensional accordion-CEST spectrum plus a reference spectrum. ACCEST is based on the concept of accordion spectroscopy, where in the present implementation the carrier frequency of the weak saturating B1 field is stepped in synchrony with the dwell-time incrementation in the indirect dimension of the two-dimensional spectrum. We benchmarked ACCEST against conventional CEST, resulting in excellent agreement for both backbone 15N and methyl 13C CEST profiles. ACCEST offers substantial time savings that scale linearly with the number of spectra required in the corresponding conventional CEST experiment. Thus, ACCEST can dramatically speed up lengthy serial experiments, such as ligand titrations or temperature-dependent studies, and enable studies of non-equilibrium systems or samples with limited lifetimes.

The Gradient Impulse Response Function (GIRF) is widely used to model and correct gradient system imperfections in MRI, but scanner-specific GIRF measurement remains inaccessible to many research groups because existing approaches rely on specialised field monitoring hardware or fragmented and non-reproducible software workflows. To address this limitation, an open-source, end-to-end framework for phantom-based GIRF measurement is presented, providing a reproducible workflow requiring only standard MRI hardware and a spherical water phantom. The framework integrates vendor-independent pulse sequence generation, phantom-based data acquisition, automated data processing, and GIRF estimation. The framework was validated by comparing GIRF-predicted non-Cartesian k-space trajectories with independent measurements acquired using NMR field probes, which served as the gold-standard for trajectory characterization. Accurate prediction of rosette and spiral trajectories was demonstrated across multiple imaging orientations, with substantially lower trajectory error than the corresponding nominal trajectories. By providing the first openly available end-to-end implementation for phantom-based GIRF measurement, the barrier to routine scanner-specific GIRF characterisation is reduced, facilitating broader adoption of GIRF-based methods across the MRI community.

Proton magnetic resonance spectroscopic imaging (1H MRSI) enables quantitative mapping of brain metabolites, but its clinical use remains limited by long acquisition time. The goal of this work to improve the applicability of high-resolution 1H FID-MRSI at 7T by enhancing GRAPPA-based acceleration through deep learning-driven k-space reconstruction. In particular, compared with conventional GRAPPA, MultiNet PyGRAPPA enables substantially higher in-plane acceleration while suppressing residual lipid aliasing and preserving metabolite map fidelity in non-lipid-suppressed MRSI. Building on the MultiNet PyGRAPPA framework, we introduce a comprehensive comparison of advanced machine-learning models for predicting missing k-space points. Multiple architectures--including multilayer perceptrons, convolutional neural networks, and several U-Net variants--were trained within a variable-density k-space undersampling scheme to support acceleration factors of R = 4, 6, and 7. The proposed U-Net model extends the MultiNet concept by leveraging nonlinear hierarchical feature extraction, thereby improving reconstruction fidelity while maintaining robustness to noise.The methods were evaluated in vivo using retrospectively undersampled 7T 1H FID-MRSI datasets from healthy volunteers and patients. Quantitative analyses demonstrate that the U-Net outperforms the original MultiNet approach, offering improved SNR retention rate, reduced lipid RMSE, and higher structural similarity of major metabolites. Metabolite maps reconstructed with the U-Net showed reduced lipid artifacts and improved anatomical consistency. In conclusion, integrating deep convolutional networks into GRAPPA-based k-space prediction provides a more reliable and higher-fidelity reconstruction pipeline. When combined with variable-density undersampling, this approach enables faster acquisition of high-resolution 1H MRSI without compromising spectral quality or metabolite quantification.

Ex vivo diffusion weighted imaging (DWI) enables high-resolution characterization of brain connectivity and is increasingly applied in comparative and evolutionary neuroscience. However, variability in tissue preparation and contrast agent exposure can substantially affect relaxation properties and compromise reproducibility, particularly in non-mammalian species. Here, we systematically assess the impact of different gadolinium-based contrast agent exposure protocols on relaxation stability and DWI compatibility in fixed pigeon brains. Brains were perfusion-fixed with 2% paraformaldehyde and assigned to four preparation protocols: (i) contrast agent exposure during perfusion, post-fixation, and rehydration; (ii) post-fixation and rehydration only; (iii) rehydration only; (iv) no contrast agent. Quantitative T1, T2, T2*, and DWI data were acquired at five time points over 70 days using a 7T MRI system. Protocols involving contrast agent during perfusion or post-fixation produced comparable relaxation trajectories, with T1, T2, and T2* stabilizing by Day 13. On day 13 the T1 values of tissue that was exposed to contrast agent, regardless of the application protocol were between 230.86 ms and 266.89 ms, while the T1 values of the control group were over 1100 ms at this point in time. T2 values of the experimental groups were between 39.97 ms and 56.17 ms while T2 values of the control group were between 58.68 ms and 77.82 ms. T2* values of the experimental groups were between 27.27 ms and 43.33 ms while T2* values of the control group were between 46.16 ms and 65.93 ms. Importantly, contrast agent exposure during rehydration alone resulted in equivalent stabilization after two weeks, reflecting gradual contrast agent diffusion into the tissue. In contrast, control samples without contrast agent exhibited significantly elevated T2 and T2* at later time points. These results demonstrate that post-fixation contrast agent exposure during rehydration is sufficient to achieve stable relaxation parameters and DWI compatibility, assessed via fractional anisotropy (FA) and mean diffusivity (MD) in ex vivo avian brain tissue. This minimal preparation protocol enhances reproducibility, reduces handling complexity, and supports standardized cross-species neuroimaging of brain connectivity.

Background: Acute phase response is an early immunometabolic response to brain injuries, primarily coordinated by the liver via the activation of acute phase proteins. These immune responses can be both beneficial, promoting tissue repair, and detrimental, exacerbating neurological deficits, if not properly controlled. Despite the central role of the liver in immunometabolism, how hepatic metabolism dynamically adapts to traumatic brain injury remains under explored, primarily due to limited liver-specific modalities that can assess metabolic pathways in vivo. 13C MRI utilizing hyperpolarized 13C-pyruvate can assess key regulatory enzyme activities in hepatic metabolism. Methods: Rats with controlled cortical impact were studied in vivo using hyperpolarized [1-13C]pyruvate and [2-13C]pyruvate under fed and fasted conditions 3-4 days after injury. Hyperpolarized 13C products, including [13C]bicarbonate from [1-13C]pyruvate and [5-13C]glutamate, [1-13C]acetyl-L-carnitine, and [2-13C]phosphoenolpyruvate from [2-13C]pyruvate, were evaluated to assess mitochondrial and gluconeogenic metabolism. In parallel, liver tissues were collected following [U-13C3]pyruvate injection for NMR isotopomer analysis of phosphoenolpyruvate, glucose, and glutamate. Results: While no metabolic differences were detected under fed condition, [13C]bicarbonate and [2-13C]phosphoenolpyruvate increased after brain injury under fasted condition, indicating an upregulation of the hepatic gluconeogenic pathway after injury. 13C NMR of liver tissue extracts from injured rats showed an elevated [2,3-13C2]glutamate-to-[4,5-13C2]glutamate ratio and increased 13C-labeling in phosphoenolpyruvate than controls, confirming enhanced hepatic gluconeogenic pathway. Conclusion: This study demonstrates that hepatic acute phase response to brain injuries can be monitored in vivo by hyperpolarized pyruvate, which may be further utilized for longitudinal immunometabolic evaluation of the liver during pathogenesis and therapeutic interventions.

1Abstract/SummarySingle-channel surface coils remain central to rodent MRI, but conventional circular loop designs face an inherent trade-off between surface and depth sensitivity, limiting whole-brain coverage for applications such as resting-state BOLD fMRI. This work introduces a single-channel strongly-coupled geometry surface coil. It consists of a stop-sign shaped loop inductively overcoupled to a nested, three-turn elongated racetrack spiral designed to improve depth sensitivity and thru-plane coverage while remaining robust to variable sample loading. Benchtop characterization across three phantoms of differing size showed the parallel resonant mode and loaded quality factor changed negligibly with loading. In phantom imaging at 9.4 T, the SCG coil achieved in-plane SNR and temporal SNR comparable to, and at shallow depths exceeding, a commercial Bruker 2x2 receive-only rat brain array, while showing substantially more consistent tSNR across loading conditions. The SCG coil also demonstrated superior thru-plane tSNR over a 20 mm slice range at 3.5 mm depth, approximating the anterior-posterior extent of the rat brain. In vivo resting-state BOLD fMRI in eight rats, acquired with a double asymmetric spin-echo EPI sequence, yielded a default mode network consistent with prior reports and revealed a previously undescribed subcortical network spanning superior/inferior colliculi and cerebellar regions. These results establish the single-channel SCG as a promising foundation for next-generation rodent receive coil arrays, combining loading-independent tuning with extended sensitive coverage suitable for whole-brain functional imaging.

BACKGROUND: Circulating lipoprotein measures such as low-density lipoprotein (LDL) cholesterol and apolipoprotein B are causal biomarkers of cardiovascular risk. These can be quantified quickly and accurately by nuclear magnetic resonance (NMR) spectroscopy, but clinical translation has been slow. We investigated easy-to-operate and affordable benchtop NMR technology as a new means to quantify lipoprotein biomarkers in point-of-care settings. METHODS: Serum samples from 336 individuals were analysed with a benchtop NMR spectrometer operating at 80 MHz and a high-field NMR spectrometer operating at 600 MHz. Glucose, apolipoprotein A-I, apolipoprotein B, total triglycerides, total cholesterol, LDL cholesterol and high-density cholesterol were determined by standard biochemistry. Corresponding NMR-based measures were quantified by linear regression. The 80 MHz dataset included experiments with different scan settings to optimize measurement time (1,987 spectra in total). RESULTS: We identified 32 scans (2 min 8 s) as the minimum runtime for lipoprotein quantification. Total triglycerides and glucose were quantified with the highest accuracy (CV [&le;]5.2%, R2 [&ge;]95%), while LDL cholesterol was more challenging (CV = 10.1%, R2 = 72%) and apolipoprotein B in between (CV = 7.4%, R2 = 74%). Epidemiological correlations between biochemistry assays and sex, obesity, glycemia and blood pressure were reproduced by the corresponding benchtop assays (P [&ge;]0.11 for difference). CONCLUSIONS: We developed a new lipoprotein quantification method and demonstrated its feasibility for standard lipoprotein analytics. The portability and cost-effectiveness of benchtop NMR make it an appealing choice for research and clinical settings where rapid and robust results on site are an advantage.

Arterial spin labeling (ASL) provides a valuable non-invasive tool for investigating cerebrospinal fluid (CSF) dynamics. While existing generalized kinetic models provide a useful analytical framework, incorporating explicit fluid mass-conservation constraints may improve the reliability of ventricular CSF quantification. We developed and validated a physics-constrained kinetic model that assumes a constant ventricular volume, under which the volumetric influx and efflux rates are balanced. Under this assumption, the localized CSF renewal rate (f) is modeled as a distinct washout process that acts jointly with intrinsic CSF T1 relaxation R1,CSF, yielding an effective decay rate Reff = R1,CSF + f, providing a more mechanistically interpretable description of the post-arrival signal decay. The model was further tailored to the global inversion physics of the FAIR (Flow-sensitive Alternating Inversion Recovery) sequence and incorporates an explicit zero-clamped pre-arrival boundary condition. When applied to an in vivo preclinical dataset, the proposed model, improved fitting stability and removed the finite-bolus truncation observed in the raw conventional model. Compared with the conventional model, the proposed model showed significantly improved goodness-of-fit (R2 = 0.95 {+/-} 0.05 vs. 0.82 {+/-} 0.06, p < 0.001) and a lower Akaike Information Criterion (AIC = 94.96 {+/-} 5.83 vs. 106.93 {+/-} 2.50, p < 0.001), suggesting it provides a more adequate and efficient representation of CSF dynamics. The proposed model yielded CSF dynamics estimates 14.70% higher than those obtained with the conventional model, with a mean ventricular CSF renewal time of 4.01 {+/-} 0.97 min and a renewal-equivalent volumetric flow rate of 0.97 {+/-} 0.41 {micro}L/min. The resulting estimates might be interpreted as localized, ASL-derived renewal metrics rather than direct measurements of net CSF production.

Background and purpose: Gliomas are characterised by a complex tumour microenvironment (TME) that contributes to treatment resistance and tumour heterogeneity. Therefore, the non-invasive interrogation of both the intracellular and extracellular compartments of gliomas remains a key unmet need. We investigated the feasibility and complementarity of combining diffusion-weighted MRI (DW-MRI) with biophysical modelling Vascular, Extracellular, and Restricted Diffusion for Cytometry in Tumours (VERDICT) and diffusion-weighted MR spectroscopy (DW MRS) for simultaneous characterisation of glioma tumour cells and the glioma TME. Methods: 14 patients with newly diagnosed glioma (WHO grades 2 to 4: 4 IDH wildtype and 10 IDH mutant) underwent DW-MRI at 3 T; DW-MRS was additionally acquired in 10 patients. Tumours were automatically segmented into enhancing, non-enhancing, and oedema regions using a validated pipeline. VERDICT models were fitted to multi-shell DW-MRI data to estimate intracellular volume fraction (fIC), cell radius, extracellular diffusivities, and free-water fraction (fFW). Single voxel DW-MRS provided metabolite-specific apparent diffusion coefficients (ADCs) for total N-acetylaspartate (tNAA), Creatine (tCr), and choline (tCho). T-tests assessed DW-MRI and descriptive statistics assessed DW-MRS parameters in tumour regions compared to normal appearing white matter (NAWM) and IDH mutation status. Pearsons correlations assessed associations between DW-MRS metabolite ADCs and DW-MRI parameters. Results: VERDICT-MRI distinguished high grade IDH-wildtype from lower grade IDH-mutant gliomas, with significantly higher fIC and lower extracellular diffusivities; in enhancing and non-enhancing regions of IDH-wildtype lesions. DW-MRS demonstrated a trend towards reduction in tNAA ADC in tumour versus contralateral NAWM, consistent with neuronal loss, and a trend towards increased tCho ADC, suggesting glial activation. A descriptive trend towards decreased tNAA ADC in IDH-wildtype tumours was observed. Significant positive correlations were identified between tumoral tCho ADC and VERDICT parameters fEES, extracellular diffusivity; and negative correlations for ADC and fFW, in non-enhancing tumour regions. Conclusion: This proof-of-concept study demonstrates the feasibility of combining multi b- value DW-MRI and DW-MRS within a clinically feasible protocol to simultaneously probe the extracellular and intracellular compartments of the glioma TME. VERDICT captured cell-level and extracellular matrix differences in IDH mutation status, while DW-MRS provided metabolite-specific indices of neuronal and glial compartment integrity. The correlation between tCho ADC and VERDICT metrics in infiltrative tumour regions supports the complementarity of these modalities. With this combined approach, it is possible to simultaneously characterise the tumour compartment and the tumour microenvironment in gliomas.

PurposeTo develop a data-driven technique, Scout-based Multi-Echo NAvigator (SMENA), for joint estimation of motion and B0 inhomogeneity ({delta}B0) at a temporal resolution of [~]200 ms with minimal additional scan time for gradient-echo acquisition. MethodsSMENA consists of two key acquisition components: SMENA-scout and SMENA-nav. SMENA-scout is a rapid 3D 4-mm multi-echo acquisition completed in less than 8 seconds, providing images with matched contrast and phase at multiple echo times. SMENA-nav captures signal variations induced by motion and{delta} B0 during the scan using compact multi-echo navigator trajectories (3.5 ms) embedded within each TR. Motion and{delta} B0 maps were jointly estimated every [~]200 ms through a model-based optimization framework relating SMENA-scout to SMENA-nav. The estimation accuracy and correction performance of SMENA were evaluated in simulations and in vivo using multi-echo GRE and GRE-EPTI acquisitions. Multiple prospective motion experiments, including large continuous movement and deep breathing, were investigated. ResultsIn both simulations and in vivo experiments, accurate motion and{delta} B0 estimation were achieved. Compared with motion-only estimation, joint estimation reduced rotation and translation errors. Joint motion and{delta} B0 correction resulted in substantial improvements in image quality, particularly at longer echo times, producing an NRMSE of 10.4% compared to 31.6% with motion-only correction. High-temporal-resolution tracking of motion and{delta} B0 enabled improved reconstruction quality in scenarios involving continuous motion and deep breathing. ConclusionSMENA enables high-temporal-resolution joint estimation of motion and{delta} B0 with minimal additional acquisition cost, providing a practical solution for motion- and{delta} B0-robust MRI.

The hindlimb ischaemia (HLI) mouse model is a widely used preclinical model of chronic limb-threatening ischaemia (CLTI). While CLTI involves complex interactions between impaired perfusion, inflammation and muscle wasting, the standard imaging approach, laser Doppler imaging (LDI), only assesses perfusion. MRI is used clinically to assess neural tracts, inflammation, and perfusion in the brain. We therefore evaluated whether a multimodal MRI approach could longitudinally monitor recovery in the HLI mouse model. Mice underwent MRI three days pre-HLI surgery, and on Days +3 and +7 post-surgery, with histology on Day +7. The MRI detected significant increases in muscle volume and inflammation after HLI surgery, with significant decreases in perfusion, vascular length, and muscle fibre integrity. Overall, MRI can monitor inflammation, muscle fibre integrity, and vascular recovery post-HLI and should be applied in future studies to identify mechanisms of therapeutic recovery in a sequential in vivo analysis without requiring animal sacrifice. O_FIG O_LINKSMALLFIG WIDTH=186 HEIGHT=200 SRC="FIGDIR/small/739107v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@79843dorg.highwire.dtl.DTLVardef@1d8e90borg.highwire.dtl.DTLVardef@1abd740org.highwire.dtl.DTLVardef@c0d296_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical AbstractC_FLOATNO C_FIG

BackgroundSingle-voxel magnetic resonance spectroscopy (MRS) is a non-invasive method for measuring clinically and cognitively relevant metabolites. Reliable measurements require precise voxel placement across sessions and participants. We developed a scanner-console-based approach to improve voxel placement precision. MethodsIn a crossover design (n=7; six sessions each), we compared test-retest reliability of three voxel placement methods in a reference benchmark (left parietal cortex) and a technically challenging region (left ventromedial prefrontal cortex). Methods included (1) conventional anatomy-based placement, (2) mask-guided real-time positioning (MGRP), and (3) semiautomated session-locked voxel repositioning (SSVR). Resting-state MRS data were acquired using PRESS and MEGA-PRESS. Within-subject reliability of voxel placement and metabolite concentrations, namely, total N-acetylaspartate (tNAA), total Creatine (tCr), GABA (gamma-aminobutyric acid), and Glx (glutamate + glutamine) are reported using the coefficient of variation (CV), the intraclass correlation coefficient (ICC), minimal detectable change (MDC), and the spatial overlap. ResultsSSVR markedly improved voxel placement reliability, increasing spatial overlap (up to 88%) and achieving near-perfect geometric reproducibility (ICC = 0.99) compared to conventional anatomy-based placement and MGRP. SSVR improved tissue composition consistency and reduced metabolite variability in the technically challenging region (variability reduction of [~]70% tCr, [~]59% tNAA, and [~]51% Glx) while further refining already stable measurements in the benchmark region (tNAA from [~]15% to [~]10%). ConclusionBoth MGRP and SSVR improved voxel placement and metabolite measurement reproducibility compared with conventional anatomy-based placement. SSVR further enhanced within-subject reproducibility across repeated sessions, particularly in the technically challenging region, providing a robust approach for longitudinal single-voxel MRS studies.

Transparent assessment of diffusion magnetic resonance imaging (dMRI) techniques with empirical verification of confounding factors requires adequately designed protocols and collected datasets. Publicly available diffusion-weighted MR datasets often provide limited sampling across b-values, making it difficult to study optimal acquisition protocols or the relationships between different processes occurring in brain tissue. In this work, we introduce a new densely sampled longitudinal test-retest diffusion-weighted MR dataset of the brain. Our dataset was collected from eleven healthy volunteers, each scanned four times: two sessions on consecutive days, which form the test data, followed by two additional sessions completed one week later (retest data). The data were acquired using twenty-two b-values ranging from 10 to 3000 s/mm2, along with structural T1-weighted scans. Potential applications of the dataset include, but are not limited to, assessing longitudinal reproducibility and reliability of quantitative metrics, evaluating robust and outlier-resistant estimation techniques, investigating experimental factors affecting estimation procedures, and verifying optimal acquisition protocols for different signal models. The dataset is publicly available in raw and fully preprocessed variants.

"Remote palpation" appears to be an oxymoron, but here we demonstrate a non-contacting MRI method to obtain mechanical stiffness parameters of the human brain solely by measuring deformations caused by the pumping action of the heart. Mechanical stiffness is an important tissue property that is highly sensitive to subtle changes in the tissue milieu; MR elastography (MRE) is among a handful of methods used to measure it, typically via an external driver/tamper that introduces mechanical waves into the tissue. Applying MRE in the brain is challenging due to the use of an external actuator/tamper and the mechanical anisotropy of brain tissue, which requires a 4th-order tensor to describe it. In this study, we use the intrinsic deformation of brain tissue caused by periodic cardiac pulsations to measure the 4th-order elasticity tensor throughout the brain while simultaneously estimating the 2nd-order diffusion tensor in each voxel throughout the cardiac cycle which we use as a priori information in the reconstruction of the elasticity tensor. While the DTI-derived mean diffusivity (MD) appears uniform throughout brain parenchyma, stiffness maps obtained at about 1 Hz (i.e., at the fundamental cardiac frequency) show that brain tissue is very soft within gray matter, and within white matter pathways, such as along the corpus callosum, corona radiata, etc. Generally, stiffness differences at internal tissue boundaries are expected to produce local stress concentration there, which may predispose tissues to damage, e.g., in traumatic brain injury (TBI). Therefore, our novel tamperless MRE method has the potential to not only identify such interfaces, but assess and follow changes in tissue stiffness there that might occur following injury.