This study describes an approach for remote measuring of on-site temperature and particle concentration using magnetic nanoparticles (MNPs) via simulation and also experimentally. The sensor model indicates that under different applied magnetic fields, the magnetization equation of the MNPs can be discretized to give a higher-order nonlinear equation in two variables that consequently separates information regarding temperature and particle concentration. As a result, on-site tissue temperature or nanoparticle concentration can be determined using remote detection of the magnetization. In order to address key issues in the higher-order equation we propose a new solution method of the first-order model from the perspective of the generalized inverse matrix. Simulations for solving the equation, as well as to optimize the solution of higher equations, were carried out. In the final section we describe a prototype experiment used to investigate the measurement of the temperature in which we used a superconducting magnetometer and commercial MNPs. The overall error after nine repeated measurements was found to be less than 0.57 K within 310-350 K, with a corresponding root mean square of less than 0.55 K. A linear relationship was also found between the estimated concentration of MNPs and the sample's mass.

In this study, we report on a new approach for remote temperature probing that provides accuracy as good as 0.017°C (0.0055% accuracy) by measuring the magnetisation curve of magnetic nanoparticles. We included here the theoretical model construction and the inverse calculation method, and explored the impact caused by the temperature dependence of the saturation magnetisation and the applied magnetic field range. The reported results are of great significance in the establishment of safer protocols for the hyperthermia therapy and for the thermal assisted drug delivery technology. Likewise, our approach potentially impacts basic science as it provides a robust thermodynamic tool for noninvasive investigation of cell metabolism.

In this study, we propose and demonstrate the usefulness of employing time-varying magnetization of a magnetic nanoparticle (MNP) based sample, induced by low frequency (f = 25 Hz) triangular-wave magnetic field, to achieve the approach of real-time recording of magnetization curve, which allows precise and noninvasive temperature probing with real-time performance. Moreover, the present report introduces the design and performed the test of a detection system for accurate and real-time recording of the magnetization curve of MNP-based samples. We found that by employing the magnetization curve of a magnetic fluid sample containing magnetite nanoparticles of about 30 nm in diameter the accuracy of the temperature probing is about 0.32 K (0.1% relative accuracy), with response time of 1 s. Furthermore, an increase in response time from 1 to 8 s improves the accuracy of temperature probing from 0.32 to 0.20 K. Finally, we envisage that breakthroughs in clinical hyperthermia, targeted drug delivery and basic cell research can be accomplished while using the approach reported in this study.

Purpose:To develop a method based on fat-water transition region extraction (TREE) for robust fat-water separation and quantification in challenging scenarios, including low signal-to-noise ratio (SNR), fast changing B 0 field, and disjointed anatomies. Theory and Methods: In TREE method, the phasor solutions of each pixel were categorized into fat-dominant and water-dominant groups. The fat-water transition region was then extracted by detecting sudden changes in the phasor maps. The phasor solutions of the pixels in the transition region were solved by choosing the smoothest phasor combinations. For the remaining subregions, the phasor solution was then determined by all the surrounding transition region pixels. The proposed method was validated using various datasets, including some from the International Society for Magnetic Resonance in Medicine (ISMRM) 2012 Challenge. Results: Quantitative score of proposed method (9936.8 of 10,000) is comparable to the winner (9951.9) of ISMRM 2012 Challenge. The total processing time was 179.3 s for 15 datasets. Sagittal spine data with ~400 mm field of view in head-foot direction were used to compare TREE with several representative region-growing methods. Results showed that the proposed method was robust under fast changing B 0 field, disjointed anatomies and low SNR area. No apparent fat-water swap was observed in the low SNR (SNR ~ 10) dataset. Accurate proton density fat fraction results were also produced from the proposed method. Conclusion: A method based on fat-water transition region extraction was proposed for robust water-fat separation and fat fraction quantification. The method worked well in spatially disjointed objects, fast changing B 0 field, and low SNR application. K E Y W O R D Sfat quantification, fat-water separation, region-growing, transition region extraction | 437 PENG Et al.

This study reports on a new approach for remote nanothermometry with short response time (milliseconds) aiming to operate in liquid media using AC susceptibility components of a suspended magnetic nanoparticle subjected to the Brownian relaxation mechanism. A simple, low cost, and accurate system was designed to measure AC susceptibility using an AC magnetic field at small amplitude (6 Oe) and frequency range (5 kHz) superimposed on a weak DC magnetic field (up to 30 Oe). A model based on the AC susceptibility of magnetic nanoparticles (30 nm average diameter) was constructed to describe the temperature measurement sensitivity of the dominated Brownian relaxation time. A new approach for remote nanothermometry was achieved with measured AC susceptibility by the designed system and the proposed model. Our experimental results show that our magnetonanothermometer allows temperature errors lower than 0.3 K with standard deviations lower than 0.1 K in the temperature range from 310 to 320 K.