GPU‐assisted real‐time coupling of blood flow and vessel wall

Abstract

The vessel wall and the blood flow interact and influence each other, and real-time coupling between them is of great importance to the virtual surgery as well as the research and diagnosis of vascular disease. On the basis of smoothed particle hydrodynamics (SPH), we present a new approach to solve non-Newtonian viscous force of blood and a parallel mixed particles-based coupling method for blood flow and vessel wall. Meanwhile, we also design a proxy particle-based vessel wall force visualization method. Our method is as follows. Firstly, we solve the non-Newtonian viscous forces of blood through the SPH method to discretize the Casson equation. Secondly, in each time step, we combine blood particles and sampling proxy particles on the blood vessel wall to form mixed particles and calculate the interaction forces through the SPH method between every pair of the neighboring mixed particles inside the graphics processing unit. Thirdly, the forces of the proxy particles will be mapped to the color display of the proxy particle. Experimental results demonstrate that our method is able to implement real-time sizeable coupling of blood flow and vessel wall while mainly ensuring physical authenticity and it can also provide real-time and obvious information about vessel wall force distribution.

Periodic-corrected data-driven coupling of blood flow and the vessel wall for virtual surgery

“…The environment for the experiments is as follows: Windows 7 Ultimate 64bits SP1, Intel Xeon E 3-1230 V2@ 3.30-GHz quad-core processor, 8 GB internal storage, and graphics card of NVIDIA GeForces GTX 650 Ti (1 GB). We choose the GPU accelerated blood vessel wall coupling method proposed by Guo et al 15 as a physical simulation method for acquiring training samples and as a contrast method for the proposed method. The simulation scenario where we get the input data (the particle state feature vector of the current frame) and the target data (the particle acceleration of the next frame of blood flow) is as follows: Initialize a columnar blood flow of a certain height and let it flow into the fixed blood vessel model under gravity.…”

“…Lai and Xiang 14 implemented graphics processing unit (GPU)assisted blood flow simulation using the Compute Unified Device Architecture (CUDA), achieving 50 fps simulation at 9000 particles, but they did not consider the interaction of blood flow with blood vessels. Guo et al 15 proposed a GPU-accelerated mixed particle-based coupling method for blood flow and the vessel wall that real-time simulated at the 100,000 particle size. Although these studies have made some improvements in computational efficiency, a more efficient method is urgently needed due to the multiphase coupling involved in the virtual surgery scene with flexible organs and surgical instruments.…”

“…Blood flow is essentially a non-Newtonian fluid, and thus we describe the blood flow using the Navier-Stokes equation, which includes non-Newtonian terms, as follows 15 :…”

“…14 Guo et al proposed a GPUaccelerated mixed particle-based coupling method for blood flow and vessel wall that real-time simulated at 100,000 particle size. 15 Although these studies have made some improvements in computational efficiency, a more efficient method is urgently needed due to the multi-phase coupling involved in the virtual surgery scene with flexible organs and surgical instruments.…”