Department of Industrial and Systems Engineering, University of Florida, Gainesville, Florida, USA.
Department of Radiation Oncology, Mayo Clinic in Florida, Jacksonville, Florida, USA.
Med Phys. 2024 Oct;51(10):7523-7544. doi: 10.1002/mp.17265. Epub 2024 Jun 23.
Intensity Modulated Proton Therapy (IMPT) is a sophisticated radiation treatment allowing for precise dose distributions. However, conventional spot selection strategies in IMPT face challenges, particularly with minimum monitor unit (MU) constraints, affecting planning quality and efficiency.
This study introduces an innovative Two-Stage Mixed Integer Linear Programming (MILP) method to optimize spot intensity in IMPT with Lower Bound (LB) constraints. This method seeks to improve treatment planning efficiency and precision, overcoming limitations of existing strategies.
Our approach evaluates prevalent IMPT spot selection strategies, identifying their limitations, especially concerning MU constraints. We integrated LB constraints into a MILP framework, using a novel three-phase strategy for spot pool selection, to enhance performance over traditional heuristic methods and L1 + L∞ strategies. The method's efficacy was tested in eight study cases, using Dose-Volume Histograms (DVHs), spot selection efficiency, and computation time analysis for benchmarking against established methods.
The proposed method showed superior performance in DVH quality, adhering to LB constraints while maintaining high-quality treatment plans. It outperformed existing techniques in spot selection, reducing unnecessary spots and balancing precision with efficiency. Cases studies confirmed the method's effectiveness in producing clinically feasible plans with enhanced dose distributions and reduced hotspots, especially in cases with elevated LB constraints.
Our Two-Stage MILP strategy signifies a significant advancement in IMPT treatment planning. By incorporating LB constraints directly into the optimization process, it achieves superior plan quality and deliverability compared to current methods. This approach is particularly advantageous in clinical settings requiring minimum spot number and high MU LB constraints, offering the potential for improved patient outcomes through more precise and efficient radiation therapy plans.
强度调制质子治疗（IMPT）是一种精确的放射治疗方法，能够实现精确的剂量分布。然而，IMPT 中的传统光斑选择策略面临挑战，特别是在最小监测单位（MU）限制下，这会影响计划质量和效率。
本研究引入了一种创新的两阶段混合整数线性规划（MILP）方法，通过下限（LB）约束来优化 IMPT 中的光斑强度。该方法旨在提高治疗计划的效率和精度，克服现有策略的局限性。
我们的方法评估了常见的 IMPT 光斑选择策略，确定了它们的局限性，特别是在 MU 限制方面。我们将 LB 约束集成到 MILP 框架中，使用一种新颖的三阶段光斑池选择策略，以提高性能，优于传统启发式方法和 L1+L∞策略。该方法在八个研究案例中进行了测试，使用剂量-体积直方图（DVH）、光斑选择效率和计算时间分析来与现有方法进行基准测试。
所提出的方法在 DVH 质量方面表现出优异的性能，在遵守 LB 约束的同时保持高质量的治疗计划。它在光斑选择方面优于现有技术，减少了不必要的光斑，并在效率和精度之间取得平衡。案例研究证实了该方法在产生具有增强剂量分布和减少热点的临床可行计划方面的有效性，特别是在 LB 约束较高的情况下。
我们的两阶段 MILP 策略是 IMPT 治疗计划的重大进展。通过将 LB 约束直接纳入优化过程，与现有方法相比，它实现了更高质量和可交付性的计划。这种方法在需要最小光斑数量和高 MU LB 约束的临床环境中特别有利，通过更精确和高效的放射治疗计划，为改善患者结果提供了潜力。
