Evaluating the sensitivity of Halcyon's automatic transit image acquisition for treatment error detection: A phantom study using static IMRT.
Evaluating the sensitivity of Halcyon's automatic transit image acquisition for treatment error detection: A phantom study using static IMRT.
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评估 Halcyon 自动传输图像采集对治疗错误检测的敏感性：使用静态 IMRT 的模型研究。
DOI：
10.1002/acm2.12749
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发表时间：
2019
影响因子：
2.1
通讯作者：
Moore,KevinL
中科院分区：
文献类型：
--
作者：
Ray,Xenia;Bojechko,Casey;Moore,KevinL
目的瓦里安 Halcyon™ 电子射野成像探测器始终与光束对齐，并自动为每位患者采集全视野的传输图像。这些图像可用于“每个患者、每个监测单元”的质量保证（QA）并最终用于适应性放射治疗。本研究评估了成像仪对潜在临床错误和临床退出图像的日常变化的敏感性。方法针对每个潜在错误提供开放和调制场。为了评估输出变化，监测单元按 2%–10% 缩放，并交付给固体水板和同质 CIRS 模型。为了模拟重量变化，在固体水中添加了 0.5–5.0 厘米的堆积物。为了评估位置变化，同质和异质 CIRS 体模分别移动 2-10 厘米和 0.2-1.5 厘米。对于每个测试，计算测试图像和基线图像之间像素差异直方图（σRD）的平均相对差（MRD）和标准差。使用互相关和边缘检测过滤计算横向位移幅度。为了评估患者的差异，我们根据 6 名前列腺患者的每日出口图像计算了 MRD 和 σRD，并比较了存在气体和不存在气体的分数。结果 MRD 对输出和累积变化呈线性响应，标准偏差为 0.3%，这意味着可以以 2.5σ 置信度检测 1% 的输出变化和 0.2 cm 的累积变化。横向移动同质体模会导致可检测到的 MRD 和σRD 变化，并且互相关函数计算出异质体模的移动范围在 0.5 mm 以内。六名患者中的五名患者的 MRD 和 σRD 值与气体的存在显着相关。 结论 对自动采集的 Halcyon™ 出口图像进行快速分析可以高灵敏度地检测治疗中期的变化，但需要设置适当的阈值。这项研究展示了为每位患者治疗的各个方面开发轻松图像评估的第一步。
PurposeThe Varian Halcyon™ electronic portal imaging detector is always in‐line with the beam and automatically acquires transit images for every patient with full‐field coverage. These images could be used for “every patient, every monitor unit” quality assurance (QA) and eventually adaptive radiotherapy. This study evaluated the imager’s sensitivity to potential clinical errors and day‐to‐day variations from clinical exit images.MethodsOpen and modulated fields were delivered for each potential error. To evaluate output changes, monitor units were scaled by 2%–10% and delivered to solid water slabs and a homogeneous CIRS phantom. To mimic weight changes, 0.5–5.0 cm of buildup was added to the solid water. To evaluate positioning changes, a homogeneous and heterogeneous CIRS phantom were shifted 2–10 cm and 0.2–1.5 cm, respectively. For each test, mean relative differences (MRDs) and standard deviations in the pixel‐difference histograms (σRD) between test and baseline images were calculated. Lateral shift magnitudes were calculated using cross‐correlation and edge‐detection filtration. To assess patient variations, MRD andσRDwere calculated from six prostate patients’ daily exit images and compared between fractions with and without gas present.ResultsMRDs responded linearly to output and buildup changes with a standard deviation of 0.3%, implying a 1% output change and 0.2 cm changes in buildup could be detected with 2.5σ confidence. Shifting the homogenous phantom laterally resulted in detectable MRD andσRDchanges, and the cross‐correlation function calculated the shift to within 0.5 mm for the heterogeneous phantom. MRD andσRDvalues were significantly associated with the presence of gas for five of the six patients.ConclusionsRapid analyses of automatically acquired Halcyon™ exit images could detect mid‐treatment changes with high sensitivity, though appropriate thresholds will need to be set. This study presents the first steps toward developing effortless image evaluation for all aspects of every patient’s treatment.