PDF(Pubmed)
Abstract：
Objective. The optimization of energy layer distributions is crucial to proton arc therapy: on one hand, a sufficient number of energy layers is needed to ensure the plan quality; on the other hand, an excess number of energy jumps (NEJ) can substantially slow down the treatment delivery. This work will develop a new treatment plan optimization method with direct minimization of (NEJ), which will be shown to outperform state-of-the-art methods in both plan quality and delivery efficiency.Approach. The proposed method jointly optimizes the plan quality and minimizes the NEJ. To minimize NEJ, (1) the proton spotsxis summed per energy layer to form the energy vectory; (2)yis binarized via sigmoid transform intoy1; (3)y1is multiplied with a predefined energy order vector via dot product intoy2; (4)y2is filtered through the finite-differencing kernel intoy3in order to identify NEJ; (5) only the NEJ ofy3is penalized, whilexis optimized for plan quality. The solution algorithm to this new method is based on iterative convex relaxation.Main results. The new method is validated in comparison with state-of-the-art methods called energy sequencing (ES) method and energy matrix (EM) method. In terms of delivery efficiency, the new method had fewer NEJ, less energy switching time, and generally less total delivery time. In terms of plan quality, the new method had smaller optimization objective values, lower normal tissue dose, and generally better target coverage.Significance. We have developed a new treatment plan optimization method with direct minimization of NEJ, and demonstrated that this new method outperformed state-of-the-art methods (ES and EM) in both plan quality and delivery efficiency.
摘要：
目的：能量层分布的优化对质子ARC治疗至关重要：一方面，需要足够数量的能量层来确保计划质量；另一方面，过量的能量跳跃可以显著减慢治疗递送。这项工作将开发一种新的治疗计划优化方法，直接最小化能量跳跃次数（NEJ），这将被证明在计划质量和交付效率方面优于最先进的方法。＆＃xD;方法：所提出的方法共同优化了计划质量，并最大程度地减少了NEJ。为了最小化NEJ,（1）每个能量层对质子点x进行求和，以形成能量矢量y；（2）通过sigmoid变换将y二值化为y1；（3）y1通过点积与预定义的能量顺序矢量相乘为y2；（4）y2通过有限差分内核过滤为y3，以识别NEJ；（5）仅对y3的NEJ进行惩罚，而x针对计划质量进行了优化。这种新方法的求解算法基于迭代凸松弛。＆＃xD;主要结果：与称为能量测序（ES）方法和能量矩阵（EM）方法的最先进的方法相比，新方法得到了验证。在交付效率方面，新方法有更少的NEJ，更少的能量切换时间，和一般较少的总交货时间。在计划质量方面，新方法的优化目标值较小，正常组织剂量较低，和通常更好的目标覆盖率。＆＃xD;意义：我们开发了一种直接最小化NEJ的新治疗计划优化方法，并证明了这种新方法在计划质量和交付效率方面都优于最先进的方法（ES和EM）。
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