Modeling of soft tissue thermal damage based on GPU acceleration

Figures & data

Figure 1. GPU-accelerated computation framework: the mesh data is loaded along with simulation parameters at the host (CPU), and the numerical computation is performed on the designed device (GPU) via a sequential execution of five compute shaders in the GPU rendering pipeline.

Table 1. Execution of compute shaders.

Phase	Shader	Function
1	Shader#1	Clear values of each element in the global coefficient matrix.
2	Shader#2	Calculate the matrices and vectors of each element.
3	Shader#3	Sum element inputs to form the global coefficient matrix and load vector for numerical iterations.
4	Shader#4	Perform the Gauss-Seidel iteration on the linear system of equations.
5	Shader#5	Store the computed temperatures and thermal damage for the subsequent copy from the device (GPU) to host (CPU).

Figure 2. Distribution of temperature ($T$) for the mid-plane ($xy$) at 30 s, where the temperature at the point source is 54 °C.

Figure 3. Transient thermal damage $\phi$ at the mid-plane ($xy$) at (a) 1 s; (b) 10 s; (c) 20 s; (d) 60 s; (e) 150 s; and (f) 300 s; the tissue at the heat source node necrotizes quickly within 20 s, while directly neighboring tissues have not necrotized completely until 300 s.

Figure 4. Time to cellular necrosis (seconds) versus tissue temperature (°C); the time to necrotize the tissue is drastically decreased with the increase of temperature, and the tissue will be necrotized almost instantly when the temperature is above 54 °C.

Figure 5. Thermal damage $\phi$ distribution at the mid-plane ($xy$) at 1200 s.

Figure 6. GPU solution time versus the number of nodes: a mesh of 22,000 nodes can be simulated at 40 ms (intersecting lines).