3 research outputs found

    Preclinical validation of the advection diffusion flow estimation method using computational patient specific coronary tree phantoms

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    Coronary computed tomography angiography (CCTA) does not allow the quantification of reduced blood flow due to coronary artery disease (CAD). In response, numerical methods based on the CCTA image have been developed to compute coronary blood flow and assess the impact of disease. However to compute blood flow in the coronary arteries, numerical methods require specification of boundary conditions that are difficult to estimate accurately in a patient-specific manner. We describe herein a new noninvasive flow estimation method, called Advection Diffusion Flow Estimation (ADFE), to compute coronary artery flow from CCTA to use as boundary conditions for numerical models of coronary blood flow. ADFE uses image contrast variation along the tree-like structure to estimate flow in each vessel. For validating this method we used patient specific software phantoms on which the transport of contrast was simulated. This controlled validation setting enables a direct comparison between estimated flow and actual flow and a detailed investigation of factors affecting accuracy. A total of 10 CCTA image data sets were processed to extract all necessary information for simulating contrast transport. A spectral element method solver was used for computing the ground truth simulations with high accuracy. On this data set, the ADFE method showed a high correlation coefficient of 0.998 between estimated flow and the ground truth flow together with an average relative error of only 1 % . Comparing the ADFE method with the best method currently available (TAFE) for image-based blood flow estimation, which showed a correlation coefficient of 0.752 and average error of 20 % , it can be concluded that the ADFE method has the potential to significantly improve the quantification of coronary artery blood flow derived from contrast gradients in CCTA images. </p

    Image-based blood flow estimation using a semi-analytical solution to the advection-diffusion equation in cylindrical domains

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    We propose a semi-analytical solution for the advection-diffusion equation in cylindrical domains, with an aim towards extracting blood flow rates from contrast variations in a coronary computed tomography angiography image. The solution proposed in this work, in contrast with existing methods, which only consider advection, incorporates both radial velocity variation and diffusion. By means of a Galerkin approach using Bessel functions, a solution for a three-dimensional concentration field at a single time point is obtained after a Laplace transformation. This semi-analytical solution forms the basis for a novel advection-diffusion flow estimation (ADFE) method. The ADFE is derived, validated through numerical spectral-element method computations, and shown to exhibit improved accuracy against the state-of-the-art method for image-based blood flow extraction
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