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首页> 外文期刊>Medical Physics >The application of the sinusoidal model to lung cancer patient respiratory motion.
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The application of the sinusoidal model to lung cancer patient respiratory motion.

机译：正弦模型在肺癌患者呼吸运动中的应用。

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Accurate modeling of the respiratory cycle is important to account for the effect of organ motion on dose calculation for lung cancer patients. The aim of this study is to evaluate the accuracy of a respiratory model for lung cancer patients. Lujan et al. [Med. Phys. 26(5), 715-720 (1999)] proposed a model, which became widely used, to describe organ motion due to respiration. This model assumes that the parameters do not vary between and within breathing cycles. In this study, first, the correlation of respiratory motion traces with the model f(t) as a function of the parameter n (n = 1, 2, 3) was undertaken for each breathing cycle from 331 four-minute respiratory traces acquired from 24 lung cancer patients using three breathing types: free breathing, audio instruction, and audio-visual biofeedback. Because cos2 and cos4 had similar correlation coefficients, and cos2 and cos1 have a trigonometric relationship, for simplicity, the cos1 value was consequently used for further analysis in which the variations in mean position (z0), amplitude of motion (b) and period (tau) with and without biofeedback or instructions were investigated. For all breathing types, the parameter values, mean position (z0), amplitude of motion (b), and period (tau) exhibited significant cycle-to-cycle variations. Audio-visual biofeedback showed the least variations for all three parameters (z0, b, and tau). It was found that mean position (z0) could be approximated with a normal distribution, and the amplitude of motion (b) and period (tau) could be approximated with log normal distributions. The overall probability density function (pdf) of f(t) for each of the three breathing types was fitted with three models: normal, bimodal, and the pdf of a simple harmonic oscillator. It was found that the normal and the bimodal models represented the overall respiratory motion pdfs with correlation values from 0.95 to 0.99, whereas the range of the simple harmonic oscillator pdf correlation values was 0.71 to 0.81. This study demonstrates that the pdfs of mean position (z0), amplitude of motion (b), and period (tau) can be used for sampling to obtain more realistic respiratory traces. The overall standard deviations of respiratory motion were 0.48, 0.57, and 0.55 cm for free breathing, audio instruction, and audio-visual biofeedback, respectively.
机译：呼吸周期的准确建模对于说明器官运动对肺癌患者剂量计算的影响很重要。这项研究的目的是评估肺癌患者呼吸模型的准确性。 Lujan等。 [医生。物理[26（5），715-720（1999）]提出了一种模型，该模型被广泛使用来描述由于呼吸引起的器官运动。该模型假设参数在呼吸周期之间和之内没有变化。在这项研究中，首先，对于每个呼吸周期，从331个四分钟的呼吸道中获取了呼吸运动轨迹与模型f（t）随参数n（n = 1，2，3）的相关性。 24名肺癌患者使用三种呼吸类型：自由呼吸，音频教学和视听生物反馈。由于cos2和cos4具有相似的相关系数，并且cos2和cos1具有三角关系，因此为简单起见，因此将cos1值用于进一步分析，其中平均位置（z0），运动幅度（b）和周期（牛头）有或没有生物反馈或说明进行了调查。对于所有呼吸类型，参数值，平均位置（z0），运动幅度（b）和周期（tau）表现出明显的周期变化。视听生物反馈显示所有三个参数（z0，b和tau）的变化最小。发现平均位置（z0）可以近似为正态分布，运动幅度（b）和周期（tau）可以近似为对数正态分布。三种呼吸类型中每种呼吸的f（t）的总体概率密度函数（pdf）都装有三种模型：正态，双峰和简单谐波振荡器的pdf。发现正常模型和双峰模型代表整体呼吸运动pdf，相关值在0.95至0.99之间，而简单谐波振荡器pdf相关值的范围在0.71至0.81之间。这项研究表明，平均位置（z0），运动幅度（b）和周期（tau）的pdfs可用于采样以获得更真实的呼吸轨迹。对于自由呼吸，音频指令和视听生物反馈，呼吸运动的总体标准偏差分别为0.48、0.57和0.55 cm。

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