Inhomogeneity Correction Research Articles

3T sodium-MRI as predictor of neurocognition in nondemented older adults: a cross sectional study.

Dementia is a burgeoning global problem. Novel magnetic resonance imaging (MRI) metrics beyond volumetry may bring new insight and aid clinical trial evaluation of interventions early in the Alzheimer's disease course to complement existing imaging and clinical metrics. To determine whether: (i) normalized regional sodium-MRI values (Na-SI) are better predictors of neurocognitive status than volumetry (ii) cerebral amyloid PET status improves modelling. Nondemented older adult (>60 years) volunteers of known Alzheimer's Disease Assessment Scale (ADAS-Cog11), Mini-Mental State Examination (MMSE) and Consortium to Establish a Registry for Alzheimer's Disease (CERAD) neurocognitive test scores, ApolipoproteinE (APOE) e4 +/- cerebral amyloid PET status were prospectively recruited for 3T sodium-MRI brain scans. Left and right hippocampal, entorhinal and precuneus volumes and Na-SI (using the proportional intensity scaling normalization method with field inhomogeneity and partial volume corrections) were obtained after segmentation and co-registration of 3D-T1-weighted proton images. Descriptive statistics, correlation and best-subset regression analyses were performed. In our 76 nondemented participants (mean(standard deviation) age 75(5) years; woman 47(62%); cognitively unimpaired 54/76(71%), mildly cognitively impaired 22/76(29%)), left hippocampal Na-SI, not volume, was preferentially in the best models for predicting MMSE (Odds Ratio (OR) = 0.19(Confidence Interval (CI) = 0.07,0.53), P-value = 0.001) and ADAS-Cog11 (Beta(B) = 1.2(CI = 0.28,2.1), P-value = 0.01) scores. In the entorhinal analysis, right entorhinal Na-SI, not volume, was preferentially selected in the best model for predicting ADAS-Cog11 (B = 0.94(CI = 0.11,1.8), P-value = 0.03). While right entorhinal Na-SI and volume were both selected for MMSE modelling (Na-SI OR = 0.23(CI = 0.09,0.6), P-value = 0.003; volume OR = 2.6(CI = 1.0,6.6), P-value = 0.04), independently, Na-SI explained more of the variance (Na-SI R 2 = 10.3; volume R 2 = 7.5). No imaging variable was selected in the best CERAD models. Adding cerebral amyloid status improved model fit (Akaike Information Criterion increased 2.0 for all models, P-value < 0.001-0.045). Regional Na-SI were more predictive of MMSE and ADAS-Cog11 scores in our nondemented older adult cohort than volume, hippocampal more robust than entorhinal region of interest. Positive amyloid status slightly further improved model fit.

Improving detection of wheat canopy chlorophyll content based on inhomogeneous light correction

Effectively improving the detection accuracy of wheat chlorophyll content is of great significance for the detection of photosynthetic capacity and growth status of wheat canopy. However, due to inhomogeneous light distribution issues in canopy, the existence of shaded and sun wheat leaves in wheat canopy has influence for spectral-based detection of chlorophyll content. Therefore, in order to improve detection of wheat canopy chlorophyll content, a light distribution correction method was proposed to correct intact leaves’ light distribution based on shaded and sun leaves in multispectral images. Firstly, R-G-NIR images were reconstructed to segment and analyze shaded and sun leaves of wheat. Secondly, Homomorphic Filter (HF) and Gamma light correction method was used to optimize shaded leaves’ light distribution. Then, the differential responses of 10 different types of vegetation indices in shaded, sun, original intact and corrected intact leaves were analyzed to screen chlorophyll-sensitive parameters based on Random Frog Method (RFM). Finally, Random Forest (RF), Support Vector Regression (SVR), and Partial Least Squares Regression (PLSR) were used to establish models for the detection of chlorophyll content in shaded, sun, original intact and corrected intact leaves of wheat, respectively. The results showed that the proposed light correction method reduced the inhomogeneous light and kept more uniform. Normalized difference vegetation index (NDVI), green normalized difference vegetation index (GNDVI), difference vegetation index (DVI), normalized redness intensity (NRI), and optimized soil-adjusted vegetation index (OSAVI) were selected as the optimal spectral variables. And the models after correction had higher accuracy than the models before correction. The wheat chlorophyll content model of corrected intact leaves based on RF had the highest accuracy, with a calibration set Rc2 of 0.816, RMSEc of 3.702, a validation set Rv2 of 0.804, RMSEv of 3.958, respectively. The research integrates the above results to improve detection of wheat canopy chlorophyll content, which provides technical support for the light distribution correction in multispectral images.

Synthetic CT for gamma knife radiosurgery dose calculation: A feasibility study

PurposeTo determine if MRI-based synthetic CTs (sCT), generated with no predefined pulse sequence, can be used for inhomogeneity correction in routine gamma knife radiosurgery (GKRS) treatment planning dose calculation. MethodsTwo sets of sCTs were generated from T1post and T2 images using cycleGAN. Twenty-eight patients (18 training, 10 validation) were retrospectively selected. The image quality of the generated sCTs was compared with the original CT (oCT) regarding the HU value preservation using histogram comparison, RMSE and MAE, and structural integrity. Dosimetric comparisons were also made among GKRS plans from 3 calculation approaches: TMR10 (oCT), and convolution (oCT and sCT), at four locations: original disease site, bone/tissue interface, air/tissue interface, and mid-brain. ResultsThe study showed that sCTs and oCTs’ HU were similar, with T2-sCT performing better. TMR10 significantly underdosed the target by a mean of 5.4% compared to the convolution algorithm. There was no significant difference in convolution algorithm shot time between the oCT and sCT generated with T2. The highest and lowest dosimetric differences between the two CTs were observed in the bone and air interface, respectively. Dosimetric differences of 3.3% were observed in sCT predicted from MRI with stereotactic frames, which was not included in the training sets. ConclusionsMRI-based sCT can be utilized for GKRS convolution dose calculation without the unnecessary radiation dose, and sCT without metal artifacts could be generated in framed cases. Larger datasets inclusive of all pulse sequences can improve the training set. Further investigation and validation studies are needed before clinical implementation.

Relative Homogenization of Climatic Time Series

Homogenization of the time series of observed climatic data aims to remove non-climatic biases caused by technical changes during the history of the climate observations. The spatial redundancy of climate information helps to recognize station-specific inhomogeneities with statistical methods, but the correct detection and removal of inhomogeneity biases is generally not easy for the combined effects of individual inhomogeneities. In a homogenization procedure, several time series of a given climatic variable observed in one climatic region are usually homogenized together via a large number of spatial comparisons between them. Such procedures are called relative homogenization. A relative homogenization procedure may include one or more homogenization cycles where a cycle includes the steps of time series comparison, inhomogeneity detection and corrections for inhomogeneities, and they may include other steps like the filtering of outlier values or spatial interpolations for infilling data gaps. Relative homogenization methods differ according to the number and content of the individual homogenization cycles, the procedure for the time series comparisons, the statistical inhomogeneity detection method, the way of the inhomogeneity bias removal, among other specifics. Efficient homogenization needs the use of tested statistical methods to be included in partly or fully automated homogenization procedures. Due to the large number and high variety of homogenization experiments fulfilled in the Spanish MULTITEST project (2015–2017), its method comparison test results are still the most informative about the efficiencies of homogenization methods in use. This study presents a brief review of the advances in relative homogenization, recalls some key results of the MULTITEST project, and analyzes some theoretical aspects of successful homogenization.

Fast and motion-robust saturation transfer MRI with inherent B0 correction using rosette trajectories and compressed sensing.

To implement rosette readout trajectories with compressed sensing reconstruction for fast and motion-robust CEST and magnetization transfer contrast imaging with inherent correction of B0 inhomogeneity. A pulse sequence was developed for fast saturation transfer imaging using a stack of rosette trajectories with a higher sampling density near the k-space center. Each rosette lobe was segmented into two halves to generate dual-echo images. B0 inhomogeneities were estimated using the phase difference between the images and corrected subsequently. The rosette-based imaging was evaluated in comparison to a fully sampled Cartesian trajectory and demonstrated on CEST phantoms (creatine solutions and egg white) and healthy volunteers at 3 T. Compared with the conventional Cartesian acquisition, compressed sensing reconstructed rosette images provided image quality with overall higher contrast-to-noise ratio and significantly faster readout time. Accurate B0 map estimation was achieved from the rosette acquisition with a negligible bias of 0.01 Hz between the rosette and dual-echo Cartesian gradient echo B0 maps, using the latter as ground truth. The water-saturation spectra (Z-spectra) and amide proton transfer weighted signals obtained from the rosette-based sequence were well preserved compared with the fully sampled data, both in the phantom and human studies. Fast, motion-robust, and inherent B0-corrected CEST and magnetization transfer contrast imaging using rosette trajectories could improve subject comfort and compliance, contrast-to-noise ratio, and provide inherent B0 homogeneity information. This work is expected to significantly accelerate the translation of CEST-MRI into a robust, clinically viable approach.

A three-step, "brute-force" approach toward optimized affine spatial normalization.

The first step in spatial normalization of magnetic resonance (MR) images commonly is an affine transformation, which may be vulnerable to image imperfections (such as inhomogeneities or "unusual" heads). Additionally, common software solutions use internal starting estimates to allow for a more efficient computation, which may pose a problem in datasets not conforming to these assumptions (such as those from children). In this technical note, three main questions were addressed: one, does the affine spatial normalization step implemented in SPM12 benefit from an initial inhomogeneity correction. Two, does using a complexity-reduced image version improve robustness when matching "unusual" images. And three, can a blind "brute-force" application of a wide range of parameter combinations improve the affine fit for unusual datasets in particular. A large database of 2081 image datasets was used, covering the full age range from birth to old age. All analyses were performed in Matlab. Results demonstrate that an initial removal of image inhomogeneities improved the affine fit particularly when more inhomogeneity was present. Further, using a complexity-reduced input image also improved the affine fit and was beneficial in younger children in particular. Finally, blindly exploring a very wide parameter space resulted in a better fit for the vast majority of subjects, but again particularly so in infants and young children. In summary, the suggested modifications were shown to improve the affine transformation in the large majority of datasets in general, and in children in particular. The changes can easily be implemented into SPM12.

Dosimetry and Monte Carlo modelling of the Papillon+ contact X-ray brachytherapy device

PurposeThis study aimed to develop and validate a Monte Carlo (MC) model for the Papillon+ contact x-ray brachytherapy (CXB) device, producing 50 kilovolt (kV) x-rays, specifically focusing on its application with a 25 mm diameter rectal applicator for contact therapy. Material and methodsThe validation process involved depth dose and transverse dose profile measurements using EBT3 gafchromic films positioned in a Plastic Water Low Energy Range phantom. The half-value layer (HVL) was further measured and derived from the simulated x-ray spectra. ResultsExcellent agreement within ± 2 % was achieved between the measured and simulated on-axis depth dose curves for the 25 mm rectal applicator. Transverse dose profile measurements showed a high level of agreement between the simulation and measurements, on average 3.1 % in contact with the applicator at the surface of the phantom and on average 1.7 % at 10 mm depth. A close agreement within 5.5 % was noticed concerning the HVL between the measurement and simulation. The simulated gamma spectra and 2D-dose distribution demonstrated a soft x-ray energy spectrum and a uniform dose distribution in contact with the applicator. ConclusionsAn MC model was successfully developed for the Papillon+ eBT device with a 25 mm diameter rectal applicator. The validated model, with its demonstrated accuracy in depth dose and transverse dose profile simulations, is a valuable tool for quality assurance and patient safety and, in a later phase, may be used for treatment planning, dose calculations and tissue inhomogeneity corrections.

Fast and reliable quantitative measures of white matter development with magnetic resonance fingerprinting.

Developmental cognitive neuroscience aims to shed light on evolving relationships between brain structure and cognitive development. To this end, quantitative methods that reliably measure individual differences in brain tissue properties are fundamental. Standard qualitative MRI sequences are influenced by scan parameters and hardware-related biases, and also lack physical units, making the analysis of individual differences problematic. In contrast, quantitative MRI can measure physical properties of the tissue but with the cost of long scan durations and sensitivity to motion. This poses a critical limitation for studying young children. Here, we examine the reliability and validity of an efficient quantitative multiparameter mapping method - Magnetic Resonance Fingerprinting (MRF) - in children scanned longitudinally. We focus on T1 values in white matter, since quantitative T1 values are known to primarily reflect myelin content, a key factor in brain development. Forty-nine children aged 8-13y (mean 10.3y ±1.4) completed two scanning sessions 2-4 months apart. In each session, two 2-minute 3D-MRF scans at 1mm isotropic resolution were collected to evaluate the effect of scan duration on image quality and scan-rescan reliability. A separate calibration scan was used to measure B0 inhomogeneity and correct for bias. We examined the impact of scan time and B0 inhomogeneity correction on scan-rescan reliability of values in white matter, by comparing single 2-min and combined two 2-min scans, with and without B0-correction. Whole-brain voxel-based reliability analysis showed that combining two 2-min MRF scans improved reliability (pearson's r=0.87) compared with a single 2-min scan (r=0.84), while B0-correction had no effect on reliability in white matter (r=0.86 and 0.83 4-min vs 2-min). Using diffusion tractography, we delineated MRF-derived T1 profiles along major white matter fiber tracts and found similar or higher reliability for T1 from MRF compared to diffusion parameters (based on a 10-minute dMRI scan). Lastly, we found that T1 values in multiple white matter tracts were significantly correlated with age. In sum, MRF-derived T1 values were highly reliable in a longitudinal sample of children and replicated known age effects. Reliability in white matter was improved by longer scan duration but was not affected by B0-correction, making it a quick and straightforward scan to collect. We propose that MRF provides a promising avenue for acquiring quantitative brain metrics in children and patient populations where scan time and motion are of particular concern.

3D printing of ferromagnetic passive shims for field shaping in magnetic resonance imaging

Magnetic Resonance Imaging (MRI) often encounters image quality degradation due to magnetic field inhomogeneities. Conventional passive shimming techniques involve the manual placement of discrete magnetic materials, imposing limitations on correcting complex inhomogeneities. To overcome this, we propose a novel 3D printing method utilizing binder jetting technology to enable precise deposition of a continuous range of concentrations of ferromagnetic ink. This approach grants complete control of the magnitude of the magnetic moment within the passive shim enabling tailored corrections of B0 field inhomogeneities. By optimizing the magnetic field distribution using linear programming and an in-house written Computer-Aided Design (CAD) generation software, we printed shims with promising results in generating low spherical harmonic corrections. Experimental evaluations demonstrate feasibility of these 3D printed passive shims to induce target magnetic fields corresponding to second-order spherical harmonic, as evidenced by acquired B0 maps. The electrically insulating properties of the printed shims eliminate the risk of eddy currents and heating, thus ensuring safety. The dimensional fabrication accuracy of the printed shims surpasses previous methods, enabling more precise and localized correction of subject-specific inhomogeneities. The findings highlight the potential of binder-jetted 3D printed passive shims in MRI shimming as a versatile and efficient solution for fabricating passive shims, with the potential to enhance the quality of MRI imaging while also being applicable to other types of Magnetic Resonance systems.

Three-phase equilibria of hydrates from computer simulation. III. Effect of dispersive interactions in the methane and carbon dioxide hydrates.

In this work, the effect of the range of dispersive interactions in determining the three-phase coexistence line of the CO2 and CH4 hydrates has been studied. In particular, the temperature (T3) at which solid hydrate, water, and liquid CO2/gas CH4 coexist has been determined through molecular dynamics simulations using different cutoff values (from 0.9 to 1.6nm) for dispersive interactions. The T3 of both hydrates has been determined using the direct coexistence simulation technique. Following this method, the three phases in equilibrium are put together in the same simulation box, the pressure is fixed, and simulations are performed at different temperatures T. If the hydrate melts, then T > T3. Conversely, if the hydrate grows, then T < T3. The effect of the cutoff distance on the dissociation temperature has been analyzed at three different pressures for CO2 hydrate: 100, 400, and 1000bar. Then, we have changed the guest and studied the effect of the cutoff distance on the dissociation temperature of the CH4 hydrate at 400bar. Moreover, the effect of long-range corrections for dispersive interactions has been analyzed by running simulations with homo- and inhomogeneous corrections and a cutoff value of 0.9nm. The results obtained in this work highlight that the cutoff distance for the dispersive interactions affects the stability conditions of these hydrates. This effect is enhanced when the pressure is decreased, displacing the T3 about 2-4K depending on the system and the pressure.

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

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. 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/ , 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. 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. The proposed method enables reliable B1 inhomogeneity correction from at least two CEST acquisitions, providing an effective way to improve quantitative CEST MRI.

Assessing regional intracortical myelination in schizophrenia spectrum and bipolar disorders using the optimized T1w/T2w-ratio.

Dysmyelination could be part of the pathophysiology of schizophrenia spectrum (SCZ) and bipolar disorders (BPD), yet few studies have examined myelination of the cerebral cortex. The ratio of T1- and T2-weighted magnetic resonance images (MRI) correlates with intracortical myelin. We investigated the T1w/T2w-ratio and its age trajectories in patients and healthy controls (CTR) and explored associations with antipsychotic medication use and psychotic symptoms. Patients with SCZ (n = 64; mean age = 30.4 years, s.d. = 9.8), BPD (n = 91; mean age 31.0 years, s.d. = 10.2), and CTR (n = 155; mean age = 31.9 years, s.d. = 9.1) who participated in the TOP study (NORMENT, University of Oslo, Norway) were clinically assessed and scanned using a General Electric 3 T MRI system. T1w/T2w-ratio images were computed using an optimized pipeline with intensity normalization and field inhomogeneity correction. Vertex-wise regression models were used to compare groups and examine group × age interactions. In regions showing significant differences, we explored associations with antipsychotic medication use and psychotic symptoms. No main effect of diagnosis was found. However, age slopes of the T1w/T2w-ratio differed significantly between SCZ and CTR, predominantly in frontal and temporal lobe regions: Lower T1w/T2w-ratio values with higher age were found in CTR, but not in SCZ. Follow-up analyses revealed a more positive age slope in patients who were using antipsychotics and patients using higher chlorpromazine-equivalent doses. While we found no evidence of reduced intracortical myelin in SCZ or BPD relative to CTR, different regional age trajectories in SCZ may suggest a promyelinating effect of antipsychotic medication.

Teaching a hands-on session on simultaneous Positron Emission Tomography and Magnetic Resonance image acquisition and quantification in a clinical setting

Positron Emission Tomography/Magnetic Resonance (PET/MR) imaging, is a novel imaging modality that combines the capabilities of two powerful imaging techniques in a single acquisition. This unique integration allows for simultaneous acquisition of both metabolic and structural data within a single imaging session. In this sense, PET/MR offers a comprehensive and innovative approach to medical imaging, but accompanied by its intrinsic physics and engineering complexity, involving intricate synchronization of high-performance detectors, electromagnetic shielding, and sophisticated correction algorithms, among others. In this hands-on session performed during the 6th INFIERI summer school (Madrid, Spain), we described an introduction to simultaneous PET/MR image acquisition and quantification in a real clinical to students from diverse backgrounds in physics and engineering. We first presented the fundamental aspects of PET/MR image acquisition, including the main theoretical characteristics of PET/MR physics and electronics, visiting the PET/MR facilities at Hospital Universitario HM Puerta del Sur (HM Hospitales, Móstoles, Madrid), and discussing the main PET/MR clinical and research applications. Then, we followed with a practical session on PET/MR image quantification, preparing the students to understand and solve examples on image reconstruction, multimodal data visualization, inhomogeneity correction, image registration, and attenuation correction exploiting the simplicity and usefulness of 3D Slicer.

DeepN4: Learning N4ITK Bias Field Correction for T1-weighted Images.

T1-weighted (T1w) MRI has low frequency intensity artifacts due to magnetic field inhomogeneities. Removal of these biases in T1w MRI images is a critical preprocessing step to ensure spatially consistent image interpretation. N4ITK bias field correction, the current state-of-the-art, is implemented in such a way that makes it difficult to port between different pipelines and workflows, thus making it hard to reimplement and reproduce results across local, cloud, and edge platforms. Moreover, N4ITK is opaque to optimization before and after its application, meaning that methodological development must work around the inhomogeneity correction step. Given the importance of bias fields correction in structural preprocessing and flexible implementation, we pursue a deep learning approximation / reinterpretation of the N4ITK bias fields correction to create a method which is portable, flexible, and fully differentiable. In this paper, we trained a deep learning network "DeepN4" on eight independent cohorts from 72 different scanners and age ranges with N4ITK-corrected T1w MRI and bias field for supervision in log space. We found that we can closely approximate N4ITK bias fields correction with naïve networks. We evaluate the peak signal to noise ratio (PSNR) in test dataset against the N4ITK corrected images. The median PSNR of corrected images between N4ITK and DeepN4 was 47.96dB. In addition, we assess the DeepN4 model on eight additional external datasets and show the generalizability of the approach. This study establishes that incompatible N4ITK preprocessing steps can be closely approximated by naïve deep neural networks, facilitating more flexibility. All code and models are released at https://github.com/MASILab/DeepN4 .

Accelerated liver water T1 mapping using single-shot continuous inversion-recovery spiral imaging.

Liver T1 mapping techniques typically require long breath holds or long scan time in free-breathing, need correction for inhomogeneities and process composite (water and fat) signals. The purpose of this work is to accelerate the multi-slice acquisition of liver water selective T1 (wT1) mapping in a single breath hold, improving the k-space sampling efficiency. The proposed continuous inversion-recovery (IR) Look-Locker methodology combines a single-shot gradient echo spiral readout, Dixon processing and a dictionary-based analysis for liver wT1 mapping at 3 T. The sequence parameters were adapted to obtain short scan times. The influence of fat, inhomogeneities and TE on the estimation of T1 was first assessed using simulations. The proposed method was then validated in a phantom and in 10 volunteers, comparing it with MRS and the modified Look-Locker inversion-recovery (MOLLI) method. Finally, the clinical feasibility was investigated by comparing wT1 maps with clinical scans in nine patients. The phantom results are in good agreement with MRS. The proposed method encodes the IR-curve for the liver wT1 estimation, is minimally sensitive to inhomogeneities and acquires one slice in 1.2 s. The volunteer results confirmed the multi-slice capability of the proposed method, acquiring nineslices in a breath hold of 11 s. The present work shows robustness to inhomogeneities ( , good repeatability ( and is in better agreement with MRS ( than is MOLLI ( . The wT1 maps in patients captured diverse lesions, thus showing their clinical feasibility. A single-shot spiral acquisition can be combined with a continuous IR Look-Locker method to perform rapid repeatable multi-slice liver water T1 mapping at a rate of 1.2 s per slice without a map. The proposed method is suitable for nine-slice liver clinical applications acquired in a single breath hold of 11 s.

Reproducibility of 3D pH-weighted chemical exchange saturation transfer contrast in the healthy cervical spinal cord.

Spinal cord ischemia and hypoxia can be caused by compression, injury, and vascular alterations. Measuring ischemia and hypoxia directly in the spinal cord noninvasively remains challenging. Ischemia and hypoxia alter tissue pH, providing a physiologic parameter that may be more directly related to tissue viability. Chemical exchange saturation transfer (CEST) is an MRI contrast mechanism that can be made sensitive to pH. More specifically, amine/amide concentration independent detection (AACID) is a recently developed endogenous CEST contrast that has demonstrated sensitivity to intracellular pH at 9.4 T. The goal of this study was to evaluate the reproducibility of AACID CEST measurements at different levels of the healthy cervical spinal cord at 3.0 T incorporating B1 correction. Using a 3.0 T MRI scanner, two 3D CEST scans (saturation pulse train followed by a 3D snapshot gradient-echo readout) were performed on 12 healthy subjects approximately 10 days apart, with the CEST volume centered at the C4 level for all subjects. Scan-rescan reproducibility was evaluated by examining between and within-subject coefficients of variation (CVs) and absolute AACID value differences. The C4 level of the spinal cord demonstrated the lowest within-subject CVs (4.1%-4.3%), between-subject CVs (5.6%-6.3%), and absolute AACID percent difference (5.8-6.1%). The B1 correction scheme significantly improved reproducibility (adjusted p-value = 0.002) compared with the noncorrected data, suggesting that implementing B1 corrections in the spinal cord is beneficial. It was concluded that pH-weighted AACID measurements, incorporating B1-inhomogeneity correction, were reproducible within subjects along the healthy cervical spinal cord and that optimal image quality was achieved at the center of the 3D CEST volume.

Inflationary quantum spectrum of the quasi-isotropic Universe

We investigate the quantum dynamics of the quasi-isotropic inflationary solution. This is achieved by deriving the Lagrangian and Hamiltonian for both the FLRW background and the inhomogeneous correction, via an expansion of the Einstein–Hilbert action up to second order in the perturbation amplitudes. Then we implement a semiclassical WKB scenario for which the inhomogeneous component of the Universe is treated as a “small” quantum subsystem, evolving on the classical isotropic background. Starting from the Wheeler–DeWitt equation, we recover a Schrödinger dynamics for the perturbations, in which the time dependence of the wave function emerges thanks to the classicality of the background, and we solve it for an inflationary phase. The main result of this paper is to show that, while the scalar component of the power spectrum has the standard scale invariant profile, the tensor one results to be not constrained by the inflationary expansion, apart from an overall normalization factor which guarantees a small tensor-to-scalar ratio. This means that the spatial distribution of the quasi-isotropic correction to the metric remains preserved, with the consequence that some information about the pre-inflationary Universe survives to the de Sitter expansion.

KinKal: A Kinematic Kalman filter Track Fitting Package for the Mu2e Experiment

Many current physics experiments require precision reconstruction of low-energy particles. One example is the Mu2e experiment, which requires reconstructing an isolated 105 MeV electron with better than 500 KeV/c momentum resolution. Mu2e uses a low-mass straw tube tracker, and a CsI crystal calorimeter, to reconstruct tracks. In this paper, we present the design and performance of a track reconstruction algorithm optimized for Mu2e’s unusual requirements. The algorithm is based on the KinKal [1] kinematic Kalman filter track fit package. KinKal supports multiple track parameterizations, including one optimized for looping tracks, such as Mu2e signal tracks, and others optimized for straight or slightly-curved tracks, such as the high-momentum (&gt;1 GeV/c) cosmic ray muons used to calibrate and align the Mu2e detectors. All KinKal track parameterizations include the track origin time, to correctly model correlations arising from measurements that couple time and space, such as the straw drift time or the calorimeter cluster time. KinKal employs magnetic field inhomogeneity and material effect correction algorithms with 10−4 fractional precision. The Mu2e fit uses Artificial Neural Net functions to discriminate background hits from signal hits, and to resolve the straw tube hit left-right ambiguity, while iterating the extended Kalman filter. The efficiency, accuracy, and precision of the Mu2e track reconstruction, as tested on detailed simulations of Mu2e data, are presented.

ПОБУДОВА ТА ПЕРШІ РЕЗУЛЬТАТИ ІНТЕРПРЕТАЦІЇ ТРИВИМІРНОЇ МОДЕЛІ ЩІЛЬНОСТІ МАНТІЇ ПІД УКРАЇНСЬКИМ ЩИТОМ

Background. Mantle density models are key tools for understanding fundamental geological and physical processes occurring within the Earth. Many parameters used in mantle density models remain poorly understood and undefined. Among others, these include data on the composition and rheology of the mantle, which can vary significantly. Methods. The method of creating density models (density) significantly influences the final result. Modeling with one-dimensional models simplifies the calculation process but generalizes the distribution of mantle density, assuming it is homogeneous in the horizontal direction. This limitation does not allow for the consideration of lateral variations in mantle density, which can be important at the regional level. In this study, we present a quasi-three-dimensional model of mantle density beneath the Ukrainian Shield, obtained on the basis of a set of one-dimensional density curves. Polynomial corrections for heterogeneity were applied during the calculations, compensating for the shortcomings of one-dimensional models. This three-dimensional model was derived by recalculating one-dimensional velocity curves obtained by seismic tomography for 21 mantle domains in the depth range of 50 to 2600 km. The process of transforming P-wave velocity curves into a density model includes the following steps: determining seismic boundaries in the mantle as points of inflection of the first derivative of P-wave velocity curves for each mantle domain; creating a synthetic S-wave mantle model beneath the Ukrainian Shield by recalculating P-wave velocity curves; solving the Adams-Williamson equation using seismic velocities (P, S) for each domain with subsequent polynomial correction to account for heterogeneity; selecting a reference mantle model that would serve as the basis for converting velocity curves into density through the comparison of gravitational potential on the Earth's surface and calculated values from existing reference mantle models (PREM, PREMA, PREMC, IASP91 AK135). The AK135 model was chosen as the reference model based on the comparison of calculated and observed gravitational potential at the central point of the Ukrainian Shield. This study focuses on the final stages of constructing the mantle density model, taking into account mass balancing of the upper and lower mantle for each domain when determining density using the Adams-Williamson equation and introducing polynomial corrections relative to the AK135 reference model; calculating densities for each of the 21 mantle domains and their three-dimensional integration. Results. In this study, we present a quasi-three-dimensional model of mantle density beneath the Ukrainian Shield, obtained on the basis of a set of one-dimensional density curves, with polynomial corrections for inhomogeneity incorporated into the calculations, compensating for the shortcomings of one-dimensional model calculations. This three-dimensional model was obtained by recalculating one-dimensional velocity curves obtained by the seismic tomography method for P-waves, calculated for 21 mantle domains in the depth range from 50 to 2600 km. Conclusions. This study focuses on the final stages of constructing the mantle density model, considering balancing the mass of the upper and lower mantle for each domain in determining density using the Adams-Williamson equation and introducing polynomial corrections relative to the AK135 reference model; calculating densities for each of the 21 mantle domains and their three-dimensional integration. The obtained mantle density model of the Ukrainian Shield is well aligned with the division of the mantle into three main layers: lithosphere, upper mantle, and lower mantle. Each of the structural layers has its own visual pattern of density heterogeneity.

Topographic mapping of oxygen extraction and cerebral venous blood volume fraction in Brain tumors using quantitative BOLD: A case report

Background: While oxygen extraction fraction (OEF) reflects the underlying variations in cerebral brain oxygen metabolism, tissue voxels having elevated volume fraction of blood vessel network with deoxygenated blood, will apparently contribute to higher cerebral venous blood volume fraction (CVBVF). This Case report examines the difference in intra and peri-tumoral topographical patterns of OEF and CVBVF in cases of a meningioma tumor (Case-I) and a low- grade glioma (Case-II). Methods: Using a “static dephasing regime” BOLD model, we use the BOLD signal model containing parameters representing OEF and CVBVF. For each voxel in the region of interest, the parameters are solved by non-linearly fitting the signal model using paired differences between logarithms of the measured echo signal after inhomogeneity correction. Results: OEF and CVBVF maps in Case-I reveals an interesting phenomenon in the peritumoral parenchyma showing reduced OEF and increased CVBVF levels. The uniformly low CVBVF and elevated OEF in Case-II indicates that even with less density of vasculature, the region extracts higher amount of oxygen. Conclusion: While topographic mapping using qBOLD revealed elevated levels of intra-tumoral OEF for both cases, the pattern of CVBVF variation was uniformly low in Case-II.