Comment on "Structure-Correlated Magnetic Resonance Transverse Relaxivity Enhancement in Superparamagnetic Ensembles with Complex Anisotropy Landscape".

In a recent article, Konwar et al. [ Langmuir 2022, 38, 11087-11098.] reported a new relationship between the structure of clusters of superparamagnetic nanoparticles and the proton nuclear magnetic resonance transverse relaxation they induce. In this comment, we would like to express reservations concerning the adequacy of the new relaxation model proposed in this work.

NMR relaxation induced by iron oxide particles: testing theoretical models.

Superparamagnetic iron oxide particles find their main application as contrast agents for cellular and molecular magnetic resonance imaging. The contrast they bring is due to the shortening of the transverse relaxation time T 2 of water protons. In order to understand their influence on proton relaxation, different theoretical relaxation models have been developed, each of them presenting a certain validity domain, which depends on the particle characteristics and proton dynamics. The validation of these models is crucial since they allow for predicting the ideal particle characteristics for obtaining the best contrast but also because the fitting of T 1 experimental data by the theory constitutes an interesting tool for the characterization of the nanoparticles. In this work, T 2 of suspensions of iron oxide particles in different solvents and at different temperatures, corresponding to different proton diffusion properties, were measured and were compared to the three main theoretical models (the motional averaging regime, the static dephasing regime, and the partial refocusing model) with good qualitative agreement. However, a real quantitative agreement was not observed, probably because of the complexity of these nanoparticulate systems. The Roch theory, developed in the motional averaging regime (MAR), was also successfully used to fit T 1 nuclear magnetic relaxation dispersion (NMRD) profiles, even outside the MAR validity range, and provided a good estimate of the particle size. On the other hand, the simultaneous fitting of T 1 and T 2 NMRD profiles by the theory was impossible, and this occurrence constitutes a clear limitation of the Roch model. Finally, the theory was shown to satisfactorily fit the deuterium T 1 NMRD profile of superparamagnetic particle suspensions in heavy water.

Improvement of the Off-Resonance Saturation, an MRI sequence for positive contrast with SPM particles: Theoretical and experimental study.

The SuperParaMagnetic particles (SPM particles) are used as contrast agents in MRI and produce negative contrast with conventional T2 or T2(∗)-weighted sequences. Unfortunately, the SPM particle detection on images acquired with such sequences is sometimes difficult because negative contrast can be created by artifacts such as air bubbles or calcification. To overcome this problem, new sequences as Off-Resonance Saturation (ORS) were developed to produce positive contrast with SPM particles. This work explores a new way to optimize the contrast generated by the ORS sequence by increasing the number of saturation pulses applied before the imaging sequence. This modified sequence is studied with numerical simulations and experiments on agarose gel phantoms. A theoretical model able to predict the contrast for different values of the sequence parameters is also developed. The results show that the contrast increases with the saturation pulses number with an optimal value of three saturation pulses in order to avoid artifacts and limit the Specific Absorption Rate (SAR) effect. The dependence of the contrast on the SPM particle concentration and sequence parameters is comparable to what was observed for the ORS sequence.

Bottom-up study of the MRI positive contrast created by the Off-Resonance Saturation sequence.

Superparamagnetic iron oxide nanoparticles (SPM particles) are used in MRI to highlight regions such as tumors through negative contrast. Unfortunately, sources as air bubbles or tissues interfaces also lead to negative contrast, which complicates the image interpretation. New MRI sequences creating positive contrast in the particle surrounding, such as the Off-Resonance Saturation sequence (ORS), have thus been developed. However, a theoretical study of the ORS sequence is still lacking, which hampers the optimization of this sequence. For this reason, this work provides a self-consistent analytical expression able to predict the dependence of the contrast on the sequence parameters and the SPM particles properties. This expression was validated by numerical simulations and experiments on agarose gel phantoms on a 11.7 T scanner system. It provides a fundamental understanding of the mechanisms leading to positive contrast, which could allow the improvement of the sequence for future in vivo applications. The influence of the SPM particle relaxivities, the SPM particle concentration, the echo time and the saturation pulse parameters on the contrast were investigated. The best contrast was achieved with SPM particles possessing the smallest transverse relaxivity, an optimal particle concentration and for low echo times.

Theoretical and experimental study of ON-Resonance Saturation, an MRI sequence for positive contrast with superparamagnetic nanoparticles.

Superparamagnetic iron oxide nanoparticles (SPM particles) are widely used in MRI as negative contrast agents. Their detection is sometimes difficult because negative contrast can be caused by different artifacts. To overcome this problem, MRI protocols achieving positive contrast specific to SPM particles were developed such as the ON-Resonance Saturation (ONRS) sequence. The aim of the present work is to achieve a bottom-up study of the ONRS sequence by an understanding of the physical mechanisms leading to positive contrast. A complete theoretical modeling, a novel numerical simulation approach and experiments on agarose gel phantoms on a 11.7 T MRI system were carried out for this purpose. The influence of the particle properties and concentration - as well as the effect of the sequence parameters on the contrast - were investigated. It was observed that theory and experiments were in strong agreement. The tools developed in this work allowed to predict the parameters leading to the maximum contrast. For example, particles presenting a low transverse relaxivity can provide an interesting positive contrast after optimization of their concentration in the sample.

New simulation approach using classical formalism to water nuclear magnetic relaxation dispersions in presence of superparamagnetic particles used as MRI contrast agents.

Superparamagnetic nanoparticles are used as negative contrast agents in magnetic resonance imaging: owing to their large magnetic moment the water proton spins are dephased, which accelerates the nuclear magnetic relaxation of an aqueous sample containing these particles. Transverse and longitudinal relaxation times depend on several parameters of the nanoparticles such as radius and magnetization and on experimental parameters such as the static magnetic field or echo time. In this work, we introduce a new simulation methodology, using a classical formalism, allowing the simulation of the NMR signal during transverse and longitudinal relaxation induced by superparamagnetic particles in an aqueous solution, which, to our knowledge has never been done before. Nuclear magnetic relaxation dispersion profiles are obtained for a wide range of nanoparticle radii and magnetizations. The results can be classified in two regimes--the well-known motional averaging and static regimes. This generalizes previous studies focusing on transverse relaxation at high magnetic field (larger than 1 T). Simulation results correspond to analytical theories in their validity range and so far unknown dependences of the relaxation with magnetization and radii of the NMR dispersions profiles are observed, which could be used to characterize experimental samples containing large superparamagnetic particles.