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PNaV:一种通过在多维权衡可视化引导下遍历帕累托曲面来生成高剂量率近距离放射治疗计划的工具。

PNaV: A tool for generating a high-dose-rate brachytherapy treatment plan by navigating the Pareto surface guided by the visualization of multidimensional trade-offs.

作者信息

Deufel Christopher L, Epelman Marina A, Pasupathy Kalyan S, Sir Mustafa Y, Wu Victor W, Herman Michael G

机构信息

Department of Radiation Oncology, Mayo Clinic, Rochester, MN.

Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI.

出版信息

Brachytherapy. 2020 Jul-Aug;19(4):518-531. doi: 10.1016/j.brachy.2020.02.013. Epub 2020 May 15.

Abstract

PURPOSE

A Pareto Navigation and Visualization (PNaV) tool is presented for interactively constructing a high-dose-rate (HDR) brachytherapy treatment plan by navigating and visualizing the multidimensional Pareto surface. PNaV aims to improve treatment planning time and quality and is generalizable to any number of dose-volume histogram (DVH) and convex dose metrics.

METHODS AND MATERIALS

Pareto surface visualization and navigation were demonstrated for prostate, breast, and cervix HDR brachytherapy sites. A library of treatment plans was created to span the Pareto surfaces over a 30% range of doses in each of five DVH metrics. The PNaV method, which uses a nonnegative least-squares model to interpolate the library plans, was compared against pure optimization for 11,250 navigated plans using data envelopment analysis. The visualization of the metric trade-offs was accomplished using numerically estimated partial derivatives to plot the local curvature of the Pareto surface. PNaV enables the user to control both the magnitude and direction of the trade-off during navigation.

RESULTS

Proof of principle of PNaV was demonstrated using a graphical user interface with visualization tools to enabled rapid plan selection and a quantitative review of metric trade-offs. PNaV produced deliverable plans with DVH metrics within < 0.4%, 0.6%, and 1.1% (95% confidence interval) of the Pareto surface using plan libraries with nominal plan spacing of 10%, 15%, and 30% in each metric dimension, respectively. The interpolation used for the navigation executed in 0.1 s. The fast interpolation allows for quick and efficient exploration of trade-off options by the physician, after an initial preprocessing step to generate the library.

CONCLUSIONS

Generation, visualization, and navigation of the Pareto surface were validated for brachytherapy treatment planning. The PNaV method enables efficient and informed decision-making for radiotherapy.

摘要

目的

提出一种帕累托导航与可视化(PNaV)工具,用于通过对多维帕累托曲面进行导航和可视化来交互式构建高剂量率(HDR)近距离放射治疗计划。PNaV旨在改善治疗计划的时间和质量,并且可推广到任意数量的剂量体积直方图(DVH)和凸剂量指标。

方法与材料

展示了针对前列腺、乳腺和宫颈HDR近距离放射治疗部位的帕累托曲面可视化和导航。创建了一个治疗计划库,以涵盖五个DVH指标中每个指标在30%剂量范围内的帕累托曲面。使用非负最小二乘模型对库计划进行插值的PNaV方法,与使用数据包络分析对11250个导航计划进行的纯优化方法进行了比较。通过数值估计的偏导数来绘制帕累托曲面的局部曲率,从而实现指标权衡的可视化。PNaV使用户能够在导航过程中控制权衡的幅度和方向。

结果

使用带有可视化工具的图形用户界面展示了PNaV的原理证明,该界面能够实现快速计划选择和对指标权衡的定量审查。PNaV分别使用每个指标维度标称计划间距为10%、15%和30%的计划库,生成了DVH指标在帕累托曲面的<0.4%、0.6%和1.1%(95%置信区间)内的可交付计划。用于导航的插值在0.1秒内执行完毕。快速插值使得医生在生成库的初始预处理步骤之后,能够快速有效地探索权衡选项。

结论

帕累托曲面的生成、可视化和导航在近距离放射治疗计划中得到了验证。PNaV方法能够为放射治疗提供高效且明智的决策。

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