Magnetic Resonance in Medicine

PurposeTo improve the SNR efficiency of zero echo time (ZTE) MRI pulse sequences for faster imaging of short-T2 components at large dead-time gaps. MethodsHYFI is s strategy of retrieving inner k-space data missed during the dead-time gap arising from radio-frequency excitation and switching in ZTE imaging. It performs hybrid filling of the inner k-space with a small single-point-imaging core surrounded by a stack of shells acquired on radial readouts in an onion-like fashion. The exposition of this concept is followed by translation into guidelines for parameter choice and implementation details. The imaging properties and performance of HYFI are studied in simulations as well as phantom, in-vitro and in-vivo imaging, with an emphasis on comparison with the PETRA technique (pointwise encoding time reduction with radial acquisition). ResultsSimulations predict higher SNR efficiency of HYFI compared to PETRA at preserved image quality with the advantage increasing with the size of the k-space gap. These results are confirmed by imaging experiments with gap sizes of 25 to 50 Nyquist dwells, in which scan times for similar SNR could be reduced by 25 to 60%. ConclusionThe HYFI technique provides both high SNR efficiency and image quality, thus outperforming previously known ZTE-based pulse sequences in particular for large k-space gaps. Promising applications include direct imaging of ultra-short T2 components, such as the myelin bilayer or collagen, T2 mapping of ultra-fast relaxing signals, and ZTE imaging with reduced chemical shift artifacts.

PurposeSegmented 3D Gradient and Spin Echo (GRASE) is commonly used in Arterial Spin Labeling (ASL) perfusion imaging. However, it is vulnerable to inter-shot motion, leading to subtraction errors that cannot be corrected. We developed a retrospective self-navigated inter-shot motion correction method for segmented 3D-GRASE ASL imaging with Controlled Aliasing in Parallel Imaging (CAIPI). MethodsMultiple shots, each uniformly covering k-space at distinct sample locations, allow a self-navigator image to be reconstructed using SENSE for each shot. Rigid-body motion estimation across the self-navigators is incorporated into a motion-compensated forward model for image reconstruction. To support self-navigation, two CAIPI-sampled segmented 3D-GRASE trajectories that ensure full k-space coverage were explored for point spread function (PSF) profiles and g-factor effects. Our approach was evaluated against conventional inter-volume registration and a previously proposed method, alignedSENSE. Additionally, we compared tag-control interleaving strategies to assess their impact on motion robustness in five healthy volunteers with instructed head motion. ResultsOur method effectively reduced motion artifacts and outperformed conventional inter-volume correction by 12.3% in correlation coefficient, 4.5% in Structural Similarity Index Measure (SSIM), and 40.1% in temporal SNR. It matched alignedSENSE performance while requiring only 20% of the computational time. All evaluated CAIPI sampling variants enabled robust motion correction, although tradeoffs were observed between through-plane blurring and SNR performance. The tag-control (T/C) inner loop acquisition yielded better motion robustness across all quantitative metrics. ConclusionSelf-navigated inter-shot motion correction using CAIPI sampling and a T/C inner loop for segmented 3D-GRASE ASL can improve image quality and motion robustness.

PurposeTo quantitatively assess the bias in the intravoxel incoherent motions (IVIM)-derived pseudo-diffusion volume fraction (f) caused by the differences in relaxation times between the tissue and fluid compartments, and to develop a 2D fitting approach and an optimal acquisition protocol for the relaxation compensated T2-IVIM imaging in the liver and kidney. MethodsNumerical simulations were conducted to investigate the TR- and TE-dependent bias in f when using the conventional IVIM model, and to evaluate the applicability of the extended 2D T2-IVIM model for reducing this bias. The in silico findings were then validated using the in vivo IVIM data from healthy volunteers on a clinical 3-Tesla MRI scanner. Finally, a numerical framework for optimizing the T2-IVIM protocol for relaxation-compensated f parameter estimation was proposed and tested using in vivo data. ResultsWhen using the traditional IVIM model, a trend toward higher f with increasing TE was found in the liver (R = 0.42, P = 0.043), but not in the kidney cortex (R = -0.067, P = 0.76) and medulla (R = 0.039, P = 0.86). The 2D T2-IVIM modeling yielded lower f and reduced the intra-subject variability in the liver. Our results also suggest that a b-TE protocol with six b-values and three different TE values (50, 55, and 100 ms) might be optimal for liver T2-IVIM. ConclusionThe extended 2D T2-IVIM model combined effectively minimizes the TE-dependent bias in f and allows simultaneous estimation of the IVIM parameter and compartmental T2 values in the liver and kidney.

PurposeIn localized MR spectroscopy, spurious echo artifacts commonly occur when unsuppressed signal outside the volume-of-interest is exicted and refocused. In the spectral domain, these signals often overlap with metabolite resonances and hinder accurate quantification. Since the artifacts orginate from regions separate from the target MRS voxel, this work proposes that sensitivity encoding based on receive coil sensitivity profiles may be used to separate these signal contributions. MethodsNumerical simulations were performed to explore the effect of sensitivity encoded separation for unknown artifact regions. An imaging-based approach was developed to identify regions that may contribute to spurious echo artifacts, and tested for sensitivity-based unfolding of signal contribution on 6 datasets from 3 brain regions. Spectral data reconstructed using the proposed method ( ERASE) were compared to standard coil combination. ResultsThe method was able to fully separate metabolite and artifact signals if regions were known a priori. Mismatch between estimated and actual artifact locations reduced the efficiency of artifact removal. Water suppression imaging (WSI) was able to identify unsuppressed signal remote from the MRS voxel in all cases, and ERASE reconstruction (of up to 8 distinct locations) led to improvements in spectral quality and reduced fitting errors for the major metabolites compared to standard reconstruction, without significant degradation of spectral SNR. ConclusionThe ERASE reconstruction tool was demonstrated to reduce spurious echo artifacts in single voxel MRS. ERASE may be incorporated into standard MRS workflows to improve spectral quality when scanner hardware limitations or other factors result in out-of-voxel signal contamination.

Vessel-encoded arterial spin labeling (VEASL) enables simultaneous, non-contrast imaging of multiple vascular territories that is useful for differential diagnosis and treatment monitoring of cerebrovascular diseases. However, the existing encoding methods are either signal-to-noise ratio (SNR) inefficient or requiring the spatial modulation to approximate a cosine function. To address these limitations, we developed a MOdulation-Guided ENcoding (MOGEN) scheme that directly exploits the spatial modulation pattern to obtain SNR-efficient encoding matrix. Simulation studies demonstrated that MOGEN achieves significantly higher theoretical SNR efficiency than previous methods across both four-and six-artery configurations. In healthy volunteers, MOGEN improved in vivo SNR by approximately 15% and provided more robust vessel decoding, particularly when the spatial modulation deviated from the cosine profile. In patients with Moyamoya disease, MOGEN enabled reliable visualization of collateral pathways even when scan time was reduced to [~]5 minutes for six arteries. Furthermore, by incorporating vessel size information and ensuring sharp label/control transitions, MOGEN enhanced single-artery selectivity in vessel-encoded angiography. We also demonstrated that a straightforward approach of off-resonance correction for VEASL at ultra-high field was feasible by using MOGEN.

PurposeA modified interleaved flyback (miFB) approach is introduced, designed to mitigate flow artifacts caused by alternating readout polarities in Echo Planar Imaging (EPI), while preserving acquisition efficiency. MethodsWe propose reconstructing odd and even echoes of 3D-EPI separately. To this end, the respective missing lines are acquired in interleaved shots with inverted polarity and an additional precursor gradient. Thereby, high scan efficiency is maintained compared to unsampled flyback gradients. Our miFB approach is additionally combined with gradient moment smoothing and compared to the interleaved dual-echo with acceleration (IDEA) method in phantom and in vivo scans at 7 Tesla. ResultsOur results demonstrate a significant reduction in ghosting and signal dropout using the miFB approach, yielding comparable image quality to non-EPI acquisitions while reducing acquisition time by approximately half. ConclusionThe miFB approach offers a substantial reduction in flow artifacts, allowing for decreased acquisition times in TOF-MRA.

PurposeSufficient control of the RF transmit field (B1+) in small regions-of-interest (ROIs) is critical for single voxel MR spectroscopy at ultra-high field. Static RF shimming, using parallel transmit (pTx), can improve B1+, but must be calibrated for each participant and ROI, which limits its applicability. Additionally, specific-absorption-rate (SAR) becomes hard to predict. This work aimed to find RF shims, which can be applied to any participant, to produce the desired |B1+| within pre-defined target ROIs. MethodsRF shims were found offline by joint-optimisation on a database, comprising B1+ maps from 11 subjects, considering ROIs in occipital cortex, hippocampus and posterior-cingulate, as well as the whole brain. The B1+ magnitude achieved using calibration-free RF shims was compared to a tailored shimming approach, and MR spectra were acquired using tailored and calibration-free RF shimming in 4 participants. Global and local 10g SAR deposition were modelled. ResultsCalibration-free RF shims resulted in similar |B1+| in small ROIs compared to tailored shimming, in addition to producing spectra of excellent quality and equivalent SNR. Only a small database size was required. SAR deposition was reduced compared to operating in quadrature mode for all ROIs. ConclusionThis work demonstrates that static RF shims, optimised offline for small regions in single voxel MRS, avoid the need for lengthy B1+ mapping and pTx optimisation for each ROI and participant. Furthermore, power settings may be increased when using calibration-free shims to better take advantage of the flexibility provided by RF shimming for regional acquisition at ultra-high field.

PurposeMR spectroscopy of dynamic systems is limited by low signal to noise. Denoising along a series of acquired spectra exploits their temporal correlation to improve the quality of individual spectra, and reduce errors in fitting metabolite peaks. In this study we compare the performance of several denoising methods. MethodsSix different denoising methods were considered: SIFT (Spectral Improvement by Fourier Thresholding), HSVD (Hankel Singular Value Decomposition), spline, wavelet, sliding window and sliding Gaussian. Pseudo-synthetic data was constructed to mimic 31Phosphorus spectra from exercising muscle. For each method the optimal tuning parameters were determined for SNRs of 2, 5, 10 and 20 using a Monte Carlo approach. Denoised data from each method was then fitted using the AMARES algorithm and the results compared to the pseudo-synthetic ground truth. ResultsAll six methods produced improvements in both fitting accuracy and agreement with the ground truth, compared to unprocessed noisy data. The least effective methods, SIFT and HSVD, achieved around 10-20% reduction in RMS error, while the most effective, Spline, reduced RMS error by 70%. The improvement from denoising was typically greater for lower SNR data. ConclusionsIndirect time domain denoising of dynamic MR spectroscopy data can substantially improve subsequent metabolite fitting. Spline-based denoising was found to be the most flexible and effective technique.

BackgroundSegmented cine cardiac MRI combines data from multiple heartbeats to achieve high spatiotemporal resolution cardiac images, yet predefined k-space segmentation trajectories can lead to suboptimal k-space sampling. In this work, we developed and evaluated an autonomous and closed-loop control system for radial k-space sampling to increase sampling uniformity. MethodsThe closed-loop system autonomously selects radial k-space sampling trajectory during live segmented cine MRI and attempts to optimize angular sampling uniformity by selecting views in regions of k-space that were not previously well-sampled. Sampling uniformity and robustness to arrhythmias was assessed using ECG data acquired from 10 normal subjects in an MRI scanner. The approach was then implemented with a fast gradient echo sequence on a whole-body clinical MRI scanner and imaging was performed in 4 healthy volunteers. The closed-loop k-space trajectory was compared to random, uniformly distributed and golden angle view trajectories via measurement of k-space uniformity and the point spread function. Lastly, an arrhythmic dataset was used to evaluate a potential application of the approach. ResultsThe autonomous trajectory increased k-space sampling uniformity by 13{+/-}7%, main lobe point spread function (PSF) signal intensity by 14{+/-}6%, and reduced ringing relative to golden angle sampling. When implemented, the autonomous pulse sequence prescribed radial view angles faster than the scan TR (0.98 {+/-} 0.02 ms, maximum = 1.38 ms) and increased k-space sampling mean uniformity by 5{+/-}12%, decreased uniformity variability by 45{+/-}14%, and increased PSF signal ratio by 5{+/-}5% relative to golden angle sampling. ConclusionThe closed-loop approach enables near-uniform radial sampling in a segmented acquisition approach which was higher than predetermined golden-angle radial sampling. This can be utilized to increase the sampling or decrease the temporal footprint of an acquisition and the closed-loop framework has the potential to be applied to patients with complex heart rhythms.

Multichannel transceiver coil arrays are needed to enable parallel imaging and B1 manipulation in ultrahigh field MR imaging and spectroscopy. However, the design of such transceiver coils and coil arrays often faces technical challenges in achieving the required high operating frequency at the ultrahigh fields and sufficient electromagnetic (EM) decoupling between resonant elements. In this work, we propose a high impedance microstrip transmission line resonator (HIMTL) technique that has unique high frequency capability and adequate EM decoupling without the use of dedicated decoupling circuits. To validate the proposed technique for the ultrahigh field 10.5T applications, a two-channel high impedance microstrip array with the element dimension of 8cm by 8cm was built and tuned to 447 MHz, Larmor frequency of proton at 10.5T, for signal excitation and reception. Bench tests and numerical simulations were performed to evaluate its feasibility and performance. The results show that the proposed high impedance microstrip technique can be a simple and robust way to design high frequency transceiver coils and coil arrays for ultrahigh field MR applications.

BackgroundThe heart has metabolic flexibility, which is influenced by fed/fasting states, and pathologies such as myocardial ischemia and hypertrophic cardiomyopathy (HCM). Hyperpolarized (HP) 13C-pyruvate MRI is a promising new tool for non-invasive quantification of myocardial glycolytic and Krebs cycle flux. However, human studies of HP 13C-MRI have yet to demonstrate regional quantification of metabolism, which is important in regional ischemia and HCM patients with asymmetric septal/apical hypertrophy. MethodsWe developed and applied methods for whole-heart imaging of 13C-pyruvate, 13C-lactate and 13C-bicarbonate, following intravenous administration of [1-13C]-pyruvate. The image acquisition used an autonomous scanning method including bolus tracking, real-time magnetic field calibrations and metabolite-specific imaging. For quantification of metabolism, we evaluated 13C metabolite images, ratio metrics, and pharmacokinetic modeling to provide measurements of myocardial lactate dehydrogenase (LDH) and pyruvate dehydrogenase (PDH) mediated metabolic conversion in 5 healthy volunteers (fasting & 30 min following oral glucose load). ResultsWe demonstrate whole heart coverage for dynamic measurement of pyruvate-to-lactate conversion via LDH and pyruvate-to-bicarbonate conversion via PDH at a resolution of 6x6x21 mm3 (13C-pyruvate) and 12x12x21 mm3 (13C-lactate, 13C-bicarbonate). 13C-pyruvate and 13C-lactate were detected simultaneously in the RV blood pool, immediately after intravenous injection, reflecting LDH activity in blood. In healthy volunteers, myocardial 13C-pyruvate-SNR, 13C-lactate-SNR, 13C-bicarbonate-SNR, 13C-lactate/pyruvate ratio, 13C-pyruvate-to-lactate conversion rate, kPL, and 13C-pyruvate-to-bicarbonate conversion rate, kPB, all had statistically significant increases following oral glucose challenge. kPB, reflecting PDH activity and pyruvate entering the Krebs Cycle, had the highest correlation with blood glucose levels and was statistically significant. ConclusionsWe demonstrate first-in-human regional quantifications of cardiac metabolism by HP 13C-pyruvate MRI that aims to reflect LDH and PDH activity.

ObjectivesConventional gadolinium-enhanced cardiac magnetic resonance imaging (MRI) typically evaluates myocardial tissues at a single post-contrast time point. In contrast, dynamic T1 mapping enables the estimation of contrast agent concentrations and subsequent pharmacokinetic modeling. This study compared a normal composite two-compartment model incorporating myocardial vascular components with the conventional Brix model. Materials and MethodsThis retrospective study included 107 participants who underwent dynamic T1 mapping at 2, 5, 9, and 15 min after contrast administration. Exclusion criteria included contraindications to MR imaging, acute coronary syndrome, pregnancy, an estimated glomerular filtration rate < 30 mL/min/1.73 m2, claustrophobia, and known allergy to gadolinium-based contrast medium. Contrast agent concentrations derived from MOLLI-based T1 maps were fitted using the Brix and composite pharmacokinetic models. Model performance was assessed using the residual sum of squares (RSS), Akaike information criterion (AIC), and Bayesian information criterion (BIC). The myocardial blood fraction estimated by the composite model was compared with the extracellular volume (ECV). ResultsThe composite model exhibited significantly lower RSS, AIC, and BIC values than the Brix model (all p < 0.001). Absolute parameter estimation errors were reduced across all time points. The estimated myocardial blood fraction averaged 35.0% and demonstrated a positive correlation with the ECV (r = 0.61, p < 0.001). ConclusionsIn myocardial pharmacokinetic analysis using dynamic T1 maps, the composite model achieved superior fitting performance compared with the Brix model. Explicit incorporation of vascular kinetics improves the longitudinal characterization of contrast behavior and enhances quantitative assessment of myocardial tissue properties.

Diffusion-weighted imaging (DWI) is routinely used to aid in the detection and characterization of prostate cancer. Given imaging time constraints in a clinical setting, it is important to maximize the statistical efficiency of a DWI examination of the prostate. The objective is to maximize the accuracy with which microstructural information about the prostate can be obtained while minimizing diffusion scan time. In this study, we apply estimation theory to evaluate the statistical efficiency of different DWI acquisitions and methods. Specifically, we show that the variance of DWI parameters estimated using nonlinear multiexponential signal models is considerably higher than the variance observed using linear signal models. We then derive a simple analytical expression for the efficiency of a linear estimator and use it to optimize b-value sampling for DWI of the prostate.

In this work, we demonstrate the sodium magnetic resonance imaging (MRI) capabilities of a three-dimensional (3D) dual-echo ultrashort echo time (UTE) sequence with a novel rosette petal trajectory (PETALUTE), in comparison to the 3D density-adapted (DA) radial spokes UTE sequence. We scanned five healthy subjects using a 3D dual-echo PETALUTE acquisition and two comparable implementations of 3D DA-radial spokes acquisitions, one matching the number of k-space projections (Radial - Matched Spokes) and the other matching the total number of samples (Radial - Matched Samples) acquired in k-space. The PETALUTE acquisition enabled equivalent sodium quantification in articular cartilage volumes of interest (168.8 {+/-} 29.9 mM) to those derived from the 3D radial acquisitions (171.62 {+/-} 28.7 mM and 149.8 {+/-} 22.2 mM, respectively). We achieved a 41% shorter scan time of 2:06 for 3D PETALUTE, compared to 3:36 for 3D radial acquisitions. We also evaluated the feasibility of further acceleration of the PETALUTE sequence through retrospective compressed sensing with 2x and 4x acceleration of the first echo and showed structural similarity of 0.89 {+/-} 0.03 and 0.87 {+/-} 0.03 when compared to non-retrospectively accelerated reconstruction. Together, these results demonstrate improved scan time with equivalent performance of the PETALUTE sequence compared to the 3D DA-radial sequence for sodium MRI of articular cartilage.

PurposeMulti-echo gradient-echo (ME-GRE) imaging in the spinal cord is susceptible to breathing-induced B0 field fluctuations due to the proximity of the lungs, leading to ghosting artifacts. A navigator readout can be used to monitor the fluctuations; however, standard navigator processing often fails in the spinal cord. Here, we introduce navigator processing tailored specifically for spinal cord imaging. MethodsME-GRE data covering all spinal cord regions were acquired in six healthy volunteers during free breathing at 3T. Centerline navigator readouts and respiratory belt recordings were collected during the acquisitions. The navigator processing included a Fast Fourier Transform and subsequent interval selection targeting the spinal cord, as well as SNR-weighted averaging over samples and coils on the complex data. Furthermore, a phase unwrapping algorithm making use of the belt recordings was developed. Imaging data were corrected by phase demodulation before image reconstruction. ResultsB0 field fluctuations and ghosting artifacts were largest in the lower cervical and upper lumbosacral cord ([~]5 Hz std), close to the edges of the lungs. Image reconstruction based on optimized navigator correction improved visual image quality and quantitative metrics (SNR, CNR, ghosting) in all regions of the spinal cord. The improvement was largest in regions with large field fluctuations (group-averaged increase in SNR/CNR of up to 29%/37% in single-echo images). ConclusionsOptimized navigator-based correction can reduce ghosting artifacts and increase SNR/CNR in anatomical ME-GRE of the spinal cord. The enhanced image quality and ease of implementation across sites makes the technique attractive for clinical and scientific applications.

Changes in myelination are a cardinal feature of brain development and the pathophysiology of several cerebral diseases, including multiple sclerosis and dementias. Advanced magnetic resonance imaging (MRI) methods have been developed to probe myelin content through the measurement of myelin water fraction (MWF). However, the prolonged data acquisition and post-processing times of current MWF mapping methods pose substantial hurdles to their clinical implementation. Recently, fast steady-state MRI sequences have been implemented to produce high spatial resolution whole-brain MWF mapping within [~] 20 min. Despite the subsequent significant advances in the inversion algorithm to derive MWF maps from steady-state MRI, the high-dimensional nature of such inversion does not permit further reduction of the acquisition time by data under-sampling. In this work, we present an unprecedented reduction in the computation ([~] 30 s) and the acquisition time ([~] 7 min) required for whole-brain high-resolution MWF mapping through a new Neural Network (NN)-based approach, named: Relaxometry of Extremely Under-SamplEd Data (NN-REUSED). Our analyses demonstrate virtually similar accuracy and precision in derived MWF values using the NN-REUSED approach as compared to results derived from the fully-sampled reference method. The reduction in the acquisition and computation times represents a breakthrough toward clinically practical MWF mapping.

ObjectiveUltra-high-field (B0 [&ge;] 7 Tesla) cardiovascular magnetic resonance (CMR) offers increased resolution. However, ECG gating is impacted by the magneto-hydrodynamic (MHD) effect distorting the ECG trace. We explored the technical feasibility of a 7T MR scanner using ECG trigger learning algorithm to quantitatively assess cardiac volumes and vascular flow. Methods7T scans performed on 10 healthy volunteers on a whole-body research MRI (Siemens Healthcare, Erlangen, Germany) with 8 channel Tx/32 channel Rx cardiac coil (MRI Tools GmbH, Berlin, Germany). Vectorcardiogram ECG was performed using a learning phase outside of the magnetic field, with a trigger algorithm overcoming severe ECG signal distortions. Vectorcardiograms were quantitatively analyzed for false negative and false positive events. Cine CMR was performed after 3rd-order B0 shimming using a high-resolution breath-held ECG-retro-gated segmented spoiled gradient echo, and 2D phase contrast flow imaging. Artefacts were assessed using a semi-quantitative scale. Results7T CMR scans were acquired in all patients (100%) using the VCG learning method. 3,142 R-waves were quantitatively analyzed, yielding sensitivity 97.6%, specificity 98.7%. Mean image quality score was 0.9, sufficient to quantitate both cardiac volumes, ejection fraction (EF), aortic and pulmonary blood flow. Mean LVEF was 56.4%, RVEF 51.4%. ConclusionReliable cardiac ECG triggering is feasible in healthy volunteers at 7T utilizing a state-of-the-art 3-lead trigger device despite signal distortion from the MHD effect. This provides sufficient image quality for quantitative analysis. Other ultra-high-field imaging applications such as human brain functional MRI with physiologic noise correction may benefit from this method of ECG triggering. Key pointsO_LIUltra-high field 7 Tesla cardiac MRI is challenging due to the impact of the magneto-hydrodynamic (MHD) effect causing severe distortions in the ECG trace. C_LIO_LIUsing VCG with a learning phase outside the ultra-high field magnet, the R waves can be adequately detected to perform high quality Cardiac MRI scans, overcoming signal distortion from the MHD effect. C_LI

PurposeTo establish and optimize abdominal deuterium MRSI in conjunction with orally administered 2H-labelled molecules. MethodsA flexible transmit-receive surface coil was used to image naturally abundant deuterium signal in phantoms and healthy volunteers and after orally administered 2H2O in a patient with a benign renal tumor (oncocytoma). ResultsWater and lipid peaks were fitted with high confidence from both unlocalized spectra and from voxels within the liver, kidney, and spleen on spectroscopic imaging. Artifacts were minimal despite the high 2H2O concentration in the stomach immediately after ingestion, which can be problematic with the use of a volume coil. ConclusionWe have shown the feasibility of abdominal deuterium MRSI at 3 T using a flexible surface coil. Water measurements were obtained in healthy volunteers and images were acquired in a patient with a renal tumor after drinking 2H2O. The limited depth penetration of the surface coil may have advantages in characterizing early uptake of orally administered agents in abdominal organs despite the high concentrations in the stomach which can pose challenges with other coil combinations.

PurposeWe aim to inform the design of new diffusion MRI (dMRI) approaches for microvasculature mapping that enhance the biological specificity of imaging towards cancer. MethodsWe adopted simulation-informed modelling of the vascular dMRI signal. We synthesised signals from 1500 synthetic vascular networks, for a variety of protocols (flow-compensated (FC), non-compensated (NC), hybrid), featuring different b samplings and diffusion times. We estimated the number of independent, recoverable signal degrees of freedom in presence of noise (signal-to-noise ratio of 5), and ranked 12 microvascular metrics depending on the quality of their estimation. Lastly, we demonstrated the feasibility of estimating the top-ranking metrics on 3T dMRI of a healthy volunteer and of a metastatic colorectal cancer (CRC) patient. ResultsBoth NC and FC synthetic vascular signals exhibit complex behaviour, e.g., non-zero kurtosis and diffusion time dependence. Two independent degrees of freedom appear recoverable from directionally-averaged vascular signals (SNR of 5). Mean volumetric flow rate qm and an Apparent Network Branching (ANB) index maximise correlations between ground truth and estimated values in silico. Their estimation is proposed for in vivo imaging, and demonstrated herein. In the patient, both qm and ANB detect re-vascularisation after 3 months of targeted therapy against liver metastases, consistently with Intra-Voxel Incoherent Motion (IVIM) metrics. ConclusionsSimulation-based modelling of the vas-cular dMRI signal informs the design of promising approaches for in vivo microvasculature characterisation.

PurposeMagnetic resonance current density imaging (MRCDI) can non-invasively validate electric field simulations in volume conductor head models. Weak electric currents are injected using scalp electrodes while measuring the MR phase perturbations caused by the tiny magnetic fields (1-2 nT) induced by the current flow in tissue. MRCDI generally has a low signal-to-noise ratio, making it susceptible to technical imperfections and physiological noise. Here, we tested and optimized simultaneous multi-slice (SMS) EPI for time-efficient and robust brain MRCDI. MethodsMRCDI data was acquired in a phantom and five human brains using SMS-EPI optimized for measuring current-induced phase perturbations. Multiband factors and interslice gaps were systematically varied and the resulting image quality assessed. In particular, the impact of interslice signal leakage on the measured phase was tested. ResultsCurrent-free acquisitions showed the expected noise amplification with decreasing interslice distances. However, physiological noise generally dominated the human data, making the overall noise levels identical to single-slice EPI for interslice gaps of at least 12 mm and multiband factors between 3 and 5. Upon application of electric currents, the phantom data revealed subtle artifacts for multiband factors 5 and 6, even for large gaps. Nevertheless, artifacts were absent in the human brain for multiband factors up to 5, where the performance of SMS-EPI approached that of single-slice measurements for sufficient interslice distances. ConclusionOptimized SMS-EPI with multiband factors up to 5 and minimum interslice gaps of 12 mm performs on par with single-slice EPI, making it attractive for increasing brain coverage in MRCDI.