Quantifying Proton Fields for Midline Brain Tumors: A Benefit/Cost Analysis of Planning Objectives

量化质子场治疗中线脑肿瘤:规划目标的效益/成本分析

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Abstract

PURPOSE: We sought to quantify the optimum number of beams by using a midline sagittal arrangement for midline brain tumors when considering the competing demands of a high degree of target conformation and maximizing reduction of nontarget brain dose. The volume of nontarget brain tissue receiving between 5 and 20 Gy (V5-V20) was selected to measure "low-dose bath" to normal brain. MATERIALS AND METHODS: An exploratory model was developed with 6 midline brain targets created by using spheres of 1-, 3-, and 5-cm diameters located in superficial and deep locations. For each, five 3-dimensional proton treatment plans with uniform beam scanning were generated by using 1 to 5 fields. Dose-volume histograms were analyzed to calculate conformation number and V5-V20. A benefit/cost analysis was performed to determine the marginal gain in conformation number and the marginal cost of V5-V20 for the addition of each field and hypothesize the optimum number of treatment fields. We tested our hypothesis by re-planning 10 actual patient tumors with the same technique to compare the averages of these 50 plans to our model. RESULTS: Our model and validation cohort demonstrated the largest marginal benefit in target conformation and the lowest marginal cost in normal brain V5-V20 with the addition of a second proton field. The addition of a third field resulted in a relative marginal benefit in target conformation of just 3.9% but a relative marginal cost in V5-V20 of 78.7%. Normal brain absolute V5-V20 increased in a nearly linear fashion with each additional field. CONCLUSIONS: When treating midline brain lesions with 3-dimensional proton therapy in an array of midline sagittal beams, our model suggests the most appropriate number of fields is 2. There was little marginal benefit in target conformation and increasing cost of normal brain dose when increasing the number of fields beyond this.

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