Iterative 3D projection reconstruction of 23 Na data with an 1 H MRI constraint

Accelerated multiple-quantum-filtered sodium magnetic resonance imaging using compressed sensing at 7 T

PURPOSE

Multiple-quantum-filtered (MQF) sodium magnetic resonance imaging (MRI), such as enhanced single-quantum and triple-quantum-filtered imaging of 23Na (eSISTINA), enables images to be weighted towards restricted sodium, a promising biomarker in clinical practice, but often suffers from clinically infeasible acquisition times and low image quality. This study aims to mitigate the above limitation by implementing a novel eSISTINA sequence at 7 T with the application of compressed sensing (CS) to accelerate eSISTINA acquisitions without a noticeable loss of information.

METHODS

A novel eSISTINA sequence with a 3D spiral-based sampling scheme was implemented at 7 T for the application of CS. Fully sampled datasets were obtained from one phantom and ten healthy subjects, and were then retrospectively undersampled by various undersampling factors. CS undersampled reconstructions were compared to fully sampled and undersampled nonuniform fast Fourier transform (NUFFT) reconstructions. Reconstruction performance was evaluated based on structural similarity (SSIM), signal-to-noise ratio (SNR), weightings towards total and compartmental sodium, and in vivo quantitative estimates.

RESULTS

CS-based phantom and in vivo images have less noise and better structural delineation while maintaining the weightings towards total, non-restricted (predominantly extracellular), and restricted (primarily intracellular) sodium. CS generally outperforms NUFFT with a higher SNR and a better SSIM, except for the SSIM in TQ brain images, which is likely due to substantial noise contamination. CS enables in vivo quantitative estimates with <15% errors at an undersampling factor of up to two.

CONCLUSIONS

Successful implementation of an eSISTINA sequence with an incoherent sampling scheme at 7 T was demonstrated. CS can accelerate eSISTINA by up to twofold at 7 T with reduced noise levels compared to NUFFT, while maintaining major structural information, reasonable weightings towards total and compartmental sodium, and relatively reliable in vivo quantification. The associated reduction in acquisition time has the potential to facilitate the clinical applicability of MQF sodium MRI.

Recent technical developments and clinical research applications of sodium (23Na) MRI

Sodium is an essential ion that plays a central role in many physiological processes including the transmembrane electrochemical gradient and the maintenance of the body's homeostasis. Due to the crucial role of sodium in the human body, the sodium nucleus is a promising candidate for non-invasively assessing (patho-)physiological changes. Almost 10 years ago, Madelin et al. provided a comprehensive review of methods and applications of sodium (23Na) MRI (Madelin et al., 2014) [1]. More recent review articles have focused mainly on specific applications of 23Na MRI. For example, several articles covered 23Na MRI applications for diseases such as osteoarthritis (Zbyn et al., 2016, Zaric et al., 2020) [2,3], multiple sclerosis (Petracca et al., 2016, Huhn et al., 2019) [4,5] and brain tumors (Schepkin, 2016) [6], or for imaging certain organs such as the kidneys (Zollner et al., 2016) [7], the brain (Shah et al., 2016, Thulborn et al., 2018) [8,9], and the heart (Bottomley, 2016) [10]. Other articles have reviewed technical developments such as radiofrequency (RF) coils for 23Na MRI (Wiggins et al., 2016, Bangerter et al., 2016) [11,12], pulse sequences (Konstandin et al., 2014) [13], image reconstruction methods (Chen et al., 2021) [14], and interleaved/simultaneous imaging techniques (Lopez Kolkovsky et al., 2022) [15]. In addition, 23Na MRI topics have been covered in review articles with broader topics such as multinuclear MRI or ultra-high-field MRI (Niesporek et al., 2019, Hu et al., 2019, Ladd et al., 2018) [16-18]. During the past decade, various research groups have continued working on technical improvements to sodium MRI and have investigated its potential to serve as a diagnostic and prognostic tool. Clinical research applications of 23Na MRI have covered a broad spectrum of diseases, mainly focusing on the brain, cartilage, and skeletal muscle (see Fig. 1). In this article, we aim to provide a comprehensive summary of methodological and hardware developments, as well as a review of various clinical research applications of sodium (23Na) MRI in the last decade (i.e., published from the beginning of 2013 to the end of 2022).

Influence of image contrasts and reconstruction methods on the classification of multiple sclerosis-like lesions in simulated sodium magnetic resonance imaging

PURPOSE

To evaluate the classifiability of small multiple sclerosis (MS)-like lesions in simulated sodium (²³ Na) MRI for different ²³ Na MRI contrasts and reconstruction methods.

METHODS

²³ Na MRI and ²³ Na inversion recovery (IR) MRI of a phantom and simulated brain with and without lesions of different volumes (V = 1.3-38.2 nominal voxels) were simulated 100 times by adding Gaussian noise matching the SNR of real 3T measurements. Each simulation was reconstructed with four different reconstruction methods (Gridding without and with Hamming filter, Compressed sensing (CS) reconstruction without and with anatomical ¹ H prior information). Based on the mean signals within the lesion volumes of simulations with and without lesions, receiver operating characteristics (ROC) were determined and the area under the curve (AUC) was calculated to assess the classifiability for each lesion volume.

RESULTS

Lesions show higher classifiability in ²³ Na MRI than in ²³ Na IR MRI. For typical parameters and SNR of a 3T scan, the voxel normed minimal classifiable lesion volume (AUC > 0.9) is 2.8 voxels for ²³ Na MRI and 19 voxels for ²³ Na IR MRI, respectively. In terms of classifiability, Gridding with Hamming filter and CS without anatomical ¹ H prior outperform CS reconstruction with anatomical ¹ H prior.

CONCLUSION

Reliability of lesion classifiability strongly depends on the lesion volume and the ²³ Na MRI contrast. Additional incorporation of ¹ H prior information in the CS reconstruction was not beneficial for the classification of small MS-like lesions in ²³ Na MRI.

Clinically feasible B1 field correction for multi-organ sodium imaging at 3 T

Sodium MRI allows the non-invasive quantification of intra-organ sodium concentration. RF inhomogeneity introduces uncertainty in this estimated concentration. B₁ field corrections can be used to overcome some of these limitations. However, the low signal-to-noise ratio in sodium MRI makes accurate B₁ mapping in reasonable scan times challenging. The study aims to evaluate Bloch-Siegert off-resonance (BLOSI) B₁ field correction for sodium MRI using a 3D Fermat looped, orthogonally encoded trajectories (FLORET) read-out trajectory. We propose a clinically feasible B₁ field map correction method for sodium imaging at 3 T, evaluating five healthy subjects' brain, heart blood, kidneys, and thigh muscle. We scanned the subjects twice for repeatability measures and used sodium phantoms to determine organ total sodium concentration. Conventional proton scans were compared with sodium images for organ structural integrity. The BLOSI approach based on the 3D FLORET read-out trajectory was used in B₁ field correction and 3D density-adapted radial acquisition for sodium imaging. Results indicate improvements in sodium imaging based on B₁ field correction in a clinically feasible protocol. Improvements are determined in all organs by enhanced anatomical representation, organ homogeneity, and an increase in the total sodium concentration after applying a B₁ field correction. The proposed BLOSI-based B₁ field correction using a 3D FLORET read-out trajectory is clinically feasible for sodium imaging, which is shown in the brain, heart, kidney, and thigh muscle. This supports using fast B₁ field mapping in the clinical setting.

Arterial spin labeling MR image denoising and reconstruction using unsupervised deep learning

Arterial spin labeling (ASL) imaging is a powerful magnetic resonance imaging technique that allows to quantitatively measure blood perfusion non-invasively, which has great potential for assessing tissue viability in various clinical settings. However, the clinical applications of ASL are currently limited by its low signal-to-noise ratio (SNR), limited spatial resolution, and long imaging time. In this work, we propose an unsupervised deep learning-based image denoising and reconstruction framework to improve the SNR and accelerate the imaging speed of high resolution ASL imaging. The unique feature of the proposed framework is that it does not require any prior training pairs but only the subject's own anatomical prior, such as T1-weighted images, as network input. The neural network was trained from scratch in the denoising or reconstruction process, with noisy images or sparely sampled k-space data as training labels. Performance of the proposed method was evaluated using in vivo experiment data obtained from 3 healthy subjects on a 3T MR scanner, using ASL images acquired with 44-min acquisition time as the ground truth. Both qualitative and quantitative analyses demonstrate the superior performance of the proposed txtc framework over the reference methods. In summary, our proposed unsupervised deep learning-based denoising and reconstruction framework can improve the image quality and accelerate the imaging speed of ASL imaging.

Enhancing the spatial resolution of hyperpolarized carbon-13 MRI of human brain metabolism using structure guidance

PURPOSE

Dynamic nuclear polarization is an emerging imaging method that allows noninvasive investigation of tissue metabolism. However, the relatively low metabolic spatial resolution that can be achieved limits some applications, and improving this resolution could have important implications for the technique.

METHODS

We propose to enhance the 3D resolution of carbon-13 magnetic resonance imaging (13 C-MRI) using the structural information provided by hydrogen-1 MRI (1 H-MRI). The proposed approach relies on variational regularization in 3D with a directional total variation regularizer, resulting in a convex optimization problem which is robust with respect to the parameters and can efficiently be solved by many standard optimization algorithms. Validation was carried out using an in silico phantom, an in vitro phantom and in vivo data from four human volunteers.

RESULTS

The clinical data used in this study were upsampled by a factor of 4 in-plane and by a factor of 15 out-of-plane, thereby revealing occult information. A key finding is that 3D super-resolution shows superior performance compared to several 2D super-resolution approaches: for example, for the in silico data, the mean-squared-error was reduced by around 40% and for all data produced increased anatomical definition of the metabolic imaging.

CONCLUSION

The proposed approach generates images with enhanced anatomical resolution while largely preserving the quantitative measurements of metabolism. Although the work requires clinical validation against tissue measures of metabolism, it offers great potential in the field of 13 C-MRI and could significantly improve image quality in the future.

Compressed Sensing in Sodium Magnetic Resonance Imaging: Techniques, Applications, and Future Prospects

Sodium (²³ Na) yields the second strongest nuclear magnetic resonance (NMR) signal in biological tissues and plays a vital role in cell physiology. Sodium magnetic resonance imaging (MRI) can provide insights into cell integrity and tissue viability relative to pathologies without significant anatomical alternations, and thus it is considered to be a potential surrogate biomarker that provides complementary information for standard hydrogen (¹ H) MRI in a noninvasive and quantitative manner. However, sodium MRI suffers from a relatively low signal-to-noise ratio and long acquisition times due to its relatively low NMR sensitivity. Compressed sensing-based (CS-based) methods have been shown to accelerate sodium imaging and/or improve sodium image quality significantly. In this manuscript, the basic concepts of CS and how CS might be applied to improve sodium MRI are described, and the historical milestones of CS-based sodium MRI are briefly presented. Representative advanced techniques and evaluation methods are discussed in detail, followed by an expose of clinical applications in multiple anatomical regions and diseases as well as thoughts and suggestions on potential future research prospects of CS in sodium MRI. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 1.

Assessment of Low-Grade Focal Cartilage Lesions in the Knee With Sodium MRI at 7 T: Reproducibility and Short-Term, 6-Month Follow-up Data

OBJECTIVES

Several articles have investigated potential of sodium (Na) magnetic resonance imaging (MRI) for the in vivo evaluation of cartilage health, but so far no study tested its feasibility for the evaluation of focal cartilage lesions of grade 1 or 2 as defined by the International Cartilage Repair Society. The aims of this study were to evaluate the ability of Na-MRI to differentiate between early focal lesions and normal-appearing cartilage, to evaluate within-subject reproducibility of Na-MRI, and to monitor longitudinal changes in participants with low-grade, focal chondral lesions.

MATERIALS AND METHODS

Thirteen participants (mean age, 50.1 ± 10.9 years; 7 women, 6 men) with low-grade, focal cartilage lesions in the weight-bearing region of femoral cartilage were included in this prospective cohort study. Participants were assessed at baseline, 1 week, 3 months, and 6 months using morphological MRI at 3 T and 7 T, compositional Na-MRI at 7 T, and the Knee Injury and Osteoarthritis Outcome Score (KOOS) questionnaire. Na signal intensities corrected for coil sensitivity and partial volume effect (Na-cSI) were calculated in the lesion, and in weight-bearing and non-weight-bearing regions of healthy femoral cartilage. Coefficients of variation, repeated measures analysis of covariance models, and Pearson correlation coefficients were calculated to evaluate within-subject reproducibility as well as cross-sectional and longitudinal changes in Na-cSI values.

RESULTS

The mean coefficients of variation of Na-cSI values between the baseline and 1-week follow-up were 5.1% or less in all cartilage regions. Significantly lower Na-cSI values were observed in lesion than in weight-bearing and non-weight-bearing regions at all time points (all P values ≤ 0.002). Although a significant decrease from baseline Na-cSI values in lesion was found at 3-month visit (P = 0.015), no substantial change was observed at 6 months. KOOS scores have improved in all subscales at 3 months and 6 months visit, with a significant increase observed only in the quality of life subscale (P = 0.004).

CONCLUSIONS

In vivo Na-MRI is a robust and reproducible method that allows to differentiate between low-grade, focal cartilage lesions and normal-appearing articular cartilage, which supports the concept that compositional cartilage changes can be found early, before the development of advanced morphological changes visible at clinical 3-T MRI.

23 Na MRI in ischemic stroke: Acquisition time reduction using postprocessing with convolutional neural networks

Quantitative ²³ Na magnetic resonance imaging (MRI) provides tissue sodium concentration (TSC), which is connected to cell viability and vitality. Long acquisition times are one of the most challenging aspects for its clinical establishment. K-space undersampling is an approach for acquisition time reduction, but generates noise and artifacts. The use of convolutional neural networks (CNNs) is increasing in medical imaging and they are a useful tool for MRI postprocessing. The aim of this study is ²³ Na MRI acquisition time reduction by k-space undersampling. CNNs were applied to reduce the resulting noise and artifacts. A retrospective analysis from a prospective study was conducted including image datasets from 46 patients (aged 72 ± 13 years; 25 women, 21 men) with ischemic stroke; the ²³ Na MRI acquisition time was 10 min. The reconstructions were performed with full dataset (FI) and with a simulated dataset an image that was acquired in 2.5 min (RI). Eight different CNNs with either U-Net-based or ResNet-based architectures were implemented with RI as input and FI as label, using batch normalization and the number of filters as varying parameters. Training was performed with 9500 samples and testing included 400 samples. CNN outputs were evaluated based on signal-to-noise ratio (SNR) and structural similarity (SSIM). After quantification, TSC error was calculated. The image quality was subjectively rated by three neuroradiologists. Statistical significance was evaluated by Student's t-test. The average SNR was 21.72 ± 2.75 (FI) and 10.16 ± 0.96 (RI). U-Nets increased the SNR of RI to 43.99 and therefore performed better than ResNet. SSIM of RI to FI was improved by three CNNs to 0.91 ± 0.03. CNNs reduced TSC error by up to 15%. The subjective rating of CNN-generated images showed significantly better results than the subjective image rating of RI. The acquisition time of ²³ Na MRI can be reduced by 75% due to postprocessing with a CNN on highly undersampled data.

High-resolution sodium imaging using anatomical and sparsity constraints for denoising and recovery of novel features

PURPOSE

To develop and evaluate a novel method for reconstruction of high-quality sodium MR images from noisy, limited k-space data.

THEORY AND METHODS

A novel reconstruction method was developed for reconstruction of high-quality sodium images from noisy, limited k-space data. This method is based on a novel image model that contains a motion-compensated generalized series model and a sparse model. The motion-compensated generalized series model enables effective use of anatomical information from a proton image for denoising and resolution enhancement of sodium data, whereas the sparse model enables high-resolution reconstruction of sodium-dependent novel features. The underlying model estimation problems were solved efficiently using convex optimization algorithms.

RESULTS

The proposed method has been evaluated using both simulation and experimental data obtained from phantoms, healthy human volunteers, and tumor patients. Results showed a substantial improvement in spatial resolution and SNR over state-of-the-art reconstruction methods, including compressed sensing and anatomically constrained reconstruction methods. Quantitative tissue sodium concentration maps were obtained from both healthy volunteers and brain tumor patients. These tissue sodium concentration maps showed improved lesion fidelity and allowed accurate interrogation of small targets.

CONCLUSION

A new method has been developed to obtain high-resolution sodium images with good SNR at 3 T. The proposed method makes effective use of anatomical prior information for denoising, while using a sparse model synergistically to recover sodium-dependent novel features. Experimental results have been obtained to demonstrate the feasibility of achieving high-quality tissue sodium concentration maps and their potential for improved detection of spatially heterogeneous responses of tumor to treatment.

Compressed sensing and the use of phased array coils in 23Na MRI: a comparison of a SENSE-based and an individually combined multi-channel reconstruction

PURPOSE

To implement and to evaluate a compressed sensing (CS) reconstruction algorithm based on the sensitivity encoding (SENSE) combination scheme (CS-SENSE), used to reconstruct sodium magnetic resonance imaging (23Na MRI) multi-channel breast data sets.

METHODS

In a simulation study, the CS-SENSE algorithm was tested and optimized by evaluating the structural similarity (SSIM) and the normalized root-mean-square error (NRMSE) for different regularizations and different undersampling factors (USF=1.8/3.6/7.2/14.4). Subsequently, the algorithm was applied to data from in vivo measurements of the healthy female breast (n=3) acquired at 7T. Moreover, the proposed CS-SENSE algorithm was compared to a previously published CS algorithm (CS-IND).

RESULTS

The CS-SENSE reconstruction leads to an increased image quality for all undersampling factors and employed regularizations. Especially if a simple 2nd order total variation is chosen as sparsity transformation, the CS-SENSE reconstruction increases the image quality of highly undersampled data sets (CS-SENSE: SSIMUSF=7.2=0.234, NRMSEUSF=7.2=0.491 vs. CS-IND: SSIMUSF=7.2=0.201, NRMSEUSF=7.2=0.506).

CONCLUSION

The CS-SENSE reconstruction supersedes the need of CS weighting factors for each channel as well as a method to combine single channel data. The CS-SENSE algorithm can be used to reconstruct undersampled data sets with increased image quality. This can be exploited to reduce total acquisition times in 23Na MRI.

Towards accelerated quantitative sodium MRI at 7 T in the skeletal muscle: Comparison of anisotropic acquisition- and compressed sensing techniques

PURPOSE

To compare three anisotropic acquisition schemes and three compressed sensing (CS) approaches for accelerated tissue sodium concentration (TSC) quantification using ²³Na MRI at 7 T.

MATERIALS AND METHODS

Three anisotropic 3D-radial acquisition sequences were evaluated using simulations, phantom- and in vivo TSC measurements: An anisotropic density-adapted 3D-radial sequence (3DPR-C), a 3D acquisition-weighted density-adapted stack-of-stars sampling scheme (SOS) and a SOS approach with golden-ratio rotation (SOS-GR). Eight healthy volunteers were examined at a 7 Tesla MRI system. TSC measurements of the calf were conducted with a nominal spatial resolution of Δx = (3.0 × 3.0 × 15.0) mm³ and a field of view of (156.0 × 156.0 × 240.0) mm³ for multiple undersampling factors (USF). Three CS reconstructions were evaluated: Total variation CS (TV-CS), 3D dictionary-learning compressed sensing (3D-DLCS) and TV-CS with a block matching prior (TV-BL-CS). Results of the simulations and measurements were compared to a simulated ground truth (GT) or a fully sampled reference measurement (FS), respectively. The deviation of the mean TSC evaluated in multiple ROI (mE_GT/FS) and the normalized root-mean-squared error (NRMSE) for simulations were evaluated for CS and NUFFT reconstructions.

RESULTS

In simulations, the SOS-GR yielded the lowest NRMSE and mE_GT (< 4%) with NUFFT for an acquisition time (TA) of less than 2 min. CS further improved the results. In simulations and measurements, the best TSC quantification results were obtained with 3D-DLCS and SOS-GR (lowest NRMSE, mE_GT < 2.6% in simulations, mE_GT < 10.7% for phantom measurements and mE_FS < 6% in vivo) with an USF = 4.1 (TA < 2 min). TV-CS showed no or only slight improvements to NUFFT. The results of TV-BL-CS were similar to 3D-DLCS.

DISCUSSION

The TA for TSC measurements could be reduced to less than 2 min by using adapted sequences such as SOS-GR and CS reconstruction approaches such as 3D-DLCS or TV-BL-CS, while the quantitative accuracy stays comparable to a fully sampled NUFFT reconstruction (approx. 8 min TA). In future, the lower TA could improve clinical applicability of TSC measurements.

Potential of Sodium MRI as a Biomarker for Neurodegeneration and Neuroinflammation in Multiple Sclerosis

In multiple sclerosis (MS), experimental and ex vivo studies indicate that pathologic intra- and extracellular sodium accumulation may play a pivotal role in inflammatory as well as neurodegenerative processes. Yet, in vivo assessment of sodium in the microenvironment is hard to achieve. Here, sodium magnetic resonance imaging (²³NaMRI) with its non-invasive properties offers a unique opportunity to further elucidate the effects of sodium disequilibrium in MS pathology in vivo in addition to regular proton based MRI. However, unfavorable physical properties and low in vivo concentrations of sodium ions resulting in low signal-to-noise-ratio (SNR) as well as low spatial resolution resulting in partial volume effects limited the application of ²³NaMRI. With the recent advent of high-field MRI scanners and more sophisticated sodium MRI acquisition techniques enabling better resolution and higher SNR, ²³NaMRI revived. These studies revealed pathologic total sodium concentrations in MS brains now even allowing for the (partial) differentiation of intra- and extracellular sodium accumulation. Within this review we (1) demonstrate the physical basis and imaging techniques of ²³NaMRI and (2) analyze the present and future clinical application of ²³NaMRI focusing on the field of MS thus highlighting its potential as biomarker for neuroinflammation and -degeneration.

Pros and cons of ultra-high-field MRI/MRS for human application

Magnetic resonance imaging and spectroscopic techniques are widely used in humans both for clinical diagnostic applications and in basic research areas such as cognitive neuroimaging. In recent years, new human MR systems have become available operating at static magnetic fields of 7 T or higher (≥300 MHz proton frequency). Imaging human-sized objects at such high frequencies presents several challenges including non-uniform radiofrequency fields, enhanced susceptibility artifacts, and higher radiofrequency energy deposition in the tissue. On the other side of the scale are gains in signal-to-noise or contrast-to-noise ratio that allow finer structures to be visualized and smaller physiological effects to be detected. This review presents an overview of some of the latest methodological developments in human ultra-high field MRI/MRS as well as associated clinical and scientific applications. Emphasis is given to techniques that particularly benefit from the changing physical characteristics at high magnetic fields, including susceptibility-weighted imaging and phase-contrast techniques, imaging with X-nuclei, MR spectroscopy, CEST imaging, as well as functional MRI. In addition, more general methodological developments such as parallel transmission and motion correction will be discussed that are required to leverage the full potential of higher magnetic fields, and an overview of relevant physiological considerations of human high magnetic field exposure is provided.

3D CMRO2 mapping in human brain with direct 17O MRI: Comparison of conventional and proton-constrained reconstructions

Oxygen metabolism is altered in brain tumor regions and is quantified by the cerebral metabolic rate of oxygen consumption (CMRO₂). Direct dynamic ¹⁷O MRI with inhalation of isotopically enriched ¹⁷O₂ gas can be used to quantify CMRO₂; however, pixel-wise CMRO₂ quantification in human brain is challenging due to low natural abundance of ¹⁷O isotope and, thus, the low signal-to-noise ratio (SNR) of ¹⁷O MR images. To test the feasibility CMRO₂ mapping at a clinical 3 T MRI system, a new iterative reconstruction was proposed, which uses the edge information contained in a co-registered ¹H gradient image to construct a non-homogeneous anisotropic diffusion (AD) filter. AD-constrained reconstruction of ¹⁷O MR images was compared to conventional Kaiser-Bessel gridding without and with Hanning filtering, and to iterative reconstruction with a total variation (TV) constraint. For numerical brain phantom and in two in vivo data sets of one healthy volunteer, AD-constrained reconstruction provided ¹⁷O images with improved resolution of fine brain structures and resulted in higher SNR. CMRO₂ values of 0.78 - 1.55µmol/g_tissue/min (white brain matter) and 1.03 - 2.01µmol/g_tissue/min (gray brain matter) as well as the CMRO₂ maps are in a good agreement with the results of ¹⁵O-PET and ¹⁷O MRI at 7 T and at 9.4 T. In conclusion, the proposed AD-constrained reconstruction enabled calculation of 3D CMRO₂ maps at 3 T MRI system, which is an essential step towards clinical translation of ¹⁷O MRI for non-invasive CMRO₂ quantification in tumor patients.

Quantification of oxygen metabolic rates in Human brain with dynamic 17 O MRI: Profile likelihood analysis

PURPOSE

Parameter identifiability and confidence intervals were determined using a profile likelihood (PL) analysis method in a quantification model of the cerebral metabolic rate of oxygen consumption (CMRO₂ ) with direct ¹⁷ O MRI.

METHODS

Three-dimensional dynamic ¹⁷ O MRI datasets of the human brain were acquired after inhalation of ¹⁷ O₂ gas with the help of a rebreathing system, and CMRO₂ was quantified with a pharmacokinetic model. To analyze the influence of the different model parameters on the identifiability of CMRO₂ , PLs were calculated for different settings of the model parameters. In particular, the ¹⁷ O enrichment fraction of the inhaled ¹⁷ O₂ gas, α, was investigated assuming a constant and a linearly varying model. Identifiability was analyzed for white and gray matter, and the dependency on different priors was studied.

RESULTS

Prior knowledge about only one α-related parameter was sufficient to resolve the CMRO₂ nonidentifiability, and CMRO₂ rates (0.72-0.99 µmol/g_tissue /min in white matter, 1.02-1.78 µmol/g_tissue /min in gray matter) are in a good agreement with the results of ¹⁵ O positron emission tomography studies. Nonconstant α values significantly improved model fitting.

CONCLUSION

The profile likelihood analysis shows that CMRO₂ can be measured reliably in ¹⁷ O gas MRI experiment if the ¹⁷ O enrichment fraction is used as prior information for the model calculations. Magn Reson Med 78:1157-1167, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

W(h)ither human cardiac and body magnetic resonance at ultrahigh fields? technical advances, practical considerations, applications, and clinical opportunities

The objective of this study was to document and review advances and groundbreaking progress in cardiac and body MR at ultrahigh fields (UHF, B0 ≥ 7.0 T) with the goal to attract talent, clinical adopters, collaborations and resources to the biomedical and diagnostic imaging communities. This review surveys traits, advantages and challenges of cardiac and body MR at 7.0 T. The considerations run the gamut from technical advances to clinical opportunities. Key concepts, emerging technologies, practical considerations, frontier applications and future directions of UHF body and cardiac MR are provided. Examples of UHF cardiac and body imaging strategies are demonstrated. Their added value over the kindred counterparts at lower fields is explored along with an outline of research promises. The achievements of cardiac and body UHF-MR are powerful motivators and enablers, since extra speed, signal and imaging capabilities may be invested to overcome the fundamental constraints that continue to hamper traditional cardiac and body MR applications. If practical obstacles, concomitant physics effects and technical impediments can be overcome in equal measure, sophisticated cardiac and body UHF-MR will help to open the door to new MRI and MRS approaches for basic research and clinical science, with the lessons learned at 7.0 T being transferred into broad clinical use including diagnostics and therapy guiding at lower fields. Copyright © 2015 John Wiley & Sons, Ltd.

Imaging of sodium in the brain: a brief review

Sodium-based MRI plays a vital role in the study of metabolism and can unveil valuable information about emerging and existing pathology--in particular in the human brain. Sodium is the second most abundant MR active nucleus in living tissue and, due to its quadrupolar nature, has magnetic properties not common to conventional proton MRI, which can reveal further insights, such as information on the compartmental distribution of intra- and extracellular sodium. Nevertheless, the use of sodium nuclei for imaging comes at the expense of a lower sensitivity and significantly reduced relaxation times, making in vivo sodium studies feasible only at high magnetic field strength and by the use of dedicated pulse sequences. Hybrid imaging combining sodium MRI and positron emission tomography (PET) simultaneously is a novel and promising approach to access information on dynamic metabolism with much increased, PET-derived specificity. Application of this new methodology is demonstrated herein using examples from tumour imaging.

Magnetic resonance spectroscopic imaging at superresolution: Overview and perspectives

The notion of non-invasive, high-resolution spatial mapping of metabolite concentrations has long enticed the medical community. While magnetic resonance spectroscopic imaging (MRSI) is capable of achieving the requisite spatio-spectral localization, it has traditionally been encumbered by significant resolution constraints that have thus far undermined its clinical utility. To surpass these obstacles, research efforts have primarily focused on hardware enhancements or the development of accelerated acquisition strategies to improve the experimental sensitivity per unit time. Concomitantly, a number of innovative reconstruction techniques have emerged as alternatives to the standard inverse discrete Fourier transform (DFT). While perhaps lesser known, these latter methods strive to effect commensurate resolution gains by exploiting known properties of the underlying MRSI signal in concert with advanced image and signal processing techniques. This review article aims to aggregate and provide an overview of the past few decades of so-called "superresolution" MRSI reconstruction methodologies, and to introduce readers to current state-of-the-art approaches. A number of perspectives are then offered as to the future of high-resolution MRSI, with a particular focus on translation into clinical settings.

Enhancing the quantification of tissue sodium content by MRI: time-efficient sodium B1 mapping at clinical field strengths

Tissue sodium content (TSC) is a sensitive measure of pathological changes and can be detected non-invasively by MRI. For the absolute quantification of TSC, B1 inhomogeneities must be corrected, which is not well established beyond research applications. An in-depth analysis of B1 mapping methods which are suitable for application in TSC quantification is presented. On the basis of these results, a method for simultaneous B1 mapping and imaging is proposed in order to enhance accuracy and to reduce measurement time at clinical field strengths. The B1 mapping techniques used were phase-sensitive (PS), Bloch-Siegert shift (BSS), double-angle (DAM) and actual flip-angle imaging (AFI) methods. Experimental and theoretical comparisons demonstrated that the PS technique yields the most accurate field profiles and exhibits the highest signal-to-noise ratio (SNR). Simultaneous B1 mapping and imaging was performed for the PS method, employing both degrees of freedom of the MR signal: the B1 field is encoded into signal phase and the amplitude provides the concentration information. In comparison with the more established DAM, a 13% higher SNR was obtained and field effects could be corrected more accurately without the need for additional measurement time. The protocol developed was applied to measure TSC in the healthy human head at an isotropic resolution of 4 mm. TSC was determined to be 35 ± 1 mM in white matter and 134 ± 3 mM in vitreous humor. By employing the proposed simultaneous characterization of the B1 field and acquisition of the spin density-weighted sodium signal, the accuracy of the non-invasive measurement of TSC is enhanced and the measurement time is reduced. This should allow (23)Na MRI to be better incorporated into clinical studies and routine.

Sodium-23 MRI of whole spine at 3 Tesla using a 5-channel receive-only phased-array and a whole-body transmit resonator

Sodium magnetic resonance imaging ((23)Na MRI) is a unique and non-invasive imaging technique which provides important information on cellular level about the tissue of the human body. Several applications for (23)Na MRI were investigated with regard to the examination of the tissue viability and functionality for example in the brain, the heart or the breast. The (23)Na MRI technique can also be integrated as a potential monitoring instrument after radiotherapy or chemotherapy. The main contribution in this work was the adaptation of (23)Na MRI for spine imaging, which can provide essential information on the integrity of the intervertebral disks with respect to the early detection of disk degeneration. In this work, a transmit-only receive-only dual resonator system was designed and developed to cover the whole human spine using (23)Na MRI and increase the receive sensitivity. The resonator system consisted of an already presented (23)Na whole-body resonator and a newly developed 5-channel receive-only phased-array. The resonator system was first validated using bench top and phantom measurements. A threefold SNR improvement at the depth of the spine (∼7cm) over the whole-body resonator was achieved using the spine array. (23)Na MR measurements of the human spine using the transmit-only receive-only resonator system were performed on a healthy volunteer within an acquisition time of 10minutes. A density adapted 3D radial sequence was chosen with 6mm isotropic resolution, 49ms repetition time and a short echo time of 540μs. Furthermore, it was possible to quantify the tissue sodium concentration in the intervertebral discs in the lumbar region (120ms repetition time) using this setup.

Anatomically weighted second-order total variation reconstruction of 23Na MRI using prior information from 1H MRI

Sodium ((23)Na) MRI is a noninvasive tool to assess cell viability, which is linked to the total tissue sodium concentration (TSC). However, due to low in vivo concentrations, (23)Na MRI suffers from low signal-to-noise ratio (SNR) and limited spatial resolution. As a result, image quality is compromised by Gibbs ringing artifacts and partial volume effects. An iterative reconstruction algorithm that incorporates prior information from (1)H MRI is developed to reduce partial volume effects and to increase the SNR in non-proton MRI. Anatomically weighted second-order total variation (AnaWeTV) is proposed as a constraint for compressed sensing reconstruction of 3D projection reconstruction (3DPR) data. The method is evaluated in simulations and a MR measurement of a multiple sclerosis (MS) patient by comparing it to gridding and other reconstruction techniques. AnaWeTV increases resolution of known structures and reduces partial volume effects. In simulated MR brain data (nominal resolution Δx(3) = 3 × 3 × 3 mm(3)), the intensity error of four small MS lesions was reduced from (6.9 ± 3.8)% (gridding) to (2.8 ± 1.4)% (AnaWeTV with T2-weighted reference images). Compared to gridding, a substantial SNR increase of 130% was found in the white matter of the MS patient. The algorithm is robust against misalignment of the prior information on the order of the (23)Na image resolution. Features without prior information are still reconstructed with high contrast. AnaWeTV allows a more precise quantification of TSC in structures with prior knowledge. Thus, the AnaWeTV algorithm is in particular beneficial for the assessment of tissue structures that are visible in both (23)Na and (1)H MRI.