Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD, USA.
Phys Med Biol. 2010 Feb 7;55(3):883-902. doi: 10.1088/0031-9155/55/3/022. Epub 2010 Jan 14.
The conventional IMRT planning process involves two stages in which the first stage consists of fast but approximate idealized pencil beam dose calculations and dose optimization and the second stage consists of discretization of the intensity maps followed by intensity map segmentation and a more accurate final dose calculation corresponding to physical beam apertures. Consequently, there can be differences between the presumed dose distribution corresponding to pencil beam calculations and optimization and a more accurately computed dose distribution corresponding to beam segments that takes into account collimator-specific effects. IMRT optimization is computationally expensive and has therefore led to the use of heuristic (e.g., simulated annealing and genetic algorithms) approaches that do not encompass a global view of the solution space. We modify the traditional two-stage IMRT optimization process by augmenting the second stage via an accurate Monte Carlo-based kernel-superposition dose calculations corresponding to beam apertures combined with an exact mathematical programming-based sequential optimization approach that uses linear programming (SLP). Our approach was tested on three challenging clinical test cases with multileaf collimator constraints corresponding to two vendors. We compared our approach to the conventional IMRT planning approach, a direct-aperture approach and a segment weight optimization approach. Our results in all three cases indicate that the SLP approach outperformed the other approaches, achieving superior critical structure sparing. Convergence of our approach is also demonstrated. Finally, our approach has also been integrated with a commercial treatment planning system and may be utilized clinically.
传统的调强放射治疗（IMRT）计划过程包括两个阶段，第一阶段包括快速但近似理想化的铅笔束剂量计算和剂量优化，第二阶段包括强度图的离散化，随后是强度图分割以及更准确的对应物理射束孔径的最终剂量计算。因此，铅笔束计算和优化对应的假定剂量分布与更准确地考虑准直器特定效应的对应射束段的计算剂量分布之间可能存在差异。IMRT 优化计算成本高，因此导致使用启发式（例如模拟退火和遗传算法）方法，这些方法不包括解决方案空间的全局视图。我们通过在第二阶段通过准确的基于蒙特卡罗的针对射束孔径的核叠加剂量计算进行增强来修改传统的两阶段 IMRT 优化过程，同时结合使用线性规划（SLP）的精确基于数学规划的顺序优化方法。我们的方法在三个具有多叶准直器约束的具有挑战性的临床测试案例中进行了测试，这些案例对应于两个供应商。我们将我们的方法与传统的 IMRT 计划方法、直接孔径方法和分段权重优化方法进行了比较。我们在所有三个案例中的结果表明，SLP 方法优于其他方法，实现了更好的关键结构保护。我们还证明了我们方法的收敛性。最后，我们的方法还与商业治疗计划系统集成，可以在临床上使用。
