Temperature of the magnetic nanoparticle microenvironment: estimation from relaxation times.

Accurate temperature measurements are essential to safe and effective thermal therapies for cancer and other diseases. However, conventional thermometry is challenging so using the heating agents themselves as probes allows for ideal local measurements. Here, we present a new noninvasive method for measuring the temperature of the microenvironment surrounding magnetic nanoparticles from the Brownian relaxation time of nanoparticles. Experimentally, the relaxation time can be determined from the nanoparticle magnetization induced by an alternating magnetic field at various applied frequencies. A previously described method for nanoparticle temperature estimation used a low frequency Langevin function description of magnetic dipoles and varied the excitation field amplitude to estimate the energy state distribution and the corresponding temperature. We show that the new method is more accurate than the previous method at higher applied field frequencies that push the system farther from equilibrium.

Effects of frequency- and direction-dependent elastic materials on linearly elastic MRE image reconstructions.

The mechanical model commonly used in magnetic resonance elastography (MRE) is linear elasticity. However, soft tissue may exhibit frequency- and direction-dependent (FDD) shear moduli in response to an induced excitation causing a purely linear elastic model to provide an inaccurate image reconstruction of its mechanical properties. The goal of this study was to characterize the effects of reconstructing FDD data using a linear elastic inversion (LEI) algorithm. Linear and FDD phantoms were manufactured and LEI images were obtained from time-harmonic MRE acquisitions with variations in frequency and driving signal amplitude. LEI responses to artificially imposed uniform phase shifts in the displacement data from both purely linear elastic and FDD phantoms were also evaluated. Of the variety of FDD phantoms considered, LEI appeared to tolerate viscoelastic data-model mismatch better than deviations caused by poroelastic and anisotropic mechanical properties in terms of visual image contrast. However, the estimated shear modulus values were substantially incorrect relative to independent mechanical measurements even in the successful viscoelastic cases and the variations in mean values with changes in experimental conditions associated with uniform phase shifts, driving signal frequency and amplitude were unpredictable. Overall, use of LEI to reconstruct data acquired in phantoms with FDD material properties provided biased results under the best conditions and significant artifacts in the worst cases. These findings suggest that the success with which LEI is applied to MRE data in tissue will depend on the underlying mechanical characteristics of the tissues and/or organs systems of clinical interest.

Time-harmonic magnetic resonance elastography of the normal feline brain.

Imaging of the mechanical properties of in vivo brain tissue could eventually lead to non-invasive diagnosis of hydrocephalus, Alzheimer's disease and other pathologies known to alter the intracranial environment. The purpose of this work is to (1) use time-harmonic magnetic resonance elastography (MRE) to estimate the mechanical property distribution of cerebral tissue in the normal feline brain and (2) compare the recovered properties of grey and white matter. Various in vivo and ex vivo brain tissue property measurement strategies have led to the highly variable results that have been reported in the literature. MR elastography is an imaging technique that can estimate mechanical properties of tissue non-invasively and in vivo. Data was acquired in 14 felines and elastic parameters were estimated using a globo-regional nonlinear image reconstruction algorithm. Results fell within the range of values reported in the literature and showed a mean shear modulus across the subject group of 7-8 kPa with all but one animal falling within 5-15 kPa. White matter was statistically stiffer (p<0.01) than grey matter by about 1 kPa on a per subject basis. To the best of our knowledge, the results reported represent the most extensive set of estimates in the in vivo brain which have been based on MRE acquisition of the three-dimensional displacement field coupled to volumetric shear modulus image reconstruction achieved through nonlinear parameter estimation. However, the inter-subject variation in mean shear modulus indicates the need for further study, including the possibility of applying more advanced models to estimate the relevant tissue mechanical properties from the data.