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Systems and Methods For Predicting Lung Cancer Immune Therapy Responsiveness Using Quantitative Textural Analysis
Systems and Methods For Predicting Lung Cancer Immune Therapy Responsiveness Using Quantitative Textural Analysis
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机译:使用定量纹理分析预测肺癌免疫治疗反应性的系统和方法
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摘要
Methods and apparatus for predicting responsiveness to immune therapy in lung cancer. The method includes the steps of: identifying a first population of known responders and a second population of known non-responders; processing imaging data for the first and second populations using quantitative textural analysis (QTA); generating, for each member of both populations, quantitative metrics using the QTA; performing logistical regression on the quantitative metrics for both populations to yield a predictive signature expressed in the form of Y=Mx+B where x comprises mean pixel density; performing QTA on a lung cancer scan for a subsequent patient; comparing the predictive signature to one or more relevant metrics associated with the subsequent patient; and predicting responsiveness to immune therapy for the subsequent patient based on the comparison.
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