Zhijun Cai | PubMed Health

PubMed2006

Bolus characteristics based on Magnetic Resonance Angiography.

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.

Computer Simulation↗

PubMedDate not supplied

Projection-based bolus detection for computed tomographic angiography.

Computed tomographic (CT) angiography is important for imaging studies on cardiovascular structures, peripheral vessels, and solid organs. In practice, a CT angiography scan is triggered by the bolus arrival at a prespecified anatomical location, which is determined using CT fluoroscopy. In this article, we propose a projection-based method adapted from the Grangeat formula to detect the bolus arrival. Then, we evaluate our new method in numerical and animal studies. Our results indicate that this method allows significantly better temporal resolution and is computationally more efficient, as compared with the image-based methods.

Algorithms↗