B1 inhomogeneity corrected CEST MRI based on direct saturation removed omega plot model at 5T.

PURPOSE: CEST can image macromolecules/compounds via detecting chemical exchange between labile protons and bulk water. B1 field inhomogeneity impairs CEST quantification. Conventional B1 inhomogeneity correction methods depend on interpolation algorithms, B1 choices, acquisition number or calibration curves, making reliable correction challenging. This study proposed a novel B1 inhomogeneity correction method based on a direct saturation (DS) removed omega plot model. METHODS: Four healthy volunteers underwent B1 field mapping and CEST imaging under four nominal B1 levels of 0.75, 1.0, 1.5, and 2.0 µT at 5T. DS was resolved using a multi-pool Lorentzian model and removed from respective Z spectrum. Residual spectral signals were used to construct the omega plot as a linear function of 1/ B 1 2 $$ {B}_1^2 $$ , from which corrected signals at nominal B1 levels were calculated. Routine asymmetry analysis was conducted to quantify amide proton transfer (APT) effect. Its distribution across white matter was compared before and after B1 inhomogeneity correction and also with the conventional interpolation approach. RESULTS: B1 inhomogeneity yielded conspicuous artifact on APT images. Such artifact was mitigated by the proposed method. Homogeneous APT maps were shown with SD consistently smaller than that before B1 inhomogeneity correction and the interpolation method. Moreover, B1 inhomogeneity correction from two and four CEST acquisitions yielded similar results, superior over the interpolation method that derived inconsistent APT contrasts among different B1 choices. CONCLUSION: The proposed method enables reliable B1 inhomogeneity correction from at least two CEST acquisitions, providing an effective way to improve quantitative CEST MRI.

Analytical corrections for B1 -inhomogeneity and signal decay in multi-slice 2D spiral hyperpolarized 129 Xe MRI using keyhole reconstruction.

PURPOSE: Hyperpolarized xenon MRI suffers from heterogeneous coil bias and magnetization decay that obscure pulmonary abnormalities. Non-physiological signal variability can be mitigated by measuring and mapping the nominal flip angle, and by rescaling the images to correct for signal bias and decay. While flip angle maps can be calculated from sequentially acquired images, scan time and breath-hold duration are doubled. Here, we exploit the low-frequency oversampling of 2D-spiral and keyhole reconstruction to measure flip angle maps from a single acquisition. METHODS: Flip angle maps were calculated from two images generated from a single dataset using keyhole reconstructions and a Bloch-equation-based model suitable for hyperpolarized substances. Artifacts resulting from acquisition and reconstruction schemes (e.g., keyhole reconstruction radius, slice-selection profile, spiral-ordering, and oversampling) were assessed using point-spread functions. Simulated flip angle maps generated using keyhole reconstruction were compared against the paired-image approach using RMS error (RMSE). Finally, feasibility was demonstrated for in vivo xenon ventilation imaging. RESULTS: Simulations demonstrated accurate flip angle maps and B1 -inhomogeneity correction can be generated with only 1.25-fold central-oversampling and keyhole reconstruction radius = 5% (RMSE = 0.460°). These settings also generated accurate flip angle maps in a healthy control (RSME = 0.337°) and a person with cystic fibrosis (RMSE = 0.404°) in as little as 3.3 s. CONCLUSION: Regional lung ventilation images with reduced impact of B1 -inhomogeneity can be acquired rapidly by combining 2D-spiral acquisition, Bloch-equation-based modeling, and keyhole reconstruction. This approach will be especially useful for breath-hold studies where short scan durations are necessary, such as dynamic imaging and applications in children or people with severely compromised respiratory function.

B 1 + $$ {\mathrm{B}}_1

PURPOSE: Nuclear Overhauser effect magnetization transfer ratio (NOEMTR ) is a technique used to investigate brain lipids and macromolecules in greater detail than other techniques and benefits from increased contrast at 7 T. However, this contrast can become degraded because of B 1 + $$ {\mathrm{B}}_1^{+} $$ inhomogeneities present at ultra-high field strengths. High-permittivity dielectric pads (DP) have been used to correct for these inhomogeneities via displacement currents generating secondary magnetic fields. The purpose of this work is to demonstrate that dielectric pads can be used to mitigate B 1 + $$ {\mathrm{B}}_1^{+} $$ inhomogeneities and improve NOEMTR contrast in the temporal lobes at 7 T. METHODS: Partial 3D NOEMTR contrast images and whole brain B 1 + $$ {\mathrm{B}}_1^{+} $$ field maps were acquired on a 7 T MRI across six healthy subjects. Calcium titanate DP, having a relative permittivity of 110, was placed next to the subject's head near the temporal lobes. Pad corrected NOEMTR images had a separate postprocessing linear correction applied. RESULTS: DP provided supplemental B 1 + $$ {\mathrm{B}}_1^{+} $$ to the temporal lobes while also reducing the B 1 + $$ {\mathrm{B}}_1^{+} $$ magnitude across the posterior and superior regions of the brain. This resulted in a statistically significant increase in NOEMTR contrast in substructures of the temporal lobes both with and without linear correction. The padding also produced a convergence in NOEMTR contrast toward approximately equal mean values. CONCLUSION: NOEMTR images showed significant improvement in temporal lobe contrast when DP were used, which resulted from an increase in B 1 + $$ {\mathrm{B}}_1^{+} $$ homogeneity across the entire brain slab. DP-derived improvements in NOEMTR are expected to increase the robustness of the brain substructural measures both in healthy and pathological conditions.

B0 Correction for 3T Amide Proton Transfer (APT) MRI Using a Simplified Two-Pool Lorentzian Model of Symmetric Water and Asymmetric Solutes.

Amide proton transfer (APT)-weighted MRI is a promising molecular imaging technique that has been employed in clinic for detection and grading of brain tumors. MTRasym, the quantification method of APT, is easily influenced by B0 inhomogeneity and causes artifacts. Current model-free interpolation methods have enabled moderate B0 correction for middle offsets, but have performed poorly at limbic offsets. To address this shortcoming, we proposed a practical B0 correction approach that is suitable under time-limited sparse acquisition scenarios and for B1 ≥ 1 µT under 3T. In this study, this approach employed a simplified Lorentzian model containing only two pools of symmetric water and asymmetric solutes, to describe the Z-spectral shape with wide and 'invisible' CEST peaks. The B0 correction was then performed on the basis of the fitted two-pool Lorentzian lines, instead of using conventional model-free interpolation. The approach was firstly evaluated on densely sampled Z-spectra data by using the spline interpolation of all acquired 16 offsets as the gold standard. When only six offsets were available for B0 correction, our method outperformed conventional methods. In particular, the errors at limbic offsets were significantly reduced (n = 8, p < 0.01). Secondly, our method was assessed on the six-offset APT data of nine brain tumor patients. Our MTRasym (3.5 ppm), using the two-pool model, displayed a similar contrast to the vendor-provided B0-orrected MTRasym (3.5 ppm). While the vendor failed in correcting B0 at 4.3 and 2.7 ppm for a large portion of voxels, our method enabled well differentiation of B0 artifacts from tumors. In conclusion, the proposed approach could alleviate analysis errors caused by B0 inhomogeneity, which is useful for facilitating the comprehensive metabolic analysis of brain tumors.

Effect of a lead block on alveolar bone protection in image-guided high-dose-rate interstitial brachytherapy for tongue cancer: using model-based dose calculation algorithms to correct for inhomogeneity.

PURPOSE: The purpose of this study was to evaluate the effect of a lead block for alveolar bone protection in image-guided high-dose-rate interstitial brachytherapy for tongue cancer. MATERIAL AND METHODS: We treated 6 patients and delivered 5,400 cGy in 9 fractions using a lead block. Effects of lead block (median thickness, 4 mm) on dose attenuation by distance were visually examined using TG-43 formalism-based dose distribution curves to determine whether or not the area with the highest dose is located in the alveolar bone, where there is a high-risk of infection. Dose re-calculations were performed using TG-186 formalism with advanced collapsed cone engine (ACE) for inhomogeneity correction set to cortical bone density for the whole mandible and alveolar bone, water density for clinical target volume (CTV), air density for outside body and lead density, and silastic density for lead block and its' silicon replica, respectively. RESULTS: The highest dose was detected outside the alveolar bone in five of the six cases. For dose-volume histogram analysis, median minimum doses delivered per fraction to the 0.1 cm3 of alveolar bone (D0.1cm3 TG-43, ACE-silicon, and ACE-lead) were 344.3 (range, 262.9-427.4) cGy, 336.6 (253.3-425.0) cGy, and 169.7 (114.9-233.3) cGy, respectively. D0.1cm3 ACE-lead was significantly lower than other parameters. No significant difference was observed between CTV-related parameters. CONCLUSIONS: The results suggested that using a lead block for alveolar bone protection with a thickness of about 4 mm, can shift the highest dose area to non-alveolar regions. In addition, it reduced D0.1cm3 of alveolar bone to about half, without affecting tumor dose.

Ultrahigh field brain magnetic resonance imaging using semiadiabatic radiofrequency pulses.

Great attention is being paid to solving, or mitigating, the technical problems associated with MRI at ultrahigh field strengths of 7 T and higher. This paper explores the use of the semiadiabatic spin-echo (SA-SE) pulse sequence, which uses semiadiabatic radiofrequency (RF) pulses to remove and/or mitigate the effects of the nonuniform B1 excitation field and B0 inhomogeneity associated with the electromagnetic properties of the human brain. A semiadiabatic RF pulse version of the recently published serial transmit excitation pulse (STEP) RF pulse sequence is also presented that now incorporates semiadiabatic pulses, henceforth is called SA-STEP. As demonstrated by computer simulation, and confirmed using head imaging, both techniques can produce multislice SE MR imaging at 7 T. These new methods use relatively low RF power and achieve good coverage of the human brain in a single scan.

Volume and surface coil simultaneous reception (VSSR) method for intensity inhomogeneity correction in MRI.

BACKGROUND: Addressing intensity inhomogeneity is critical in magnetic resonance imaging (MRI) because associated errors can adversely affect post-processing and quantitative analysis of images (i.e., segmentation, registration, etc.), as well as the accuracy of clinical diagnosis. Although several prior methods have been proposed to eliminate or correct intensity inhomogeneity, some significant disadvantages have remained, including alteration of tissue contrast, poor reliability and robustness of algorithms, and prolonged acquisition time. OBJECTIVE: In this study, we propose an intensity inhomogeneity correction method based on volume and surface coils simultaneous reception (VSSR). METHODS: The VSSR method comprises of two major steps: 1) simultaneous image acquisition from both volume and surface coils and 2) denoising of volume coil images and polynomial surface fitting of bias field. Extensive in vivo experiments were performed considering various anatomical structures, acquisition sequences, imaging resolutions, and orientations. In terms of correction performance, the proposed VSSR method was comparatively evaluated against several popular methods, including multiplicative intrinsic component optimization and improved nonparametric nonuniform intensity normalization bias correction methods. RESULTS: Experimental results show that VSSR is more robust and reliable and does not require prolonged acquisition time with the volume coil. CONCLUSION: The VSSR may be considered suitable for general implementation.

Mapping gradient nonlinearity and miscalibration using diffusion-weighted MR images of a uniform isotropic phantom.

PURPOSE: To use diffusion measurements to map the spatial dependence of the magnetic field produced by the gradient coils of an MRI scanner with sufficient accuracy to correct errors in quantitative diffusion MRI (DMRI) caused by gradient nonlinearity and gradient amplifier miscalibration. THEORY AND METHODS: The field produced by the gradient coils is expanded in regular solid harmonics. The expansion coefficients are found by fitting a model to a minimum set of diffusion-weighted images of an isotropic diffusion phantom. The accuracy of the resulting gradient coil field maps is evaluated by using them to compute corrected b-matrices that are then used to process a multi-shell diffusion tensor imaging (DTI) dataset with 32 diffusion directions per shell. RESULTS: The method substantially reduces both the spatial inhomogeneity of the computed mean diffusivities (MD) and the computed values of the fractional anisotropy (FA), as well as virtually eliminating any artifactual directional bias in the tensor field secondary to gradient nonlinearity. When a small scaling miscalibration was purposely introduced in the x, y, and z, the method accurately detected the amount of miscalibration on each gradient axis. CONCLUSION: The method presented detects and corrects the effects of gradient nonlinearity and gradient gain miscalibration using a simple isotropic diffusion phantom. The correction would improve the accuracy of DMRI measurements in the brain and other organs for both DTI and higher order diffusion analysis. In particular, it would allow calibration of MRI systems, improving data harmony in multicenter studies.

Selecting software pipelines for change in flortaucipir SUVR: Balancing repeatability and group separation.

Since tau PET tracers were introduced, investigators have quantified them using a wide variety of automated methods. As longitudinal cohort studies acquire second and third time points of serial within-person tau PET data, determining the best pipeline to measure change has become crucial. We compared a total of 415 different quantification methods (each a combination of multiple options) according to their effects on a) differences in annual SUVR change between clinical groups, and b) longitudinal measurement repeatability as measured by the error term from a linear mixed-effects model. Our comparisons used MRI and Flortaucipir scans of 97 Mayo Clinic study participants who clinically either: a) were cognitively unimpaired, or b) had cognitive impairments that were consistent with Alzheimer's disease pathology. Tested methods included cross-sectional and longitudinal variants of two overarching pipelines (FreeSurfer 6.0, and an in-house pipeline based on SPM12), three choices of target region (entorhinal, inferior temporal, and a temporal lobe meta-ROI), five types of partial volume correction (PVC) (none, two-compartment, three-compartment, geometric transfer matrix (GTM), and a tau-specific GTM variant), seven choices of reference region (cerebellar crus, cerebellar gray matter, whole cerebellum, pons, supratentorial white matter, eroded supratentorial WM, and a composite of eroded supratentorial WM, pons, and whole cerebellum), two choices of region masking (GM or GM and WM), and two choices of statistic (voxel-wise mean vs. median). Our strongest findings were: 1) larger temporal-lobe target regions greatly outperformed entorhinal cortex (median sample size estimates based on a hypothetical clinical trial were 520-526 vs. 1740); 2) longitudinal processing pipelines outperformed cross-sectional pipelines (median sample size estimates were 483 vs. 572); and 3) reference regions including supratentorial WM outperformed traditional cerebellar and pontine options (median sample size estimates were 370 vs. 559). Altogether, our results favored longitudinally SUVR methods and a temporal-lobe meta-ROI that includes adjacent (juxtacortical) WM, a composite reference region (eroded supratentorial WM + pons + whole cerebellum), 2-class voxel-based PVC, and median statistics.

Effect of offset-frequency step size and interpolation methods on chemical exchange saturation transfer MRI computation in human brain.

Chemical exchange saturation transfer (CEST) MRI is a non-invasive molecular imaging technique with potential applications in pre-clinical and clinical studies. Applications of amide proton transfer-weighted (APT-w), glutamate-weighted (Glu-w) and creatine-weighted (Cr-w) CEST, among others, have been reported. In general, CEST data are acquired at multiple offset-frequencies. In reported studies, different offset-frequency step sizes and interpolation methods have been used during B0 inhomogeneity correction of data. The objective of the current study was to evaluate the effects of different step sizes and interpolation methods on CEST value computation. In the current study, simulation (Glu-w, Cr-w and APT-w) and experimental data from the brain were used. Experimental CEST data (Glu-w) were acquired from human volunteers at 7 T and brain tumor patients (APT-w) at 3 T. During B0 inhomogeneity correction, different interpolation methods (polynomial [degree-1, 2 and 3], cubic-Hermite, cubic-spline and smoothing-spline) were compared. CEST values were computed using asymmetry analysis. The effects of different step sizes and interpolation methods were evaluated using coefficient of variation (CV), normalized mean square error (nMSE) and coefficient of correlation parameters. Additionally, an optimum interpolation method for APT-w values was selected based upon fitting accuracy, T-test, receiver operating characteristic analysis, and its diagnostic performance in differentiating low-grade and high-grade tumors. CV and nMSE increase with an increase in step size irrespective of the interpolation method (except for cubic-Hermite and cubic-spline). The nMSE of Cr-w and Glu-w CEST values were least for polynomial (degree-2 and 3). The quality of Glu-w CEST maps became coarse with the increase in step size. There was a significant difference (P < .05) between low-grade and high-grade tumors using polynomial interpolation (degree-1, 2 and 3); however, linear interpolation outperforms other methods for APT-w data, providing the highest sensitivity and specificity. In conclusion, depending upon the saturation parameters and field strength, optimization of step size and interpolation should be carried out for different CEST metabolites/molecules. Glu-w, Cr-w and APT-w CEST data should be acquired with a step size of between 0.2 and 0.3 ppm. For B0 inhomogeneity correction, polynomial (degree-2) should be used for Glu-w and Cr-w CEST data at 7 T and linear interpolation should be used for APT-w data at 3 T for a limited frequency range.

Ultra-high-field MRI using composite RF (STEP) pulses.

Ultra-high field MRI offers many opportunities to expand the applications of MRI. In order for this to be realized, the technical problems associated with MRI at field strengths of 7 T and greater need to be solved or mitigated. This paper explores the use of new variations of composite RF pulses, named serial transmit excitation pulses (STEP), in contrast to parallel pulse techniques, in order to remove and/or mitigate the effects of non-uniform B1 excitation fields associated with the subject (eg the human brain). Several techniques based on STEP sequences are introduced and their application to human brain imaging is presented and evaluated.

Intravoxel B0 inhomogeneity corrected reconstruction using a low-rank encoding operator.

PURPOSE: To present a general and efficient method for macroscopic intravoxel B0 inhomogeneity corrected reconstruction from multi-TE acquisitions. THEORY AND METHODS: A signal encoding model for multi-TE gradient echo (GRE) acquisitions that incorporates 3D intravoxel B0 field variations is derived, and a low-rank approximation to the encoding operator is introduced under piecewise linear B0 assumption. The low-rank approximation enables very efficient computation and memory usage, and allows the proposed signal model to be integrated into general inverse problem formulations that are compatible with multi-coil and undersampling acquisitions as well as different regularization functions. RESULTS: Experimental multi-echo GRE data were acquired to evaluate the proposed method. Effective reduction of macroscopic intravoxel B0 inhomogeneity induced artifacts was demonstrated. Improved R2∗ estimation from the corrected reconstruction over standard Fourier reconstruction has also been obtained. CONCLUSIONS: The proposed method can effectively correct the effects of intravoxel B0 inhomogeneity, and can be useful for various imaging applications involving GRE-based acquisitions, including fMRI, quantitative R2∗ and susceptibility mapping, and MR spectroscopic imaging.

Evaluation of the Geometric and Dosimetric Accuracy of Synthetic Computed Tomography Images for Magnetic Resonance Imaging-only Stereotactic Radiosurgery.

Introduction Stereotactic radiosurgery (SRS) plans created using synthetic computed tomography (CT) images derived from magnetic resonance imaging (MRI) data may offer the advantage of inhomogeneity correction by convolution algorithms, as is done for CT-based plans. We sought to determine and validate the clinical significance and accuracy of synthetic CT images for inhomogeneity correction in MRI-only stereotactic radiosurgery plans for treatment of brain tumors. Methods In this retrospective study, data from two patients with brain metastases and one with meningioma who underwent imaging with multiple modalities and received frameless SRS treatment were analyzed. The SRS plans were generated using a convolution algorithm to account for brain inhomogeneity using CT and synthetic CT images and compared with the original clinical TMR10 plans created using MRI images. Results Synthetic CT-derived SRS plans are comparable with CT-based plans using convolution algorithm, and for some targets, based on location, they provided better coverage and a lower maximum dose. Conclusions The results suggest similar dose delivery results for CT and synthetic CT-based treatment plans. Synthetic CT plans offered a noticeable improvement in target dose coverage and a more gradual dose fall-off relative to TMR10 MRI-based plans. The major disadvantage is a slightly increased dose (by 0.37%) to nearby healthy tissue (brainstem) for synthetic CT-based plans relative to those created using clinical MRI images, which may be a problem for patients undergoing high-dose treatment.

Retrospective correction of intensity inhomogeneity with sparsity constraints in transform-domain: Application to brain MRI.

An effective retrospective correction method is introduced in this paper for intensity inhomogeneity which is an inherent artifact in MR images. Intensity inhomogeneity problem is formulated as the decomposition of acquired image into true image and bias field which are expected to have sparse approximation in suitable transform domains based on their known properties. Piecewise constant nature of the true image lends itself to have a sparse approximation in framelet domain. While spatially smooth property of the bias field supports a sparse representation in Fourier domain. The algorithm attains optimal results by seeking the sparsest solutions for the unknown variables in the search space through L1 norm minimization. The objective function associated with defined problem is convex and is efficiently solved by the linearized alternating direction method. Thus, the method estimates the optimal true image and bias field simultaneously in an L1 norm minimization framework by promoting sparsity of the solutions in suitable transform domains. Furthermore, the methodology doesn't require any preprocessing, any predefined specifications or parametric models that are critically controlled by user-defined parameters. The qualitative and quantitative validation of the proposed methodology in simulated and real human brain MR images demonstrates the efficacy and superiority in performance compared to some of the distinguished algorithms for intensity inhomogeneity correction.

Crossing muscle fibers of the human tongue resolved in vivo using constrained spherical deconvolution.

BACKGROUND: Surgical resection of tongue cancer may impair swallowing and speech. Knowledge of tongue muscle architecture affected by the resection could aid in patient counseling. Diffusion tensor imaging (DTI) enables reconstructions of muscle architecture in vivo. Reconstructing crossing fibers in the tongue requires a higher-order diffusion model. PURPOSE: To develop a clinically feasible diffusion imaging protocol, which facilitates both DTI and constrained spherical deconvolution (CSD) reconstructions of tongue muscle architecture in vivo. STUDY TYPE: Cross-sectional study. SUBJECTS/SPECIMEN: One ex vivo bovine tongue resected en bloc from mandible to hyoid bone. Ten healthy volunteers (mean age 25.5 years; range 21-34 years; four female). FIELD STRENGTH/SEQUENCE: Diffusion-weighted echo planar imaging at 3 T using a high-angular resolution diffusion imaging scheme acquired twice with opposing phase-encoding for B0 -field inhomogeneity correction. The scan of the healthy volunteers was divided into four parts, in between which the volunteers were allowed to swallow, resulting in a total acquisition time of 10 minutes. ASSESSMENT: The ability of resolving crossing muscle fibers using CSD was determined on the bovine tongue specimen. A reproducible response function was estimated and the optimal peak threshold was determined for the in vivo tongue. The quality of tractography of the in vivo tongue was graded by three experts. STATISTICAL TESTS: The within-subject coefficient of variance was calculated for the response function. The qualitative results of the grading of DTI and CSD tractography were analyzed using a multilevel proportional odds model. RESULTS: Fiber orientation distributions in the bovine tongue specimen showed that CSD was able to resolve crossing muscle fibers. The response function could be determined reproducibly in vivo. CSD tractography displayed significantly improved tractography compared with DTI tractography (P = 0.015). DATA CONCLUSION: The 10-minute diffusion imaging protocol facilitates CSD fiber tracking with improved reconstructions of crossing tongue muscle fibers compared with DTI. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:96-105.

Evaluation of dose calculations with inhomogeneity correction in intensity-modulated radiation therapy for esophagus cancer.

BACKGROUND: Differences often exist in the dose calculation accuracy caused by using different dose calculation algorithms in non-uniform tissues. OBJECTIVE: To evaluate the accuracy of dose calculation with inhomogeneity correction in intensity-modulated radiation therapy (IMRT) by comparing dose calculated in Monaco with measurements in lung-chest phantom for esophagus cancer treatments. METHODS: Finite size pencil beam (FSPB) and X-ray voxel Monte Carlo (XVMC) were used respectively for IMRT dose recalculations. Ten IMRT plans were recalculated and measured in the chest-lung phantom. The dose measurements using the Gafchromic ® (EBT3) dosimetry films were validated with open fields in the interfaces of materials with various physical densities. The accuracy of dose calculations was then evaluated by both point dose comparison and Gamma analysis against the film measurements. RESULTS: For regular open fields, the discrepancies of the point doses were less than 3.0% and 2.0% between measurement and calculations by FSPB and XVMC, respectively. For 6 MV IMRT plans, the average passing rates based on 3% /3 mm Gamma criteria were 82.8±1.0% and 96.4±0.7% for FSPB and XVMC, respectively. CONCLUSIONS: The XVMC algorithms more accurate in IMRT dose calculations with inhomogeneity correction for esophagus cancer.

Comparison of B0 versus B0 and B1 field inhomogeneity correction for glycosaminoglycan chemical exchange saturation transfer imaging.

PURPOSE: The study compares glycosaminoglycan chemical exchange saturation transfer (gagCEST) imaging of intervertebral discs corrected for solely B0 inhomogeneities or both B0 and B1 inhomogeneities. METHODS: Lumbar intervertebral discs of 20 volunteers were examined with T2-weighted and gagCEST imaging. Field inhomogeneity correction was performed with B0 correction only and with correction of both B0 and B1. GagCEST effects measured by the asymmetric magnetization transfer ratio (MTRasym) and signal-to-noise ratio (SNR) were compared between both methods. RESULTS: Significant higher MTRasym and SNR values were obtained in the nucleus pulposus using B0 and B1 correction compared with B0-corrected gagCEST. The GagCEST effect was significantly different in the nucleus pulposus compared with the annulus fibrosus for both methods. CONCLUSION: The B0 and B1 field inhomogeneity correction method leads to an improved quality of gagCEST imaging in IVDs compared with only B0 correction.

Machine learning RF shimming: Prediction by iteratively projected ridge regression.

PURPOSE: To obviate online slice-by-slice RF shim optimization and reduce B1+ mapping requirements for patient-specific RF shimming in high-field magnetic resonance imaging. THEORY AND METHODS: RF Shim Prediction by Iteratively Projected Ridge Regression (PIPRR) predicts patient-specific, SAR-efficient RF shims with a machine learning approach that merges learning with training shim design. To evaluate it, a set of B1+ maps was simulated for 100 human heads for a 24-element coil at 7T. Features were derived from tissue masks and the DC Fourier coefficients of the coils' B1+ maps in each slice, which were used for kernelized ridge regression prediction of SAR-efficient RF shim weights. Predicted shims were compared to directly designed shims, circularly polarized mode, and nearest-neighbor shims predicted using the same features. RESULTS: PIPRR predictions had 87% and 13% lower B1+ coefficients of variation compared to circularly polarized mode and nearest-neighbor shims, respectively, and achieved homogeneity and SAR similar to that of directly designed shims. Predictions were calculated in 4.92 ms on average. CONCLUSION: PIPRR predicted uniform, SAR-efficient RF shims, and could save a large amount of B1+ mapping and computation time in RF-shimmed ultra-high field magnetic resonance imaging.

Intensity inhomogeneity correction of SD-OCT data using macular flatspace.

Images of the retina acquired using optical coherence tomography (OCT) often suffer from intensity inhomogeneity problems that degrade both the quality of the images and the performance of automated algorithms utilized to measure structural changes. This intensity variation has many causes, including off-axis acquisition, signal attenuation, multi-frame averaging, and vignetting, making it difficult to correct the data in a fundamental way. This paper presents a method for inhomogeneity correction by acting to reduce the variability of intensities within each layer. In particular, the N3 algorithm, which is popular in neuroimage analysis, is adapted to work for OCT data. N3 works by sharpening the intensity histogram, which reduces the variation of intensities within different classes. To apply it here, the data are first converted to a standardized space called macular flat space (MFS). MFS allows the intensities within each layer to be more easily normalized by removing the natural curvature of the retina. N3 is then run on the MFS data using a modified smoothing model, which improves the efficiency of the original algorithm. We show that our method more accurately corrects gain fields on synthetic OCT data when compared to running N3 on non-flattened data. It also reduces the overall variability of the intensities within each layer, without sacrificing contrast between layers, and improves the performance of registration between OCT images.

A non-iterative multi-scale approach for intensity inhomogeneity correction in MRI.

Intensity inhomogeneity is the prime obstacle for MR image processing like automatic segmentation, registration etc. This complication has strong dependence on the associated acquisition hardware and patient anatomy which recommends retrospective correction. In this paper, a new method is developed for correcting the intensity inhomogeneity using a non-iterative multi-scale approach that doesn't necessitate segmentation and any prior knowledge on the scanner or subject. The proposed algorithm extracts bias field at different scales using a Log-Gabor filter bank followed by smoothing operation. Later, they are combined to fit a third degree polynomial to estimate the bias field. Finally, the corrected image is estimated by performing pixel-wise division of original image and bias field. The performance of the same was tested on BrainWeb simulated data, HCP dataset and is found to provide better performance than the state-of-the-art method, N4. A good agreement between the extracted and ground truth bias field is observed through correlation coefficient on different MR modality images that include T1w, T2w and PD. Significant reduction in coefficient variation and coefficient of joint variation ratios in real data indicate an improved inter-class separation and reduced intra-class intensity variations across white and grey matter tissue regions.