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Niall Moore

Publications and source records attributed to Niall Moore.

3 recordsLinked to original sources

Extracting and visualizing physiological parameters using dynamic contrast-enhanced magnetic resonance imaging of the breast.

An analysis procedure is presented that enables the acquisition and visualization of physiologically relevant parameters using dynamic contrast-enhanced magnetic resonance imaging. The first stage of the process involves the use of a signal model that relates the measured magnetic resonance signal to the contrast agent concentration. Since the model requires knowledge of the longitudinal relaxation time T(1), a novel optimization scheme is presented which ensures a reliable measurement. Pharmacokinetic modelling of the observed contrast agent uptake is then performed to obtain physiological parameters relating to microvessel leakage permeability and volume fraction and the assumptions made in the derivation of these parameters are discussed. A simple colour representation is utilized that enables the relevant physiological information to be conveyed to the clinician in a visually efficient and meaningful manner. A second representation, based on vector maps, is also devised and it is demonstrated how this can be used for malignant tumour segmentation. Finally, the procedure is applied to 14 pre- and post-chemotherapy breast cases to demonstrate the clinical value of the technique. In particular, the apparent improved representation of tissue vascularity when compared to conventional methods and the implications for this in treatment assessment are discussed.

Algorithms↗

Fusion of contrast-enhanced breast MR and mammographic imaging data.

Increasing use is being made of Gd-DTPA contrast-enhanced magnetic resonance imaging for breast cancer assessment since it provides 3D functional information via pharmacokinetic interaction between contrast agent and tumour vascularity, and because it is applicable to women of all ages as well as patients with post-operative scarring. Contrast-enhanced MRI (CE-MRI) is complementary to conventional X-ray mammography, since it is a relatively low-resolution functional counterpart of a comparatively high-resolution 2D structural representation. However, despite the additional information provided by MRI, mammography is still an extremely important diagnostic imaging modality, particularly for several common conditions such as ductal carcinoma in situ (DCIS) where it has been shown that there is a strong correlation between microcalcification clusters and malignancy. Pathological indicators such as calcifications and fine spiculations are not visible in CE-MRI and therefore there is clinical and diagnostic value in fusing the high-resolution structural information available from mammography with the functional data acquired from MRI imaging. This paper presents a novel data fusion technique whereby medial-lateral oblique (MLO) and cranial-caudal (CC) mammograms (2D data) are registered to 3D contrast-enhanced MRI volumes. We utilise a combination of pharmacokinetic modelling, projection geometry, wavelet-based landmark detection and thin-plate spline non-rigid 'warping' to transform the coordinates of regions of interest (ROIs) from the 2D mammograms to the spatial reference frame of the contrast-enhanced MRI volume. Of key importance is the use of a flexible wavelet-based feature extraction technique that enables feature correspondences to be robustly determined between the very different image characteristics of X-ray mammography and MRI. An evaluation of the fusion framework is demonstrated with a series of clinical cases and a total of 14 patient examples.

Adult↗