Browsing by Subject "Magnetic Resonance Angiography"
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Item An Automated Tool for Measuring Aortic Pulse Wave Velocity(2013-01-22) Goel, Akshay; Peshock, Ronald M.; McColl, Roderick; King, Kevin; Whittemore, AnthonyPURPOSE: Aortic Pulse wave Velocity (APV) has been shown to be associated with end organ damage independent of age, sex, and hypertension duration. The purpose of this study is to evaluate an automated approach for computing transit time (Δt) for the measurement of APV as a tool for future investigations and clinical application. METHODS AND MATERIALS: Phase contrast cardiac gated MRI of the aorta in the transverse plane at the level of the pulmonary artery was utilized from the Dallas Heart Study-2 (DHS2), a multiethnic, population-based study of cardiovascular health. A three-step algorithm was used to analyze all 1884 phase contrast MRI studies from the DHS2 central database. The algorithm functions in three key steps: 1) Isolating contours for the ascending aorta and descending aorta using a computer vision technique known as the Hough Transform. 2) Using isolated contours and phase contrast MRI to generate flow curves for the ascending and descending aorta. 3) Computing Δt defined as the time shift between the flow curves in the ascending aorta (AA) and descending aorta (DA), calculated using the half maximum of AA and DA. Fifty of these studies uniformly distributed across all Δt were then randomly selected and manually analyzed with the standard approach utilizing QFlow (v. 4.1.6, Medis) and the corresponding manually derived flow curves were used to compute Δt. The results from the manual analysis using QFlow were compared to results from the automated algorithm using linear regression Bland-Altman difference analysis. RESULTS: The mean Δt in the 1884 studies analyzed with our automated tool was 19.8+/-6.5 ms. In the validation set of 50 studies, linear regression analysis showed an excellent correlation between the automated (A) and manual (M) methods (r=0.97, A = 1.01M-0.885 ms). Bland-Altman difference analysis showed strong agreement with no significant bias (mean difference (A-M) = -0.386 ± 0.768 ms). CONCLUSION: Our automated approach for computing transit time (Δt) for the measurement of APV demonstrates excellent agreement with the standard manual method. These findings suggest this approach could serve as a useful tool for future investigations and clinical application.Item Measurement of Cerebral Blood Flow Using Arterial Spin Labeling Magnetic Resonance Imaging(2011-02-01) Aslan, Sina; Lu, HanzhangCerebral Blood Flow (CBF) reflects the amount of blood perfusion in the brain, often defined as ml of blood per 100 gram of brain per minute. CBF is an important measure in understanding brain physiology and pathophysiology. Thus, it is important to establish a robust method suitable for longitudinal and cross-sectional studies of neurovascular and neurodegenerative diseases non-invasively. Pseudo-Continuous Arterial Spin Labeling (pCASL) MRI is a new MRI technique that is able to detect blood flow changes, non-invasively. The blood flow change detected by pCASL MRI is relative and it is expressed in terms of arbitrary MRI units which does not have any physiological meaning. Thus, quantifying absolute CBF map is of a great interest. In the first part of this study, I quantified absolute CBF (aCBF) map by utilizing phase contrast MRI as a normalization factor. Next, I provided a systematic investigation into the detection power of ASL and the optimal strategies for data analysis. The power of ASL MRI in detecting CBF differences between patient and control subjects is hampered by inter-subject variations in global CBF, which are associated with non-neural factors and may contribute to the noise in the across-group comparison. I found that when normalizing the CBF with whole-brain CBF or CBF in a reference region (termed relative CBF, rCBF), the statistical significance was improved considerably (p<0.003). In the last part of this study, the aCBF of ten major brain human fibers were estimated for the first time and the relationship between Fractional Anisotropy (FA) and aCBF was investigated. The inverse association between aCBF and FA suggests that higher myelination restricted the blood flow to the center of the fiber or higher myelination made the conductance of the action potential more efficient. In summary, ASL MRI has become the method of choice for measuring cerebral blood flow and it has a great potential in clinical settings for diagnosis of most neurological disorders before anatomical changes are observed.Item Multiparametric Estimation of Brain Hemodynamics with MR Fingerprinting ASL(2018-12-28) Su, Pan; McColl, Roderick W.; Liu, Hanli; Pinho, Marco Da Cunha; Choi, Changho; Lu, HanzhangCerebral perfusion is a process of delivering of blood to tissue capillary beds, supplying sufficient nutrients and oxygen to the brain. It is an important physiology indicator of brain function. The disorder of perfusion such as cerebral vascular disease leads to physiological changes and impaired function of brain. Noninvasive imaging of brain perfusion would contribute significantly to the research of cerebral physiology and clinical application in cerebrovascular diseases. Arterial Spin Labeling (ASL) MRI technique is capable of estimating cerebral blood flow (CBF) without radioactive tracer or contrast agent. However, the signal from ASL is affected by multiple parameters in the kinetic model, causing the complexity in interpreting the underlying physiological mechanism. This thesis develops a novel non-contrast technique for assessing multiple hemodynamic parameters in a single MR scan less than four minutes. The concept of magnetic resonance fingerprinting (MRF) was incorporated into the framework of ASL technique, and a novel sequence, MRF-ASL, was proposed. It is a promising alternative technique in cerebrovascular patients who cannot receive contrast agent based MRI perfusion. This thesis consists of three major components. First, I developed an MR perfusion technique (MRF-ASL) that can provide non-contrast and multi-parametric estimation of hemodynamic markers, in particular measuring timing parameters that are critical for applications in cerebrovascular disease, e.g. bolus arrival time (BAT). Feasibility, reproducibility, comparison to conventional multi-delay ASL and sensitivity were studied. Second, I optimized the key component in MRF-ASL, the TR timing sequence and further increased the spatial coverage of MRF-ASL with multi-slice acquisition. Then with the optimized sequence, I validated the MRF-ASL derived hemodynamic maps with Dynamic Susceptibility Contrast (DSC) MRI. The results showed that these two methods provided visually consistent and quantitatively correlated estimations of CBF and BAT results. Finally, I demonstrated the clinical utility of MRF-ASL by applying our technique to two types of cerebrovascular diseases, ischemic stroke and Moyamoya disease. Results showed that MRF-ASL can detect the prolonged bolus arrival and decreased CBF in these two diseases.