Intrauterine exposure to SARS-CoV-2 infection and early newborn brain development.

Epidemiologic studies suggest that prenatal exposures to certain viruses may influence early neurodevelopment, predisposing offspring to neuropsychiatric conditions later in life. The long-term effects of maternal COVID-19 infection in pregnancy on early brain development, however, remain largely unknown. We prospectively enrolled infants in an observational cohort study for a single-site study in the Washington, DC Metropolitan Area from June 2020 to November 2021 and compared these infants to pre-pandemic controls (studied March 2014-February 2020). The primary outcomes are measures of cortical morphometry (tissue-specific volumes), along with global and regional measures of local gyrification index, and sulcal depth. We studied 210 infants (55 infants of COVID-19 unexposed mothers, 47 infants of COVID-19-positive mothers, and 108 pre-pandemic healthy controls). We found increased cortical gray matter volume (182.45 ± 4.81 vs. 167.29 ± 2.92) and accelerated sulcal depth of the frontal lobe (5.01 ± 0.19 vs. 4.40 ± 0.13) in infants of COVID-19-positive mothers compared to controls. We found additional differences in infants of COVID-19 unexposed mothers, suggesting both maternal viral exposures, as well as non-viral stressors associated with the pandemic, may influence early development and warrant ongoing follow-up.

Anisotropy of T2 and T1ρ relaxation time in articular cartilage at 3 T.

PURPOSE: The anisotropy of R2 and R1ρ relaxation rates in articular cartilage contains information about the collagenous structure of the tissue. Here we determine and study the anisotropic and isotropic components of T2 and T1ρ relaxation parameters in articular cartilage with a clinical 3T MRI device. Furthermore, a visual representation of the topographical variation in anisotropy is given via anisotropy mapping. METHODS: Eight bovine stifle joints were imaged at 22 orientations with respect to the main magnetic field using T2, continuous-wave (CW) T1ρ, and adiabatic T1ρ mapping sequences. Relaxation rates were separated into isotropic and anisotropic relaxation components using a previously established relaxation anisotropy model. Pixel-wise anisotropy values were determined from the relaxation-time maps using Michelson contrast. RESULTS: The relaxation rates obtained from the samples displayed notable variation depending on the sample orientation, magnetization preparation, and cartilage layer. R2 demonstrated significant anisotropy, whereas CW-R1ρ (300 Hz) and CW-R1ρ (500 Hz) displayed a low degree of anisotropy. Adiabatic R1ρ was largely isotropic. In the deep cartilage regions, relaxation rates were generally faster and more anisotropic than in the cartilage closer to the tissue surface. The isotropic relaxation rate components were found to have similar values regardless of measurement sequence. CONCLUSIONS: The fitted relaxation model for T2 and T1ρ demonstrated varying amounts anisotropy, depending on magnetization preparation, and studied the articular cartilage layer. Anisotropy mapping of full joints showed varying amounts of anisotropy depending on the quantitative MRI parameter and topographical location, and in the case of T2, showed systematic changes in anisotropy across cartilage depth.

Radiation damping at clinical field strength: Characterization and compensation in quantitative measurements.

PURPOSE: In any MR experiment, the bulk magnetization acts on itself, caused by the induced current in the RF receiver circuit that generates an oscillating damping field. This effect, known as "radiation damping" (RD), is usually weak and, therefore, unconsidered in MRI, but can affect quantitative studies performed with dedicated coils that provide a high SNR. The current work examined RD in a setup for investigations of small tissue specimens including a quantitative characterization of the spin-coil system. THEORY AND METHODS: A custom-made Helmholtz coil (radius and spacing 16 mm) was interfaced to a transmit-receive (Tx/Rx) switch with integrated passive feedback for modulation or suppression of RD similar to preamplifier decoupling. Pulse sequences included pulse-width arrays to demonstrate the absence/ presence of RD and difference techniques employing gradient pulses or composite RF pulses to quantify RD effects during free precession and transmission, respectively. Experiments were performed at 3T in small samples of MnCl2 solution. RESULTS: Significant RD effects may impact RF pulse application and evolution periods. Effective damping time constants were comparable to typical T2 * times or echo spacings in multi-echo sequences. Measurements of the phase relation showed that deviations from the commonly assumed 90° angle between the damping field and the transverse magnetization may occur. CONCLUSION: Radiation damping may affect the accuracy of quantitative MR measurements performed with dedicated RF coils. Efficient mitigation can be achieved hardware-based or by appropriate consideration in the pulse sequence.

Muscle diffusion tensor imaging in facioscapulohumeral muscular dystrophy.

INTRODUCTION/AIMS: Muscle diffusion tensor imaging has not yet been explored in facioscapulohumeral muscular dystrophy (FSHD). We assessed diffusivity parameters in FSHD subjects compared with healthy controls (HCs), with regard to their ability to precede any fat replacement or edema. METHODS: Fat fraction (FF), water T2 (wT2), mean, radial, axial diffusivity (MD, RD, AD), and fractional anisotropy (FA) of thigh muscles were calculated in 10 FSHD subjects and 15 HCs. All parameters were compared between FSHD and controls, also exploring their gradient along the main axis of the muscle. Diffusivity parameters were tested in a subgroup analysis as predictors of disease involvement in muscle compartments with different degrees of FF and wT2 and were also correlated with clinical severity scores. RESULTS: We found that MD, RD, and AD were significantly lower in FSHD subjects than in controls, whereas we failed to find a difference for FA. In contrast, we found a significant positive correlation between FF and FA and a negative correlation between MD, RD, and AD and FF. No correlation was found with wT2. In our subgroup analysis we found that muscle compartments with no significant fat replacement or edema (FF < 10% and wT2 < 41 ms) showed a reduced AD and FA compared with controls. Less involved compartments showed different diffusivity parameters than more involved compartments. DISCUSSION: Our exploratory study was able to demonstrate diffusivity parameter abnormalities even in muscles with no significant fat replacement or edema. Larger cohorts are needed to confirm these preliminary findings.

Quantitative magnetic resonance imaging vs. perioperative arthroscopy to measure stage 1 ruptures of the supraspinatus tendon for surgical planning.

BACKGROUND: Accurate preoperative assessment of supraspinatus tendon tear (STT) size is important for surgical planning. Our aims were to evaluate the correlation between stage 1 STT size measured preoperatively by quantitative magnetic resonance imaging (qMRI) and size measured perioperatively by arthroscopy. The concordance between preoperative tear size and the surgical plan was also assessed. METHODS: This prospective, nonrandomized, noncontrolled, interventional study was carried out in patients with a stable stage 1 STT. Three months before surgery, STT size was measured in the sagittal and coronal planes by a radiologist by qMRI (1.5 T). Three months later, the surgeon measured the size of the tear again on the same qMRI scans and decided on the most appropriate surgical plan. During arthroscopy, the surgeon measured the size of the tear again using a graduated sensor hook and carried out the repair. STT size measured preoperatively was compared to that measured by arthroscopy and the concordance between preoperative STT size and the surgical plan was determined. RESULTS: Sixty-seven patients were included (mean age: 59.5 ± 8.9 years; 58.2% female). There was good concordance between STT size measured by qMRI vs. arthroscopy in the coronal plane (concordance correlation coefficient = 0.36 [95% confidence interval (CI): 0.16-0.53]; Pearson's correlation coefficient = 0.42 [95% CI: 0.2-0.6]; P = .0004) and in the sagittal plane (concordance correlation coefficient = 0.51 [95% CI: 0.33-0.65]; Pearson's correlation coefficient = 0.57 [95% CI: 0.38-0.71]; P < .0001). Preoperative STT size concurred with the surgical plan in 85% of patients. CONCLUSION: There was good concordance between STT size measured by qMRI and that measured perioperatively by arthroscopy. However, preoperative STT size measured by qMRI did not concur with the surgical plan in 15% of patients and in these patients the surgical procedure had to be revised during surgery.

ADEPT: Accurate Diffusion Echo-Planar imaging with multi-contrast shoTs.

PURPOSE: To introduce a novel imaging and parameter estimation framework for accurate multi-shot diffusion MRI. THEORY AND METHODS: We propose a new framework called ADEPT (Accurate Diffusion Echo-Planar imaging with multi-contrast shoTs) that enables fast diffusion MRI by allowing diffusion contrast settings to change between shots in a multi-shot EPI acquisition (i.e., intra-scan modulation). The framework estimates diffusion parameter maps directly from the acquired intra-scan modulated k-space data, while simultaneously accounting for shot-to-shot phase inconsistencies. The performance of the estimation framework is evaluated using Monte Carlo simulation studies and in-vivo experiments and compared to that of reference methods that rely on parallel imaging for shot-to-shot phase correction. RESULTS: Simulation and real-data experiments show that ADEPT yields more accurate and more precise estimates of the diffusion metrics in multi-shot EPI data in comparison with the reference methods. CONCLUSION: ADEPT allows fast multi-shot EPI diffusion MRI without significantly degrading the accuracy and precision of the estimated diffusion maps.

Adaptive model-based Magnetic Resonance.

PURPOSE: Conventional sequences are static in nature, fixing measurement parameters in advance in anticipation of a wide range of expected tissue parameter values. We set out to design and benchmark a new, personalized approach-termed adaptive MR-in which incoming subject data is used to update and fine-tune the pulse sequence parameters in real time. METHODS: We implemented an adaptive, real-time multi-echo (MTE) experiment for estimating T2 s. Our approach combined a Bayesian framework with model-based reconstruction. It maintained and continuously updated a prior distribution of the desired tissue parameters, including T2 , which was used to guide the selection of sequence parameters in real time. RESULTS: Computer simulations predicted accelerations between 1.7- and 3.3-fold for adaptive multi-echo sequences relative to static ones. These predictions were corroborated in phantom experiments. In healthy volunteers, our adaptive framework accelerated the measurement of T2 for n-acetyl-aspartate by a factor of 2.5. CONCLUSION: Adaptive pulse sequences that alter their excitations in real time could provide substantial reductions in acquisition times. Given the generality of our proposed framework, our results motivate further research into other adaptive model-based approaches to MRI and MRS.

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.

B1 mapping using an EPI-based double angle approach: A practical guide for correcting slice profile and B0 distortion effects.

PURPOSE: Aim of this study was to develop a reliable B1 mapping method for brain imaging based on vendor MR sequences available on clinical scanners. Correction procedures for B0 distortions and slice profile imperfections are proposed, together with a phantom experiment for deriving the approximate time-bandwidth-product (TBP) of the excitation pulse, which is usually not known for vendor sequences. METHODS: The double angle method was used, acquiring two gradient echo echo-planar imaging data sets with different excitation angles. A correction factor C (B1 , TBP, B0 ) was derived from simulations for converting double angle method signal quotients into bias-free B1 maps. In vitro and in vivo tests compare results with reference B1 maps based on an established in-house sequence. RESULTS: The simulation shows that C has a negligible B1 dependence, allowing for a polynomial approximation of C (TBP, B0 ). Signal quotients measured in a phantom experiment with known TBP reconfirm the simulation results. In vitro and in vivo B1 maps based on the proposed method, assuming TBP = 5.8 as derived from a phantom experiment, match closely the reference B1 maps. Analysis without B0 correction shows marked deviations in areas of distorted B0 , highlighting the importance of this correction. CONCLUSION: Double angle method-based B1 mapping was set up for vendor gradient echo-echo-planar imaging sequences, using a correction procedure for slice profile imperfections and B0 distortions. This will help to set up quantitative MRI studies on clinical scanners with release sequences, as the method does not require knowledge of the exact RF-pulse profiles or the use of in-house sequences.

A method for measuring B0 field inhomogeneity using quantitative double-echo in steady-state.

PURPOSE: To develop and validate a method for B 0 $$ {B}_0 $$ mapping for knee imaging using the quantitative Double-Echo in Steady-State (qDESS) exploiting the phase difference ( Δ Î¸ $$ \Delta \theta $$ ) between the two echoes acquired. Contrary to a two-gradient-echo (2-GRE) method, Δ Î¸ $$ \Delta \theta $$ depends only on the first echo time. METHODS: Bloch simulations were applied to investigate robustness to noise of the proposed methodology and all imaging studies were validated with phantoms and in vivo simultaneous bilateral knee acquisitions. Two phantoms and five healthy subjects were scanned using qDESS, water saturation shift referencing (WASSR), and multi-GRE sequences. Δ B 0 $$ \Delta {B}_0 $$ maps were calculated with the qDESS and the 2-GRE methods and compared against those obtained with WASSR. The comparison was quantitatively assessed exploiting pixel-wise difference maps, Bland-Altman (BA) analysis, and Lin's concordance coefficient ( ρ c $$ {\rho}_c $$ ). For in vivo subjects, the comparison was assessed in cartilage using average values in six subregions. RESULTS: The proposed method for measuring Δ B 0 $$ \Delta {B}_0 $$ inhomogeneities from a qDESS acquisition provided Δ B 0 $$ \Delta {B}_0 $$ maps that were in good agreement with those obtained using WASSR. Δ B 0 $$ \Delta {B}_0 $$ ρ c $$ {\rho}_c $$ values were ≥ $$ \ge $$ 0.98 and 0.90 in phantoms and in vivo, respectively. The agreement between qDESS and WASSR was comparable to that of a 2-GRE method. CONCLUSION: The proposed method may allow B0 correction for qDESS T 2 $$ {T}_2 $$ mapping using an inherently co-registered Δ B 0 $$ \Delta {B}_0 $$ map without requiring an additional B0 measurement sequence. More generally, the method may help shorten knee imaging protocols that require an auxiliary Δ B 0 $$ \Delta {B}_0 $$ map by exploiting a qDESS acquisition that also provides T 2 $$ {T}_2 $$ measurements and high-quality morphological imaging.

Inline dual-echo T2 quantification in brain using a fast mapping reconstruction technique.

T2 mapping from 2D proton density and T2-weighted images (PD-T2) using Bloch equation simulations can be time consuming and introduces a latency between image acquisition and T2 map production. A fast T2 mapping reconstruction method is investigated and compared with a previous modeling approach to reduce computation time and allow inline T2 maps on the MRI console. Brain PD-T2 images from five multiple sclerosis patients were used to compare T2 map reconstruction times between the new subtraction method and the Euclidean norm minimization technique. Bloch equation simulations were used to create the lookup table for decay curve matching in both cases. Agreement of the two techniques used Bland-Altman analysis for investigating individual subsets of data and all image points in the five volumes (meta-analysis). The subtraction method resulted in an average reduction of computation time for single slices from 134 s (minimization method) to 0.44 s. Comparing T2 values between the subtraction and minimization methods resulted in a confidence interval ranging from -0.06 to 0.06 ms (95% of values were within ± 0.06 ms between the techniques). Using identical reconstruction code based on the subtraction method, inline T2 maps were produced from PD-T2 images directly on the scanner console. The excellent agreement between the two methods permits the subtraction technique to be interchanged with the previous method, reducing computation time and allowing inline T2 map reconstruction based on Bloch simulations directly on the scanner.

Generalizability of Deep Learning Segmentation Algorithms for Automated Assessment of Cartilage Morphology and MRI Relaxometry.

BACKGROUND: Deep learning (DL)-based automatic segmentation models can expedite manual segmentation yet require resource-intensive fine-tuning before deployment on new datasets. The generalizability of DL methods to new datasets without fine-tuning is not well characterized. PURPOSE: Evaluate the generalizability of DL-based models by deploying pretrained models on independent datasets varying by MR scanner, acquisition parameters, and subject population. STUDY TYPE: Retrospective based on prospectively acquired data. POPULATION: Overall test dataset: 59 subjects (26 females); Study 1: 5 healthy subjects (zero females), Study 2: 8 healthy subjects (eight females), Study 3: 10 subjects with osteoarthritis (eight females), Study 4: 36 subjects with various knee pathology (10 females). FIELD STRENGTH/SEQUENCE: A 3-T, quantitative double-echo steady state (qDESS). ASSESSMENT: Four annotators manually segmented knee cartilage. Each reader segmented one of four qDESS datasets in the test dataset. Two DL models, one trained on qDESS data and another on Osteoarthritis Initiative (OAI)-DESS data, were assessed. Manual and automatic segmentations were compared by quantifying variations in segmentation accuracy, volume, and T2 relaxation times for superficial and deep cartilage. STATISTICAL TESTS: Dice similarity coefficient (DSC) for segmentation accuracy. Lin's concordance correlation coefficient (CCC), Wilcoxon rank-sum tests, root-mean-squared error-coefficient-of-variation to quantify manual vs. automatic T2 and volume variations. Bland-Altman plots for manual vs. automatic T2 agreement. A P value < 0.05 was considered statistically significant. RESULTS: DSCs for the qDESS-trained model, 0.79-0.93, were higher than those for the OAI-DESS-trained model, 0.59-0.79. T2 and volume CCCs for the qDESS-trained model, 0.75-0.98 and 0.47-0.95, were higher than respective CCCs for the OAI-DESS-trained model, 0.35-0.90 and 0.13-0.84. Bland-Altman 95% limits of agreement for superficial and deep cartilage T2 were lower for the qDESS-trained model, ±2.4 msec and ±4.0 msec, than the OAI-DESS-trained model, ±4.4 msec and ±5.2 msec. DATA CONCLUSION: The qDESS-trained model may generalize well to independent qDESS datasets regardless of MR scanner, acquisition parameters, and subject population. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 1.

Compositional and Functional MRI of Skeletal Muscle: A Review.

Due to its exceptional sensitivity to soft tissues, MRI has been extensively utilized to assess anatomical muscle parameters such as muscle volume and cross-sectional area. Quantitative Magnetic Resonance Imaging (qMRI) adds to the capabilities of MRI, by providing information on muscle composition such as fat content, water content, microstructure, hypertrophy, atrophy, as well as muscle architecture. In addition to compositional changes, qMRI can also be used to assess function for example by measuring muscle quality or through characterization of muscle deformation during passive lengthening/shortening and active contractions. The overall aim of this review is to provide an updated overview of qMRI techniques that can quantitatively evaluate muscle structure and composition, provide insights into the underlying biological basis of the qMRI signal, and illustrate how qMRI biomarkers of muscle health relate to function in healthy and diseased/injured muscles. While some applications still require systematic clinical validation, qMRI is now established as a comprehensive technique, that can be used to characterize a wide variety of structural and compositional changes in healthy and diseased skeletal muscle. Taken together, multiparametric muscle MRI holds great potential in the diagnosis and monitoring of muscle conditions in research and clinical applications. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.

[Formula: see text] Field inhomogeneity correction for qDESS [Formula: see text] mapping: application to rapid bilateral knee imaging.

PURPOSE: [Formula: see text] mapping is a powerful tool for studying osteoarthritis (OA) changes and bilateral imaging may be useful in investigating the role of between-knee asymmetry in OA onset and progression. The quantitative double-echo in steady-state (qDESS) can provide fast simultaneous bilateral knee [Formula: see text] and high-resolution morphometry for cartilage and meniscus. The qDESS uses an analytical signal model to compute [Formula: see text] relaxometry maps, which require knowledge of the flip angle (FA). In the presence of [Formula: see text] inhomogeneities, inconsistencies between the nominal and actual FA can affect the accuracy of [Formula: see text] measurements. We propose a pixel-wise [Formula: see text] correction method for qDESS [Formula: see text] mapping exploiting an auxiliary [Formula: see text] map to compute the actual FA used in the model. METHODS: The technique was validated in a phantom and in vivo with simultaneous bilateral knee imaging. [Formula: see text] measurements of femoral cartilage (FC) of both knees of six healthy participants were repeated longitudinally to investigate the association between [Formula: see text] variation and [Formula: see text]. RESULTS: The results showed that applying the [Formula: see text] correction mitigated [Formula: see text] variations that were driven by [Formula: see text] inhomogeneities. Specifically, [Formula: see text] left-right symmetry increased following the [Formula: see text] correction ([Formula: see text] = 0.74 > [Formula: see text] = 0.69). Without the [Formula: see text] correction, [Formula: see text] values showed a linear dependence with [Formula: see text]. The linear coefficient decreased using the [Formula: see text] correction (from 24.3 ± 1.6 ms to 4.1 ± 1.8) and the correlation was not statistically significant after the application of the Bonferroni correction (p value > 0.01). CONCLUSION: The study showed that [Formula: see text] correction could mitigate variations driven by the sensitivity of the qDESS [Formula: see text] mapping method to [Formula: see text], therefore, increasing the sensitivity to detect real biological changes. The proposed method may improve the robustness of bilateral qDESS [Formula: see text] mapping, allowing for an accurate and more efficient evaluation of OA pathways and pathophysiology through longitudinal and cross-sectional studies.

Early MRI-based quantitative outcomes are associated with a positive functional performance trajectory from 6 to 24 months post-ACL surgery.

PURPOSE: Quantitative magnetic resonance imaging (qMRI) has been used to determine the failure properties of ACL grafts and native ACL repairs and/or restorations. How these properties relate to future clinical, functional, and patient-reported outcomes remain unknown. The study objective was to investigate the relationship between non-contemporaneous qMRI measures and traditional outcome measures following Bridge-Enhanced ACL Restoration (BEAR). It was hypothesized that qMRI parameters at 6 months would be associated with clinical, functional, and/or patient-reported outcomes at 6 months, 24 months, and changes from 6 to 24 months post-surgery. METHODS: Data of BEAR patients (n = 65) from a randomized control trial of BEAR versus ACL reconstruction (BEAR II Trial; NCT02664545) were utilized retrospectively for the present analysis. Images were acquired using the Constructive Interference in Steady State (CISS) sequence at 6 months post-surgery. Single-leg hop test ratios, arthrometric knee laxity values, and International Knee Documentation Committee (IKDC) subjective scores were determined at 6 and 24 months post-surgery. The associations between traditional outcomes and MRI measures of normalized signal intensity, mean cross-sectional area (CSA), volume, and estimated failure load of the healing ACL were evaluated based on bivariate correlations and multivariable regression analyses, which considered the potential effects of age, sex, and body mass index. RESULTS: CSA (r = 0.44, p = 0.01), volume (r = 0.44, p = 0.01), and estimated failure load (r = 0.48, p = 0.01) at 6 months were predictive of the change in single-leg hop ratio from 6 to 24 months in bivariate analysis. CSA (ßstandardized = 0.42, p = 0.01), volume (ßstandardized = 0.42, p = 0.01), and estimated failure load (ßstandardized = 0.48, p = 0.01) remained significant predictors when considering the demographic variables. No significant associations were observed between MRI variables and either knee laxity or IKDC when adjusting for demographic variables. Signal intensity was also not significant at any timepoint. CONCLUSION: The qMRI-based measures of CSA, volume, and estimated failure load were predictive of a positive functional outcome trajectory from 6 to 24 months post-surgery. These variables measured using qMRI at 6 months post-surgery could serve as prospective markers of the functional outcome trajectory from 6 to 24 months post-surgery, aiding in rehabilitation programming and return-to-sport decisions to improve surgical outcomes and reduce the risk of reinjury. LEVEL OF EVIDENCE: Level II.

Myeloarchitectonic plasticity in elite golf players' brains.

Human neuroimaging studies have demonstrated that exercise influences the cortical structural plasticity as indexed by gray or white matter volume. It remains elusive, however, whether exercise affects cortical changes at the finer-grained myelination structure level. To answer this question, we scanned 28 elite golf players in comparison with control participants, using a novel neuroimaging technique-quantitative magnetic resonance imaging (qMRI). The data showed myeloarchitectonic plasticity in the left temporal pole of the golf players: the microstructure of this brain region of the golf players was better proliferated than that of control participants. In addition, this myeloarchitectonic plasticity was positively related to golfing proficiency. Our study has manifested that myeloarchitectonic plasticity could be induced by exercise, and thus, shed light on the potential benefits of exercise on brain health and cognitive enhancement.

Vendor-neutral sequences and fully transparent workflows improve inter-vendor reproducibility of quantitative MRI.

PURPOSE: We developed an end-to-end workflow that starts with a vendor-neutral acquisition and tested the hypothesis that vendor-neutral sequences decrease inter-vendor variability of T1, magnetization transfer ratio (MTR), and magnetization transfer saturation-index (MTsat) measurements. METHODS: We developed and deployed a vendor-neutral 3D spoiled gradient-echo (SPGR) sequence on three clinical scanners by two MRI vendors. We then acquired T1 maps on the ISMRM-NIST system phantom, as well as T1, MTR, and MTsat maps in three healthy participants. We performed hierarchical shift function analysis in vivo to characterize the differences between scanners when the vendor-neutral sequence is used instead of commercial vendor implementations. Inter-vendor deviations were compared for statistical significance to test the hypothesis. RESULTS: In the phantom, the vendor-neutral sequence reduced inter-vendor differences from 8% to 19.4% to 0.2% to 5% with an overall accuracy improvement, reducing ground truth T1 deviations from 7% to 11% to 0.2% to 4%. In vivo, we found that the variability between vendors is significantly reduced (p = 0.015) for all maps (T1, MTR, and MTsat) using the vendor-neutral sequence. CONCLUSION: We conclude that vendor-neutral workflows are feasible and compatible with clinical MRI scanners. The significant reduction of inter-vendor variability using vendor-neutral sequences has important implications for qMRI research and for the reliability of multicenter clinical trials.

MULTI-parametric MR imaging with fLEXible design (MULTIPLEX).

PURPOSE: To introduce a gradient echo (GRE) -based method, namely MULTIPLEX, for single-scan 3D multi-parametric MRI with high resolution, signal-to-noise ratio (SNR), accuracy, efficiency, and acquisition flexibility. THEORY: With a comprehensive design with dual-repetition time (TR), dual flip angle (FA), multi-echo, and optional flow modulation features, the MULTIPLEX signals contain information on radiofrequency (RF) B1t fields, proton density, T1 , susceptibility and blood flows, facilitating multiple qualitative images and parametric maps. METHODS: MULTIPLEX was evaluated on system phantom and human brains, via visual inspection for image contrasts and quality or quantitative evaluation via simulation, phantom scans and literature comparison. Region-of-interest (ROI) analysis was performed on parametric maps of the system phantom and brain scans, extracting the mean and SD of the T1 , T2∗ , proton density (PD), and/or quantitative susceptibility mapping (QSM) values for comparison with reference values or literature. RESULTS: One MULTIPLEX scan offers multiple sets of images, including but not limited to: composited PDW/T1 W/ T2∗ W, aT1 W, SWI, MRA (optional), B1t map, T1 map, T2∗ / R2∗ maps, PD map, and QSM. The quantitative error of phantom T1 , T2∗ and PD mapping were <5%, and those in brain scans were in good agreement with literature. MULTIPLEX scan times for high resolution (0.68 × 0.68 × 2 mm3 ) whole brain coverage were about 7.5 min, while processing times were <1 min. With flow modulation, additional MRA images can be obtained without affecting the quality or accuracy of other images. CONCLUSION: The proposed MUTLIPLEX method possesses great potential for multi-parametric MR imaging.

Correcting inter-scan motion artifacts in quantitative R1 mapping at 7T.

PURPOSE: Inter-scan motion is a substantial source of error in R1 estimation methods based on multiple volumes, for example, variable flip angle (VFA), and can be expected to increase at 7T where B1 fields are more inhomogeneous. The established correction scheme does not translate to 7T since it requires a body coil reference. Here we introduce two alternatives that outperform the established method. Since they compute relative sensitivities they do not require body coil images. THEORY: The proposed methods use coil-combined magnitude images to obtain the relative coil sensitivities. The first method efficiently computes the relative sensitivities via a simple ratio; the second by fitting a more sophisticated generative model. METHODS: R1 maps were computed using the VFA approach. Multiple datasets were acquired at 3T and 7T, with and without motion between the acquisition of the VFA volumes. R1 maps were constructed without correction, with the proposed corrections, and (at 3T) with the previously established correction scheme. The effect of the greater inhomogeneity in the transmit field at 7T was also explored by acquiring B1+ maps at each position. RESULTS: At 3T, the proposed methods outperform the baseline method. Inter-scan motion artifacts were also reduced at 7T. However, at 7T reproducibility only converged on that of the no motion condition if position-specific transmit field effects were also incorporated. CONCLUSION: The proposed methods simplify inter-scan motion correction of R1 maps and are applicable at both 3T and 7T, where a body coil is typically not available. The open-source code for all methods is made publicly available.

Circumventing the curse of dimensionality in magnetic resonance fingerprinting through a deep learning approach.

Magnetic resonance fingerprinting (MRF) is a rapidly developing approach for fast quantitative MRI. A typical drawback of dictionary-based MRF is an explosion of the dictionary size as a function of the number of reconstructed parameters, according to the "curse of dimensionality", which determines an explosion of resource requirements. Neural networks (NNs) have been proposed as a feasible alternative, but this approach is still in its infancy. In this work, we design a deep learning approach to MRF using a fully connected network (FCN). In the first part we investigate, by means of simulations, how the NN performance scales with the number of parameters to be retrieved in comparison with the standard dictionary approach. Four MRF sequences were considered: IR-FISP, bSSFP, IR-FISP-B1 , and IR-bSSFP-B1 , the latter two designed to be more specific for B1+ parameter encoding. Estimation accuracy, memory usage, and computational time required to perform the estimation task were considered to compare the scalability capabilities of the dictionary-based and the NN approaches. In the second part we study optimal training procedures by including different data augmentation and preprocessing strategies during training to achieve better accuracy and robustness to noise and undersampling artifacts. The study is conducted using the IR-FISP MRF sequence exploiting both simulations and in vivo acquisitions. Results demonstrate that the NN approach outperforms the dictionary-based approach in terms of scalability capabilities. Results also allow us to heuristically determine the optimal training strategy to make an FCN able to predict T1 , T2 , and M0 maps that are in good agreement with those obtained with the original dictionary approach. k-SVD denoising is proposed and found to be critical as a preprocessing step to handle undersampled data.