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• W2735529892 abstract "Abstract Personalized cancer therapy seeks to tailor treatment to an individual patient’s biology. Therefore, a means to characterize radiosensitivity is necessary. In this study, we investigated radiosensitivity in the normal esophagus using an imaging biomarker of radiation-response and esophageal toxicity, esophageal expansion, as a method to quantify radiosensitivity in 134 non-small-cell lung cancer patients, by using K-Means clustering to group patients based on esophageal radiosensitivity. Patients within the cluster of higher response and lower dose were labelled as radiosensitive. This information was used as a variable in toxicity prediction modelling (lasso logistic regression). The resultant model performance was quantified and compared to toxicity prediction modelling without utilizing radiosensitivity information. The esophageal expansion-response was highly variable between patients, even for similar radiation doses. K-Means clustering was able to identify three patient subgroups of radiosensitivity: radiosensitive, radio-normal, and radioresistant groups. Inclusion of the radiosensitive variable improved lasso logistic regression models compared to model performance without radiosensitivity information. Esophageal radiosensitivity can be quantified using esophageal expansion and K-Means clustering to improve toxicity prediction modelling. Finally, this methodology may be applied in clinical trials to validate pre-treatment biomarkers of esophageal toxicity." @default.
• W2735529892 created "2017-07-21" @default.
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• W2735529892 date "2017-07-20" @default.
• W2735529892 modified "2023-09-28" @default.
• W2735529892 title "A Novel Methodology using CT Imaging Biomarkers to Quantify Radiation Sensitivity in the Esophagus with Application to Clinical Trials" @default.
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• W2735529892 doi "https://doi.org/10.1038/s41598-017-05003-x" @default.
• W2735529892 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/5519548" @default.
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