Computational techniques for fast hyperthermia temperature optimization
Computational techniques for fast hyperthermia temperature optimization
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DOI：
10.1118/1.598519
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发表时间：
1999-02-01
期刊：
影响因子：
3.8
通讯作者：
Samulski, TV
中科院分区：
文献类型：
--
作者：
Das, SK;Clegg, ST;Samulski, TV
热疗温度优化涉及达到使所述目标函数最小化的温度分布，所述目标函数具有使肿瘤细胞杀伤最大化同时不超过正常组织毒性的生物学基础。这涉及温度目标函数的多次评估的计算密集型过程，需要重复评估功率沉积及其对应的温度分布。提出了两种计算方案来加快温度优化过程：（1）通过叠加预先计算的分布来评估温度分布，以及（2）使用代表性组织组（而不是域中的每个点）来评估目标函数。这些计划的应用说明了一个典型的优化问题，适用于对称和非对称，异构模型。这些方案的应用减少了DEC Alpha 1000 4/266（Alpha是Digital Equipment Corporation的注册商标）上的优化时间。从几小时到几分钟，结果几乎没有差别。计算方案，虽然在电磁热疗的背景下，通常适用于其他形式的非电离辐射热疗治疗。(C)1999年美国医学物理学家协会。[S0094-2405（99）01602-8]。
Hyperthermia temperature optimization involves arriving at a temperature distribution which minimizes a stated goal function, the goal function having a biological basis in maximizing tumor cell kill while not exceeding normal tissue toxicity. This involves the computationally intensive process of multiple evaluations of the temperature goal function, requiring repeated evaluations of the power deposition and its corresponding temperature distribution. Two computational schemes are proposed to expedite the temperature optimization process: (1) temperature distribution evaluation by superpositioning precomputed distributions, and (2) using representative tissue groups (rather than every point in the domain) to evaluate the goal function. The application of these schemes is illustrated with a typical optimization problem, as applied to symmetric and asymmetric, heterogeneous models. Application of these schemes reduced the optimization time on a DEC Alpha 1000 4/266 (Alpha is a registered trademark of Digital Equipment Corporation.) from several h to min, with little difference in results. The computational schemes, though demonstrated in the context of electromagnetic hyperthermia, are generally applicable to other forms of nonionizing radiation employed in hyperthermia therapy. (C) 1999 American Association of Physicists in Medicine. [S0094-2405(99)01602-8].