A semi-automated method for measuring the evolution of both lumen area and blood flow in carotid from Phase Contrast MRI

Phase-Contrast (PC) velocimetry Magnetic Resonance Imaging (MRI) is a useful modality to explore cardiovascular pathologies, but requires the automatic segmentation of vessels and the measurement of both lumen area and blood flow evolutions. In this paper, we propose a semi-automated method for extracting lumen boundaries of the carotid artery and compute both lumen area and blood flow evolutions over the cardiac cycle. This method uses narrow band region-based active contours in order to correctly capture the lumen boundary without being corrupted by surrounding structures. This approach is compared to traditional edge-based active contours, considered in related works, which significantly underestimate lumen area and blood flow. Experiments are performed using both a sequence of a homemade phantom and sequences of 20 real carotids, including a comparison with manual segmentation performed by a radiologist expert. Results obtained on the phantom sequence show that the edge-based approach leads to an underestimate of carotid lumen area and related flows of respectively 18.68% and 4.95%. This appears significantly larger than weak errors obtained using the region-based approach (respectively 2.73% and 1.23%). Benefits appear even better on the real sequences. The edge-based approach leads to underestimates of 40.88% for areas and 13.39% for blood flows, compared to limited errors of 7.41% and 4.6% with our method. Experiments also illustrate the high variability and therefore the lack of reliability of manual segmentation

Measuring blood flow and pulsatility with MRI: optimisation, validation and application in cerebral small vessel disease

Cerebral small vessel disease (SVD) is the breakdown of the small blood vessels of the brain, leading to many cases of stroke and dementia. The pathophysiology of SVD is largely unknown, although several mechanisms have been suggested. One such mechanism is the role of increased blood flow pulsatility into the brain, caused by vessel stiffening, leading to damage of the microvasculature. Magnetic resonance imaging (MRI) allows us to non-invasively measure blood flow and velocity using a technique called phase contrast-MRI – traditionally used with 2D slices across the vessel(s) of interest. An advanced form of phase-contrast MRI, known as 4D flow, has emerged in recent years that allows for a volume of data to be acquired, containing velocity information in all directions. However, to keep scan times practical when collecting this amount of data, spatiotemporal resolution has to be sacrificed. The main aim of this thesis was to assess 4D flow’s capabilities, including comparing it to the more well-established 2D method in healthy volunteers, patients, and phantom experiments, so as to better understand its role in investigating SVD. Another aim was to learn more about the role of flow and pulsatility in SVD development in patients using data acquired in the longitudinal Mild Stroke Study 3 (MSS3). Firstly, I systematically reviewed studies that have assessed the human brain using 4D flow. Across 61 relevant studies, I found a general consensus for the current use of the technique in this context. I then optimised the Siemens prototype 4D flow sequence (N = 11 healthy volunteers), testing different parameters to find the combination that best balanced scan quality and duration. I then assessed the test-retest repeatability and intra-rater reliability of both 2D and 4D methods (N = 11 healthy volunteers), as well as differences between them. Following this, I performed the same 4D-2D comparison on SVD patients (N = 10). Absolute flow measurements using 4D flow were shown to have moderate repeatability and reliability, while flow pulsatility measurements showed acceptable repeatability and reliability. Furthermore, 2D arterial pulsatility was measured higher than with 4D, while 4D often measured higher flow rates than 2D. 4D flow was shown to be feasible when used on SVD patients, with no noticeable issues caused by potential patient movement. Flow data analysis from the longitudinal SVD study MSS3 showed that intracranial pulsatility is associated with cross-sectional SVD lesion volume but not longitudinal lesion growth, with stronger associations seen in the arteries of the neck compared to the venous sinuses

Carotid plaque imaging and the risk of atherosclerotic cardiovascular disease

Carotid artery plaque is a measure of atherosclerosis and is associated with future risk of atherosclerotic cardiovascular disease (ASCVD), which encompasses coronary, cerebrovascular, and peripheral arterial diseases. With advanced imaging techniques, computerized tomography (CT) and magnetic resonance imaging (MRI) have shown their potential superiority to routine ultrasound to detect features of carotid plaque vulnerability, such as intraplaque hemorrhage (IPH), lipid-rich necrotic core (LRNC), fibrous cap (FC), and calcification. The correlation between imaging features and histological changes of carotid plaques has been investigated. Imaging of carotid features has been used to predict the risk of cardiovascular events. Other techniques such as nuclear imaging and intra-vascular ultrasound (IVUS) have also been proposed to better understand the vulnerable carotid plaque features. In this article, we review the studies of imaging specific carotid plaque components and their correlation with risk scores

CT imaging features of carotid artery plaque vulnerability

Despite steady advances in medical care, cardiovascular disease remains one of the main causes of death and long-term morbidity worldwide. Up to 30% of strokes are associated with the presence of carotid atherosclerotic plaques. While the degree of stenosis has long been recognized as the main guiding factor in risk stratification and therapeutical decisions, recent evidence suggests that features of unstable, or 'vulnerable', plaques offer better prognostication capabilities. This paradigmatic shift has motivated researchers to explore the potentialities of non-invasive diagnostic tools to image not only the lumen, but also the vascular wall and the structural characteristics of the plaque. The present review will offer a panoramic on the imaging modalities currently available to characterize carotid atherosclerotic plaques and, in particular, it will focus on the increasingly important role covered by multidetector computed tomographic angiography

Brain Tumour Classification Using Deep Features from Structural MRI

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