TY - JOUR
T1 - Bolus characteristics based on Magnetic Resonance Angiography
AU - Cai, Zhijun
AU - Stolpen, Alan
AU - Sharafuddin, Melhem J.
AU - McCabe, Robert
AU - Bai, Henri
AU - Potts, Tom
AU - Vannier, Michael
AU - Li, Debiao
AU - Bi, Xiaoming
AU - Bennett, James
AU - Golzarian, Jafar
AU - Sun, Shiliang
AU - Wang, Ge
AU - Bai, Er Wei
PY - 2006/10/17
Y1 - 2006/10/17
N2 - Background: A detailed contrast bolus propagation model is essential for optimizing bolus-chasing Computed Tomography Angiography (CTA). Bolus characteristics were studied using bolus-timing datasets from Magnetic Resonance Angiography (MRA) for adaptive controller design and validation. Methods: MRA bolus-timing datasets of the aorta in thirty patients were analyzed by a program developed with MATLAB. Bolus characteristics, such as peak position, dispersion and bolus velocity, were studied. The bolus profile was fit to a convolution function, which would serve as a mathematical model of bolus propagation in future controller design. Results: The maximum speed of the bolus in the aorta ranged from 5-13 cm/ s and the dwell time ranged from 7-13 seconds. Bolus characteristics were well described by the proposed propagation model, which included the exact functional relationships between the parameters and aortic location. Conclusion: The convolution function describes bolus dynamics reasonably well and could be used to implement the adaptive controller design.
AB - Background: A detailed contrast bolus propagation model is essential for optimizing bolus-chasing Computed Tomography Angiography (CTA). Bolus characteristics were studied using bolus-timing datasets from Magnetic Resonance Angiography (MRA) for adaptive controller design and validation. Methods: MRA bolus-timing datasets of the aorta in thirty patients were analyzed by a program developed with MATLAB. Bolus characteristics, such as peak position, dispersion and bolus velocity, were studied. The bolus profile was fit to a convolution function, which would serve as a mathematical model of bolus propagation in future controller design. Results: The maximum speed of the bolus in the aorta ranged from 5-13 cm/ s and the dwell time ranged from 7-13 seconds. Bolus characteristics were well described by the proposed propagation model, which included the exact functional relationships between the parameters and aortic location. Conclusion: The convolution function describes bolus dynamics reasonably well and could be used to implement the adaptive controller design.
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U2 - 10.1186/1475-925X-5-53
DO - 10.1186/1475-925X-5-53
M3 - Article
C2 - 17044929
AN - SCOPUS:33750606532
SN - 1475-925X
VL - 5
JO - BioMedical Engineering Online
JF - BioMedical Engineering Online
M1 - 53
ER -