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.
ObjectiveTo analyze the impact of the lymph node ratio (LNR, ratio of metastatic to examined nodes) on the prognosis of hypopharyngeal cancer patients.MethodsSEER (Surveillance, Epidemiology and End Results)-registered hypopharyngeal cancer patients with lymph node metastasis were evaluated using multivariate Cox regression analysis to identify the prognostic role of the LNR. The categorical LNR was compared with the continuous LNR and pN classifications to predict cause-specific survival (CSS) and overall survival (OS) rates of hypopharyngeal cancer patients.ResultsMultivariate analysis of 916 pN+ hypopharyngeal cancer cases identified race, primary site, radiation sequence, T classification, N classification, M classification, the number of regional lymph nodes examined, the continuous LNR (Hazard ratio 2.415, 95% CI 1.707–3.416, P<0.001) and age as prognostic variables that were associated with CSS in hypopharyngeal cancer. The categorical LNR showed a higher C-index and lower Akaike information criterion (AIC) value than the continuous LNR. When patients (n = 1152) were classified into four risk groups according to LNR, R0 (LNR = 0), R1 (LNR ≤0.05), R2 (LNR 0.05–0.30) and R3 (LNR >0.30), the Cox regression model for CSS and OS using the R classification had a higher C-index value and lower AIC value than the model using the pN classification. Significant improvements in both CSS and OS were found for R2 and R3 patients with postoperative radiotherapy.ConclusionsLNR is a significant prognostic factor for the survival of hypopharyngeal cancer patients. Using the cutoff points 0.05/0.30, the R classification was more accurate than the pN classification in predicting survival and can be used to select high risk patients for postoperative treatment.
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