Department of Radiotherapy, University of Regensburg, Regensburg, Germany.
Z Med Phys. 2010;20(3):197-205. doi: 10.1016/j.zemedi.2010.03.003. Epub 2010 Apr 2.
Direct Monte Carlo Optimization (DMCO) is a powerful method for dose optimization with Monte Carlo accuracy and direct aperture optimization with simulated annealing. Recently, we presented quasi intensity modulated arc therapy (qIMAT), a step-and-shoot technique that simulates a rotational technique by using a high number of beams and reducing the number of segments. In the present work, we applied a combination of both techniques to optimize an anal cancer case. Because of the limited memory of standard computers, two techniques for reducing the size of the inverse kernel (IK) were investigated. The standard deviation degradation technique (SDDT) and the reduced resolution technique (RRT) were applied to a 7-field IMRT plan on the CarPet phantom. Several IKs with an estimated standard deviation (SD) of the MC-calculation of 5%, 10% and 15% and another three IKs with voxel size of 4, 8 and 16mm were calculated. All IKs were optimized with DMCO; after optimization, a final dose calculation with 5% SD and 4mm resolution was carried out. SDDT was a better compromise between plan quality and IK-size reduction than RRT. PTV homogeneity and dose sparing to the OAR was almost identical for SDDT, while for RRT the quality was degraded by low resolution. Therefore, SDDT was applied to the anal cancer case. The IK-file of a quasi-IMAT plan with 30 beams was calculated with XVMC with 15% SD and a voxel size of 4mm. After optimization with DMCO using one segment per beam, a final dose calculation with 2% variance was performed. By comparing the DVHs of qIMAT with a 7-field IMRT (commercial therapy planning system) and with a 7-field IMRT (DMCO), qIMAT showed considerably advantages over IMRT in OARs dose sparing. In this way, the DMCO optimization with qIMAT of complex cases with large treatment volumes, such as anal cancer, are possible. Furthermore, for anal cancer, the comparison of qIMAT with IMRT showed that qIMAT can improve the plan quality.
直接蒙特卡罗优化（DMCO）是一种强大的方法，可实现蒙特卡罗精度的剂量优化，并具有模拟退火的直接孔径优化。最近，我们提出了准强度调制弧形治疗（qIMAT），这是一种分步射击技术，通过使用大量射束并减少段数来模拟旋转技术。在本工作中，我们将这两种技术结合起来优化一例肛门癌病例。由于标准计算机的内存有限，研究了两种减小逆核（IK）大小的技术。标准偏差降低技术（SDDT）和降低分辨率技术（RRT）应用于 CarPet 体模上的 7 野 IMRT 计划。计算了估计 MC 计算标准偏差（SD）为 5％、10％和 15％的几个 IK 以及另三个体素大小为 4、8 和 16mm 的 IK。所有 IK 均使用 DMCO 进行优化；优化后，进行了具有 5％SD 和 4mm 分辨率的最终剂量计算。与 RRT 相比，SDDT 是在计划质量和 IK 尺寸减小之间的更好折衷。对于 SDDT，PTV 均匀性和 OAR 剂量节省几乎与 RRT 相同，而对于 RRT，低分辨率会降低质量。因此，将 SDDT 应用于肛门癌病例。使用 XVMC 计算了具有 30 个射束的准-IMAT 计划的 IK 文件，其 SD 为 15％，体素大小为 4mm。使用每个射束一个段进行 DMCO 优化后，进行了具有 2％方差的最终剂量计算。通过比较 qIMAT 与 7 野 IMRT（商业治疗计划系统）和 7 野 IMRT（DMCO）的 DVH，qIMAT 在 OAR 剂量节省方面明显优于 IMRT。通过这种方式，可以对具有大治疗体积（例如肛门癌）的复杂病例进行 qIMAT 的 DMCO 优化。此外，对于肛门癌，qIMAT 与 IMRT 的比较表明，qIMAT 可以改善计划质量。
