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Implementation of the structural SIMilarity (SSIM) index as a quantitative evaluation tool for dose distribution error detection

机译:实现结构相似性(SSIM)指数作为剂量分布错误检测的定量评估工具

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摘要

Purpose To apply an imaging metric of the structural SIMilarity (SSIM) index to the radiotherapy dose verification field and evaluate its capability to reveal the different types of errors between two dose distributions. Method The SSIM index consists of three sub‐indices: luminance, contrast, and structure. Given two images, luminance analysis compares the local mean result, contrast analysis compares the local standard deviation, and the structure index represents the local Pearson correlation. Three test error patterns (absolute dose error, dose gradient error, and dose structure error) were designed to characterize the response of SSIM and its sub‐indices and establish the correlation between the indices and different dose error types. After establishing the correlation, four radiotherapy plans (one MLC picket‐fence test plan, one brain stereotactic radiotherapy plan, and two head‐and‐neck plans) were tested by computing each index and compared with the gamma analysis results to determine their similarities and differences. Results Among the three test error patterns, the luminance index decreased from 1 to 0.1 when the absolute dose agreement fell from 100% to 5%, the contrast index decreased from 1 to 0.36 when the dose gradient agreement fell from 100% to 10%, and the structure index decreased from 1 to 0.23 when the periodical dose pattern shifted (leading to a lower correlation). Thus, the luminance, contrast and structure index can detect the absolute dose error, gradient discrepancy, and dose structure error, respectively. For the four clinical cases, the sub‐indices can reveal the type of error when gamma analysis only provided limited information. Conclusions The correlation between the subcomponents of the SSIM index and the error types of the dose distribution were established. The SSIM index provides additional error information compared to that provided by gamma analysis.
机译:目的要应用的结构相似性(SSIM)索引到所述放射治疗剂量验证字段的成像度量并评价其能力以显示2个剂量分布之间的不同类型的错误。方法将SSIM指数包括三个分项指数:亮度,对比度和结构。给定两个图像,亮度分析比较了局部平均结果,对比度分析比较了局部标准偏差,并且该结构指数表示本地Pearson相关。三个测试错误模式(绝对剂量误差,剂量梯度误差,和剂量结构误差)被设计为表征SSIM及其子索引的响应,并建立索引和不同剂量的错误类型之间的相关性。建立的相关性后,四个放疗计划(一个MLC栅栏测试计划,一个脑立体定向放射治疗计划,和两个头部和颈部的计划)通过计算每个指标测试和比较用伽马分析结果,以确定它们的相似和差异。结果在三个测试错误模式中,亮度指数从1减少到0.1时的绝对剂量协议从100%下降到5%时,对比度指数从1减少到0.36,当剂量梯度协议从100%下降到10%,和结构指数从1时周期性剂量图案移位(导致较低的相关性)降低到0.23。因此,亮度,对比度和结构指数可检测绝对剂量误差,梯度差异,和剂量结构误差,分别。对于四临床病例,该分项指数可以揭示错误的类型时,伽马分析仅供有限的信息。结论SSIM索引的子组件和所述错误类型的剂量分布之间的相关性来建立。所述SSIM索引提供相比于通过γ分析提供了额外的错误信息。

著录项

  • 来源
    《Medical Physics》 |2020年第4期|共13页
  • 作者单位

    Department of Radiation OncologyFudan University Shanghai Cancer CenterShanghai China;

    Department of Medical PhysicsMemorial Sloan Kettering Cancer CenterNew York NY USA;

    Department of Radiation OncologyWashington UniversitySt. Louis MO 63110 USA;

    Department of Radiation OncologyFudan University Shanghai Cancer CenterShanghai China;

    Department of Radiation OncologyFudan University Shanghai Cancer CenterShanghai China;

    Department of Radiation OncologyWashington UniversitySt. Louis MO 63110 USA;

    Department of Radiation OncologyWashington UniversitySt. Louis MO 63110 USA;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 基础医学;
  • 关键词

    dose distribution; quality assurance; SSIM;

    机译:剂量分配;质量保证;SSIM;

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