Although 1.5 and 3 Tesla (T) magnetic resonance (MR) systems remain the clinical standard, the number of 7 T MR systems has increased over the past decade because of the promise of higher signal-to-noise ratio (SNR), which can translate to images with higher resolution, improved image quality and faster acquisition times. However, there are a number of technical challenges that have prevented exploiting the full potential of ultra-high field (≥ 7 T) MR imaging (MRI), such as the inhomogeneous distribution of the radiofrequency (RF) electromagnetic field and specific energy absorption rate (SAR), which can compromise image quality and patient safety.
To better understand the origin of these issues, we first investigated the dependence of the spatial distribution of the magnetic field associated with a surface RF coil on the operating frequency and electrical properties of the sample. Our results demonstrated that the asymmetries between the transmit (B1+) and receive (B 1–) circularly polarized components of the magnetic field, which are in part responsible for RF inhomogeneity, depend on the electric conductivity of the sample. On the other hand, when sample conductivity is low, a high relative permittivity can result in an inhomogeneous RF field distribution, due to significant constructive and destructive interference patterns between forward and reflected propagating magnetic field within the sample.
We then investigated the use of high permittivity materials (HPMs) as a method to alter the field distribution and improve transmit and receive coil performance in MRI. We showed that HPM placed at a distance from an RF loop coil can passively shape the field within the sample. Our results showed improvement in transmit and receive sensitivity overlap, extension of coil field-of-view, and enhancement in transmit/receive efficiency. We demonstrated the utility of this concept by employing HPM to improve performance of an existing commercial head coil for the inferior regions of the brain, where the specific coil’s imaging efficiency was inherently poor. Results showed a gain in SNR, while the maximum local and head SAR values remained below the prescribed limits. We showed that increasing coil performance with HPM could improve detection of functional MR activation during a motor-based task for whole brain fMRI.
Finally, to gain an intuitive understanding of how HPM improves coil performance, we investigated how HPM separately affects signal and noise sensitivity to improve SNR. For this purpose, we employed a theoretical model based on dyadic Green’s functions to compare the characteristics of current patterns, i.e. the optimal spatial distribution of coil conductors, that would either maximize SNR (ideal current patterns), maximize signal reception (signal-only optimal current patterns), or minimize sample noise (dark mode current patterns). Our results demonstrated that the presence of a lossless HPM changed the relative balance of signal-only optimal and dark mode current patterns. For a given relative permittivity, increasing the thickness of the HPM altered the magnitude of the currents required to optimize signal sensitivity at the voxel of interest as well as decreased the net electric field in the sample, which is associated, via reciprocity, to the noise received from the sample. Our results also suggested that signal-only current patterns could be used to identify HPM configurations that lead to high SNR gain for RF coil arrays. We anticipate that physical insights from this work could be utilized to build the next generation of high performing RF coils integrated with HPM.
|Advisor:||Lattanzi, Riccardo, Sodickson, Daniel K.|
|Commitee:||Chang, Gregory, Collins, Christopher M.|
|School:||New York University|
|Department:||Basic Medical Science|
|School Location:||United States -- New York|
|Source:||DAI-B 79/02(E), Dissertation Abstracts International|
|Subjects:||Biomedical engineering, Medical imaging, Physics|
|Keywords:||7 Tesla, Electromagnetic fields, High field, High permittivity materials, Ideal current patterns, Magnetic resonance imaging|
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