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

Sodium triple quantum MR signal extraction using a single-pulse sequence with single quantum time efficiency

PURPOSE

Sodium triple quantum (TQ) signal has been shown to be a valuable biomarker for cell viability. Despite its clinical potential, application of Sodium TQ signal is hindered by complex pulse sequences with long scan times. This study proposes a method to approximate the TQ signal using a single excitation pulse without phase cycling.

METHODS

The proposed method is based on a single excitation pulse and a comparison of the free induction decay (FID) with the integral of the FID combined with a shifting reconstruction window. The TQ signal is calculated from this FID only. As a proof of concept, the method was also combined with a multi-echo UTE imaging sequence on a 9.4 T preclinical MRI scanner for the possibility of fast TQ MRI.

RESULTS

The extracted Sodium TQ signals of single-pulse and spin echo FIDs were in close agreement with theory and TQ measurement by traditional three-pulse sequence (TQ time proportional phase increment [TQTPPI)]. For 2%, 4%, and 6% agar samples, the absolute deviations of the maximum TQ signals between SE and theoretical (time proportional phase increment TQTPPI) TQ signals were less than 1.2% (2.4%), and relative deviations were less than 4.6% (6.8%). The impact of multi-compartment systems and noise on the accuracy of the TQ signal was small for simulated data. The systematic error was <3.4% for a single quantum (SQ) SNR of 5 and at maximum <2.5% for a multi-compartment system. The method also showed the potential of fast in vivo SQ and TQ imaging.

CONCLUSION

Simultaneous SQ and TQ MRI using only a single-pulse sequence and SQ time efficiency has been demonstrated. This may leverage the full potential of the Sodium TQ signal in clinical applications.

Rapid 2D 23Na MRI of the calf using a denoising convolutional neural network

PURPOSE

23Na MRI can be used to quantify in-vivo tissue sodium concentration (TSC), but the inherently low 23Na signal leads to long scan times and/or noisy or low-resolution images. Reconstruction algorithms such as compressed sensing (CS) have been proposed to mitigate low signal-to-noise ratio (SNR); although, these can result in unnatural images, suboptimal denoising and long processing times. Recently, machine learning has been increasingly used to denoise 1H MRI acquisitions; however, this approach typically requires large volumes of high-quality training data, which is not readily available for 23Na MRI. Here, we propose using 1H data to train a denoising convolutional neural network (CNN), which we subsequently demonstrate on prospective 23Na images of the calf.

METHODS

1893 1H fat-saturated transverse slices of the knee from the open-source fastMRI dataset were used to train denoising CNNs for different levels of noise. Synthetic low SNR images were generated by adding gaussian noise to the high-quality 1H k-space data before reconstruction to create paired training data. For prospective testing, 23Na images of the calf were acquired in 10 healthy volunteers with a total of 150 averages over ten minutes, which were used as a reference throughout the study. From this data, images with fewer averages were retrospectively reconstructed using a non-uniform fast Fourier transform (NUFFT) as well as CS, with the NUFFT images subsequently denoised using the trained CNN.

RESULTS

CNNs were successfully applied to 23Na images reconstructed with 50, 40 and 30 averages. Muscle and skin apparent TSC quantification from CNN-denoised images were equivalent to those from CS images, with <0.9 mM bias compared to reference values. Estimated SNR was significantly higher in CNN-denoised images compared to NUFFT, CS and reference images. Quantitative edge sharpness was equivalent for all images. For subjective image quality ranking, CNN-denoised images ranked equally best with reference images and significantly better than NUFFT and CS images.

CONCLUSION

Denoising CNNs trained on 1H data can be successfully applied to 23Na images of the calf; thus, allowing scan time to be reduced from ten minutes to two minutes with little impact on image quality or apparent TSC quantification accuracy.

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.

Multidimensional compressed sensing to advance 23 Na multi-quantum coherences MRI

PURPOSE

Sodium (23 Na) multi-quantum coherences (MQC) MRI was accelerated using three-dimensional (3D) and a dedicated five-dimensional (5D) compressed sensing (CS) framework for simultaneous Cartesian single (SQ) and triple quantum (TQ) sodium imaging of in vivo human brain at 3.0 and 7.0 T.

THEORY AND METHODS

3D 23 Na MQC MRI requires multi-echo paired with phase-cycling and exhibits thus a multidimensional space. A joint reconstruction framework to exploit the sparsity in all imaging dimensions by extending the conventional 3D CS framework to 5D was developed. 3D MQC images of simulated brain, phantom and healthy brain volunteers obtained from 3.0 T and 7.0 T were retrospectively and prospectively undersampled. Performance of the CS models were analyzed by means of structural similarity index (SSIM), root mean squared error (RMSE), signal-to-noise ratio (SNR) and signal quantification of tissue sodium concentration and TQ/SQ ratio.

RESULTS

It was shown that an acceleration of three-fold, leading to less than2 × 10 $$ 2\times 10 $$ min of scan time with a resolution of8 × 8 × 20   mm 3 $$ 8\times 8\times 20\;{\mathrm{mm}}^3 $$ at 3.0 T, are possible. 5D CS improved SSIM by 3%, 5%, 1% and reduced RMSE by 50%, 30%, 8% for in vivo SQ, TQ, and TQ/SQ ratio maps, respectively. Furthermore, for the first time prospective undersampling enabled unprecedented high resolution from8 × 8 × 20   mm 3 $$ 8\times 8\times 20\;{\mathrm{mm}}^3 $$ to6 × 6 × 10   mm 3 $$ 6\times 6\times 10\;{\mathrm{mm}}^3 $$ MQC images of in vivo human brain at 7.0 T without extending acquisition time.

CONCLUSION

5D CS proved to allow up to three-fold acceleration retrospectively on 3.0 T data. 2-fold acceleration was demonstrated prospectively at 7.0 T to reach higher spatial resolution of 23 Na MQC 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).

MR-Nucleomics: The study of pathological cellular processes with multinuclear magnetic resonance spectroscopy and imaging in vivo

Clinical medicine has experienced a rapid development in recent decades, during which therapies targeting specific cellular signaling pathways, or specific cell surface receptors, have been increasingly adopted. While these developments in clinical medicine call for improved precision in diagnosis and treatment monitoring, modern medical imaging methods are restricted mainly to anatomical imaging, lagging behind the requirements of precision medicine. Although positron emission tomography and single photon emission computed tomography have been used clinically for studies of metabolism, their applications have been limited by the exposure risk to ionizing radiation, the subsequent limitation in repeated and longitudinal studies, and the incapability in assessing downstream metabolism. Magnetic resonance spectroscopy (MRS) or spectroscopic imaging (MRSI) are, in theory, capable of assessing molecular activities in vivo, although they are often limited by sensitivity. Here, we review some recent developments in MRS and MRSI of multiple nuclei that have potential as molecular imaging tools in the clinic.

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.

An approach to evaluation of the point-spread function for 23 Na magnetic resonance imaging

Despite the technical challenges that require lengthy acquisitions to overcome poor signal-to-noise ratio (SNR), sodium (²³ Na) magnetic resonance imaging (MRI) is an intriguing area of research due to its essential role in human metabolism. Low SNR images can impact the measurement of the point-spread function (PSF) by adding uncertainty into the resulting quantities. Here, we present methods to calculate the PSF by using the modulation transfer function (MTF), and a 3D-printed line-pair phantom in the context of ²³ Na MRI. A simulation study investigated the effect of noise on the resulting MTF curves, which were derived by direct modulation (DM) and a method utilizing Fourier harmonics (FHs). Experimental data utilized a line-pair phantom with nine spatial frequencies, filled with different concentrations (15, 30, and 60 mM) of sodium in 3% agar. MTF curves were calculated using both methods from data acquired from density-adapted 3D radial projections (DA-3DRP) and Fermat looped orthogonally encoded trajectories (FLORET). Simulations indicated that the DM method increased variability in the MTF curves at all tested noise levels over the FH method. For the experimental data, the FH method resulted in PSFs with a narrower full width half maximum with reduced variability, although the improvement in variability was not as pronounced as predicted by simulations. The DA-3DRP data indicated an improvement in the PSF over FLORET. It was concluded that a 3D-printed line-pair phantom represents a convenient method to measure the PSF experimentally. The MTFs from the noisy images in ²³ Na MRI have reduced variability from a FH method over DM.

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.