A theoretical framework to investigate the effect of high permittivity materials in MRI using anatomy-mimicking cylinders.

PURPOSE: Recent numerical and empirical results proved that high permittivity materials (HPM) used in pads placed near the subject or directly integrated with coils can increase the SNR and reduce the specific absorption rate (SAR) in MRI. In this paper, we propose an analytical investigation of the effect on the magnetic field distribution of a layer of HPM surrounding an anatomy-mimicking cylindrical sample. METHODS: The study is based on a reformulation of the Mie scattering for cylindrical geometry, following an approach recently introduced for spherical samples. The total field in each medium is decomposed in terms of inward and outward electromagnetic waves, and the fields are expressed as series of cylindrical harmonics, whose coefficients can be interpreted as classical reflection and transmission coefficients. RESULTS: Our new formulation allows a quantitative evaluation of the effect of the HPM layer for varying permittivity and thickness, and it provides an intuitive understanding of such effect in terms of propagation and scattering of the RF field. CONCLUSION: We show how HPM can filter out the modes that only contribute to the noise or RF power deposition, resulting in higher SNR or lower SAR, respectively. Our proposed framework provides physical insight on how to properly design HPM for MRI applications.

Fat suppression using frequency-sweep RF saturation and iterative reconstruction.

PURPOSE: To introduce an alternative idea for fat suppression that is suited both for low-field applications where conventional fat-suppression approaches become ineffective due to narrow spectral separation and for applications with strong B0 homogeneities. METHODS: Separation of fat and water is achieved by sweeping the frequency of RF saturation pulses during continuous radial acquisition and calculating frequency-resolved images using regularized iterative reconstruction. Voxel-wise signal-response curves are extracted that reflect tissue's response to RF saturation at different frequencies and allow the classification into fat or water. This information is then utilized to generate water-only composite images. The principle is demonstrated in free-breathing abdominal and neck examinations using stack-of-stars 3D balanced SSFP (bSSFP) and gradient-recalled echo (GRE) sequences at 0.55 and 3T. Moreover, a potential extension toward quantitative fat/water separation is described. RESULTS: Experiments with a proton density fat fraction (PDFF) phantom validated the reliability of fat/water separation using signal-response curves. As demonstrated for abdominal imaging at 0.55T, the approach resulted in more uniform fat suppression without loss of water signal and in improved CSF-to-fat signal ratio. Moreover, the approach provided consistent fat suppression in 3T neck exams where conventional spectrally-selective fat saturation failed due to strong local B0 inhomogeneities. The feasibility of simultaneous fat/water quantification has been demonstrated in a PDFF phantom. CONCLUSION: The proposed principle achieves reliable fat suppression in low-field applications and adapts to high-field applications with strong B0 inhomogeneity. Moreover, the principle potentially provides a basis for developing an alternative approach for PDFF quantification.

Performance of receive head arrays versus ultimate intrinsic SNR at 7 T and 10.5 T.

PURPOSE: We examined magnetic field dependent SNR gains and ability to capture them with multichannel receive arrays for human head imaging in going from 7 T, the most commonly used ultrahigh magnetic field (UHF) platform at the present, to 10.5 T, which represents the emerging new frontier of >10 T in UHFs. METHODS: Electromagnetic (EM) models of 31-channel and 63-channel multichannel arrays built for 10.5 T were developed for 10.5 T and 7 T simulations. A 7 T version of the 63-channel array with an identical coil layout was also built. Array performance was evaluated in the EM model using a phantom mimicking the size and electrical properties of the human head and a digital human head model. Experimental data was obtained at 7 T and 10.5 T with the 63-channel array. Ultimate intrinsic SNR (uiSNR) was calculated for the two field strengths using a voxelized cloud of dipoles enclosing the phantom or the digital human head model as a reference to assess the performance of the two arrays and field depended SNR gains. RESULTS: uiSNR calculations in both the phantom and the digital human head model demonstrated SNR gains at 10.5 T relative to 7 T of 2.6 centrally, ˜2 at the location corresponding to the edge of the brain, ˜1.4 at the periphery. The EM models demonstrated that, centrally, both arrays captured ˜90% of the uiSNR at 7 T, but only ˜65% at 10.5 T, leading only to ˜2-fold gain in array SNR in going from 7 to 10.5 T. This trend was also observed experimentally with the 63-channel array capturing a larger fraction of the uiSNR at 7 T compared to 10.5 T, although the percentage of uiSNR captured were slightly lower at both field strengths compared to EM simulation results. CONCLUSIONS: Major uiSNR gains are predicted for human head imaging in going from 7 T to 10.5 T, ranging from ˜2-fold at locations corresponding to the edge of the brain to 2.6-fold at the center, corresponding to approximately quadratic increase with the magnetic field. Realistic 31- and 63-channel receive arrays, however, approach the central uiSNR at 7 T, but fail to do so at 10.5 T, suggesting that more coils and/or different type of coils will be needed at 10.5 T and higher magnetic fields.

Deep-Learning-Based Contrast Synthesis From MRF Parameter Maps in the Knee Joint.

BACKGROUND: Magnetic resonance fingerprinting (MRF) is a method to speed up acquisition of quantitative MRI data. However, MRF does not usually produce contrast-weighted images that are required by radiologists, limiting reachable total scan time improvement. Contrast synthesis from MRF could significantly decrease the imaging time. PURPOSE: To improve clinical utility of MRF by synthesizing contrast-weighted MR images from the quantitative data provided by MRF, using U-nets that were trained for the synthesis task utilizing L1- and perceptual loss functions, and their combinations. STUDY TYPE: Retrospective. POPULATION: Knee joint MRI data from 184 subjects from Northern Finland 1986 Birth Cohort (ages 33-35, gender distribution not available). FIELD STRENGTH AND SEQUENCE: A 3 T, multislice-MRF, proton density (PD)-weighted 3D-SPACE (sampling perfection with application optimized contrasts using different flip angle evolution), fat-saturated T2-weighted 3D-space, water-excited double echo steady state (DESS). ASSESSMENT: Data were divided into training, validation, test, and radiologist's assessment sets in the following way: 136 subjects to training, 3 for validation, 3 for testing, and 42 for radiologist's assessment. The synthetic and target images were evaluated using 5-point Likert scale by two musculoskeletal radiologists blinded and with quantitative error metrics. STATISTICAL TESTS: Friedman's test accompanied with post hoc Wilcoxon signed-rank test and intraclass correlation coefficient. The statistical cutoff P <0.05 adjusted by Bonferroni correction as necessary was utilized. RESULTS: The networks trained in the study could synthesize conventional images with high image quality (Likert scores 3-4 on a 5-point scale). Qualitatively, the best synthetic images were produced with combination of L1- and perceptual loss functions and perceptual loss alone, while L1-loss alone led to significantly poorer image quality (Likert scores below 3). The interreader and intrareader agreement were high (0.80 and 0.92, respectively) and significant. However, quantitative image quality metrics indicated best performance for the pure L1-loss. DATA CONCLUSION: Synthesizing high-quality contrast-weighted images from MRF data using deep learning is feasible. However, more studies are needed to validate the diagnostic accuracy of these synthetic images. EVIDENCE LEVEL: 4. TECHNICAL EFFICACY: Stage 1.

Twenty-four-channel high-impedance glove array for hand and wrist MRI at 3T.

PURPOSE: To present a novel 3T 24-channel glove array that enables hand and wrist imaging in varying postures. METHODS: The glove array consists of an inner glove holding the electronics and an outer glove protecting the components. The inner glove consists of four main structures: palm, fingers, wrist, and a flap that rolls over on top. Each structure was constructed out of three layers: a layer of electrostatic discharge flame-resistant fabric, a layer of scuba neoprene, and a layer of mesh fabric. Lightweight and flexible high impedance coil (HIC) elements were inserted into dedicated tubes sewn into the fabric. Coil elements were deliberately shortened to minimize the matching interface. Siemens Tim 4G technology was used to connect all 24 HIC elements to the scanner with only one plug. RESULTS: The 24-channel glove array allows large motion of both wrist and hand while maintaining the SNR needed for high-resolution imaging. CONCLUSION: In this work, a purpose-built 3T glove array that embeds 24 HIC elements is demonstrated for both hand and wrist imaging. The 24-channel glove array allows a great range of motion of both the wrist and hand while maintaining a high SNR and providing good theoretical acceleration performance, thus enabling hand and wrist imaging at different postures to extract kinematic information.

Novel Numerical Basis Sets for Electromagnetic Field Expansion in Arbitrary Inhomogeneous Objects.

We investigated how to construct low-order subspace basis sets to accurately represent electromagnetic fields generated within inhomogeneous arbitrary objects by radio-frequency sources external to a Huygen's surface. The basis generation relies on the singular value decomposition of Green's functions integro-differential operators which makes it feasible to derive a reduced-order yet stable model. We present a detailed study of the theoretical and numerical requisites for generating such basis, and show how it can be used to calculate performance limits in magnetic resonance imaging applications. Finally, we propose a novel numerical framework for the computation of characteristic modes of arbitrary inhomogeneous objects. We validated accuracy and convergence properties of the numerical basis against a complete analytical basis in the case of a uniform spherical object. We showed that the discretization of the Huygens's surface has a minimal effect on the accuracy of the calculations, which mainly depended on the electromagnetic solver resolution and order of approximation.

Compression of volume-surface integral equation matrices via Tucker decomposition for magnetic resonance applications.

In this work, we propose a method for the compression of the coupling matrix in volume-surface integral equation (VSIE) formulations. VSIE methods are used for electromagnetic analysis in magnetic resonance imaging (MRI) applications, for which the coupling matrix models the interactions between the coil and the body. We showed that these effects can be represented as independent interactions between remote elements in 3D tensor formats, and subsequently decomposed with the Tucker model. Our method can work in tandem with the adaptive cross approximation technique to provide fast solutions of VSIE problems. We demonstrated that our compression approaches can enable the use of VSIE matrices of prohibitive memory requirements, by allowing the effective use of modern graphical processing units (GPUs) to accelerate the arising matrix-vector products. This is critical to enable numerical MRI simulations at clinical voxel resolutions in a feasible computation time. In this paper, we demonstrate that the VSIE matrix-vector products needed to calculate the electromagnetic field produced by an MRI coil inside a numerical body model with 1 mm3 voxel resolution, could be performed in ~ 33 seconds in a GPU, after compressing the associated coupling matrix from ~ 80 TB to ~ 43 MB.

Effect of radiofrequency shield diameter on signal-to-noise ratio at ultra-high field MRI.

PURPOSE: In this work, we investigated how the position of the radiofrequency (RF) shield can affect the signal-to-noise ratio (SNR) of a receive RF coil. Our aim was to obtain physical insight for the design of a 10.5T 32-channel head coil, subject to the constraints on the diameter of the RF shield imposed by the head gradient coil geometry. METHOD: We used full-wave numerical simulations to investigate how the SNR of an RF receive coil depends on the diameter of the RF shield at ultra-high magnetic field (UHF) strengths (≥7T). RESULTS: Our simulations showed that there is an SNR-optimal RF shield size at UHF strength, whereas at low field the SNR monotonically increases with the shield diameter. For a 32-channel head coil at 10.5T, an optimally sized RF shield could act as a cylindrical waveguide and increase the SNR in the brain by 27% compared to moving the shield as far as possible from the coil. Our results also showed that a separate transmit array between the RF shield and the receive array could considerably reduce SNR even if they are decoupled. CONCLUSION: At sufficiently high magnetic field strength, the design of local RF coils should be optimized together with the design of the RF shield to benefit from both near field and resonant modes.

Displacement current distribution on a high dielectric constant helmet and its effect on RF field at 10.5 T (447 MHz).

PURPOSE: Investigating the designs and effects of high dielectric constant (HDC) materials in the shape of a conformal helmet on the enhancement of RF field and reduction of specific absorption rate at 10.5 T for human brain studies. METHODS: A continuous and a segmented four-piece HDC helmet fit to a human head inside an eight-channel fractionated-dipole array were constructed and studied with a phantom and a human head model using computer electromagnetic simulations. The simulated transmit efficiency and receive sensitivity were experimentally validated using a phantom with identical electric properties and helmet-coil configurations of the computer model. The temporal and spatial distributions of displacement currents on the HDC helmets were analyzed. RESULTS: Using the continuous HDC helmet, simulation results in the human head model demonstrated an average transmit efficiency enhancement of 66%. A propagating displacement current was induced on the continuous helmet, leading to an inhomogeneous RF field enhancement in the brain. Using the segmented four-piece helmet design to reduce this effect, an average 55% and 57% enhancement in the transmit efficiency and SNR was achieved in human head, respectively, along with 8% and 28% reductions in average and maximum local specific absorption rate. CONCLUSION: The HDC helmets enhanced the transmit efficiency and SNR of the dipole array coil in the human head at 10.5 T. The segmentation of the helmet to disrupt the continuity of circumscribing displacement currents in the helmet produced a more uniform distribution of the transmit field and lower specific absorption rate in the human head compared with the continuous helmet design.

Seeking a Widely Adoptable Practical Standard to Estimate Signal-to-Noise Ratio in Magnetic Resonance Imaging for Multiple-Coil Reconstructions.

BACKGROUND: Signal-to-noise ratio (SNR) is used to evaluate the performance of magnetic resonance (MR) imaging systems. Accurate and consistent estimations are needed to routinely use SNR to assess coils and image reconstruction techniques. PURPOSE: To identify a reliable and practical method for SNR estimation in multiple-coil reconstructions. STUDY TYPE: Technical evaluation and comparison. SUBJECTS/PHANTOM: A uniform phantom and four healthy volunteers: 35, 38, 39 y/o males, 25 y/o female. FIELD STRENGTH/SEQUENCE: Two-dimensional multislice gradient-echo pulse sequence at 3 T and 7 T. ASSESSMENT: Reference-standard SNR was calculated from 100 multiple replicas. Six SNR methods were compared against it: difference image (DI), analytic array combination (AC), pseudo-multiple-replica (PMR), generalized pseudo-replica (GPR), smoothed image subtraction (SIS), and DI with temporal instability correction (TIC). The assessment was repeated for different multiple-coil reconstructions. STATISTICAL TESTS: SNR methods were evaluated in terms of relative deviation (RD) and normalized mutual information (NMI) with respect to the reference-standard, using a linear regression (0.05 significance level) to assess how different factors affect accuracy. RESULTS: Average RD (phantom) for DI, AC, PMR, GPR, SIS, and TIC was 7.9%, 6%, 6.7%, 10.1%, 40%, and 14.6%, respectively. RD increased with acceleration. SNR maps with AC were the most similar to the reference standard (NMI = 0.358). Considering all brain regions of interest, average RD for all SNR methods varied 96% among volunteers but remained approximately 10% for AC, PMR, and GPR, whereas it was more than 30% for DI, SIS, and TIC. RD was mainly affected by image reconstruction (beta = 12) for AC and SNR entropy for SIS (beta = 19). DATA CONCLUSION: AC provided accurate and robust SNR estimation. PMR and GPR are more generally applicable than AC. DI and TIC should be used only at low acceleration factors, when an additional noise-only scan cannot be acquired. SIS is a single-acquisition alternative to DI for generalized autocalibrating partial parallel acquisition (GRAPPA) reconstructions. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 1.

Magnetization transfer in magnetic resonance fingerprinting.

PURPOSE: To study the effects of magnetization transfer (MT, in which a semi-solid spin pool interacts with the free pool), in the context of magnetic resonance fingerprinting (MRF). METHODS: Simulations and phantom experiments were performed to study the impact of MT on the MRF signal and its potential influence on T1 and T2 estimation. Subsequently, an MRF sequence implementing off-resonance MT pulses and a dictionary with an MT dimension, generated by incorporating a two-pool model, were used to estimate the fractional pool size in addition to the B1+ , T1 , and T2 values. The proposed method was evaluated in the human brain. RESULTS: Simulations and phantom experiments showed that an MRF signal obtained from a cross-linked bovine serum sample is influenced by MT. Using a dictionary based on an MT model, a better match between simulations and acquired MR signals can be obtained (NRMSE 1.3% vs. 4.7%). Adding off-resonance MT pulses can improve the differentiation of MT from T1 and T2 . In vivo results showed that MT affects the MRF signals from white matter (fractional pool-size ~16%) and gray matter (fractional pool-size ~10%). Furthermore, longer T1 (~1060 ms vs. ~860 ms) and T2 values (~47 ms vs. ~35 ms) can be observed in white matter if MT is accounted for. CONCLUSION: Our experiments demonstrated a potential influence of MT on the quantification of T1 and T2 with MRF. A model that encompasses MT effects can improve the accuracy of estimated relaxation parameters and allows quantification of the fractional pool size.

A formalism to investigate the optimal transmit efficiency in radiofrequency shimming.

Transmit efficiency specifies the amplitude of the magnetic resonance excitation field produced over a region of interest with respect to the radiofrequency (RF) power deposited in the sample. This metric is highly important at ultra-high field magnetic resonance imaging (≥7 T), where excitation inhomogeneities and electric field interference effects could prevent achieving the desired flip angle distribution while satisfying the power safety limits. The aim of this work was to introduce an approach to calculate a theoretical upper bound on the transmit efficiency (OPTXE) for RF shimming, independent from any particular coil design. We computed the OPTXE for head-mimicking uniform spherical samples and a realistic heterogeneous head model by maximizing the square of the net transmit field per unit power deposition. The corresponding RF shimming weights were used to combine the analytical surface current modes into ideal current patterns. OPTXE grew monotonically as the target excitation voxel approached the surface of the object, and overall decreased at higher field strengths, presenting similar trends in both the uniform sphere and heterogeneous head model. Arrays with an increasing number of loops could closely approach OPTXE in the central region of the object, but performance decreased closer to the surface and at higher magnetic field strengths. The performance of 32 loops for a two-dimensional excitation region at 7 T increased from 34% to 93% when they were arranged based on the shape of the ideal current patterns. OPTXE provides an absolute reference to evaluate coil designs and RF shimming algorithms, whereas ideal current patterns could serve as guidelines for novel coil designs at ultra-high field. The uniform sphere model enables rapid analytic simulations and provides a good approximation of the OPTXE distribution in a realistic heterogeneous head model with comparable dimensions.

The "Loopole" Antenna: A Hybrid Coil Combining Loop and Electric Dipole Properties for Ultra-High-Field MRI.

PURPOSE: To revisit the "loopole," an unusual coil topology whose unbalanced current distribution captures both loop and electric dipole properties, which can be advantageous in ultra-high-field MRI. METHODS: Loopole coils were built by deliberately breaking the capacitor symmetry of traditional loop coils. The corresponding current distribution, transmit efficiency, and signal-to-noise ratio (SNR) were evaluated in simulation and experiments in comparison to those of loops and electric dipoles at 7 T (297 MHz). RESULTS: The loopole coil exhibited a hybrid current pattern, comprising features of both loops and electric dipole current patterns. Depending on the orientation relative to B0, the loopole demonstrated significant performance boost in either the transmit efficiency or SNR at the center of a dielectric sample when compared to a traditional loop. Modest improvements were observed when compared to an electric dipole. CONCLUSION: The loopole can achieve high performance by supporting both divergence-free and curl-free current patterns, which are both significant contributors to the ultimate intrinsic performance at ultra-high field. While electric dipoles exhibit similar hybrid properties, loopoles maintain the engineering advantages of loops, such as geometric decoupling and reduced resonance frequency dependence on sample loading.

Disentangling the effects of high permittivity materials on signal optimization and sample noise reduction via ideal current patterns.

PURPOSE: To investigate how high-permittivity materials (HPMs) can improve SNR when placed between MR detectors and the imaged body. METHODS: We used a simulation framework based on dyadic Green's functions to calculate the electromagnetic field inside a uniform dielectric sphere at 7 Tesla, with and without a surrounding layer of HPM. SNR-optimizing (ideal) current patterns were expressed as the sum of signal-optimizing (signal-only) current patterns and dark mode current patterns that minimize sample noise while contributing nothing to signal. We investigated how HPM affects the shape and amplitude of these current patterns, sample noise, and array SNR. RESULTS: Ideal and signal-only current patterns were identical for a central voxel. HPMs introduced a phase shift into these patterns, compensating for signal propagation delay in the HPMs. For an intermediate location within the sphere, dark mode current patterns were present and illustrated the mechanisms by which HPMs can reduce sample noise. High-amplitude signal-only current patterns were observed for HPM configurations that shield the electromagnetic field from the sample. For coil arrays, these configurations corresponded to poor SNR in deep regions but resulted in large SNR gains near the surface due to enhanced fields in the vicinity of the HPM. For very high relative permittivity values, HPM thicknesses corresponding to even multiples of λ/4 resulted in coil SNR gains throughout the sample. CONCLUSION: HPMs affect both signal sensitivity and sample noise. Lower amplitude signal-only optimal currents corresponded to higher array SNR performance and could guide the design of coils integrated with HPM.

Size-adaptable "Trellis" structure for tailored MRI coil arrays.

PURPOSE: We present a novel, geometrically adjustable, receive coil array whose diameter can be tailored to the subject in order to maximize sensitivity for a range of body sizes. THEORY AND METHODS: A key mechanical feature of the size-adaptable receive array is its trellis structure that was motivated by similar structures found in gardening and fencing. Our implementation is a cylindrical trellis that features encircling, diagonally interleaved slats, which are linked together at intersecting points. The ensemble allows expansion or contraction to be controlled with the angle between the slats. This mechanical frame provides a base for radiofrequency coils wherein approximately constant overlap, and therefore coupling between adjacent elements, is maintained when the trellis is expanded or contracted. We demonstrate 2 trellis coil concepts for imaging lower extremity at 3T: a single-row 8-channel array built on a trellis support structure and a multirow 24-channel array in which the coil elements themselves form the trellis structure. RESULTS: We show that the adjustable trellis array can accommodate a range of subject sizes with robust signal-to-noise ratio, loading, and coupling. CONCLUSION: The trellis coil concept enables an array of surface coils to expand and contract with negligible effect on tuning, matching, and decoupling. This allows an encircling array to conform closely to anatomy of various sizes, which provides significant gains in signal-to-noise ratio.

Optimized quantification of spin relaxation times in the hybrid state.

PURPOSE: The optimization and analysis of spin ensemble trajectories in the hybrid state-a state in which the direction of the magnetization adiabatically follows the steady state while the magnitude remains in a transient state. METHODS: Numerical optimizations were performed to find spin ensemble trajectories that minimize the Cramér-Rao bound for T1 -encoding, T2 -encoding, and their weighted sum, respectively, followed by a comparison between the Cramér-Rao bounds obtained with our optimized spin-trajectories, Look-Locker sequences, and multi-spin-echo methods. Finally, we experimentally tested our optimized spin trajectories with in vivo scans of the human brain. RESULTS: After a nonrecurring inversion segment on the southern half of the Bloch sphere, all optimized spin trajectories pursue repetitive loops on the northern hemisphere in which the beginning of the first and the end of the last loop deviate from the others. The numerical results obtained in this work align well with intuitive insights gleaned directly from the governing equation. Our results suggest that hybrid-state sequences outperform traditional methods. Moreover, hybrid-state sequences that balance T1 - and T2 -encoding still result in near optimal signal-to-noise efficiency for each relaxation time. Thus, the second parameter can be encoded at virtually no extra cost. CONCLUSIONS: We provided new insights into the optimal encoding processes of spin relaxation times in order to guide the design of robust and efficient pulse sequences. We found that joint acquisitions of T1 and T2 in the hybrid state are substantially more efficient than sequential encoding techniques.

Rapid Radial T1 and T2 Mapping of the Hip Articular Cartilage With Magnetic Resonance Fingerprinting.

BACKGROUND: Quantitative MRI can detect early changes in cartilage biochemical components, but its routine clinical implementation is challenging. PURPOSE: To introduce a novel technique to measure T1 and T2 along radial sections of the hip for accurate and reproducible multiparametric quantitative cartilage assessment in a clinically feasible scan time. STUDY TYPE: Reproducibility, technical validation. SUBJECTS/PHANTOM: A seven-compartment phantom and three healthy volunteers. FIELD STRENGTH/SEQUENCE: A novel MR pulse sequence that simultaneously measures proton density (PD), T1 , and T2 at 3 T was developed. Automatic positioning and semiautomatic cartilage segmentation were implemented to improve consistency and simplify workflow. ASSESSMENT: Intra- and interscanner variability of our technique was assessed over multiple scans on three different MR scanners. STATISTICAL TESTS: For each scan, the median of cartilage T1 and T2 over six radial slices was calculated. Restricted maximum likelihood estimation of variance components was used to estimate intrasubject variances reflecting variation between results from the two scans using the same scanner (intrascanner variance) and variation among results from the three scanners (interscanner variance). RESULTS: The estimation error for T1 and T2 with respect to reference standard measurements was less than 3% on average for the phantom. The average interscanner coefficient of variation was 1.5% (1.2-1.9%) and 0.9% (0.0-3.7%) for T1 and T2 , respectively, in the seven compartments of the phantom. Total scan time in vivo was 7:13 minutes to obtain PD, T1 , and T2 maps along six radial hip sections at 0.6 × 0.6 × 4.0 mm3 voxel resolution. Interscanner variability for the in vivo study was 1.99% and 5.46% for T1 and T2 , respectively. in vivo intrascanner variability was 1.15% for T1 and 3.24% for T2 . DATA CONCLUSION: Our method, which includes slice positioning, model-based parameter estimation, and cartilage segmentation, is highly reproducible. It could enable employing quantitative hip cartilage evaluation for longitudinal and multicenter studies. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:810-815.

Recommendations towards standards for quantitative MRI (qMRI) and outstanding needs.

LEVEL OF EVIDENCE: 5 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2019.

An analytic expression for the ultimate intrinsic SNR in a uniform sphere.

PURPOSE: The ultimate intrinsic signal-to-noise ratio (UISNR) is normally calculated using electrodynamic simulations with a complete basis of modes. Here, we provide an exact solution for the UISNR at the center of a dielectric sphere and assess how accurately this solution approximates UISNR away from the center. METHODS: We performed a mode analysis to determine which modes contribute to central UISNR - ζ(r→0). We then derived an analytic expression to calculate ζ(r→0) and analyzed its dependence on main magnetic field strength, sample geometry, and electrical properties. We validated the proposed solution against an established method based on dyadic Green's function simulations. RESULTS: Only one divergence-free mode contributes to ζ(r→0). The UISNR given by the exact solution matched the full simulation results for various parameter settings, whereas calculation speed was approximately 1000 times faster. We showed that the analytic expression can approximate the UISNR with <5% error at positions as much as 10-20% of the radius away from the center. CONCLUSION: The proposed formula enables rapid and direct calculation of UISNR in the central region of a sphere. The resulting UISNR value may be used, for example, as an absolute reference to assess the performance of head coils with spherical phantoms.

Low rank alternating direction method of multipliers reconstruction for MR fingerprinting.

PURPOSE: The proposed reconstruction framework addresses the reconstruction accuracy, noise propagation and computation time for magnetic resonance fingerprinting. METHODS: Based on a singular value decomposition of the signal evolution, magnetic resonance fingerprinting is formulated as a low rank (LR) inverse problem in which one image is reconstructed for each singular value under consideration. This LR approximation of the signal evolution reduces the computational burden by reducing the number of Fourier transformations. Also, the LR approximation improves the conditioning of the problem, which is further improved by extending the LR inverse problem to an augmented Lagrangian that is solved by the alternating direction method of multipliers. The root mean square error and the noise propagation are analyzed in simulations. For verification, in vivo examples are provided. RESULTS: The proposed LR alternating direction method of multipliers approach shows a reduced root mean square error compared to the original fingerprinting reconstruction, to a LR approximation alone and to an alternating direction method of multipliers approach without a LR approximation. Incorporating sensitivity encoding allows for further artifact reduction. CONCLUSION: The proposed reconstruction provides robust convergence, reduced computational burden and improved image quality compared to other magnetic resonance fingerprinting reconstruction approaches evaluated in this study. Magn Reson Med 79:83-96, 2018. © 2017 International Society for Magnetic Resonance in Medicine.