Tomographic temperature imaging with magnetic nanoparticles

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Noninvasive temperature imaging beneath the surface of an object is a hot and challenging topic. This project proposes a new method to realize tomographic temperature imaging with high spatial, temperature and temporal resolutions. In a gradient dc magnetic field and a homogeneous ac magnetic field, the amplitude of each odd harmonic of a spot MNP sample decreases with increasing the distance between the spot sample and a time-average field free point (aFFP), which shows a point spread function (PSF) shape. Thus, the amplitude of each odd harmonic of a MNP assemble in a field of view can be expressed by the convolution of the PSF and the corresponding harmonic generated by the local MNPs. An existing MPI scanner is modified to enable the aFFP scanning, the generation of an ac magnetic field for MNP excitation and the measurements of the 3rd and 5th harmonics of MNP magnetization. A separate deconvolution is proposed to deconvolute the 3rd and 5th harmonics based on the corresponding harmonic PSF. Consequently, temperature imaging is realized with the deconvoluted 3rd and 5th harmonics applying MNP thermometry based on the static Langevin function. Phantom experiments are performed to demonstrate the feasibility of the proposed method for temperature imaging. Afterwards, an iterative deconvolution and a joint deconvolution with constrained conditions are, respectively, investigated to improve the temperature imaging. Furthermore, the influence of MNP dynamics on MNP thermometry is investigated to realize MNP thermometry including MNP dynamics. Consequently, a fast temperature imaging is realized with a fast aFFP scanning in a high-frequency ac magnetic field applying MNP thermometry including MNP dynamics. We emphasize that the outcomes of this proposed project have great potential for the temperature imaging beneath the surface of an object and are promising for biomedical applications such as magnetic hyperthermia, but also for other biological and industrial tasks.