The purpose of this study is to evaluate the correlations between external markers and internal targets for radiation therapy of lung cancer patients. Using an infrared camera system coupled with a clinical simulator, the simultaneous motions of multiple external markers and an internal target were obtained. The correlation between external and internal signals was analyzed using a cross-covariance function. A linear regression model was employed to generate a composite signal from multiple external markers in order to predict the internal target motion. The external and internal signals, and their correlations, demonstrated a wide range of variation with respect to marker location, motion dimension, and breathing pattern. The performance of the composite signal indicates that when more external signals were taken into account, the mean correlation between the composite signal and internal signal was improved. This implies that a combination of multiple external signals might be an improved way to predict internal target motion. Also, since the characteristics of respiratory signals can vary significantly, certain methods of preprocessing and external signal combination are necessary.
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