Clegg S T, Samulski T V, Murphy K A, Rosner G L, Dewhirst M W
Department of Radiation Oncology, Duke University Medical Center, Durham, NC 27710.
IEEE Trans Biomed Eng. 1994 Apr;41(4):373-82. doi: 10.1109/10.284965.
Numerical modeling methods and hyperthermia treatment temperature measurements have been used together to reconstruct steady-state tumor temperature distributions. However, model errors will exist which may in turn produce errors in the reconstructed temperature distributions. A series of computer experiments was conducted to study the sensitivity of reconstructed two-dimensional temperature distributions to perfusion distribution modeling errors. Temperature distributions were simulated using a finite element approximation of Pennes' bioheat transfer equation. Relevant variables such as tumor shape, perfusion distribution, and power deposition were modeled. An optimization method and the temperatures "measured" from the simulated temperature distributions were used to reconstruct the tumor temperature distribution. Using this procedure, the sensitivity of the reconstructed tumor temperature distribution to model-related errors, such as the perfusion function, was studied. It was found that: 1) if the problem is conduction dominated, large errors in the perfusion distribution produce only small errors in the reconstructed temperature distribution (maximum error < 1.0 degrees C), and 2) when the actual perfusion distribution contains a small random variation (+/- 15%) which is neglected by the model, the reconstructed temperature distribution will be in good agreement with the actual temperature distribution (maximum error < or = 0.3 degrees.
数值建模方法和热疗治疗温度测量已被结合使用，以重建稳态肿瘤温度分布。然而，模型误差将会存在，这反过来可能会在重建的温度分布中产生误差。进行了一系列计算机实验，以研究重建的二维温度分布对灌注分布建模误差的敏感性。使用彭尼斯生物热传递方程的有限元近似来模拟温度分布。对肿瘤形状、灌注分布和功率沉积等相关变量进行了建模。采用一种优化方法和从模拟温度分布中“测量”的温度来重建肿瘤温度分布。利用该程序，研究了重建的肿瘤温度分布对与模型相关的误差（如灌注函数）的敏感性。结果发现：1）如果问题以传导为主，灌注分布中的大误差只会在重建的温度分布中产生小误差（最大误差<1.0摄氏度），并且2）当实际灌注分布包含模型忽略的小随机变化（±15%）时，重建的温度分布将与实际温度分布高度吻合（最大误差<或=0.3摄氏度）。
