Low-field MRI: An MR physics perspective

Ultra-low-field magnetization transfer imaging at 0.055T with low specific absorption rate

PURPOSE

To demonstrate magnetization transfer (MT) effects with low specific absorption rate (SAR) on ultra-low-field (ULF) MRI.

METHODS

MT imaging was implemented by using sinc-modulated RF pulse train (SPT) modules to provide bilateral off-resonance irradiation. They were incorporated into 3D gradient echo (GRE) and fast spin echo (FSE) protocols on a shielding-free 0.055T head scanner. MT effects were first verified using phantoms. Brain MT imaging was conducted in both healthy subjects and patients.

RESULTS

MT effects were clearly observed in phantoms using six SPT modules with total flip angle 3600° at central primary saturation bands of approximate offset ±786 Hz, even in the presence of large relative B0 inhomogeneity. For brain, strong MT effects were observed in gray matter, white matter, and muscle in 3D GRE and FSE imaging using six and sixteen SPT modules with total flip angle 3600° and 9600°, respectively. Fat, cerebrospinal fluid, and blood exhibited relatively weak MT effects. MT preparation enhanced tissue contrasts in T2-weighted and FLAIR-like images, and improved brain lesion delineation. The estimated MT SAR was 0.0024 and 0.0008 W/kg for two protocols, respectively, which is far below the US Food and Drug Administration (FDA) limit of 3.0 W/kg.

CONCLUSION

Robust MT effects can be readily obtained at ULF with extremely low SAR, despite poor relative B0 homogeneity in ppm. This unique advantage enables flexible MT pulse design and implementation on low-cost ULF MRI platforms to achieve strong MT effects in brain and beyond, potentially augmenting their clinical utility in the future.

Optimization and validation of low-field MP2RAGE T1 mapping on 0.35T MR-Linac: Toward adaptive dose painting with hypoxia biomarkers

BACKGROUND

Stereotactic MR-guided Adaptive Radiation Therapy (SMART) dose painting for hypoxia has potential to improve treatment outcomes, but clinical implementation on low-field MR-Linac faces substantial challenges due to dramatically lower signal-to-noise ratio (SNR) characteristics. While quantitative MRI and T1 mapping of hypoxia biomarkers show promise, T1-to-noise ratio (T1NR) optimization at low fields is paramount, particularly for the clinical implementation of oxygen-enhanced (OE)-MRI. The 3D Magnetization Prepared (2) Rapid Gradient Echo (MP2RAGE) sequence stands out for its ability to acquire homogeneous T1-weighted contrast images with simultaneous T1 mapping.

PURPOSE

To optimize MP2RAGE for low-field T1 mapping; conduct experimental validation in a ground-truth phantom; establish feasibility and reproducibility of low-field MP2RAGE acquisition and T1 mapping in healthy volunteers.

METHODS

The MP2RAGE optimization was performed to maximize the contrast-to-noise ratio (CNR) of T1 values in white matter (WM) and gray matter (GM) brain tissues at 0.35T. Low-field MP2RAGE images were acquired on a 0.35T MR-Linac (ViewRay MRIdian) using a multi-channel head coil. Validation of T1 mapping was performed with a ground-truth Eurospin phantom, containing inserts of known T1 values (400-850 ms), with one and two average (1A and 2A) MP2RAGE scans across four acquisition sessions, resulting in eight T1 maps. Mean (± SD) T1 relative error, T1NR, and intersession coefficient of variation (CV) were determined. Whole-brain MP2RAGE scans were acquired in 5 healthy volunteers across two sessions (A and B) and T1 maps were generated. Mean (± SD) T1 values for WM and GM were determined. Whole-brain T1 histogram analysis was performed, and reproducibility was determined with the CV between sessions. Voxel-by-voxel T1 difference maps were generated to evaluate 3D spatial variation.

RESULTS

Low-field MP2RAGE optimization resulted in parameters: MP2RAGETR of 3250 ms, inversion times (TI1/TI2) of 500/1200 ms, and flip angles (α1/α2) of 7/5°. Eurospin T1 maps exhibited a mean (± SD) relative error of 3.45% ± 1.30%, T1NR of 20.13 ± 5.31, and CV of 2.22% ± 0.67% across all inserts. Whole-brain MP2RAGE images showed high anatomical quality with clear tissue differentiation, resulting in mean (± SD) T1 values: 435.36 ± 10.01 ms for WM and 623.29 ± 14.64 ms for GM across subjects, showing excellent concordance with literature. Whole-brain T1 histograms showed high intrapatient and intersession reproducibility with characteristic intensity peaks consistent with voxel-level WM and GM T1 values. Reproducibility analysis revealed a CV of 0.46% ± 0.31% and 0.35% ± 0.18% for WM and GM, respectively. Voxel-by-voxel T1 difference maps show a normal 3D spatial distribution of noise in WM and GM.

CONCLUSIONS

Low-field MP2RAGE proved effective in generating accurate, reliable, and reproducible T1 maps with high T1NR in phantom studies and in vivo feasibility established in healthy volunteers. While current work is focused on refining the MP2RAGE protocol to enable clinically efficient OE-MRI, this study establishes a foundation for TOLD T1 mapping for hypoxia biomarkers. This advancement holds the potential to facilitate a paradigm shift toward MR-guided biological adaptation and dose painting by leveraging 3D hypoxic spatial distributions and improving outcomes in conventionally challenging-to-treat cancers.

Ultra-low-field magnetic resonance angiography at 0.05 T: A preliminary study

We aim to explore the feasibility of head and neck time-of-flight (TOF) magnetic resonance angiography (MRA) at ultra-low-field (ULF). TOF MRA was conducted on a highly simplified 0.05 T MRI scanner with no radiofrequency (RF) and magnetic shielding. A flow-compensated three-dimensional (3D) gradient echo (GRE) sequence with a tilt-optimized nonsaturated excitation RF pulse, and a flow-compensated multislice two-dimensional (2D) GRE sequence, were implemented for cerebral artery and vein imaging, respectively. For carotid artery and jugular vein imaging, flow-compensated 2D GRE sequences were utilized with venous and arterial blood presaturation, respectively. MRA was performed on young healthy subjects. Vessel-to-background contrast was experimentally observed with strong blood inflow effect and background tissue suppression. The large primary cerebral arteries and veins, carotid arteries, jugular veins, and artery bifurcations could be identified in both raw GRE images and maximum intensity projections. The primary brain and neck arteries were found to be reproducible among multiple examination sessions. These preliminary experimental results demonstrated the possibility of artery TOF MRA on low-cost 0.05 T scanners for the first time, despite the extremely low MR signal. We expect to improve the quality of ULF TOF MRA in the near future through sequence development and optimization, ongoing advances in ULF hardware and image formation, and the use of vascular T1 contrast agents.

Zero-echo-time sequences in highly inhomogeneous fields

PURPOSE

Zero-echo-time (ZTE) sequences have proven a powerful tool for MRI of ultrashortT 2 $$ {T}_2 $$ tissues, but they fail to produce useful images in the presence of strong field inhomogeneities (14 000 ppm). Here we seek a method to correct reconstruction artifacts from non-Cartesian acquisitions in highly inhomogeneousB 0 $$ {\mathrm{B}}_0 $$ , where the standard double-shot gradient-echo approach to field mapping fails.

METHODS

We present a technique based on magnetic field maps obtained from two geometric distortion-free point-wise (SPRITE) acquisitions. To this end, we employ three scanners with varying field homogeneities. These maps are used for model-based image reconstruction with iterative algebraic techniques (ART). For comparison, the same prior information is fed also to widely used Conjugate Phase (CP) algorithms.

RESULTS

Distortions and artifacts coming from severeB 0 $$ {\mathrm{B}}_0 $$ inhomogeneities, at the level of the encoding gradient, are largely reverted by our method, as opposed to CP reconstructions. This holds even close to the limit where intra-voxel bandwidths (determined byB 0 $$ {\mathrm{B}}_0 $$ inhomogeneities, up to 1.2 kHz) are comparable to the encoding inter-voxel bandwidth (determined by the gradient fields, 625 Hz in this work).

CONCLUSION

We have benchmarked the performance of a new method for ZTE imaging in highly inhomogeneous magnetic fields. For example, this can be exploited for dental imaging in affordable low-field MRI systems, and can be expanded for arbitrary pulse sequences and extreme magnet geometries, as in, for example, single-sided MRI.

Highly efficient image navigator based 3D whole-heart cardiac MRA at 0.55T

PURPOSE

To develop and evaluate a highly efficient free-breathing and contrast-agent-free three-dimensional (3D) whole-heart Cardiac Magnetic Resonance Angiography (CMRA) sequence at 0.55T.

METHODS

Free-breathing whole-heart CMRA has been previously proposed at 1.5 and 3T. Direct application of this sequence to 0.55T is not possible due to changes in the magnetic properties of the tissues. To enable free-breathing CMRA at 0.55T, pulse sequence design and acquisition parameters of a previously proposed whole-heart CMRA framework are optimized via Bloch simulations. Image navigators (iNAVs) are used to enable nonrigid respiratory motion-correction and 100% respiratory scan efficiency. Patch-based low-rank denoising is employed to accelerate the scan and account for the reduced signal-to-noise ratio at 0.55T. The proposed approach was evaluated on 11 healthy subjects. Image quality was assessed by a clinical expert (1: poor to 5: excellent) for all intrapericardiac structures. Quantitative evaluation was performed by assessing the vessel sharpness of the proximal right coronary artery (RCA).

RESULTS

Optimization resulted in an imaging flip angle of11 0 ∘ $$ 11{0}^{\circ } $$ , fat saturation flip angle of18 0 ∘ $$ 18{0}^{\circ } $$ , and six k-space lines for iNAV encoding. The relevant cardiac structures and main coronary arteries were visible in all subjects, with excellent image quality (mean4 . 9 / 5 . 0 $$ 4.9/5.0 $$ ) and minimal artifacts (mean4 . 9 / 5 . 0 $$ 4.9/5.0 $$ ), with RCA vessel sharpness (50 . 3 % ± 9 . 8 % $$ 50.3\%\pm 9.8\% $$ ) comparable to previous studies at 1.5T.

CONCLUSION

The proposed approach enables 3D whole-heart CMRA at 0.55T in a 6-min scan (5 . 9 ± 0 . 7   min $$ 5.9\pm 0.7\;\min $$ ), providing excellent image quality, minimal artifacts, and comparable vessel sharpness to previous 1.5T studies. Future work will include the evaluation of the proposed approach in patients with cardiovascular disease.

Improved liver fat and R 2 * quantification at 0.55 T using locally low-rank denoising

PURPOSE

To improve liver proton density fat fraction (PDFF) andR 2 * $$ {R}_2^{\ast } $$ quantification at 0.55 T by systematically validating the acquisition parameter choices and investigating the performance of locally low-rank denoising methods.

METHODS

A Monte Carlo simulation was conducted to design a protocol for PDFF andR 2 * $$ {R}_2^{\ast } $$ mapping at 0.55 T. Using this proposed protocol, we investigated the performance of robust locally low-rank (RLLR) and random matrix theory (RMT) denoising. In a reference phantom, we assessed quantification accuracy (concordance correlation coefficient [ρ c $$ {\rho}_c $$ ] vs. reference values) and precision (using SD) across scan repetitions. We performed in vivo liver scans (11 subjects) and used regions of interest to compare means and SDs of PDFF andR 2 * $$ {R}_2^{\ast } $$ measurements. Kruskal-Wallis and Wilcoxon signed-rank tests were performed (p < 0.05 considered significant).

RESULTS

In the phantom, RLLR and RMT denoising improved accuracy in PDFF andR 2 * $$ {R}_2^{\ast } $$ withρ c $$ {\rho}_c $$ >0.992 and improved precision with >67% decrease in SD across 50 scan repetitions versus conventional reconstruction (i.e., no denoising). For in vivo liver scans, the mean PDFF and meanR 2 * $$ {R}_2^{\ast } $$ were not significantly different between the three methods (conventional reconstruction; RLLR and RMT denoising). Without denoising, the SDs of PDFF andR 2 * $$ {R}_2^{\ast } $$ were 8.80% and 14.17 s-1. RLLR denoising significantly reduced the values to 1.79% and 5.31 s-1 (p < 0.001); RMT denoising significantly reduced the values to 2.00% and 4.81 s-1 (p < 0.001).

CONCLUSION

We validated an acquisition protocol for improved PDFF andR 2 * $$ {R}_2^{\ast } $$ quantification at 0.55 T. Both RLLR and RMT denoising improved the accuracy and precision of PDFF andR 2 * $$ {R}_2^{\ast } $$ measurements.

MRI at low field: A review of software solutions for improving SNR

Low magnetic field magnetic resonance imaging (MRI) (B 0 $$ {B}_0 $$  < 1 T) is regaining interest in the magnetic resonance (MR) community as a complementary, more flexible, and cost-effective approach to MRI diagnosis. Yet, the impaired signal-to-noise ratio (SNR) per square root of time, or SNR efficiency, leading in turn to prolonged acquisition times, still challenges its relevance at the clinical level. To address this, researchers investigate various hardware and software solutions to improve SNR efficiency at low field, including the leveraging of latest advances in computing hardware. However, there may not be a single recipe for improving SNR at low field, and it is key to embrace the challenges and limitations of each proposed solution. In other words, suitable solutions depend on the final objective or application envisioned for a low-field scanner and, more importantly, on the characteristics of a specific lowB 0 $$ {B}_0 $$ field. In this review, we aim to provide an overview on software solutions to improve SNR efficiency at low field. First, we cover techniques for efficient k-space sampling and reconstruction. Then, we present post-acquisition techniques that enhance MR images such as denoising and super-resolution. In addition, we summarize recently introduced electromagnetic interference cancellation approaches showing great promises when operating in shielding-free environments. Finally, we discuss the advantages and limitations of these approaches that could provide directions for future applications.

Repeatability of image quality in very low-field MRI

BACKGROUND

Very low-field MR has emerged as a promising complementary device to high-field MRI scanners, offering several advantages. One of the key benefits is that very low-field scanners are generally more portable and affordable to purchase and maintain, making them an attractive option for medical facilities looking to reduce costs. Very low-field MRI systems also have lower RF power deposition, making them safer and less likely to cause tissue heating or other safety concerns. They are also simpler to maintain, as they do not require cooling agents such as liquid helium. However, these portable MR scanners are impacted by temperature, lower magnetic field strength, and inhomogeneity, resulting in images with lower signal-to-noise ratio (SNR) and higher geometric distortions. It is essential to investigate and tabulate the variations in these parameters to establish bounds so that subsequent in vivo studies and deployment of these portable systems can be well informed.

PURPOSE

The aim of this work is to investigate the repeatability of image quality metrics such as SNR and geometrical distortion at 0.05 T over 10 days and three sessions per day.

METHODS

We acquired repeatability data over 10 days with three sessions per day. The measurements included temperature, humidity, transmit frequency, off-resonance maps, and 3D turbo spin echo (TSE) images of an in vitro phantom. This resulted in a protocol with 11 sequences. We also acquired a 3 T data set for reference. The image quality metrics included computing SNR and eccentricity (to assess geometrical distortion) to investigate the repeatability of 0.05 T image quality. The image reconstruction included drift correction, k-space filtering, and off-resonance correction. We computed the experimental parameters' coefficient of variation (CV) and the resulting image quality metrics to assess repeatability. We have explored the impact of electromagnetic interference (EMI) on image quality in very low-field MRI. The investigation involved varying both the distance and amplitude of the EMI-producing coil from the signal generator to analyze their effects on image quality.

RESULTS

The range of temperature measured during the study was within 1.5 °C. The off-resonance maps acquired before and after the 3D TSE showed similar hotspots and were changed mainly by a global constant. The SNR measurements were highly repeatable across sessions and over the 10 days, quantified by a CV of 6.7%. The magnetic field inhomogeneity effects quantified by eccentricity showed a CV of 13.7%, but less than 5.1% in two of the three sessions over 10 days. The use of conjugate phase reconstruction mitigated geometrical distortion artifacts. Temperature and humidity did not significantly affect SNR or mean frequency drift within the ranges of these environmental factors investigated. The EMI experiment showed that as the amplitude increased the SNR decreased, and concurrently the root mean square of the background increased with a rise in EMI amplitude or a reduction in distance.

CONCLUSIONS

We found that humidity and temperature in the range investigated did not impact SNR or frequency. Based on the CV values computed session-wise and for the overall study, our findings indicate high repeatability for SNR and magnetic field homogeneity.

Diffusion tensor brain imaging at 0.55T: A feasibility study

PURPOSE

To investigate the feasibility of diffusion tensor brain imaging at 0.55T with comparisons against 3T.

METHODS

Diffusion tensor imaging data with 2 mm isotropic resolution was acquired on a cohort of five healthy subjects using both 0.55T and 3T scanners. The signal-to-noise ratio (SNR) of the 0.55T data was improved using a previous SNR-enhancing joint reconstruction method that jointly reconstructs the entire set of diffusion weighted images from k-space using shared-edge constraints. Quantitative diffusion tensor parameters were estimated and compared across field strengths. We also performed a test-retest assessment of repeatability at each field strength.

RESULTS

After applying SNR-enhancing joint reconstruction, the diffusion tensor parameters obtained from 0.55T data were strongly correlated (R 2 ≥ 0 . 70 $$ {R}^2\ge 0.70 $$ ) with those obtained from 3T data. Test-retest analysis showed that SNR-enhancing reconstruction improved the repeatability of the 0.55T diffusion tensor parameters.

CONCLUSION

High-resolution in vivo diffusion MRI of the human brain is feasible at 0.55T when appropriate noise-mitigation strategies are applied.

Joint [Formula: see text] and Image Reconstruction in Low-Field MRI by Physics-Informed Deep-Learning

OBJECTIVE

We present a model-based image reconstruction approach based on unrolled neural networks which corrects for image distortion and noise in low-field ( B0  ∼  50 mT) MRI.

METHODS

Utilising knowledge about the underlying physics, a novel network architecture (SH-Net) is introduced which involves the estimation of spherical harmonic coefficients to guarantee a spatially smooth field map estimate. The SH-Net is integrated in an end-to-end trainable model which jointly estimates the B0-field map as well as the image. Experiments were conducted on retrospectively simulated low-field data of human knees.

RESULTS

We compare our model to different model-based approaches at distinct noise levels and various B0-field distributions. Our results show that our physics-informed neural network approach outperforms the purely model-based methods by improving the PSNR up to 11.7% and the RMSE up to 86.3%.

CONCLUSION

Our end-to-end trained model-based approach outperforms existing methods in reconstructing image and B0-field maps in the low-field regime.

SIGNIFICANCE

low-field MRI is becoming increasingly more popular as it enables access to MR in challenging situations such as intensive care units or resource poor areas. Our method allows for fast and accurate image reconstruction in such low-field imaging with B0-inhomogeneity compensation under a wide range of various environmental conditions.

Beat Pilot Tone (BPT): Simultaneous MRI and RF motion sensing at arbitrary frequencies

PURPOSE

To introduce a simple system exploitation with the potential to turn MRI scanners into general-purpose radiofrequency (RF) motion monitoring systems.

METHODS

Inspired by Pilot Tone (PT), this work proposes Beat Pilot Tone (BPT), in which two or more RF tones at arbitrary frequencies are transmitted continuously during the scan. These tones create motion-modulated standing wave patterns that are sensed by the receiver coil array, incidentally mixed by intermodulation in the receiver chain, and digitized simultaneously with the MRI data. BPT can operate at almost any frequency as long as the intermodulation products lie within the bandwidth of the receivers. BPT's mechanism is explained in electromagnetic simulations and validated experimentally.

RESULTS

Phantom and volunteer experiments over a range of transmit frequencies suggest that BPT may offer frequency-dependent sensitivity to motion. Using a semi-flexible anterior receiver array, BPT appears to sense cardiac-induced body vibrations at microwave frequencies (≥ $$ \ge $$ 1.2 GHz). At lower frequencies, it exhibits a similar cardiac signal shape to PT, likely due to blood volume changes. Other volunteer experiments with respiratory, bulk, and head motion show that BPT can achieve greater sensitivity to motion than PT and greater separability between motion types. Basic multiple-input multiple-output (4 × 22 $$ 4\times 22 $$ MIMO) operation with simultaneous PT and BPT in head motion is demonstrated using two transmit antennas and a 22-channel head-neck coil.

CONCLUSION

BPT may offer a rich source of motion information that is frequency-dependent, simultaneous, and complementary to PT and the MRI exam.

Free-breathing 3D whole-heart joint T1/T2 mapping and water/fat imaging at 0.55 T

PURPOSE

To develop and validate a highly efficient motion compensated free-breathing isotropic resolution 3D whole-heart joint T1/T2 mapping sequence with anatomical water/fat imaging at 0.55 T.

METHODS

The proposed sequence takes advantage of shorter T1 at 0.55 T to acquire three interleaved water/fat volumes with inversion-recovery preparation, no preparation, and T2 preparation, respectively. Image navigators were used to facilitate nonrigid motion-compensated image reconstruction. T1 and T2 maps were jointly calculated by a dictionary matching method. Validations were performed with simulation, phantom, and in vivo experiments on 10 healthy volunteers and 1 patient. The performance of the proposed sequence was compared with conventional 2D mapping sequences including modified Look-Locker inversion recovery and T2-prepared balanced steady-SSFP sequence.

RESULTS

The proposed sequence has a good T1 and T2 encoding sensitivity in simulation, and excellent agreement with spin-echo reference T1 and T2 values was observed in a standardized T1/T2 phantom (R2 = 0.99). In vivo experiments provided good-quality co-registered 3D whole-heart T1 and T2 maps with 2-mm isotropic resolution in a short scan time of about 7 min. For healthy volunteers, left-ventricle T1 mean and SD measured by the proposed sequence were both comparable with those of modified Look-Locker inversion recovery (640 ± 35 vs. 630 ± 25 ms [p = 0.44] and 49.9 ± 9.3 vs. 54.4 ± 20.5 ms [p = 0.42]), whereas left-ventricle T2 mean and SD measured by the proposed sequence were both slightly lower than those of T2-prepared balanced SSFP (53.8 ± 5.5 vs. 58.6 ± 3.3 ms [p < 0.01] and 5.2 ± 0.9 vs. 6.1 ± 0.8 ms [p = 0.03]). Myocardial T1 and T2 in the patient measured by the proposed sequence were in good agreement with conventional 2D sequences and late gadolinium enhancement.

CONCLUSION

The proposed sequence simultaneously acquires 3D whole-heart T1 and T2 mapping with anatomical water/fat imaging at 0.55 T in a fast and efficient 7-min scan. Further investigation in patients with cardiovascular disease is now warranted.

Multimodal surface coils for low field MR imaging

Low field MRI is safer and more cost effective than the high field MRI. One of the inherent problems of low field MRI is its low signal-to-noise ratio or sensitivity. In this work, we introduce a multimodal surface coil technique for signal excitation and reception to improve the RF magnetic field (B1) efficiency and potentially improve MR sensitivity. The proposed multimodal surface coil consists of multiple identical resonators that are electromagnetically coupled to form a multimodal resonator. The field distribution of its lowest frequency mode is suitable for MR imaging applications. The prototype multimodal surface coils are built, and the performance is investigated and validated through numerical simulation, standard RF measurements and tests, and comparison with the conventional surface coil at low fields. Our results show that the B1 efficiency of the multimodal surface coil outperforms that of the conventional surface coil which is known to offer the highest B1 efficiency among all coil categories, i.e., volume coil, half-volume coil and surface coil. In addition, in low-field MRI, the required low-frequency coils often use large value capacitance to achieve the low resonant frequency which makes frequency tuning difficult. The proposed multimodal surface coil can be conveniently tuned to the required low frequency for low-field MRI with significantly reduced capacitance value, demonstrating excellent low-frequency operation capability over the conventional surface coil.

bSSFP Phase Contrast (PC-SSFP) at 0.55T Applied to Aortic Flow

BACKGROUND

There is a growing interest in the development and application of mid-field (0.55T) for cardiac MR, including flow imaging. However, aortic flow imaging at 0.55T has limited SNR, especially in diastolic phases where there is reduced inflow-driven contrast for spoiled gradient echo (GRE) sequences. The low SNR can limit the accuracy of flow and regurgitant fraction measurements.

METHODS

In this work, we developed a 2D phase contrast (PC) acquisition with balanced steady state free precession (bSSFP), termed PC-SSFP, for flow imaging and quantification at 0.55T. This PC-SSFP approach precisely nulls the 0th and 1st gradient moments at both the TE and TR, except for the flow-encoded acquisition, for which the 1st gradient moment at the TE is determined by the VENC. Our proposed sequence was tested in both phantoms and in healthy volunteers (n=11), to measure aortic flow. In volunteers, both a breath-hold and a free-breathing protocol, with averaging to increase SNR, were obtained. Total flow, peak flow, cardiac output and SNR were compared for PC-SSFP and PC-GRE. Stroke volumes were also measured and compared to planimetry method.

RESULTS

In a phantom, SNR was significantly higher using PC-SSFP compared to PC-GRE (25.5±9.6 vs 8.2±2.9), and the velocity measurements agreed well (R = 1.00). In healthy subjects, for both breath-hold (bh) and free-breathing (fb) protocols, PC-SSFP measured accurate peak flow (fb: R = 0.99, bh: R = 0.96) and cardiac output (fb: R = 0.98, bh: R = 0.88), compared to PC-GRE, accurate stroke volume (fb: R = 0.94, bh: R = 0.97), compared to planimetry measurement, and offered constant high SNR (fb: 28±9 vs 18±6, bh: 24±7 vs 11±3) over the cardiac cycle in 11 subjects.

CONCLUSION

PC-SSFP is a more reliable evaluation tool for aortic flow quantification, when compared to the conventional PC-GRE method at 0.55T, providing higher SNR, and thus potentially more accurate flows.

Single-point macromolecular proton fraction mapping using a 0.3 T permanent magnet MRI system: phantom and healthy volunteer study

In a 0.3 T permanent-magnet magnetic resonance imaging (MRI) system, quantifying myelin content is challenging owing to long imaging times and low signal-to-noise ratio. macromolecular proton fraction (MPF) offers a quantitative assessment of myelin in the nervous system. We aimed to demonstrate the practical feasibility of MPF mapping in the brain using a 0.3 T MRI. Both 0.3 T and 3.0 T MRI systems were used. The MPF-mapping protocol used a standard 3D fast spoiled gradient-echo sequence based on the single-point reference method. Proton density, T1, and magnetization transfer-weighted images were obtained from a protein phantom at 0.3 T and 3.0 T to calculate MPF maps. MPF was measured in all phantom sections to assess its relationship to protein concentration. We acquired MPF maps for 16 and 8 healthy individuals at 0.3 T and 3.0 T, respectively, measuring MPF in nine brain tissues. Differences in MPF between 0.3 T and 3.0 T, and between 0.3 T and previously reported MPF at 0.5 T, were investigated. Pearson's correlation coefficient between protein concentration and MPF at 0.3 T and 3.0 T was 0.92 and 0.90, respectively. The 0.3 T MPF of brain tissue strongly correlated with 3.0 T MPF and literature values measured at 0.5 T. The absolute mean differences in MPF between 0.3 T and 0.5 T were 0.42% and 1.70% in white and gray matter, respectively. Single-point MPF mapping using 0.3 T permanent-magnet MRI can effectively assess myelin content in neural tissue.

Evaluation of epilepsy lesion visualisation enhancement in low-field MRI using image quality transfer: a preliminary investigation of clinical potential for applications in developing countries

PURPOSE

Low-field (LF) MRI scanners are common in many Low- and middle-Income countries, but they provide images with worse spatial resolution and contrast than high-field (HF) scanners. Image Quality Transfer (IQT) is a machine learning framework to enhance images based on high-quality references that has recently adapted to LF MRI. In this study we aim to assess if it can improve lesion visualisation compared to LF MRI scans in children with epilepsy.

METHODS

T1-weighted, T2-weighted and FLAIR were acquired from 12 patients (5 to 18 years old, 7 males) with clinical diagnosis of intractable epilepsy on a 0.36T (LF) and a 1.5T scanner (HF). LF images were enhanced with IQT. Seven radiologists blindly evaluated the differentiation between normal grey matter (GM) and white matter (WM) and the extension and definition of epileptogenic lesions in LF, HF and IQT-enhanced images.

RESULTS

When images were evaluated independently, GM-WM differentiation scores of IQT outputs were 26% higher, 17% higher and 12% lower than LF for T1, T2 and FLAIR. Lesion definition scores were 8-34% lower than LF, but became 3% higher than LF for FLAIR and T1 when images were seen side by side. Radiologists with expertise at HF scored IQT images higher than those with expertise at LF.

CONCLUSION

IQT generally improved the image quality assessments. Evaluation of pathology on IQT-enhanced images was affected by familiarity with HF/IQT image appearance. These preliminary results show that IQT could have an important impact on neuroradiology practice where HF MRI is not available.

Magnetic Resonance-Guided Cancer Therapy Radiomics and Machine Learning Models for Response Prediction

Magnetic resonance imaging (MRI) is known for its accurate soft tissue delineation of tumors and normal tissues. This development has significantly impacted the imaging and treatment of cancers. Radiomics is the process of extracting high-dimensional features from medical images. Several studies have shown that these extracted features may be used to build machine-learning models for the prediction of treatment outcomes of cancer patients. Various feature selection techniques and machine models interrogate the relevant radiomics features for predicting cancer treatment outcomes. This study aims to provide an overview of MRI radiomics features used in predicting clinical treatment outcomes with machine learning techniques. The review includes examples from different disease sites. It will also discuss the impact of magnetic field strength, sample size, and other characteristics on outcome prediction performance.

Spatiotemporal encoding MRI in a portable low-field system

PURPOSE

Demonstrate the potential of spatiotemporal encoding (SPEN) MRI to deliver largely undistorted 2D, 3D, and diffusion weighted images on a 110 mT portable system.

METHODS

SPEN's quadratic phase modulation was used to subsample the low-bandwidth dimension of echo planar acquisitions, delivering alias-free images with an enhanced immunity to image distortions in a laboratory-built, low-field, portable MRI system lacking multiple receivers.

RESULTS

Healthy brain images with different SPEN time-bandwidth products and subsampling factors were collected. These compared favorably to EPI acquisitions including topup corrections. Robust 3D and diffusion weighted SPEN images of diagnostic value were demonstrated, with 2.5 mm isotropic resolutions achieved in 3 min scans. This performance took advantage of the low specific absorption rate and relative long TEs associated with low-field MRI.

CONCLUSION

SPEN MRI provides a robust and advantageous fast acquisition approach to obtain faithful 3D images and DWI data in low-cost, portable, low-field systems without parallel acceleration.

Modern low-field MRI

This narrative review explores recent advancements and applications of modern low-field (≤ 1 Tesla) magnetic resonance imaging (MRI) in musculoskeletal radiology. Historically, high-field MRI systems (1.5 T and 3 T) have been the standard in clinical practice due to superior image resolution and signal-to-noise ratio. However, recent technological advancements in low-field MRI offer promising avenues for musculoskeletal imaging. General principles of low-field MRI systems are being introduced, highlighting their strengths and limitations compared to high-field counterparts. Emphasis is placed on advancements in hardware design, including novel magnet configurations, gradient systems, and radiofrequency coils, which have improved image quality and reduced susceptibility artifacts particularly in musculoskeletal imaging. Different clinical applications of modern low-field MRI in musculoskeletal radiology are being discussed. The diagnostic performance of low-field MRI in diagnosing various musculoskeletal pathologies, such as ligament and tendon injuries, osteoarthritis, and cartilage lesions, is being presented. Moreover, the discussion encompasses the cost-effectiveness and accessibility of low-field MRI systems, making them viable options for imaging centers with limited resources or specific patient populations. From a scientific standpoint, the amount of available data regarding musculoskeletal imaging at low-field strengths is limited and often several decades old. This review will give an insight to the existing literature and summarize our own experiences with a modern low-field MRI system over the last 3 years. In conclusion, the narrative review highlights the potential clinical utility, challenges, and future directions of modern low-field MRI, offering valuable insights for radiologists and healthcare professionals seeking to leverage these advancements in their practice.

Coupled stack-up volume RF coils for low-field open MR imaging

Background

Low-field open magnetic resonance imaging (MRI) systems, typically operating at magnetic field strengths below 1 Tesla, has greatly expanded the accessibility of MRI technology to meet a wide range of patient needs. However, the inherent challenges of low-field MRI, such as limited signal-to-noise ratios and limited availability of dedicated radiofrequency (RF) coils, have prompted the need for innovative coil designs that can improve imaging quality and diagnostic capabilities.

Purpose

In response to these challenges, we introduce the coupled stack-up volume coil, a novel RF coil design that addresses the shortcomings of conventional birdcage in the context of low-field open MRI.

Methods

The proposed coupled stack-up volume coil design utilizes a unique architecture that optimizes both transmit/receive efficiency and RF field homogeneity and offers the advantage of a simple design and construction, making it a practical and feasible solution for low-field MRI applications. This paper presents a comprehensive exploration of the theoretical framework, design considerations, and experimental validation of this innovative coil design.

Results

We demonstrate the superior performance of the coupled stack-up volume coil in achieving 47.7% higher transmit/receive efficiency and 68% more uniform magnetic field distribution compared to traditional birdcage coils in electromagnetic simulations. Bench tests results show that the B1 field efficiency of coupled stack-up volume coil is 57.3% higher compared with that of conventional birdcage coil.

Conclusions

The proposed coupled stack-up volume coil outperforms the conventional birdcage coil in terms of B1 efficiency, imaging coverage, and low-frequency operation capability. This design provides a robust and simple solution to low-field MR RF coil design.

Development and validation of a prediction model for malignant sinonasal tumors based on MR radiomics and machine learning

OBJECTIVES

This study aimed to utilize MR radiomics-based machine learning classifiers on a large-sample, multicenter dataset to develop an optimal model for predicting malignant sinonasal tumors and tumor-like lesions.

METHODS

This study included 1711 adult patients (875 benign and 836 malignant) with sinonasal tumors or tumor-like lesions from three institutions. Patients from institution 1 (n = 1367) constituted both the training and validation cohorts, while those from institution 2 and 3 (n = 158/186) made up the test cohorts. Manual segmentation of the region of interest of the tumor was performed on T1WI, T2WI, and contrast-enhanced T1WI (CE-T1WI). Data normalization, dimensional reductions, feature selection, and classifications were performed using ten machine-learning classifiers. Four fusion models, namely T1WI + T2WI, T1WI + CE-T1WI, T2WI + CE-T1WI, and T1WI + T2WI + CE-T1WI, were constructed using the top ten features with the highest contribution in feature selection in the optimal models of T1WI, T2WI, and CE-T1WI. The Delong test compared areas under the curve (AUC) between models.

RESULTS

The AUCs of training/validation/test1/test2 datasets for T1WI, T2WI, and CE-T1WI were 0.900/0.842/0.872/0.839, 0.876/0.789/0.842/0.863, and 0.899/0.824/0.831/0.707, respectively. The fusion model from T1WI + T2WI + CE-T1WI had the highest AUC. The AUCs of training/validation/test1/test2 datasets were 0.947/0.849/0.871/0.887. The T1WI + T2WI + CE-T1WI model demonstrated a significantly higher AUC than the T2WI + CE-T1WI model in both cohorts (p < 0.05) and outperformed the T2WI model in test 1 (p = 0.008) and the T1WI model in test 2 (p = 0.006).

CONCLUSIONS

This fusion model based on radiomics from T1WI + T2WI + CE-T1WI images and machine learning can improve the power in predicting malignant sinonasal tumors with high accuracy, resilience, and robustness.

CLINICAL RELEVANCE STATEMENT

Our study proposes a radiomics-based machine learning fusion model from T1- and T2-weighted images and contrast-enhanced T1-weighted images, which can non-invasively identify the nature of sinonasal tumors and improve the performance in predicting malignant sinonasal tumors.

KEY POINTS

Differentiating benign and malignant sinonasal tumors is difficult due to similar clinical presentations. A radiomics model from T1 + T2 + contrast-enhanced T1 images can identify the nature of sinonasal tumors. This model can help distinguish benign and malignant sinonasal tumors.

Linear Bloch-Siegert phase-encoded low-field MRI: RF coils, pulse sequence, and image reconstruction

ConventionalB 0 $$ {B}_0 $$ gradient systems have several weaknesses including high cost and bulk. As a step towards addressing these while providing new degrees of freedom for spatial encoding and system design in Magnetic Resonance Imaging (MRI), a radio frequency (RF) gradient encoding system and pulse sequence for phase encoding using the Bloch-Siegert (BS) shift were developed. Optimized BS spatial encoding coils with bucking windings (counter-wound loops) were designed and constructed, along with compatible homogeneous imaging coils for excitation and signal reception. Two coil systems were developed: one for phantom imaging and a second for human wrist imaging. BS phase-encoded imaging and BS RF pulse simulations were performed. Pulse sequences were designed for linear stepping in k-space and implemented on a 47.5-mT scanner to image resolution phantoms in both coil setups. Reconstructions were performed using both the fullB 1 + $$ {B}_1^{+} $$ -based encoding fields for each BS pulse amplitude and using inverse discrete Fourier transforms. AB 0 $$ {B}_0 $$ gradient was used for frequency encoding during signal readout, and the third axis was projected. Specific absorption ratio (SAR) calculations were performed for the wrist coil to determine the safety of BS-based RF encoding forB 0 $$ {B}_0 $$ fields in the low field MRI regime. The optimized RF spatial encoding coils resulted in higher linearity (R 2 = 0.9981 $$ {R}^2=0.9981 $$ and 0.9921 in the phantom and wrist coils, respectively) than coils used in previous work. The phantom and wrist imaging coils were validated in simulations and experimentally to produce a peakB 1 + = 1.35 $$ {B}_1^{+}=1.35 $$ G and 0.8 G with 12-W input power, respectively, in the field-of-view (length = 11 cm) used for imaging. Nominal imaging resolutions of 5.22 and 7.21 mm were, respectively, achieved by the two-coil systems in the RF phase-encoded dimension. Coil systems, pulse sequences, and image reconstructions were developed for linear RF phase encoding using the BS shift and validated using a 47.5-mT open low field scanner, establishing a key component required forB 0 $$ {B}_0 $$  gradient-free imaging at lowB 0 $$ {B}_0 $$  field strengths.

Prediction models of intravenous glucocorticoids therapy response in thyroid eye disease

Background

Thyroid eye disease (TED) is an autoimmune orbital disease, with intravenous glucocorticoid (IVGC) therapy as the first-line treatment. Due to uncertain response rates and possible side effects, various prediction models have been developed to predict IVGC therapy outcomes.

Methods

A thorough search was conducted in PubMed, Embase, and Web of Science databases. Data extraction included publication details, prediction model content, and performance. Statistical analysis was performed using R software, including heterogeneity evaluation, publication bias, subgroup analysis, and sensitivity analysis. Forest plots were utilized for result visualization.

Results

Of the 12 eligible studies, 47 prediction models were extracted. All included studies exhibited a low-to-moderate risk of bias. The pooled area under the receiver operating characteristic curve (AUC) and the combined sensitivity and specificity for the models were 0.81, 0.75, and 0.79, respectively. In view of heterogeneity, multiple meta-regression and subgroup analysis were conducted, which showed that marker and modeling types may be the possible causes of heterogeneity (P < 0.001). Notably, imaging metrics alone (AUC = 0.81) or clinical characteristics combined with other markers (AUC = 0.87), incorporating with multivariate regression (AUC = 0.84) or radiomics analysis (AUC = 0.91), yielded robust and reliable prediction outcomes.

Conclusion

This meta-analysis comprehensively reviews the predictive models for IVGC therapy response in TED. It underscores that integrating clinical characteristics with laboratory or imaging indicators and employing advanced techniques like multivariate regression or radiomics analysis significantly enhance the efficacy of prediction. Our research findings offer valuable insights that can guide future studies on prediction models for IVGC therapy in TED.

Diffusion-Weighted Imaging Fluid-Attenuated Inversion Recovery Mismatch on Portable, Low-Field Magnetic Resonance Imaging Among Acute Stroke Patients

OBJECTIVE

For stroke patients with unknown time of onset, mismatch between diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) can guide thrombolytic intervention. However, access to MRI for hyperacute stroke is limited. Here, we sought to evaluate whether a portable, low-field (LF)-MRI scanner can identify DWI-FLAIR mismatch in acute ischemic stroke.

METHODS

Eligible patients with a diagnosis of acute ischemic stroke underwent LF-MRI acquisition on a 0.064-T scanner within 24 h of last known well. Qualitative and quantitative metrics were evaluated. Two trained assessors determined the visibility of stroke lesions on LF-FLAIR. An image coregistration pipeline was developed, and the LF-FLAIR signal intensity ratio (SIR) was derived.

RESULTS

The study included 71 patients aged 71 ± 14 years and a National Institutes of Health Stroke Scale of 6 (interquartile range 3-14). The interobserver agreement for identifying visible FLAIR hyperintensities was high (κ = 0.85, 95% CI 0.70-0.99). Visual DWI-FLAIR mismatch had a 60% sensitivity and 82% specificity for stroke patients <4.5 h, with a negative predictive value of 93%. LF-FLAIR SIR had a mean value of 1.18 ± 0.18 <4.5 h, 1.24 ± 0.39 4.5-6 h, and 1.40 ± 0.23 >6 h of stroke onset. The optimal cut-point for LF-FLAIR SIR was 1.15, with 85% sensitivity and 70% specificity. A cut-point of 6.6 h was established for a FLAIR SIR <1.15, with an 89% sensitivity and 62% specificity.

INTERPRETATION

A 0.064-T portable LF-MRI can identify DWI-FLAIR mismatch among patients with acute ischemic stroke. Future research is needed to prospectively validate thresholds and evaluate a role of LF-MRI in guiding thrombolysis among stroke patients with uncertain time of onset. ANN NEUROL 2024;96:321-331.

Free-breathing MRI techniques for fat and R2* quantification in the liver

OBJECTIVE

To review the recent advancements in free-breathing MRI techniques for proton-density fat fraction (PDFF) and R2* quantification in the liver, and discuss the current challenges and future opportunities.

MATERIALS AND METHODS

This work focused on recent developments of different MRI pulse sequences, motion management strategies, and reconstruction approaches that enable free-breathing liver PDFF and R2* quantification.

RESULTS

Different free-breathing liver PDFF and R2* quantification techniques have been evaluated in various cohorts, including healthy volunteers and patients with liver diseases, both in adults and children. Initial results demonstrate promising performance with respect to reference measurements. These techniques have a high potential impact on providing a solution to the clinical need of accurate liver fat and iron quantification in populations with limited breath-holding capacity.

DISCUSSION

As these free-breathing techniques progress toward clinical translation, studies of the linearity, bias, and repeatability of free-breathing PDFF and R2* quantification in a larger cohort are important. Scan acceleration and improved motion management also hold potential for further enhancement.

Assessment of the Diagnostic Efficacy of Low-Field Magnetic Resonance Imaging: A Systematic Review

BACKGROUND

In recent years, there has been an increasing effort to take advantage of the potential use of low magnetic induction devices with less than 1 T, referred to as Low-Field MRI (LF MRI). LF MRI systems were used, especially in the early days of magnetic resonance technology. Over time, magnetic induction values of 1.5 and 3 T have become the standard for clinical devices, mainly because LF MRI systems were suffering from significantly lower quality of the images, e.g., signal-noise ratio. In recent years, due to advances in image processing with artificial intelligence, there has been an increasing effort to take advantage of the potential use of LF MRI with induction of less than 1 T. This overview article focuses on the analysis of the evidence concerning the diagnostic efficacy of modern LF MRI systems and the clinical comparison of LF MRI with 1.5 T systems in imaging the nervous system, musculoskeletal system, and organs of the chest, abdomen, and pelvis.

METHODOLOGY

A systematic literature review of MEDLINE, PubMed, Scopus, Web of Science, and CENTRAL databases for the period 2018-2023 was performed according to the recommended PRISMA protocol. Data were analysed to identify studies comparing the accuracy, reliability and diagnostic performance of LF MRI technology compared to available 1.5 T MRI.

RESULTS

A total of 1275 publications were retrieved from the selected databases. Only two articles meeting all predefined inclusion criteria were selected for detailed assessment.

CONCLUSIONS

A limited number of robust studies on the accuracy and diagnostic performance of LF MRI compared with 1.5 T MRI was available. The current evidence is not sufficient to draw any definitive insights. More scientific research is needed to make informed conclusions regarding the effectiveness of LF MRI technology.

Quality assessment of routine brain imaging at 0.55 T: initial experience in a clinical workflow

The purpose of this study was to assess the quality of clinical brain imaging in healthy subjects and patients on an FDA-approved commercial 0.55 T MRI scanner, and to provide information about the feasibility of using this scanner in a clinical workflow. In this IRB-approved study, brain examinations on the scanner were prospectively performed in 10 healthy subjects (February-April 2022) and retrospectively derived from 44 patients (February-July 2022). Images collected using the following pulse sequences were available for assessment: axial DWI (diffusion-weighted imaging), apparent diffusion coefficient maps, 2D axial fluid-attenuated inversion recovery images, axial susceptibility-weighted images (both magnitude and phase), sagittal T1-weighted (T1w) Sampling Perfection with Application Optimized Contrast images, sagittal T1w MPRAGE (magnetization prepared rapid gradient echo) with contrast enhancement, axial T1w turbo spin echo (TSE) with and without contrast enhancement, and axial T2-weighted TSE. Two readers retrospectively and independently evaluated image quality and specific anatomical features in a blinded fashion on a four-point Likert scale, with a score of 1 being unacceptable and 4 being excellent, and determined the ability to answer the clinical question in patients. For each category of image sequences, the mean, standard deviation, and percentage of unacceptable quality images (<2) were calculated. Acceptable (rating ≥ 2) image quality was achieved at 0.55 T in all sequences for patients and 85% of the sequences for healthy subjects. Radiologists were able to answer the clinical question in all patients scanned. In total, 50% of the sequences used in patients and about 60% of the sequences used in healthy subjects exhibited good (rating ≥ 3) image quality. Based on these findings, we conclude that diagnostic quality clinical brain images can be successfully collected on this commercial 0.55 T scanner, indicating that the routine brain imaging protocol may be deployed on this system in the clinical workflow.

Robust EMI elimination for RF shielding-free MRI through deep learning direct MR signal prediction

PURPOSE

To develop a new electromagnetic interference (EMI) elimination strategy for RF shielding-free MRI via active EMI sensing and deep learning direct MR signal prediction (Deep-DSP).

METHODS

Deep-DSP is proposed to directly predict EMI-free MR signals. During scanning, MRI receive coil and EMI sensing coils simultaneously sample data within two windows (i.e., for MR data and EMI characterization data acquisition, respectively). Afterward, a residual U-Net model is trained using synthetic MRI receive coil data and EMI sensing coil data acquired during EMI signal characterization window, to predict EMI-free MR signals from signals acquired by MRI receive and EMI sensing coils. The trained model is then used to directly predict EMI-free MR signals from data acquired by MRI receive and sensing coils during the MR signal-acquisition window. This strategy was evaluated on an ultralow-field 0.055T brain MRI scanner without any RF shielding and a 1.5T whole-body scanner with incomplete RF shielding.

RESULTS

Deep-DSP accurately predicted EMI-free MR signals in presence of strong EMI. It outperformed recently developed EDITER and convolutional neural network methods, yielding better EMI elimination and enabling use of few EMI sensing coils. Furthermore, it could work well without dedicated EMI characterization data.

CONCLUSION

Deep-DSP presents an effective EMI elimination strategy that outperforms existing methods, advancing toward truly portable and patient-friendly MRI. It exploits electromagnetic coupling between MRI receive and EMI sensing coils as well as typical MR signal characteristics. Despite its deep learning nature, Deep-DSP framework is computationally simple and efficient.

Low-Field, Low-Cost, Point-of-Care Magnetic Resonance Imaging

Low-field magnetic resonance imaging (MRI) has recently experienced a renaissance that is largely attributable to the numerous technological advancements made in MRI, including optimized pulse sequences, parallel receive and compressed sensing, improved calibrations and reconstruction algorithms, and the adoption of machine learning for image postprocessing. This new attention on low-field MRI originates from a lack of accessibility to traditional MRI and the need for affordable imaging. Low-field MRI provides a viable option due to its lack of reliance on radio-frequency shielding rooms, expensive liquid helium, and cryogen quench pipes. Moreover, its relatively small size and weight allow for easy and affordable installation in most settings. Rather than replacing conventional MRI, low-field MRI will provide new opportunities for imaging both in developing and developed countries. This article discusses the history of low-field MRI, low-field MRI hardware and software, current devices on the market, advantages and disadvantages, and low-field MRI's global potential.

Deep Learning-based Image Enhancement Techniques for Fast MRI in Neuroimaging

Despite its superior soft tissue contrast and non-invasive nature, MRI requires long scan times due to its intrinsic signal acquisition principles, a main drawback which technological advancements in MRI have been focused on. In particular, scan time reduction is a natural requirement in neuroimaging due to detailed structures requiring high resolution imaging and often volumetric (3D) acquisitions, and numerous studies have recently attempted to harness deep learning (DL) technology in enabling scan time reduction and image quality improvement. Various DL-based image reconstruction products allow for additional scan time reduction on top of existing accelerated acquisition methods without compromising the image quality.

Electromagnetic interference elimination via active sensing and deep learning prediction for radiofrequency shielding-free MRI

At present, MRI scans are typically performed inside fully enclosed radiofrequency (RF) shielding rooms, posing stringent installation requirements and causing patient discomfort. We aim to eliminate electromagnetic interference (EMI) for MRI with no or incomplete RF shielding. In this study, a method of active sensing and deep learning EMI prediction is presented to model, predict, and remove EMI signal components from acquired MRI signals. Specifically, during each MRI scan, separate EMI-sensing coils placed in various locations are utilized to simultaneously sample external and internal EMI signals within two windows (for both conventional MRI signal acquisition and EMI characterization acquisition). A convolution neural network model is trained using the EMI characterization data to relate EMI signals detected by EMI-sensing coils to EMI signals in the MRI receive coil. This model is then used to retrospectively predict and remove EMI signal components detected by the MRI receive coil during the MRI signal acquisition window. This strategy was implemented on a low-cost ultralow-field 0.055 T permanent magnet MRI scanner without RF shielding. It produced final image signal-to-noise ratios that were comparable with those obtained using a fully enclosed RF shielding cage, and outperformed existing analytical EMI elimination methods (i.e., spectral domain transfer function and external dynamic interference estimation and removal [EDITER] methods). A preliminary experiment also demonstrated its applicability on a 1.5 T superconducting magnet MRI scanner with incomplete RF shielding. Altogether, the results demonstrated that the proposed method was highly effective in predicting and removing various EMI signals from both external environments and internal scanner electronics at both 0.055 T (2.3 MHz) and 1.5 T (63.9 MHz). The proposed strategy enables shielding-free MRI. The concept is relatively simple and is potentially applicable to other RF signal detection scenarios in the presence of external and/or internal EMI.

Mobile Diagnostic Clinics

This article reviews the revolutionary impact of emerging technologies and artificial intelligence (AI) in reshaping modern healthcare systems, with a particular focus on the implementation of mobile diagnostic clinics. It presents an insightful analysis of the current healthcare challenges, including the shortage of healthcare workers, financial constraints, and the limitations of traditional clinics in continual patient monitoring. The concept of "Mobile Diagnostic Clinics" is introduced as a transformative approach where healthcare delivery is made accessible through the incorporation of advanced technologies. This approach is a response to the impending shortfall of medical professionals and the financial and operational burdens conventional clinics face. The proposed mobile diagnostic clinics utilize digital health tools and AI to provide a wide range of services, from everyday screenings to diagnosis and continual monitoring, facilitating remote and personalized care. The article delves into the potential of nanotechnology in diagnostics, AI's role in enhancing predictive analytics, diagnostic accuracy, and the customization of care. Furthermore, the article discusses the importance of continual, noninvasive monitoring technologies for early disease detection and the role of clinical decision support systems (CDSSs) in personalizing treatment guidance. It also addresses the challenges and ethical concerns of implementing these advanced technologies, including data privacy, integration with existing healthcare infrastructure, and the need for transparent and bias-free AI systems.

Optimization of flip angle and radiofrequency pulse phase to maximize steady-state magnetization in three-dimensional missing pulse steady-state free precession

Missing pulse (MP) steady-state free precession (SSFP) is a magnetic resonance imaging (MRI) pulse sequence that is highly tolerant to the magnetic field inhomogeneity. In this study, optimal flip angle and radiofrequency (RF) phase scheduling in three-dimensional (3D) MP-SSFP is introduced to maximize the steady-state magnetization while keeping broadband excitation to cover widely distributed frequencies generated by inhomogeneous magnetic fields. Numerical optimization based on extended phase graph (EPG) simulation was performed to maximize the MP-SSFP steady-state magnetization. To limit the specific absorption rate (SAR) associated with the broadband excitation in 3D MP-SSFP, SAR constraint was introduced in the numerical optimization. Optimized flip angle and RF phase settings were experimentally tested by introducing a linear inhomogeneous magnetic field in a range of 10-20 mT/m and using a phantom with known T1/T2 relaxation and diffusion parameters at 3 T. The experimental results were validated through comparisons with EPG simulation. Image contrasts and molecular diffusion effects were investigated in in vivo human brain imaging with 3D MP-SSFP with the optimal flip angle and RF phase settings. In the phantom measurements, the optimal flip angle and RF phase settings improved the MP-SSFP steady-state magnetization/signal-to-noise ratio by up to 41% under the fixed SAR conditions, which matched well with EPG simulation results. In vivo brain imaging with the optimal RF pulse settings provided T2-like image contrasts. Diffusion effects were relatively minor with the linear inhomogeneous field of 10-20 mT/m for white and gray matter, but cerebrospinal fluid showed conspicuous signal intensity attenuation as the linear inhomogeneous field increased. Numerical optimization achieved significant improvement in the steady-state magnetization in MP-SSFP compared with the RF pulse settings used in previous studies. The proposed flip angle and RF phase optimization is promising to improve 3D MP-SSFP image quality for MRI in inhomogeneous magnetic fields.

Comparing Metal Artifact Severity and Ability to Assess Near-Metal Anatomy Between 0.55 T and 1.5 T MRI in Patients with Metallic Spinal Implants-A Scanner Comparison Study

RATIONALE AND OBJECTIVES

To compare image quality and metal artifact severity at 0.55 T and 1.5 T MRI in patients with spinal implants following posterior fusion surgery.

MATERIALS AND METHODS

50 consecutive patients (mean age: 69 ± 12 years) who underwent 0.55 T and 1.5 T MRI following posterior fusion surgery of the lumbar or thoracolumbar spine were included. Examinations used metal artifact reduction protocols from clinical routine. Images were rated by two fellowship-trained musculoskeletal radiologists for image quality, ability to assess the spinal canal and the neural foramina, and artifact severity on 5-point Likert scales. Additionally, differences in artifact severity and visibility of near-metal anatomy among implant sizes (1-level vs. 2-level vs. >2-levels) were evaluated.

RESULTS

Signal/contrast (mean: 4.0 ± 0.3 [0.55 T] vs. 4.4 ± 0.6 [1.5 T]; p < .001) and resolution (3.8 ± 0.5 vs. 4.2 ± 0.7; p < .001) were rated lower at 0.55 T. The ability to assess the spinal canal (4.4 ± 0.5 vs. 4.2 ± 0.9; p = .69) and the neural foramina (3.8 ± 0.5 vs. 3.8 ± 0.9; p = .19) were however rated equally good with excellent interrater agreement (range: 0.84-0.94). Susceptibility artifacts were rated milder at 0.55 T (1.8 ± 0.5 vs. 3.0 ± 0.6; p < .001). For implant size-based subgroups, the visibility of near-metal anatomy decreased with implant length at 1.5 T, but remained unchanged at 0.55 T. In consequence, the spinal canal and neural foramina could be better assessed at 0.55 T in patients with multi-level implants (4.4 ± 0.5 vs. 3.6 ± 1.1; p < .001).

CONCLUSION

Metal artifacts of spinal implants are substantially less pronounced at 0.55 T MRI. When examining patients with multi-level posterior fusion, this translates into a superior ability to assess near-metal anatomy, where 1.5 T MRI reaches diagnostic limitations.

Whole-body magnetic resonance imaging at 0.05 Tesla

Despite a half-century of advancements, global magnetic resonance imaging (MRI) accessibility remains limited and uneven, hindering its full potential in health care. Initially, MRI development focused on low fields around 0.05 Tesla, but progress halted after the introduction of the 1.5 Tesla whole-body superconducting scanner in 1983. Using a permanent 0.05 Tesla magnet and deep learning for electromagnetic interference elimination, we developed a whole-body scanner that operates using a standard wall power outlet and without radiofrequency and magnetic shielding. We demonstrated its wide-ranging applicability for imaging various anatomical structures. Furthermore, we developed three-dimensional deep learning reconstruction to boost image quality by harnessing extensive high-field MRI data. These advances pave the way for affordable deep learning-powered ultra-low-field MRI scanners, addressing unmet clinical needs in diverse health care settings worldwide.

Water-Fat Separation for the Knee on a 50 mT Portable MRI Scanner

OBJECTIVE

The Dixon method is frequently employed in clinical and scientific research for fat suppression, because it has lower sensitivity to static magnetic field inhomogeneity compared to chemical shift selective saturation or its variants and maintains image signal-to-noise ratio (SNR). Recently, research on very-low-field (VLF < 100 mT) magnetic resonance imaging (MRI) has regained popularity. However, there is limited literature on water-fat separation in VLF MRI. Here, we present a modified two-point Dixon method specifically designed for VLF MRI.

METHODS

Most experiments were performed on a homemade 50 mT portable MRI scanner. The receiving coil adopted a homemade quadrature receiving coil. The data were acquired using spin-echo and gradient-echo sequences. We considered the T2* effect, and added priori information to existing two-point Dixon method. Then, the method used regional iterative phasor extraction (RIPE) to extract the error phasor. Finally, least squares solutions for water and fat were obtained and fat signal fraction was calculated.

RESULTS

For phantom evaluation, water-only and fat-only images were obtained and the local fat signal fractions were calculated, with two samples being 0.94 and 0.93, respectively. For knee imaging, cartilage, muscle and fat could be clearly distinguished. The water-only images were able to highlight areas such as cartilage that could not be easily distinguished without separation.

CONCLUSION

This work has demonstrated the feasibility of using a 50 mT MRI scanner for water-fat separation.

SIGNIFICANCE

To the best of our knowledge, this is the first reported result of water-fat separation at a 50 mT portable MRI scanner.

Managing Patients With Unlabeled Passive Implants on MR Systems Operating Below 1.5 T

The standard of care for managing a patient with an implant is to identify the item and to assess the relative safety of scanning the patient. Because the 1.5 T MR system is the most prevalent scanner in the world and 3 T is the highest field strength in widespread use, implants typically have "MR Conditional" (i.e., an item with demonstrated safety in the MR environment within defined conditions) labeling at 1.5 and/or 3 T only. This presents challenges for a facility that has a scanner operating at a field strength below 1.5 T when encountering a patient with an implant, because scanning the patient is considered "off-label." In this case, the supervising physician is responsible for deciding whether to scan the patient based on the risks associated with the implant and the benefit of magnetic resonance imaging (MRI). For a passive implant, the MRI safety-related concerns are static magnetic field interactions (i.e., force and torque) and radiofrequency (RF) field-induced heating. The worldwide utilization of scanners operating below 1.5 T combined with the increasing incidence of patients with implants that need MRI creates circumstances that include patients potentially being subjected to unsafe imaging conditions or being denied access to MRI because physicians often lack the knowledge to perform an assessment of risk vs. benefit. Thus, physicians must have a complete understanding of the MRI-related safety issues that impact passive implants when managing patients with these products on scanners operating below 1.5 T. This monograph provides an overview of the various clinical MR systems operating below 1.5 T and discusses the MRI-related factors that influence safety for passive implants. Suggestions are provided for the management of patients with passive implants labeled MR Conditional at 1.5 and/or 3 T, referred to scanners operating below 1.5 T. The purpose of this information is to empower supervising physicians with the essential knowledge to perform MRI exams confidently and safely in patients with passive implants. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 3.

Multimodal surface coils for low field MR imaging

Low field MRI is safer and more cost effective than the high field MRI. One of the inherent problems of low field MRI is its low signal-to-noise ratio or sensitivity. In this work, we introduce a multimodal surface coil technique for signal excitation and reception to improve the RF magnetic field (B 1 ) efficiency and potentially improve MR sensitivity. The proposed multimodal surface coil consists of multiple identical resonators that are electromagnetically coupled to form a multimodal resonator. The field distribution of its lowest frequency mode is suitable for MR imaging applications. The prototype multimodal surface coils are built, and the performance is investigated and validated through numerical simulation, standard RF measurements and tests, and comparison with the conventional surface coil at low fields. Our results show that the B 1 efficiency of the multimodal surface coil outperforms that of the conventional surface coil which is known to offer the highest B 1 efficiency among all coil categories, i.e., volume coil, half-volume coil and surface coil. In addition, in low-field MRI, the required low-frequency coils often use large value capacitance to achieve the low resonant frequency which makes frequency tuning difficult. The proposed multimodal surface coil can be conveniently tuned to the required low frequency for low-field MRI with significantly reduced capacitance value, demonstrating excellent low-frequency operation capability over the conventional surface coil.

Characterization of spatial integrity with active and passive implants in a low-field magnetic resonance linear accelerator scanner

Background and Purpose

Standard imaging protocols can guarantee the spatial integrity of magnetic resonance (MR) images utilized in radiotherapy. However, the presence of metallic implants can significantly compromise this integrity. Our proposed method aims at characterizing the geometric distortions induced by both passive and active implants commonly encountered in planning images obtained from a low-field 0.35 T MR-linear accelerator (LINAC).

Materials and Methods

We designed a spatial integrity phantom defining 1276 control points and covering a field of view of 20x20x20 cm3. This phantom was scanned in a water tank with and without different implants used in hip and shoulder arthroplasty procedures as well as with active cardiac stimulators. The images were acquired with the clinical planning sequence (balanced steady-state free-precession, resolution 1.5x1.5x1.5 mm3). Spatial integrity was assessed by the Euclidian distance between the control point detected on the image and their theoretical locations. A first plane free of artefact (FPFA) was defined to evaluate the spatial integrity beyond the larger banding artefact.

Results

In the region extending up to 20 mm from the largest banding artefacts, the tested passive and active implants could cause distortions up to 2 mm and 3 mm, respectively. Beyond this region the spatial integrity was recovered and the image could be considered as unaffected by the implants.

Conclusions

We characterized the impact of common implants on a low field MR-LINAC planning sequence. These measurements could support the creation of extra margin while contouring organs at risk and target volumes in the vicinity of implants.

Comparison of image quality and diagnostic efficacy of routine clinical lumbar spine imaging at 0.55T and 1.5/3T

PURPOSE

To compare image quality, assess inter-reader variability, and evaluate the diagnostic efficacy of routine clinical lumbar spine sequences at 0.55T compared with those collected at 1.5/3T to assess common spine pathology.

METHODS

665 image series across 70 studies, collected at 0.55T and 1.5/3T, were assessed by two neuroradiology fellows for overall imaging quality (OIQ), artifacts, and accurate visualization of anatomical features (intervertebral discs, neural foramina, spinal cord, bone marrow, and conus / cauda equina nerve roots) using a 4-point Likert scale (1 = non-diagnostic to 4 = excellent). For the 0.55T scans, the most appropriate diagnosis(es) from a picklist of common spine pathologies was selected. The mean ± SD of all scores for all features for each sequence and reader at 0.55T and 1.5/3T were calculated. Paired t-tests (p ≤ 0.05) were used to compare ratings between field strengths. The inter-reader agreement was calculated using linear-weighted Cohen's Kappa coefficient (p ≤ 0.05). Unpaired VCG analysis for OIQ was additionally employed to represent differences between 0.55T and 1.5/3T (95 % CI).

RESULTS

All sequences at 0.55T were rated as acceptable (≥2) for diagnostic use by both readers despite significantly lower scores for some compared to those at 1.5/3T. While there was low inter-reader agreement on individual scores, the agreement on the diagnosis was high, demonstrating the potential of this system for detecting routine spine pathology.

CONCLUSIONS

Clinical lumbar spine imaging at 0.55T produces diagnostic-quality images demonstrating the feasibility of its use in diagnosing spinal pathology, including osteomyelitis/discitis, post-surgical changes with complications, and metastatic disease.

Evaluation of 12-lead electrocardiogram at 0.55T for improved cardiac monitoring in magnetic resonance imaging

BACKGROUND

The 12-lead electrocardiogram (ECG) is a standard diagnostic tool for monitoring cardiac ischemia and heart rhythm during cardiac interventional procedures and stress testing. These procedures can benefit from magnetic resonance imaging (MRI) information; however, the MRI scanner magnetic field leads to ECG distortion that limits ECG interpretation. This study evaluated the potential for improved ECG interpretation in a "low field" 0.55T MRI scanner.

METHODS

The 12-lead ECGs were recorded inside 0.55T, 1.5T, and 3T MRI scanners, as well as at scanner table "home" position in the fringe field and outside the scanner room (seven pigs). To assess interpretation of ischemic ECG changes in a 0.55T MRI scanner, ECGs were recorded before and after coronary artery occlusion (seven pigs). ECGs was also recorded for five healthy human volunteers in the 0.55T scanner. ECG error and variation were assessed over 2-minute recordings for ECG features relevant to clinical interpretation: the PR interval, QRS interval, J point, and ST segment.

RESULTS

ECG error was lower at 0.55T compared to higher field scanners. Only at 0.55T table home position, did the error approach the guideline recommended 0.025 mV ceiling for ECG distortion (median 0.03 mV). At scanner isocenter, only in the 0.55T scanner did J point error fall within the 0.1 mV threshold for detecting myocardial ischemia (median 0.03 mV in pigs and 0.06 mV in healthy volunteers). Correlation of J point deviation inside versus outside the 0.55T scanner following coronary artery occlusion was excellent at scanner table home position (r2 = 0.97), and strong at scanner isocenter (r2 = 0.92).

CONCLUSION

ECG distortion is improved in 0.55T compared to 1.5T and 3T MRI scanners. At scanner home position, ECG distortion at 0.55T is low enough that clinical interpretation appears feasible without need for more cumbersome patient repositioning. At 0.55T scanner isocenter, ST segment changes during coronary artery occlusion appear detectable but distortion is enough to obscure subtle ST segment changes that could be clinically relevant. Reduced ECG distortion in 0.55T scanners may simplify the problem of suppressing residual distortion by ECG cable positioning, averaging, and filtering and could reduce current restrictions on ECG monitoring during interventional MRI procedures.

The Future of MR-Guided Radiation Therapy

Magnetic resonance image guided radiation therapy (MRIgRT) is a relatively new technology that has already shown outcomes benefits but that has not yet reached its clinical potential. The improved soft-tissue contrast provided with MR, coupled with the immediacy of image acquisition with respect to the treatment, enables expansion of on-table adaptive protocols, currently at a cost of increased treatment complexity, use of human resources, and longer treatment slot times, which translate to decreased throughput. Many approaches are being investigated to meet these challenges, including the development of artificial intelligence (AI) algorithms to accelerate and automate much of the workflow and improved technology that parallelizes workflow tasks, as well as improvements in image acquisition speed and quality. This article summarizes limitations of current available integrated MRIgRT systems and gives an outlook about scientific developments to further expand the use of MRIgRT.

Self-gated cine phase-contrast balanced SSFP flow quantification at 0.55 T

PURPOSE

To implement cine phase-contrast balanced SSFP (PC-bSSFP) for low-field 0.55T cardiac MRI by exploiting the intrinsic flow sensitivity of the bSSFP slice-select gradient and the in-plane phase-cancelation properties of radial trajectories, enabling self-gated and referenceless PC-bSSFP flow quantification at 0.55 T.

METHODS

A free-running, tiny golden-angle radial PC-bSSFP approach was implemented on 0.55T and 1.5T systems. Cardiac and respiratory self-gating was incorporated to enable electrocardiogram-free scanning during breath-hold and free-breathing. By exploiting the intrinsic in-plane phase-cancelation properties of radial acquisitions and background phase fitting, referenceless single-point PC-bSSFP was realized. In vivo data were acquired in the ascending aorta of healthy subjects at 0.55 T and 1.5 T during breath-hold and free-breathing. Flow data, SNR, and velocity-to-noise ratio were compared relative to data obtained with phase-contrast spoiled gradient-echo variants.

RESULTS

Velocities acquired with PC-bSSFP compared well with data from phase-contrast spoiled gradient-echo (RMSEv  = 5.8 cm/s). PC-bSSFP at 0.55 T resulted in high-quality cine magnitude images and phase maps with sufficient SNR and velocity-to-noise ratio. Breath-hold and free-breathing PC-bSSFP performed very similarly, with comparable flow quantification (RMSEv  = 5.7 cm/s). Referenceless single-point PC-bSSFP results agreed well with two-point PC-bSSFP (-1.8 ± 5.2 cm/s) while reducing scan times 2-fold.

CONCLUSION

PC-bSSFP is feasible on low-field 0.55T systems, producing high-quality cine images while permitting simultaneous aortic flow measurements during breath-hold and free-breathing and without the need for electrocardiogram gating.

Deuterium metabolic imaging for 3D mapping of glucose metabolism in humans with central nervous system lesions at 3T

PURPOSE

To explore the potential of 3T deuterium metabolic imaging (DMI) using a birdcage 2 H radiofrequency (RF) coil in both healthy volunteers and patients with central nervous system (CNS) lesions.

METHODS

A modified gradient filter, home-built 2 H volume RF coil, and spherical k-space sampling were employed in a three-dimensional chemical shift imaging acquisition to obtain high-quality whole-brain metabolic images of 2 H-labeled water and glucose metabolic products. These images were acquired in a healthy volunteer and three subjects with CNS lesions of varying pathologies. Hardware and pulse sequence experiments were also conducted to improve the signal-to-noise ratio of DMI at 3T.

RESULTS

The ability to quantify local glucose metabolism in correspondence to anatomical landmarks across patients with varying CNS lesions is demonstrated, and increased lactate is observed in one patient with the most active disease.

CONCLUSION

DMI offers the potential to examine metabolic activity in human subjects with CNS lesions with DMI at 3T, promising for the potential of the future clinical translation of this metabolic imaging technique.

Self-supervised MRI denoising: leveraging Stein's unbiased risk estimator and spatially resolved noise maps

Thermal noise caused by the imaged object is an intrinsic limitation in magnetic resonance imaging (MRI), resulting in an impaired clinical value of the acquisitions. Recently, deep learning (DL)-based denoising methods achieved promising results by extracting complex feature representations from large data sets. Most approaches are trained in a supervised manner by directly mapping noisy to noise-free ground-truth data and, therefore, require extensive paired data sets, which can be expensive or infeasible to obtain for medical imaging applications. In this work, a DL-based denoising approach is investigated which operates on complex-valued reconstructed magnetic resonance (MR) images without noise-free target data. An extension of Stein's unbiased risk estimator (SURE) and spatially resolved noise maps quantifying the noise level with pixel accuracy were employed during the training process. Competitive denoising performance was achieved compared to supervised training with mean squared error (MSE) despite optimizing the model without noise-free target images. The proposed DL-based method can be applied for MR image enhancement without requiring noise-free target data for training. Integrating the noise maps as an additional input channel further enables the regulation of the desired level of denoising to adjust to the preference of the radiologist.

MRI scarcity in low- and middle-income countries

Since the introduction of MRI as a sustainable diagnostic modality, global accessibility to its services has revealed a wide discrepancy between populations-leaving most of the population in LMICs without access to this important imaging modality. Several factors lead to the scarcity of MRI in LMICs; for example, inadequate infrastructure and the absence of a dedicated workforce are key factors in the scarcity observed. RAD-AID has contributed to the advancement of radiology globally by collaborating with our partners to make radiology more accessible for medically underserved communities. However, progress is slow and further investment is needed to ensure improved global access to MRI.

Image Quality of Lumbar Spine Imaging at 0.55T Low-Field MRI is Comparable to Conventional 1.5T MRI - Initial Observations in Healthy Volunteers

RATIONALE AND OBJECTIVES

To assess the potential of 0.55T low-field MRI system in lumbar spine imaging with and without the use of additional advanced postprocessing techniques.

MATERIALS AND METHODS

The lumbar spine of 14 volunteers (32.9 ± 3.6 years) was imaged both at 0.55T and 1.5T using sequences from clinical routine. On the 0.55T scanner system, additional sequences with simultaneous multi-slice acquisition and artificial intelligence-based postprocessing techniques were acquired. Image quality of all 28 examinations was assessed by three musculoskeletal radiologists with respect to signal/contrast, resolution, and assessability of the spinal canal and neuroforamina using a 5-point Likert scale (1 = non-diagnostic to 5 = perfect quality). Interrater agreement was evaluated with the Intraclass Correlation Coefficient and the Mann-Whitney U test (significance level: p < 0.05).

RESULTS

Image quality at 0.55T was rated lower on the 5-point Likert scale compared to 1.5T regarding signal/contrast (mean: 4.16 ± 0.29 vs. 4.54 ± 0.29; p < 0.001), resolution (4.07 ± 0.31 vs. 4.49 ± 0.30; p < 0.001), assessability of the spinal canal (4.28 ± 0.13 vs. 4.73 ± 0.26; p < 0.001) and the neuroforamina (4.14 ± 0.28 vs. 4.70 ± 0.27; p < 0.001). Image quality for the AI-processed sagittal T1 TSE and T2 TSE at 0.55T was also rated slightly lower, but still good to perfect with a concomitant reduction in measurement time. Interrater agreement was good to excellent (range: 0.60-0.91).

CONCLUSION

While lumbar spine image quality at 0.55T is perceived inferior to imaging at 1.5T by musculoskeletal radiologists, good overall examination quality was observed with high interrater agreement. Advanced postprocessing techniques may accelerate intrinsically longer acquisition times at 0.55T.

Detection of Intracerebral Hemorrhage Using Low-Field, Portable Magnetic Resonance Imaging in Patients With Stroke

BACKGROUND

Neuroimaging is essential for detecting spontaneous, nontraumatic intracerebral hemorrhage (ICH). Recent data suggest ICH can be characterized using low-field magnetic resonance imaging (MRI). Our primary objective was to investigate the sensitivity and specificity of ICH on a 0.064T portable MRI (pMRI) scanner using a methodology that provided clinical information to inform rater interpretations. As a secondary aim, we investigated whether the incorporation of a deep learning (DL) reconstruction algorithm affected ICH detection.

METHODS

The pMRI device was deployed at Yale New Haven Hospital to examine patients presenting with stroke symptoms from October 26, 2020 to February 21, 2022. Three raters independently evaluated pMRI examinations. Raters were provided the images alongside the patient's clinical information to simulate real-world context of use. Ground truth was the closest conventional computed tomography or 1.5/3T MRI. Sensitivity and specificity results were grouped by DL and non-DL software to investigate the effects of software advances.

RESULTS

A total of 189 exams (38 ICH, 89 acute ischemic stroke, 8 subarachnoid hemorrhage, 3 primary intraventricular hemorrhage, 51 no intracranial abnormality) were evaluated. Exams were correctly classified as positive or negative for ICH in 185 of 189 cases (97.9% overall accuracy). ICH was correctly detected in 35 of 38 cases (92.1% sensitivity). Ischemic stroke and no intracranial abnormality cases were correctly identified as blood-negative in 139 of 140 cases (99.3% specificity). Non-DL scans had a sensitivity and specificity for ICH of 77.8% and 97.1%, respectively. DL scans had a sensitivity and specificity for ICH of 96.6% and 99.3%, respectively.

CONCLUSIONS

These results demonstrate improvements in ICH detection accuracy on pMRI that may be attributed to the integration of clinical information in rater review and the incorporation of a DL-based algorithm. The use of pMRI holds promise in providing diagnostic neuroimaging for patients with ICH.

Feasibility of cardiac MR thermometry at 0.55 T

Radiofrequency catheter ablation is an established treatment strategy for ventricular tachycardia, but remains associated with a low success rate. MR guidance of ventricular tachycardia shows promises to improve the success rate of these procedures, especially due to its potential to provide real-time information on lesion formation using cardiac MR thermometry. Modern low field MRI scanners (<1 T) are of major interest for MR-guided ablations as the potential benefits include lower costs, increased patient access and device compatibility through reduced device-induced imaging artefacts and safety constraints. However, the feasibility of cardiac MR thermometry at low field remains unknown. In this study, we demonstrate the feasibility of cardiac MR thermometry at 0.55 T and characterized its in vivo stability (i.e., precision) using state-of-the-art techniques based on the proton resonance frequency shift method. Nine healthy volunteers were scanned using a cardiac MR thermometry protocol based on single-shot EPI imaging (3 slices in the left ventricle, 150 dynamics, TE = 41 ms). The reconstruction pipeline included image registration to align all the images, multi-baseline approach (look-up-table length = 30) to correct for respiration-induced phase variations, and temporal filtering to reduce noise in temperature maps. The stability of thermometry was defined as the pixel-wise standard deviation of temperature changes over time. Cardiac MR thermometry was successfully acquired in all subjects and the stability averaged across all subjects was 1.8 ± 1.0°C. Without multi-baseline correction, the overall stability was 2.8 ± 1.6°C. In conclusion, cardiac MR thermometry is feasible at 0.55 T and further studies on MR-guided catheter ablations at low field are warranted.

Feasibility of Accelerated Prostate Diffusion-Weighted Imaging on 0.55 T MRI Enabled With Random Matrix Theory Denoising

INTRODUCTION

Prostate cancer diffusion weighted imaging (DWI) MRI is typically performed at high-field strength (3.0 T) in order to overcome low signal-to-noise ratio (SNR). In this study, we demonstrate the feasibility of prostate DWI at low field enabled by random matrix theory (RMT)-based denoising, relying on the MP-PCA algorithm applied during image reconstruction from multiple coils.

METHODS

Twenty-one volunteers and 2 prostate cancer patients were imaged with a 6-channel pelvic surface array coil and an 18-channel spine array on a prototype 0.55 T system created by ramping down a commercial magnetic resonance imaging system (1.5 T MAGNETOM Aera Siemens Healthcare) with 45 mT/m gradients and 200 T/m/s slew rate. Diffusion-weighted images were acquired with 4 non-collinear directions, for which b = 50 s/mm 2 was used with 8 averages and b = 1000 s/mm 2 with 40 averages; 2 extra b = 50 s/mm 2 were used as part of the dynamic field correction. Standard and RMT-based reconstructions were applied on DWI over different ranges of averages. Accuracy/precision was evaluated using the apparent diffusion coefficient (ADC), and image quality was evaluated over 5 separate reconstructions by 3 radiologists with a 5-point Likert scale. For the 2 patients, we compare image quality and lesion visibility of the RMT reconstruction versus the standard one on 0.55 T and on clinical 3.0 T.

RESULTS

The RMT-based reconstruction in this study reduces the noise floor by a factor of 5.8, thereby alleviating the bias on prostate ADC. Moreover, the precision of the ADC in prostate tissue after RMT increases over a range of 30%-130%, with the increase in both signal-to-noise ratio and precision being more prominent for a low number of averages. Raters found that the images were consistently of moderate to good overall quality (3-4 on the Likert scale). Moreover, they determined that b = 1000 s/mm 2 images from a 1:55-minute scan with the RMT-based reconstruction were on par with the corresponding images from a 14:20-minute scan with standard reconstruction. Prostate cancer was visible on ADC and calculated b = 1500 images even with the abbreviated 1:55-minute scan reconstructed with RMT.

CONCLUSIONS

Prostate imaging using DWI is feasible at low field and can be performed more rapidly with noninferior image quality compared with standard reconstruction.