Chang Kai-Hsiang, Ho Ming-Chih, Yeh Chi-Chuan, Chen Yu-Chien, Lian Feng-Li, Lin Win-Li, Yen Jia-Yush, Chen Yung-Yaw
Department of Electrical Engineering, National Taiwan University, Taipei 10617, Taiwan.
Med Phys. 2012 Aug;39(8):5293-301. doi: 10.1118/1.4738966.
Due to low frame rate of MRI and high radiation damage from fluoroscopy and CT, liver motion estimation using external respiratory surrogate signals seems to be a better approach to track liver motion in real-time for liver tumor treatments in radiotherapy and thermotherapy. This work proposes a liver motion estimation method based on external respiratory surrogate signals. Animal experiments are also conducted to investigate related issues, such as the sensor arrangement, multisensor fusion, and the effective time period.
Liver motion and abdominal motion are both induced by respiration and are proved to be highly correlated. Contrary to the difficult direct measurement of the liver motion, the abdominal motion can be easily accessed. Based on this idea, our study is split into the model-fitting stage and the motion estimation stage. In the first stage, the correlation between the surrogates and the liver motion is studied and established via linear regression method. In the second stage, the liver motion is estimated by the surrogate signals with the correlation model. Animal experiments on cases of single surrogate signal, multisurrogate signals, and long-term surrogate signals are conducted and discussed to verify the practical use of this approach.
The results show that the best single sensor location is at the middle of the upper abdomen, while multisurrogate models are generally better than the single ones. The estimation error is reduced from 0.6 mm for the single surrogate models to 0.4 mm for the multisurrogate models. The long-term validity of the estimation models is quite satisfactory within the period of 10 min with the estimation error less than 1.4 mm.
External respiratory surrogate signals from the abdomen motion produces good performance for liver motion estimation in real-time. Multisurrogate signals enhance estimation accuracy, and the estimation model can maintain its accuracy for at least 10 min. This approach can be used in practical applications such as the liver tumor treatment in radiotherapy and thermotherapy.
由于磁共振成像（MRI）的帧率较低，且荧光透视和计算机断层扫描（CT）会造成较高的辐射损伤，因此利用外部呼吸替代信号进行肝脏运动估计似乎是一种在放疗和热疗中实时跟踪肝脏运动以治疗肝肿瘤的更好方法。本文提出了一种基于外部呼吸替代信号的肝脏运动估计方法。还进行了动物实验以研究相关问题，如传感器布置、多传感器融合和有效时间段。
肝脏运动和腹部运动均由呼吸引起，且已证明二者高度相关。与直接测量肝脏运动的困难不同，腹部运动很容易获取。基于这一想法，我们的研究分为模型拟合阶段和运动估计阶段。在第一阶段，通过线性回归方法研究并建立替代信号与肝脏运动之间的相关性。在第二阶段，利用相关模型通过替代信号估计肝脏运动。对单替代信号、多替代信号和长期替代信号的情况进行了动物实验并进行了讨论，以验证该方法的实际应用。
结果表明，最佳的单传感器位置在上腹部中部，而多替代模型通常比单替代模型更好。估计误差从单替代模型的0.6毫米降至多替代模型的0.4毫米。估计模型在10分钟内的长期有效性相当令人满意，估计误差小于1.4毫米。
来自腹部运动的外部呼吸替代信号在实时肝脏运动估计方面表现良好。多替代信号提高了估计精度，且估计模型至少可在10分钟内保持其精度。该方法可用于放疗和热疗中肝肿瘤治疗等实际应用。
