Browsing by Author "Auger, Daniel A"

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    3D cine DENSE MRI: ventricular segmentation and myocardial stratin analysis
    (2013) Auger, Daniel A; Spottiswoode, Bruce S
    Includes abstract. Includes bibliographical references.
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    Open Access
    4D flow and displacement sensitive MR imaging of upper arm arterio-venous connections for haemodialysis
    (2016) Jermy, Stephen; Meintjes, Ernesta M; Franz, Thomas; Auger, Daniel A
    Chronic Kidney Disease (CKD) is a disease that causes kidney damage, often leading to the patient requiring haemodialysis treatment. Haemodialysis treatment requires a vascular access method, commonly Arteriovenous (AV) fistulae and grafts. These access methods must be regularly assessed to ensure the access remains unblocked and the flow rate is normal. Phase Contrast MRA (PC-MRA) is a versatile Magnetic Resonance Imaging (MRI) modality which is capable of imaging and quantifying blood flow in vivo. It is for this reason that this imaging technique was used to image blood flow in the vasculature of the upper arm of volunteers and haemodialysis patients with either an AV fistula or graft. This imaging technique is capable of producing temporally resolved Three-dimensional (3D) datasets (known as "Four-dimensional (4D)" flow) of blood flow in major vessels. Velocities are phase encoded between -π and π based on the chosen Velocity Encoding Constant (venc). To successfully characterise all velocities in the volume it is necessary to set the venc to be approximately equal to the highest velocity found in the vessel. Any lower venc value will cause phase wrapping, an imaging artefact causing all higher velocities to be wrapped by a multiple of 2 π. However, the increase in sensitivity to high velocities reduces the overall specificity of the velocities, especially for low velocities. Due to the pulsatile nature of blood flow in arterial vessels, a large range of velocities are encountered, while venous flow is more constant but lower than the peak arterial flow value. For this reason and due to the length of the 4D flow scans, 20-30 minutes, it would be preferable to perform one scan at a relatively low venc and correct any phase wrapping during post-processing. In this study, we performed both Two-dimensional (2D) PC-MRA scans at various locations in the upper arm and 4D PC-MRA scaans with similar venc settings. The purpose of the study was to implement and test several methods of phase unwrapping to remove phase wrapping artefacts from affected areas within the PC-MRA datasets.
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    Semi-automated left ventricular segmentation based on a guide point model approach for 3D cine DENSE cardiovascular magnetic resonance
    (2014-01-14) Auger, Daniel A; Zhong, Xiaodong; Epstein, Frederick H; Meintjes, Ernesta M; Spottiswoode, Bruce S
    Abstract Background The most time consuming and limiting step in three dimensional (3D) cine displacement encoding with stimulated echoes (DENSE) MR image analysis is the demarcation of the left ventricle (LV) from its surrounding anatomical structures. The aim of this study is to implement a semi-automated segmentation algorithm for 3D cine DENSE CMR using a guide point model approach. Methods A 3D mathematical model is fitted to guide points which were interactively placed along the LV borders at a single time frame. An algorithm is presented to robustly propagate LV epicardial and endocardial surfaces of the model using the displacement information encoded in the phase images of DENSE data. The accuracy, precision and efficiency of the algorithm are tested. Results The model-defined contours show good accuracy when compared to the corresponding manually defined contours as similarity coefficients Dice and Jaccard consist of values above 0.7, while false positive and false negative measures show low percentage values. This is based on a measure of segmentation error on intra- and inter-observer spatial overlap variability. The segmentation algorithm offers a 10-fold reduction in the time required to identify LV epicardial and endocardial borders for a single 3D DENSE data set. Conclusion A semi-automated segmentation method has been developed for 3D cine DENSE CMR. The algorithm allows for contouring of the first cardiac frame where blood-myocardium contrast is almost nonexistent and reduces the time required to segment a 3D DENSE data set significantly.