High-Performance 0.55-T Lung MRI in Patient with COVID-19 Infection

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.

Lung Nodule Detection With Modern Low-Field MRI (0.55 T) in Comparison to CT

OBJECTIVES

The aim of this study was to evaluate the accuracy of modern low-field magnetic resonance imaging (MRI) for lung nodule detection and to correlate nodule size measurement with computed tomography (CT) as reference.

MATERIALS AND METHODS

Between November 2020 and July 2021, a prospective clinical trial using low-field MRI at 0.55 T was performed in patients with known pulmonary nodules from a single academic medical center. Every patient underwent MRI and CT imaging on the same day. The primary aim was to evaluate the detection accuracy of pulmonary nodules using MRI with transversal periodically rotated overlapping parallel lines with enhanced reconstruction in combination with coronal half-Fourier acquired single-shot turbo spin-echo MRI sequences. The secondary outcome was the correlation of the mean lung nodule diameter with CT as reference according to the Lung Imaging Reporting and Data System. Nonparametric Mann-Whitney U test, Spearman rank correlation coefficient, and Bland-Altman analysis were applied to analyze the results.

RESULTS

A total of 46 participants (mean age ± SD, 66 ± 11 years; 26 women) were included. In a blinded analysis of 964 lung nodules, the detection accuracy was 100% for those ≥6 mm (126/126), 80% (159/200) for those ≥4-<6 mm, and 23% (147/638) for those <4 mm in MRI compared with reference CT. Spearman correlation coefficient of MRI and CT size measurement was r = 0.87 ( P < 0.001), and the mean difference was 0.16 ± 0.9 mm.

CONCLUSIONS

Modern low-field MRI shows excellent accuracy in lesion detection for lung nodules ≥6 mm and a very strong correlation with CT imaging for size measurement, but could not compete with CT in the detection of small nodules.

New clinical opportunities of low-field MRI: heart, lung, body, and musculoskeletal

Contemporary whole-body low-field MRI scanners (< 1 T) present new and exciting opportunities for improved body imaging. The fundamental reason is that the reduced off-resonance and reduced SAR provide substantially increased flexibility in the design of MRI pulse sequences. Promising body applications include lung parenchyma imaging, imaging adjacent to metallic implants, cardiac imaging, and dynamic imaging in general. The lower cost of such systems may make MRI favorable for screening high-risk populations and population health research, and the more open configurations allowed may prove favorable for obese subjects and for pregnant women. This article summarizes promising body applications for contemporary whole-body low-field MRI systems, with a focus on new platforms developed within the past 5 years. This is an active area of research, and one can expect many improvements as MRI physicists fully explore the landscape of pulse sequences that are feasible, and as clinicians apply these to patient populations.

Deep-KEDI: Deep learning-based zigzag generative adversarial network for encryption and decryption of medical images

BACKGROUND

Medical imaging techniques have improved to the point where security has become a basic requirement for all applications to ensure data security and data transmission over the internet. However, clinical images hold personal and sensitive data related to the patients and their disclosure has a negative impact on their right to privacy as well as legal ramifications for hospitals.

OBJECTIVE

In this research, a novel deep learning-based key generation network (Deep-KEDI) is designed to produce the secure key used for decrypting and encrypting medical images.

METHODS

Initially, medical images are pre-processed by adding the speckle noise using discrete ripplet transform before encryption and are removed after decryption for more security. In the Deep-KEDI model, the zigzag generative adversarial network (ZZ-GAN) is used as the learning network to generate the secret key.

RESULTS

The proposed ZZ-GAN is used for secure encryption by generating three different zigzag patterns (vertical, horizontal, diagonal) of encrypted images with its key. The zigzag cipher uses an XOR operation in both encryption and decryption using the proposed ZZ-GAN. Encrypting the original image requires a secret key generated during encryption. After identification, the encrypted image is decrypted using the generated key to reverse the encryption process. Finally, speckle noise is removed from the encrypted image in order to reconstruct the original image.

CONCLUSION

According to the experiments, the Deep-KEDI model generates secret keys with an information entropy of 7.45 that is particularly suitable for securing medical images.

Tackling SNR at low-field: a review of hardware approaches for point-of-care systems

OBJECTIVE

To review the major hardware components of low-field point-of-care MRI systems which affect the overall sensitivity.

METHODS

Designs for the following components are reviewed and analyzed: magnet, RF coils, transmit/receive switches, preamplifiers, data acquisition system, and methods for grounding and mitigating electromagnetic interference.

RESULTS

High homogeneity magnets can be produced in a variety of different designs including C- and H-shaped as well as Halbach arrays. Using Litz wire for RF coil designs enables unloaded Q values of ~ 400 to be reached, with body loss representing about 35% of the total system resistance. There are a number of different schemes to tackle issues arising from the low coil bandwidth with respect to the imaging bandwidth. Finally, the effects of good RF shielding, proper electrical grounding, and effective electromagnetic interference reduction can lead to substantial increases in image signal-to-noise ratio.

DISCUSSION

There are many different magnet and RF coil designs in the literature, and to enable meaningful comparisons and optimizations to be performed it would be very helpful to determine a standardized set of sensitivity measures, irrespective of design.

M4Raw: A multi-contrast, multi-repetition, multi-channel MRI k-space dataset for low-field MRI research

Recently, low-field magnetic resonance imaging (MRI) has gained renewed interest to promote MRI accessibility and affordability worldwide. The presented M4Raw dataset aims to facilitate methodology development and reproducible research in this field. The dataset comprises multi-channel brain k-space data collected from 183 healthy volunteers using a 0.3 Tesla whole-body MRI system, and includes T1-weighted, T2-weighted, and fluid attenuated inversion recovery (FLAIR) images with in-plane resolution of ~1.2 mm and through-plane resolution of 5 mm. Importantly, each contrast contains multiple repetitions, which can be used individually or to form multi-repetition averaged images. After excluding motion-corrupted data, the partitioned training and validation subsets contain 1024 and 240 volumes, respectively. To demonstrate the potential utility of this dataset, we trained deep learning models for image denoising and parallel imaging tasks and compared their performance with traditional reconstruction methods. This M4Raw dataset will be valuable for the development of advanced data-driven methods specifically for low-field MRI. It can also serve as a benchmark dataset for general MRI reconstruction algorithms.

Diagnostic Image Quality of a Low-Field (0.55T) Knee MRI Protocol Using Deep Learning Image Reconstruction Compared with a Standard (1.5T) Knee MRI Protocol

OBJECTIVES

Low-field MRI at 0.55 Tesla (T) with deep learning image reconstruction has recently become commercially available. The objective of this study was to evaluate the image quality and diagnostic reliability of knee MRI performed at 0.55T compared with 1.5T.

METHODS

A total of 20 volunteers (9 female, 11 male; mean age = 42 years) underwent knee MRI on a 0.55T system (MAGNETOM Free.Max, Siemens Healthcare, Erlangen, Germany; 12-channel Contour M Coil) and a 1.5T scanner (MAGNETOM Sola, Siemens Healthcare, Erlangen, Germany; 18-channel transmit/receive knee coil). Standard two-dimensional (2D) turbo spin echo (TSE), fat-suppressed (fs) proton density-weighted (PDw), T1w TSE, and T2w TSE sequences were acquired in approximately 15 min. In total, 2 radiologists blinded to the field strength subjectively assessed all MRI sequences (overall image quality, image noise, and diagnostic quality) using a 5-point Likert scale (1-5; 5 = best). Additionally, both radiologists evaluated the possible pathologies of menisci, ligaments, and cartilage. Contrast ratios (CRs) of different tissues (bone, cartilage, and menisci) were determined on coronal PDw fs TSE images. The statistical analysis included Cohen's kappa and the Wilcoxon rank sum test.

RESULTS

The overall image quality of the 0.55T T2w, T1w, and PDw fs TSE sequences was diagnostic and rated similar for T1w (p > 0.05), but lower for PDw fs TSE and T2w TSE compared with 1.5T (p < 0.05). The diagnostic accordance of meniscal and cartilage pathologies at 0.55T was similar to 1.5T. The CRs of the tissues were not significantly different between 1.5T and 0.55T (p > 0.05). The inter-observer agreement of the subjective image quality was generally fair between both readers and almost perfect for the pathologies.

CONCLUSIONS

Deep learning-reconstructed TSE imaging at 0.55T yielded diagnostic image quality for knee MRI compared with standard 1.5T MRI. The diagnostic performance of meniscal and cartilage pathologies was equal for 0.55T and 1.5T without a significant loss of diagnostic information.

Low-field 0.55 T MRI for assessment of pulmonary groundglass and fibrosis-like opacities: Inter-reader and inter-modality concordance

PURPOSE

To evaluate detection and characterization of groundglass and fibrosis-like opacities imaged by non-contrast 0.55 Tesla MRI, and versus clinically-acquired chest CT images, in a cohort of post-Covid patients.

MATERIALS AND METHODS

64 individuals (26 women, mean age 53 ± 14 years, range 19-85) with history of Covid-19 pneumonia were recruited through a survivorship registry, with 106 non-contrast low-field 0.55 T cardiopulmonary MRI exams acquired from 9/8/2020-9/28/2021. MRI exams were obtained at an average interval of 9.5 ± 4.5 months from initial symptom report (range 1-18 months). Of these, 20 participants with 22 MRI exams had corresponding clinically-acquired CT chest imaging obtained within 30 days of MRI (average interval 18 ± 9 days, range 0-30). MR and CT images were reviewed and scored by two thoracic radiologists, for presence and extent of lung opacity by quadrant, opacity distribution, and presence versus absence of fibrosis-like subpleural reticulation and subpleural lines. Scoring was performed for each of four lung quadrants: right upper and middle lobe, right lower lobe, left upper lobe and lingula, and left lower lobe. Agreement between readers and modalities was assessed with simple and linear weighted Cohen's kappa (k) coefficients.

RESULTS

Inter-reader concordance on CT for opacity presence, opacity extent, opacity distribution, and presence of subpleural lines and reticulation was 99%, 78%, 97%, 99%, and 94% (k 0.96, 0.86, 0.94, 0.97, 0.89), respectively. Inter-reader concordance on MR, among all 106 exams, for opacity presence, opacity extent, opacity distribution, and presence of subpleural lines and reticulation was 85%, 48%, 70%, 86%, and 76% (k 0.57, 0.32, 0.46, 0.47, 0.37), respectively. Inter-modality agreement between CT and MRI for opacity presence, opacity extent, opacity distribution, and presence subpleural lines and reticulation was 86%, 52%, 79%, 93%, and 76% (k 0.43, 0.63, 0.65, 0.80, 0.52).

CONCLUSION

Low-field 0.55 T non-contrast MRI demonstrates fair to moderate inter-reader concordance, and moderate to substantial inter-modality agreement with CT, for detection and characterization of groundglass and fibrosis-like opacities.

Free-Breathing Low-Field MRI of the Lungs Detects Functional Alterations Associated With Persistent Symptoms After COVID-19 Infection

OBJECTIVES

With the COVID-19 pandemic, repetitive lung examinations have become necessary to follow-up symptoms and associated alterations. Low-field MRI, benefiting from reduced susceptibility effects, is a promising alternative for lung imaging to limit radiations absorbed by patients during CT examinations, which also have limited capability to assess functional alterations. The aim of this investigative study was to explore the functional abnormalities that free-breathing 0.55 T MRI in combination with the phase-resolved functional lung (PREFUL) analysis could identify in patients with persistent symptoms after COVID-19 infection.

MATERIALS AND METHODS

Seventy-four COVID-19 patients and 8 healthy volunteers were prospectively scanned in free-breathing with a balanced steady-state free-precession sequence optimized at 0.55 T, 5 months postinfection on average. Normalized perfusion (Q), fractional ventilation (FV), and flow-volume loop correlation (FVLc) maps were extracted with the PREFUL technique. Q, FV, and FVLc defects as well as defect overlaps between these metrics were quantified. Morphological turbo-spin-echo images were also acquired, and the extent of abnormalities was scored by a board-certified radiologist. To investigate the functional correlates of persistent symptoms, a recursive feature elimination algorithm was applied to find the most informative variables to detect the presence of persistent symptoms with a logistic regression model and a cross-validation strategy. All MRI metrics, sex, age, body mass index, and the presence of preexisting lung conditions were included.

RESULTS

The most informative variables to detect persistent symptoms were the percentage of concurrent Q and FVLc defects and of areas free of those defects. A detection accuracy of 71.4% was obtained with these 2 variables when fitting the model on the entire dataset. Although none of the single variables differed between patients with and without persistent symptoms ( P > 0.05), the combined score of these 2 variables did ( P < 0.02). This score also showed a consistent increase from healthy volunteers (7.7) to patients without persistent symptoms (8.2) and with persistent symptoms (8.6). The morphological abnormality score showed poor correlation with the functional parameters.

CONCLUSIONS

Functional pulmonary examinations using free-breathing 0.55 T MRI with PREFUL analysis revealed potential quantitative markers of impaired lung function in patients with persistent symptoms after COVID-19 infection, potentially complementing morphologic imaging. Future work is needed to explore the translational relevance and clinical implication of these findings.

[Low-field magnetic resonance imaging : Just less expensive or completely different?]

Over the years the development of field strength in magnetic resonance imaging (MRI) has continued to increase from the low-field systems in the early years (0.2-0.5 T) to 1.5 T to 3 T to 7 T and more. In the last 2 years, there has been a renewed interest in MRI at lower fields, mainly driven by the development of "dry" superconductive magnets. The following article demonstrates that this renewed interest for lower fields is not a déjà vu purely driven by economic needs. The field strength appears to be from yesterday, but the combination with the tremendous improvements and innovations of all relevant components-gradients, radiofrequency system and especially new algorithms including the use of artificial intelligence (AI)-allow the realization of diagnostically adequate MRI without compromise in patient throughput and efficiency. In addition to the lower field, there are also some inherent advantages, e.g., for MRI of the lung and of metallic implants and especially for interventional MRI. It has already been shown that many of the devices used for interventional procedures (catheters, biopsy needles) can be used at lower fields without costly modifications. In addition, low-field MRI also allows the robust use of highly efficient sampling methods like spiral MRI. It is therefore safe to predict that low-field MRI is not only a cost-efficient compromise, but has the potential to open up new fields of application.

[New clinical applications for low-field magnetic resonance imaging : Technical and physical aspects]

Hintergrund

Die Niederfeld-Magnetresonanztomographie (MRT) erlebt aufgrund technischer Neuerungen eine Renaissance. Die Geräte der neuen Generation bieten neue Anwendungsspektren in der Bildgebung und eine mögliche Antwort auf den steigenden Kostendruck im Gesundheitssystem.

Fragestellung

Einfluss der Feldstärke auf die Technik, Physik, Bildakquisition und die diagnostische Qualität der Untersuchungen.

Material und Methode

Rekapitulation der wichtigen grundlegenden physikalischen Parameter für Bildgewinnung und Qualität. Erste klinische Erfahrungen mit einem neuen 0,55-T-Niederfeldscanner.

Ergebnisse

Niedrigere Feldstärken als die klinisch aktuell verbreiteten 1,5 T und 3 T sind in der Bildgewinnung durch ein zu erwartendes geringeres Signal-zu-Rausch Verhältnis gekennzeichnet. Ob dies eine diagnostische Limitation ist, muss in Studien evaluiert werden, da es verschiedene Optionen gibt, dieses vermeintliche Defizit zu kompensieren. Dies kann durch eine Verlängerung der Akquisitionszeit oder durch Einsatz von Nachverarbeitungsverfahren mit Hilfe der künstlichen Intelligenz (KI) geschehen. Zudem ist zu validieren, in welchen Körperregionen und bei welchen Krankheitsbildern die Bildqualität diagnostisch ausreichend ist. Erste Untersuchungen in unserer Klinik sind vielversprechend und zeigen beispielsweise diagnostische Qualität ohne relevanten Zeitverlust für Untersuchungen der Lendenwirbelsäule. Potenzielle Stärken aufgrund geringerer Suszeptibilitätsartefakte ergeben sich in der Lungenbildgebung oder bei Implantaten.

Schlussfolgerung

Niederfeldscanner bieten eine Vielzahl von neuen Anwendungsfeldern mit feldstärkebedingten Vorteilen. Bei den meisten anderen klinischen Untersuchungsfeldern kann mindestens eine diagnostische Qualität erwartet werden.

The Clinical Utility of Magnetic Resonance Imaging According to Field Strength, Specifically Addressing the Breadth of Current State-of-the-Art Systems, Which Include 0.55 T, 1.5 T, 3 T, and 7 T

ABSTRACT

This review provides a balanced perspective regarding the clinical utility of magnetic resonance systems across the range of field strengths for which current state-of-the-art units exist (0.55 T, 1.5 T, 3 T, and 7 T). Guidance regarding this issue is critical to appropriate purchasing, usage, and further dissemination of this important imaging modality, both in the industrial world and in developing nations. The review serves to provide an important update, although to a large extent this information has never previously been openly presented. In that sense, it serves also as a position paper, with statements and recommendations as appropriate.

Low-Field Magnetic Resonance Imaging: Its History and Renaissance

ABSTRACT

Low-field magnetic resonance imaging (MRI) systems have seen a renaissance recently due to improvements in technology (both hardware and software). Originally, the performance of low-field MRI systems was rated lower than their actual clinical usefulness, and they were viewed as low-cost but poorly performing systems. However, various applications similar to high-field MRI systems (1.5 T and 3 T) have gradually become possible, culminating with high-performance low-field MRI systems and their adaptations now being proposed that have unique advantages over high-field MRI systems in various aspects. This review article describes the physical characteristics of low-field MRI systems and presents both their advantages and disadvantages for clinical use (past to present), along with their cutting-edge clinical applications.