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A concept for classification of optimal breathing pattern for use in radiotherapy tracking, based on respiratory tumor kinematics and minimum jerk analysis

机译:用于放射疗法跟踪的最佳呼吸模式分类的概念,基于呼吸肿瘤运动学和最小的JERK分析

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摘要

Purpose: During radiotherapy, maintaining the patient in a relaxed and comfortable state helps ensure respiratory regularity and reproducibility, thereby supports accurate respiratory tracking/gating treatment. Criteria to evaluate respiratory naturalness, regularity, and phase robustness are therefore needed to aid for the treatment system numerically and medical observers visually. This study introduces a new concept of respiratory tumor kinematics that describes the trajectory of tumor motion with respiration, leading to the minimum jerk theory. Using this theory, this study proposes novel respiratory criteria for respiratory naturalness, regularity, and phase robustness. Methods: According to respiratory tumor kinematics, tumor motion follows the minimum curvature/jerk trajectory in 4D spacetime. Using this theory, the following three respiratory criteria are proposed: (1) respiratory naturalnessU s , the residual sum of the squared difference between the normalized average free respiratory wave (single inhalation/exhalation averaged over each 10 phases) and the normalized minimum jerk theoretical respiratory wave; (2) respiratory regularityC j 16 , the cumulative jerk squared cost function sampling every 0.2 s with a peak adjustment coefficient, 16; and (3) respiratory phase robustness (L ?, a secondorder partial differential in the respiratory position for regardedC j 16as the respiratory position function. To verify these respiratory criteria, values obtained from CyberKnife tracking marker log data for 15 patients were compared with regard to the correlation error between the correlation model and the imaged tumor position, as well as with the number of remodels. TheC j 16growth curve was also compared between 15 patients and 15 healthy volunteers.Results: In the 15 patients, data withU s 1 andC j 16(60 s) 10 000 satisfied average/maximum correlation errors of less than 1/3 mm. Data with higherU s values (less respiratory naturalness) and higherC j 16(60 s) values (less respiratory regularity) demonstrated more than 3 mm average/5 mm maximum correlation errors and an increased number of remodels. The data for the 15 patients and 15 volunteers demonstrated that theC j 16growth curve over 120 s from the start of sampling indicated patientspecific respiratory trends and that the distribution ofL 齝learly showed the respiratory phase shift. In 22 of 30 subjects, the degree of change in theC j growth curve trends from 60 to 120 s was 22% ?3% (average 齋D). In contrast, the residual data observed whenC j 16 1000 showed minimum and mean changes of 91% and 180%, respectively.Conclusions: The authors developed and verified novel respiratory criteria for respiratory naturalness, regularity, and phase robustness obtained using respiratory tumor kinematics and minimum jerk analysis. These criteria should be useful in monitoring respiratory trends on a realtime basis during treatment, as well as in selecting optimal breathing for tracking/gating radiation treatment and defining numerical goals for respiratory training/gating.
机译:目的:在放疗期间,以轻松舒适的状态保持患者有助于确保呼吸规律性和再现性,从而支持准确的呼吸跟踪/门控处理。因此,需要评估呼吸自然,规律性和相稳健性的标准,以便在目视和医疗观察者帮助治疗系统。本研究介绍了一种新的呼吸肿瘤运动学概念,描述了呼吸肿瘤运动的轨迹,导致最小的混蛋理论。使用本理论,本研究提出了呼吸自然,规律性和相稳健性的新型呼吸标准。方法:根据呼吸肿瘤运动学,肿瘤运动遵循4D时空中的最小曲率/混蛋轨迹。使用该理论,提出了以下三个呼吸标准:(1)呼吸自然模,归一化平均自由呼吸波之间的平方差异的残余和在每10阶段的单次吸入/呼气平均)和标准化的最小捷克理论呼吸波; (2)呼吸规则性C J 16,累积的Jerk平方成本函数采样每0.2秒,峰值调整系数16; (3)呼吸相稳健性(L?,呼吸位置中的呼吸位置中的二阶偏差,呼吸位置功能。为了验证这些呼吸标准,与Cyber​​ Knifing标记标记数据获得的值为15名患者的值相关模型与成像肿瘤位置之间的相关误差,以及重组的数量。J 16 16 Growth曲线也在15名患者和15名健康志愿者之间进行比较。结果:在15名患者中,S 1的数据ANDC J 16(60s)& 10 000满意的平均/最大相关误差小于1/3 mm。具有高度的数据(呼吸自然)和高j 16(60 s)值(较少呼吸规律)的数据超过3毫米/ 5mm的最大相关误差和增加的重新陈述。15名患者和15名志愿者的数据表明,J 16 16曲线从Samplin开始超过120秒G指示患者特异性呼吸趋势,并将其分布的分布李读入呼吸相移。在30个受试者中的22个中,60至120秒的J j生长曲线趋势的变化程度为22%?3%(平均斋D)。相反,观察到剩余数据J 16> 1000分别显示最小,平均变化为91%和180%。结论:作者开发和验证了使用呼吸肿瘤运动学获得的呼吸自然,规律性和相稳健性的新型呼吸标准和最小的JERK分析。这些标准应在治疗期间实时监测呼吸趋势,以及选择最佳呼吸以跟踪/门控辐射处理,并定义呼吸训练/门控的数值目标。

著录项

  • 来源
    《Medical Physics》 |2016年第6期|共10页
  • 作者单位

    Department of Radiation Oncology Osaka University Graduate School of Medicine Yamadaoka 2‐2;

    Department of Radiation Oncology Osaka University Graduate School of Medicine Yamadaoka 2‐2;

    Department of Radiation Oncology Osaka University Graduate School of Medicine Yamadaoka 2‐2;

    Department of Radiation Oncology Osaka University Graduate School of Medicine Yamadaoka 2‐2;

    Department of Radiation Oncology Osaka University Graduate School of Medicine Yamadaoka 2‐2;

    Department of Medical Technology Osaka University Hospital Yamadaoka 2‐15 Suita‐shi Osaka 565;

    Department of Radiation Oncology Osaka University Graduate School of Medicine Yamadaoka 2‐2;

    Department of Radiation Oncology Osaka University Graduate School of Medicine Yamadaoka 2‐2;

    Department of Radiation Oncology Osaka University Graduate School of Medicine Yamadaoka 2‐2;

    Department of Radiation Oncology Osaka University Graduate School of Medicine Yamadaoka 2‐2;

  • 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

    kinematics; patient monitoring; pneumodynamics; radiation therapy; tumours;

    机译:运动学;患者监测;肺炎;放射治疗;肿瘤;

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