London Regional Cancer Program, London Health Science Center, London, ON, N6A 4L6, Canada.
Department of Medical Biophysics, Western University, London, ON, N6A 3K7, Canada.
Med Phys. 2019 Mar;46(3):1127-1139. doi: 10.1002/mp.13368. Epub 2019 Jan 21.
The goal of this work was to develop and evaluate a fast inverse direct aperture optimization (FIDAO) algorithm for IMRT treatment planning and plan adaptation.
A previously proposed fluence map optimization algorithm called fast inverse dose optimization (FIDO) was extended to optimize the aperture shapes and weights of IMRT beams. FIDO is a very fast fluence map optimization algorithm for IMRT that finds the global minimum using direct matrix inversion without unphysical negative beam weights. In this study, an equivalent second-order Taylor series expansion of the FIDO objective function was used, which allowed for the objective function value and gradient vector to be computed very efficiently during direct aperture optimization, resulting in faster optimization. To evaluate the speed gained with FIDAO, a proof-of-concept algorithm was developed in MATLAB using an interior-point optimization method to solve the reformulated aperture-based FIDO problem. The FIDAO algorithm was used to optimize four step-and-shoot IMRT cases: on the AAPM TG-119 phantom as well as a liver, prostate, and head-and-neck clinical cases. Results were compared with a conventional DAO algorithm that uses the same interior-point method but using the standard formulation of the objective function and its gradient vector.
A substantial gain in optimization speed was obtained with the prototype FIDAO algorithm compared to the conventional DAO algorithm while producing plans of similar quality. The optimization time (number of iterations) for the prototype FIDAO algorithm vs the conventional DAO algorithm was 0.3 s (17) vs 56.7 s (50); 2.0 s (28) vs 134.1 s (57); 2.5 s (26) vs 180.6 s (107); and 6.7 s (20) vs 469.4 s (482) in the TG-119 phantom, liver, prostate, and head-and-neck examples, respectively.
A new direct aperture optimization algorithm based on FIDO was developed. For the four IMRT test cases examined, this algorithm executed approximately 70-200 times faster without compromising the IMRT plan quality.
本研究旨在开发并评估一种快速逆向直接适形调强放疗（FIDAO）算法，用于调强放疗计划制定和计划调整。
本研究对先前提出的名为快速逆向剂量优化（FIDO）的适形调强放疗射束通量图优化算法进行扩展，以优化适形调强放疗射束的孔径形状和权重。FIDO 是一种非常快速的适形调强放疗射束通量图优化算法，它通过直接矩阵反演找到全局最小值，而不会出现负射束权重的非物理现象。在本研究中，我们使用 FIDO 目标函数的等效二阶泰勒级数展开式，这使得在直接孔径优化过程中能够非常有效地计算目标函数值和梯度向量，从而实现更快的优化。为了评估 FIDAO 获得的速度增益，我们在 MATLAB 中开发了一个概念验证算法，使用内点优化方法来解决重新制定的基于孔径的 FIDO 问题。使用 FIDAO 算法优化了四个步进式调强放疗病例：在 AAPM TG-119 体模以及肝脏、前列腺和头颈部临床病例中。结果与使用相同内点方法但使用标准目标函数及其梯度向量公式的传统 DAO 算法进行了比较。
与传统的 DAO 算法相比，原型 FIDAO 算法在获得相似质量计划的同时，大大提高了优化速度。原型 FIDAO 算法与传统 DAO 算法的优化时间（迭代次数）分别为：在 TG-119 体模、肝脏、前列腺和头颈部病例中，0.3s（17）比 56.7s（50）；2.0s（28）比 134.1s（57）；2.5s（26）比 180.6s（107）；6.7s（20）比 469.4s（482）。
本研究开发了一种基于 FIDO 的新的直接适形调强放疗孔径优化算法。对于检查的四个调强放疗病例，该算法的执行速度提高了约 70-200 倍，而不会影响调强放疗计划的质量。
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