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.

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.

This study is intended to determine the feasiblity of establishing a high-quality, free-standing MR imaging center dedicated to the breast in or about the City of Redlands.

L’imagerie pondérée en diffusion (DWI) représente un outil prometteur pour augmenter la spécificité de l’IRM mammaire en vue du dépistage du cancer du sein. L’épaisseur de coupe pour une acquisition ayant un rapport signal sur bruit suffisant et couvrant les seins dans un temps compatible avec un examen clinique, reste égale ou supérieur à 3 mm, limitant la possibilité de dépistage. Dans ce travail, une méthode DWI isotrope a été développée pour obtenir des images haute résolution isotropes (1x1x1 mm3) couvrant entièrement les seins. Ces images sont obtenues en combinant : (i) une séquence à train de lecture segmenté (rs-EPI) qui correspond à plusieurs segments de lecture EPI avec écho navigation, permettant d’obtenir de hautes résolutions dans le plan, (ii) une stratégie de super-résolution (SR) consistant à acquérir trois jeux de données avec des coupes épaisses (3 mm) et des décalages de 1 mm dans le sens de coupe entre chaque acquisition et (iii) une méthode de reconstruction dédiée pour obtenir des données isotropes 1x1x1 mm3. Plusieurs schémas de reconstruction basés sur différentes régularisations ont été étudiés. La SR proposée a été comparée aux acquisitions natives de 1x1x1 mm3 sans algorithme SR sur huit sujets sains et des fantômes synthétiques. Pour valider la méthode SR, nous avons utilisé plusieurs méthodes : des simulations Monte-Carlo, des mesures de SNR et des métriques de netteté et enfin le coefficient de diffusion apparent (ADC). Ces validations ont aussi été confirmées par des mesures expérimentales sur fantômes contenant des objets de dimensions et diffusion calibrées. Un nouveau protocole de recherche clinique est proposé pour évaluer l’efficacité de la séquence de diffusion à haute résolution sur le dépistage d’un cancer mammaire, dans le but de remplacer la séquence de perfusion avec injection de produit de contraste utilisée en IRM mammaire. / Diffusion-weighted imaging (DWI) is a promising tool to increase the specificity of MRI for breast cancer screening. However, the field of view covering the breasts makes the DWI at high resolution difficult and the images obtained have low signal-to-noise ratios (SNR). The current DWI techniques are limited by the spatial resolution, mainly a slice thickness greater than or equal to 3 mm. In this work, an isotropic DWI method was developed to obtain high resolution isotropic images (1x1x1 mm3) covering the entire breast. These images are obtained by combining: (i) a readout-segmented DW-EPI sequence (rs-EPI), with several segments of k-space and echo navigator providing high in-plane resolution, (ii) a super-resolution (SR) strategy, which consists of acquiring three datasets with thick slices (3 mm) and 1mm-shifts in the slice direction, (iii) and combining them into a 1x1x1 mm3 dataset using a dedicated reconstruction. Several SR reconstruction schemes were investigated, based on different regularizations. The proposed SR strategy was compared to native 1x1x1 mm3 acquisitions (i.e. with 1 mm slice thickness) on eight healthy subjects, and synthetics phantoms. To validate the SR method, we used several methods: Monte Carlo simulations, SNR measurements and sharpness metrics, the apparent diffusion coefficient (ADC) values in normal breast tissue and breast diffusion/resolution phantom were also compared. A new clinical research protocol is proposed to evaluate the effectiveness of the high resolution diffusion sequence on breast cancer screening. The aim of this protocol is to replace the contrast-enhanced perfusion by the diffusion sequence for screening.