School of Engineering, RMIT University , Bundoora , Australia.
Robotics and Mechatronics Research Laboratory, Department of Mechanical and Aerospace Engineering, Monash University , Clayton , Australia.
Comput Assist Surg (Abingdon). 2019 Oct;24(sup1):5-12. doi: 10.1080/24699322.2018.1557891. Epub 2019 Jul 24.
Hyperthermia treatments require precise control of thermal energy to form the coagulation zones which sufficiently cover the tumor without affecting surrounding healthy tissues. This has led modeling of soft tissue thermal damage to become important in hyperthermia treatments to completely eradicate tumors without inducing tissue damage to surrounding healthy tissues. This paper presents a methodology based on GPU acceleration for modeling and analysis of bio-heat conduction and associated thermal-induced tissue damage for prediction of soft tissue damage in thermal ablation, which is a typical hyperthermia therapy. The proposed methodology combines the Arrhenius Burn integration with Pennes' bio-heat transfer for prediction of temperature field and thermal damage in soft tissues. The problem domain is spatially discretized on 3-D linear tetrahedral meshes by the Galerkin finite element method and temporally discretized by the explicit forward finite difference method. To address the expensive computation load involved in the finite element method, GPU acceleration is implemented using the High-Level Shader Language and achieved via a sequential execution of compute shaders in the GPU rendering pipeline. Simulations on a cube-shape specimen and comparison analysis with standalone CPU execution were conducted, demonstrating the proposed GPU-accelerated finite element method can effectively predict the temperature distribution and associated thermal damage in real time. Results show that the peak temperature is achieved at the heat source point and the variation of temperature is mainly dominated in its direct neighbourhood. It is also found that by the continuous application of point-source heat energy, the tissue at the heat source point is quickly necrotized in a matter of seconds, while the entire neighbouring tissues are fully necrotized in several minutes. Further, the proposed GPU acceleration significantly improves the computational performance for soft tissue thermal damage prediction, leading to a maximum reduction of 55.3 times in computation time comparing to standalone CPU execution.
热疗需要精确控制热能以形成凝固区域，这些区域应充分覆盖肿瘤，同时不影响周围的健康组织。这使得软组织热损伤建模在热疗中变得非常重要，因为其目的是在不引起周围健康组织损伤的情况下彻底消灭肿瘤。本文提出了一种基于 GPU 加速的方法，用于建模和分析生物热传导以及相关的热诱导组织损伤，以预测热消融中的软组织损伤，这是一种典型的热疗方法。所提出的方法将 Arrhenius Burn 积分与 Pennes 生物传热相结合，用于预测软组织中的温度场和热损伤。问题域在三维线性四面体网格上通过 Galerkin 有限元方法离散化，在时间上通过显式向前有限差分方法离散化。为了解决有限元方法中涉及的昂贵计算负载，使用高级着色语言在 GPU 上实现了 GPU 加速，并通过在 GPU 渲染管道中顺序执行计算着色器来实现。在立方体形状的样本上进行了模拟，并与独立的 CPU 执行进行了比较分析，结果表明，所提出的 GPU 加速有限元方法可以有效地实时预测温度分布和相关的热损伤。结果表明，峰值温度出现在热源点，温度的变化主要由其直接邻域决定。还发现，通过连续施加点源热能，热源点处的组织在几秒钟内迅速坏死，而整个邻近组织在几分钟内完全坏死。此外，所提出的 GPU 加速方法显著提高了软组织热损伤预测的计算性能，与独立的 CPU 执行相比，计算时间最多减少了 55.3 倍。
