Magnetic Properties Of Tissues Research Articles

A mechanistic computational framework to investigate the hemodynamic fingerprint of the blood oxygenation level-dependent signal.

Blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) is one of the most used imaging techniques to map brain activity or to obtain clinical information about human cortical vasculature, in both healthy and disease conditions. Nevertheless, BOLD fMRI is an indirect measurement of brain functioning triggered by neurovascular coupling. The origin of the BOLD signal is quite complex, and the signal formation thus depends, among other factors, on the topology of the cortical vasculature and the associated hemodynamic changes. To understand the hemodynamic evolution of the BOLD signal response in humans, it is beneficial to have a computational framework available that virtually resembles the human cortical vasculature, and simulates hemodynamic changes and corresponding MRI signal changes via interactions of intrinsic biophysical and magnetic properties of the tissues. To this end, we have developed a mechanistic computational framework that simulates the hemodynamic fingerprint of the BOLD signal based on a statistically defined, three-dimensional, vascular model that approaches the human cortical vascular architecture. The microvasculature is approximated through a Voronoi tessellation method and the macrovasculature is adapted from two-photon microscopy mice data. Using this computational framework, we simulated hemodynamic changes-cerebral blood flow, cerebral blood volume, and blood oxygen saturation-induced by virtual arterial dilation. Then we computed local magnetic field disturbances generated by the vascular topology and the corresponding blood oxygen saturation changes. This mechanistic computational framework also considers the intrinsic biophysical and magnetic properties of nearby tissue, such as water diffusion and relaxation properties, resulting in a dynamic BOLD signal response. The proposed mechanistic computational framework provides an integrated biophysical model that can offer better insights regarding the spatial and temporal properties of the BOLD signal changes.

Principles and applications of susceptibility weighted imaging

Susceptibility-weighted imaging (SWI), initially developed to provide an improved method for cerebral magnetic resonance (MR) venography, is now an integral part of neuroradiological diagnostics and is steadily gaining importance in non-cerebral imaging. Tissue-inherent susceptibility differences generate a local magnetic field in which the dephasing of signal-producing protons occurs. This leads to a characteristic phase shift that can be used as a means to enhance contrast in the well-known T2*-weighted imaging. Many medically relevant pathologies induce tissue alterations that also influence the magnetic properties of tissue. Thus, the detection of blood residues and calcifications in SWI is superior to conventional MR sequences. New techniques, such as quantitative susceptibility mapping (QSM) and susceptibility tensor imaging (STI) allow improved differentiation between blood residues and calcifications and provide an alternative imaging method for fiber tractography with respect to diffusion tensor imaging.

Contrast-enhanced magneto-photo-acoustic imaging in vivo using dual-contrast nanoparticles

By mapping the distribution of targeted plasmonic nanoparticles (NPs), photoacoustic (PA) imaging offers the potential to detect the pathologies in the early stages. However, optical absorption of the endogenous chromophores in the background tissue significantly reduces the contrast resolution of photoacoustic imaging. Previously, we introduced MPA imaging – a synergistic combination of magneto-motive ultrasound (MMUS) and PA imaging, and demonstrated MPA contrast enhancement using cell culture studies. In the current study, contrast enhancement was investigated in vivo using the magneto-photo-acoustic (MPA) imaging augmented with dual-contrast nanoparticles. Liposomal nanoparticles (LNPs) possessing both optical absorption and magnetic properties were injected into a murine tumor model. First, photoacoustic signals were generated from both the endogenous absorbers in the tissue and the liposomal nanoparticles in the tumor. Then, given significant differences in magnetic properties of tissue and LNPs, the magnetic response of LNPs (i.e. MMUS signal) was utilized to suppress the unwanted PA signals from the background tissue thus improving the PA imaging contrast. In this study, we demonstrated the 3D MPA imaging of LNP-labeled xenografted tumor in a live animal. Compared to conventional PA imaging, the MPA imaging show significantly enhanced contrast between the nanoparticle-labeled tumor and the background tissue. Our results suggest the feasibility of MPA imaging for high contrast in vivo mapping of dual-contrast nanoparticles.