A Novel Methodology using CT Imaging Biomarkers to Quantify Radiation Sensitivity in the Esophagus with Application to Clinical Trials

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...

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Autores principales:	Joshua S. Niedzielski, Jinzhong Yang, Francesco Stingo, Zhongxing Liao, Daniel Gomez, Radhe Mohan, Mary Martel, Tina Briere, Laurence Court
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/966915397e484ccb974449090e63c828
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spelling	oai:doaj.org-article:966915397e484ccb974449090e63c8282021-12-02T11:52:15ZA Novel Methodology using CT Imaging Biomarkers to Quantify Radiation Sensitivity in the Esophagus with Application to Clinical Trials10.1038/s41598-017-05003-x2045-2322https://doaj.org/article/966915397e484ccb974449090e63c8282017-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-05003-xhttps://doaj.org/toc/2045-2322Abstract 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.Joshua S. NiedzielskiJinzhong YangFrancesco StingoZhongxing LiaoDaniel GomezRadhe MohanMary MartelTina BriereLaurence CourtNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-9 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Joshua S. Niedzielski Jinzhong Yang Francesco Stingo Zhongxing Liao Daniel Gomez Radhe Mohan Mary Martel Tina Briere Laurence Court A Novel Methodology using CT Imaging Biomarkers to Quantify Radiation Sensitivity in the Esophagus with Application to Clinical Trials
description	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.
format	article
author	Joshua S. Niedzielski Jinzhong Yang Francesco Stingo Zhongxing Liao Daniel Gomez Radhe Mohan Mary Martel Tina Briere Laurence Court
author_facet	Joshua S. Niedzielski Jinzhong Yang Francesco Stingo Zhongxing Liao Daniel Gomez Radhe Mohan Mary Martel Tina Briere Laurence Court
author_sort	Joshua S. Niedzielski
title	A Novel Methodology using CT Imaging Biomarkers to Quantify Radiation Sensitivity in the Esophagus with Application to Clinical Trials
title_short	A Novel Methodology using CT Imaging Biomarkers to Quantify Radiation Sensitivity in the Esophagus with Application to Clinical Trials
title_full	A Novel Methodology using CT Imaging Biomarkers to Quantify Radiation Sensitivity in the Esophagus with Application to Clinical Trials
title_fullStr	A Novel Methodology using CT Imaging Biomarkers to Quantify Radiation Sensitivity in the Esophagus with Application to Clinical Trials
title_full_unstemmed	A Novel Methodology using CT Imaging Biomarkers to Quantify Radiation Sensitivity in the Esophagus with Application to Clinical Trials
title_sort	novel methodology using ct imaging biomarkers to quantify radiation sensitivity in the esophagus with application to clinical trials
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/966915397e484ccb974449090e63c828
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A Novel Methodology using CT Imaging Biomarkers to Quantify Radiation Sensitivity in the Esophagus with Application to Clinical Trials

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