Department of Radiotherapy, University of Regensburg, Franz-Josef-Strauss-Allee 11, 93053 Regensburg, Germany.
Z Med Phys. 2011 Sep;21(3):228-35. doi: 10.1016/j.zemedi.2011.02.001. Epub 2011 May 6.
The biological effects of an applied dose can be accounted for by using biological objective functions with IMRT. A commonly used concept is the generalized equivalent uniform dose (gEUD), developed by Niemierko. Unlike the equivalent uniform dose (EUD) which is defined for tumor only, the gEUD can be used for both target volume and organs-at-risk (OAR). In this study, the gEUD has been integrated in our in-house inverse treatment planning system DMCO. DMCO is based on an inverse kernel concept and maintains full Monte-Carlo precision. The system applies direct aperture optimization by means of simulated annealing. Thereby DMCO is per se predestined for the optimization of non-quadratic biological objective functions. In this work, the feasibility of gEUD-based optimization with DMCO is investigated and compared to modified physical optimization. A 'pseudo' Pareto study is performed in order to derive the gEUD-parameters 'a' for the volumes-of-interest of a prostate case. The best biological plan is compared to a physically optimized plan, based on dose-volume objectives (DVO). Furthermore, a hybrid objective function (OF) was developed. It consists of both a biological OF for the OARs and a physical OF for the PTV. The plans are compared to another physically optimized plan, which includes additional zero-DVOs in order to further improve OAR-sparing. As a result of the comparisons it turns out, that the biological OF may improve plan quality with regard to the OARs, but at the price of a degradation of the PTV. This disadvantage can be overcome by a hybrid OF, by which the advantages of both biological and physical OF can be combined. With the application of the physical OF with properly set zero-DVOs, a similar or even superior plan quality may be achieved. The physical OFs do not need the time consuming stochastic optimization, which is mandatory in biological optimization and which is included in DMCO. Furthermore, biological evaluation leaves plan quality rather similar compared to physical optimization, but it cares automatically for the target and the OARs.
应用剂量的生物效应可以通过使用 IMRT 的生物目标函数来解释。一个常用的概念是广义等效均匀剂量（gEUD），由 Niemierko 开发。与仅针对肿瘤的等效均匀剂量（EUD）不同，gEUD 可用于靶区和危及器官（OAR）。在这项研究中，gEUD 已集成到我们的内部逆治疗计划系统 DMCO 中。DMCO 基于逆核概念，并保持完全蒙特卡罗精度。该系统通过模拟退火进行直接孔径优化。因此，DMCO 本身就适合优化非二次生物目标函数。在这项工作中，研究了使用 DMCO 进行基于 gEUD 的优化的可行性，并将其与修改后的物理优化进行了比较。为了得出前列腺病例感兴趣体积的 gEUD 参数 'a'，进行了“伪”Pareto 研究。将最佳生物学计划与基于剂量体积目标（DVO）的物理优化计划进行了比较。此外，还开发了一种混合目标函数（OF）。它包括 OAR 的生物 OF 和 PTV 的物理 OF。将这些计划与另一个物理优化计划进行了比较，该计划包括额外的零-DVO，以进一步改善 OAR 保护。通过比较可以得出结论，生物 OF 可以提高 OAR 方面的计划质量，但代价是 PTV 的恶化。通过混合 OF，可以克服这一劣势，从而结合生物和物理 OF 的优势。通过应用具有适当设置零-DVO 的物理 OF，可以实现类似甚至更好的计划质量。物理 OF 不需要进行耗时的随机优化，这是生物优化中必需的，并且包含在 DMCO 中。此外，与物理优化相比，生物评估使计划质量保持相似，但它会自动考虑目标和 OAR。
