Artifact Correction and Signal Quantification in High Field Breast MRI

Abstract

This thesis investigates artifact correction and signal quantification in high field breast MRI. We focus on dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted imaging (DWI). DCE-MRI is sensitive to inhomogeneities in the radiofrequency transmit (B1+) field. Chapter 2 investigates B1+ field characterization and Chapter 3 explores the possibilities of correcting DCE-MRI for the related contrast artifact. DWI is prone to spatial distortion artifacts due to inhomogeneities in the static magnetic (B0) field. In Chapter 4 we propose a new way to better correct for these distortions, specifically in the breast. Chapter 5 focuses on better quantification of the diffusion signal measured in DWI. Chapter 2 proposes a fast and noise-free way to estimate the B1+ distribution when using local transmit coils at 7 T. In simulations, intersubject differences in local transmit B1+ fields of the breast were found to be comparable to the accuracy of B1+ mapping methods. Therefore, a generic template was proposed and tested in 15 healthy volunteers. In a subset of three volunteers, repeated measurements had an error of up to 15% of the nominal angle; this error range increased slightly by approximately 6% when using a B1+ template. Consequently, a single generic B1+ template suits subjects over a wide range of breast anatomies, eliminating the need for a time-consuming and noise-prone B1+ mapping protocol. In Chapter 3 we use the template approach developed in Chapter 2 as a basis for DCE contrast correction. Using the template as a source of B1+ information, we investigated the correctable B1+ range post acquisition. A direct mapping from measured to true signal intensities was devised to limit noise amplification during correction. Simulations showed that the correctable B1+ range extends down to 43% of the nominal angle. The distribution of curve types in a 7 T patient dataset with a wide range of B1+ levels corresponded better to those reported in literature after correction. Chapter 4 shows that the B0 field in breast has high discontinuities at gland-fat tissue interfaces. Therefore, we developed a distortion correction method that incorporates high-resolution off-resonance maps to better solve severe distortions at tissue interfaces. Quantitative comparisons showed an increase in conformity between corrected EPI images and a non-EPI high-bandwidth reference scan, both ex-vivo and in-vivo. All metrics showed a significant improvement when a high-resolution off-resonance map was used, in particular at tissue boundaries. It is this improvement at tissue interfaces, which is due to the use of high-resolution off-resonance maps that gives our method the advantage over existing distortion correction techniques. Chapter 5 explores whether the phasor transform can aid in producing more stable mixed-signal parameter maps in DWI; first in the context of fixed-diffusivity fraction estimation and second in the context of fitting the intravoxel incoherent motion (IVIM) model. While the phasor-based approach for fixed-diffusivity fraction estimation didn’t improve upon simply solving a linear system, phasor-based IVIM fitting did produce more stable parameter maps for two parameters (the pseudodiffusion fraction f, and the diffusion constant D) compared to nonlinear fitting and segmented fitting.