SEGUE: a Speedy rEgion-Growing algorithm for Unwrapping Estimated phase

Recent Magnetic Resonance Imaging (MRI) techniques, such as Quantitative magnetic Susceptibility Mapping (QSM), employ the signal phase to reveal disease-related changes in tissue composition including iron or calcium content. The MRI phase is also routinely used in functional and diffusion MRI for distortion correction. However, phase images are wrapped into a range of 2π radians. PRELUDE is the gold standard method for robust, spatial, 3-dimensional, MRI phase unwrapping. Unfortunately, PRELUDE's computation time can reach 15 minutes for a severely wrapped brain image and nearly 10 hours to unwrap a full head-and-neck image on a standard PC. Here we develop a Speedy rEgion-Growing algorithm for Unwrapping Estimated phase (SEGUE) based on similar principles to PRELUDE, implemented with additional methods for acceleration. We compared PRELUDE and SEGUE in numerical phantoms, and using in-vivo images of the brain, head-and-neck, and pelvis acquired in 4-5 healthy volunteers and at 4-6 echo times. To overcome chemical-shift-induced errors within the head-and-neck and pelvic images, we also investigated applying both techniques within fat and water masks separately. SEGUE provided almost identical unwrapped phase maps to the gold standard PRELUDE. SEGUE was (1.5 to 70 times) faster than PRELUDE, especially in severely wrapped images at later echoes as well as in the head-and-neck and pelvic images. Applying these techniques within fat and water masks separately successfully removed chemical-shiftinduced errors. SEGUE's MATLAB implementation is available for download. SEGUE is a general unwrapping algorithm not specific to MRI and could, therefore, be used in images acquired with other modalities

Optimising MRI Magnetic Susceptibility Mapping for Applications in Challenging Regions of the Body

Quantitative Susceptibility Mapping (QSM) is a recently developed Magnetic Resonance Imaging (MRI) technique that calculates the tissue magnetic susceptibility from MR phase images. While QSM is mostly used in brain images, it has great potential in other areas such as the head and neck where it has not yet been applied. Poorly oxygenated regions in head-and-neck tumours are expected to have a higher susceptibility due to the high concentration of paramagnetic deoxyhaemoglobin in the microvessels. Therefore, QSM could provide a non-invasive method for identifying hypoxic sites which are more resistant to radiation therapy. Therefore, the main goal of this work was to develop and optimise a QSM pipeline for the head-and-neck region. Applying the complicated processing procedure of QSM to this region is particularly challenging due to: ♦ unavoidable subject motion (e.g. swallowing), ♦ air-tissue interfaces inducing large background fields to be removed, ♦ and fatty tissue introducing an additional, chemical shift-induced phase component to the MRI signal. Moreover, as I have shown in the thesis, acquisition parameters such as image resolution and coverage of the region of interest have a substantial effect on measured susceptibilities. Therefore, tailoring the MRI acquisition is also crucial for accurate QSM in the head-and-neck region. I conducted a comprehensive optimisation of both the MRI acquisition and the QSM pipeline for head-and-neck images and addressed all the aforementioned problems. I developed and optimised a 6-minute acquisition protocol and a QSM processing pipeline. I also created a highly efficient phase unwrapping algorithm for challenging regions. Then, I showed that QSM, using the optimised protocol and pipeline, has high repeatability in the head and neck. Further, I applied this experience with a challenging region to clinical, pelvic MR images of the sacroiliac joint. I showed that bone marrow fat metaplasia has signi cantly higher susceptibility than normal bone marrow mainly due to its fat content