Improved compressed sensing reconstruction for $$^{19}$$ 19 F magnetic resonance imaging

How to 19F MRI: applications, technique, and getting started

Magnetic resonance imaging (MRI) plays a significant role in the routine imaging workflow, providing both anatomical and functional information. 19F MRI is an evolving imaging modality where instead of 1H, 19F nuclei are excited. As the signal from endogenous 19F in the body is negligible, exogenous 19F signals obtained by 19F radiofrequency coils are exceptionally specific. Highly fluorinated agents targeting particular biological processes (i.e., the presence of immune cells) have been visualised using 19F MRI, highlighting its potential for non-invasive and longitudinal molecular imaging. This article aims to provide both a broad overview of the various applications of 19F MRI, with cancer imaging as a focus, as well as a practical guide to 19F imaging. We will discuss the essential elements of a 19F system and address common pitfalls during acquisition. Last but not least, we will highlight future perspectives that will enhance the role of this modality. While not an exhaustive exploration of all 19F literature, we endeavour to encapsulate the broad themes of the field and introduce the world of 19F molecular imaging to newcomers. 19F MRI bridges several domains, imaging, physics, chemistry, and biology, necessitating multidisciplinary teams to be able to harness this technology effectively. As further technical developments allow for greater sensitivity, we envision that 19F MRI can help unlock insight into biological processes non-invasively and longitudinally.

Prognostic Value of Fluorine-19 MRI Oximetry Monitoring in cancer

Hypoxia is a key prognostic indicator in most solid tumors, as it is correlated to tumor angiogenesis, metastasis, recurrence, and response to therapy. Accurate measurement and mapping of tumor oxygenation profile and changes upon intervention could facilitate disease progression assessment and assist in treatment planning. Currently, no gold standard exists for non-invasive spatiotemporal measurement of hypoxia. Magnetic resonance imaging (MRI) represents an attractive option as it is a clinically available and non-ionizing imaging modality. Specifically, perfluorocarbon (PFC) beacons can be externally introduced into the tumor tissue and the linear dependence of their spin-lattice relaxation rate (R1) on the local partial pressure of oxygen (pO2) exploited for real-time tissue oxygenation monitoring in vivo. In this review, we will focus on early studies and recent developments of fluorine-19 MRI and spectroscopy (MRS) for evaluation of tumor oximetry and response to therapy.

Compressed sensing with signal averaging for improved sensitivity and motion artifact reduction in fluorine-19 MRI

Fluorine-19 (19 F) MRI of injected perfluorocarbon emulsions (PFCs) allows for the non-invasive quantification of inflammation and cell tracking, but suffers from a low signal-to-noise ratio and extended scan time. To address this limitation, we tested the hypotheses that a 19 F MRI pulse sequence that combines a specific undersampling regime with signal averaging has both increased sensitivity and robustness against motion artifacts compared with a non-averaged fully sampled pulse sequence, when both datasets are reconstructed with compressed sensing. As a proof of principle, numerical simulations and phantom experiments were performed on selected variable ranges to characterize the point spread function of undersampling patterns, as well as the vulnerability to noise of undersampling and reconstruction parameters with paired numbers of x signal averages and acceleration factor x (NAx-AFx). The numerical simulations demonstrated that a probability density function that uses 25% of the samples to fully sample the k-space central area allowed for an optimal balance between limited blurring and artifact incoherence. At all investigated noise levels, the Dice similarity coefficient (DSC) strongly depended on the regularization parameters and acceleration factor. In phantoms, the motion robustness of an NA8-AF8 undersampling pattern versus NA1-AF1 was evaluated with simulated and real motion patterns. Differences were assessed with the DSC, which was consistently higher for the NA8-AF8 compared with the NA1-AF1 strategy, for both simulated and real cyclic motion patterns (P < 0.001). Both strategies were validated in vivo in mice (n = 2) injected with perfluoropolyether. Here, the images displayed a sharper delineation of the liver with the NA8-AF8 strategy than with the NA1-AF1 strategy. In conclusion, we validated the hypotheses that in 19 F MRI the combination of undersampling and averaging improves both the sensitivity and the robustness against motion artifacts.

Emerging Magnetic Resonance Imaging Techniques for Atherosclerosis Imaging

Atherosclerosis is a prevalent disease affecting a large portion of the population at one point in their lives. There is an unmet need for noninvasive diagnostics to identify and characterize at-risk plaque phenotypes noninvasively and in vivo, to improve the stratification of patients with cardiovascular disease, and for treatment evaluation. Magnetic resonance imaging is uniquely positioned to address these diagnostic needs. However, currently available magnetic resonance imaging methods for vessel wall imaging lack sufficient discriminative and predictive power to guide the individual patient needs. To address this challenge, physicists are pushing the boundaries of magnetic resonance atherosclerosis imaging to increase image resolution, provide improved quantitative evaluation of plaque constituents, and obtain readouts of disease activity such as inflammation. Here, we review some of these important developments, with specific focus on emerging applications using high-field magnetic resonance imaging, the use of quantitative relaxation parameter mapping for improved plaque characterization, and novel ¹⁹F magnetic resonance imaging technology to image plaque inflammation.

Performance of compressed sensing for fluorine-19 magnetic resonance imaging at low signal-to-noise ratio conditions

PURPOSE

To examine the performance of compressed sensing (CS) in reconstructing low signal-to-noise ratio (SNR) ¹⁹ F MR signals that are close to the detection threshold and originate from small signal sources with no a priori known location.

METHODS

Regularization strength was adjusted automatically based on noise level. As performance metrics, root-mean-square deviations, true positive rates (TPRs), and false discovery rates were computed. CS and conventional reconstructions were compared at equal measurement time and evaluated in relation to high-SNR reference data. ¹⁹ F MR data were generated from a purpose-built phantom and benchmarked against simulations, as well as from the experimental autoimmune encephalomyelitis mouse model. We quantified the signal intensity bias and introduced an intensity calibration for in vivo data using high-SNR ex vivo data.

RESULTS

Low-SNR ¹⁹ F MR data could be reliably reconstructed. Detection sensitivity was consistently improved and data fidelity was preserved for undersampling and averaging factors of α = 2 or = 3. Higher α led to signal blurring in the mouse model. The improved TPRs at α = 3 were comparable to a 2.5-fold increase in measurement time. Whereas CS resulted in a downward bias of the ¹⁹ F MR signal, Fourier reconstructions resulted in an unexpected upward bias of similar magnitude. The calibration corrected signal-intensity deviations for all reconstructions.

CONCLUSION

CS is advantageous whenever image features are close to the detection threshold. It is a powerful tool, even for low-SNR data with sparsely distributed ¹⁹ F signals, to improve spatial and temporal resolution in ¹⁹ F MR applications.