FULL THERMAL MODELING

全热建模

• 批准号: 6102304
• 负责人: SCOTT T CLEGG
• 金额: $ 28.07万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-08-01 至 1999-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6102304
• 关键词: clinical biomedical equipment; computed axial tomography; computer simulation; cytotoxicity; magnetic resonance imaging; mathematical model; model design /development; neoplasm /cancer radiation therapy; neoplasm /cancer thermotherapy; neoplastic cell; phantom model; radiation dosage; thermometry

Accurate and complete knowledge of the power deposition and HT induced temperature distribution will aid clinical personnel in maximizing the delivery of the HT while minimizing complications. Unfortunately, such knowledge is presently unavailable. In the case of the temperature distribution, invasive sparsely sampled temperatures are typically acquired but we have shown that descriptors of the temperature distribution that rely on sparsely sampled temperatures can be biased and thus unreliable. Patient specific anatomic features make it difficult to know, a priori, the power deposition and thus its optimal delivery not possible. Numerical modeling techniques are one possible solution for overcoming these problems. During the previous funding period, we developed an FE numerical method and associated gridding algorithm to routinely compute patient specific power deposition patterns induced with a regional RF device. We verified the accuracy of the method using data obtained from phantom and clinical treatments. We have also shown, in preliminary studies, that improved temperature distributions are obtained when this numerical method is employed. Thus, we are proposing to improve the HT induced temperature distributions through the use of numerical modeling methods. Hypothesis: Prospective modeling of the EM induced power deposition will yield improved HT temperature distributions. Application of numerical modeling methods to estimate the complete temperature distribution is a more difficult and complex problem primarily due to the need to mathematically approximate the blood flow. We have shown it is both possible and feasible to reconstruct the HT induced temperature distribution using simplifying assumptions. However, we know that additional vascular data will be necessary to routinely and accurately reconstruct the complete temperature distribution. Thus, we are proposing to improve and evaluate the accuracy of our existing models of biothermal energy transport when used to reconstruct the temperatures. Hypothesis: Retrospective reconstruction of HT induced temperature distributions will be accurate and robust. Finally, because the HT induced temperature distribution is heterogeneous, empirical development of a relationship between cell survival and response is very difficult especially when confounding influences such as radiation dose and microenvironmental factors are considered. We believe that mathematical modeling methods have the potential to aid in the development and understanding these relationships. Thus, we are proposing to explore the use of mathematical modeling to estimate tumor cell survival following HT. Hypothesis: It will be possible to develop numerical models that estimate the relative importance of variations of factors that contribute to the degree of cytotoxicity from a thermoradiotherapeutic treatment.

准确完整地了解功率沉积和高温诱导 温度分布将帮助临床人员最大化 同时最大限度地减少并发症。可惜这样 知识是目前无法获得的。在温度的情况下 分布，侵入性稀疏采样温度通常是 但我们已经证明，温度的描述符 依赖于稀疏采样温度的分布可能会有偏差， 因此不可靠。患者特定的解剖特征使得难以 先验地知道功率沉积，因此不知道其最佳输送， 可能数值建模技术是一种可能的解决方案， 克服这些问题。 在上一个资助期间，我们开发了一种有限元数值方法， 以及相关的网格算法，以常规地计算患者特异性 功率沉积模式与区域RF设备诱导。我们验证 使用从体模和临床获得的数据的方法的准确性 治疗。我们还在初步研究中表明， 温度分布时，这种数值方法是 就业。因此，我们建议提高HT诱导温度 分布通过使用数值模拟方法。假设： 电磁感应功率沉积的前瞻性建模将产生 改善HT温度分布。 应用数值模拟方法估计完整的 温度分布是一个更困难和复杂问题，主要 这是因为需要在数学上近似血流。我们有 表明重建HT诱导的 使用简化假设的温度分布。但我们知道 额外的血管数据将是必要的， 精确地重建完整的温度分布。因此，我们 建议改善和评估我们现有的模型的准确性， 当用于重建温度时，生物能量传输。 假设：HT诱导温度的回顾性重建 分布将是准确和稳健的。 最后，由于高温诱导的温度分布是不均匀的， 细胞存活和反应之间关系的经验发展 特别是当干扰因素如辐射 考虑了剂量和微环境因素。我们认为 数学建模方法有可能帮助开发 理解这些关系。因此，我们建议探讨 使用数学建模来估计以下肿瘤细胞存活率 HT。假设：将有可能开发数字模型， 估计影响因素变化的相对重要性 热辐射处理的细胞毒性程度。