Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has a high sensitivity (71-
100%) for detecting breast cancers. DCE-MRI is approximately twice as sensitive as mammography for patients who are genetically predisposed to breast cancer, who have an
elevated lifetime risk (up to 85%) of contracting the disease, and who require rigorous screening. However, current methods of DCE-MRI often have difficulty distinguishing malignant from benign tumours, resulting in low positive predictive values (on average, PPV = 45%). The research in this thesis is motivated by the need for improvement in the ability of MRI to differentiate breast lesions. It is believed that the differentiation of malignant from benign lesions can be improved by acquiring images of high spatial resolution for visualizing morphological features of tumours and those of high temporal resolution for characterizing
contrast-kinetic curves. However, simultaneously achieving high spatial and temporal resolution is limited by the inherent trade-off between speed and quality in MRI, requiring one to choose a particular balance of spatial and temporal resolution. In this thesis, novel techniques are presented that reduce the need to choose a spatiotemporal resolution before the scan. Flexible methods are presented that allow images to be retrospectively reconstructed with different balances of spatial and temporal resolution from the same dataset. Flexibility is achieved through radial sampling of k-space data, with 3D radial directions based on Multidimensional
Golden Means (MGM) and Halton sequences. Radial sampling also allows constrained image
reconstruction techniques such as Compressed Sensing and Prior-Image Constrained
Compressed Sensing to be incorporated for reducing undersampling artifacts in high-temporalresolution images. This thesis demonstrates in 2D how such reconstruction algorithms are influenced by acquisition schemes and shows how reconstruction algorithms work in synergy with flexible radial sampling to provide improvements in the quality of breast MR images. The
flexibility to choose any spatiotemporal resolution combined with better image quality in fast images could potentially improve the characterization of breast lesions screened by MRI.
| Identifer | oai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/32677 |
| Date | 20 August 2012 |
| Creators | Chan, Rachel Wai-Chung |
| Contributors | Plewes, Donald Bruce |
| Source Sets | University of Toronto |
| Language | en_ca |
| Detected Language | English |
| Type | Thesis |
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