Computed tomography based radiomic signature as predictive of survival and local control after stereotactic body radiation therapy in pancreatic carcinoma.

<h4>Purpose</h4>To appraise the ability of a radiomics signature to predict clinical outcome after stereotactic body radiation therapy (SBRT) for pancreas carcinoma.<h4>Methods</h4>A cohort of 100 patients was included in this retrospective, single institution analysis. Radio...

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Main Authors: Luca Cozzi, Tiziana Comito, Antonella Fogliata, Ciro Franzese, Davide Franceschini, Cristiana Bonifacio, Angelo Tozzi, Lucia Di Brina, Elena Clerici, Stefano Tomatis, Giacomo Reggiori, Francesca Lobefalo, Antonella Stravato, Pietro Mancosu, Alessandro Zerbi, Martina Sollini, Margarita Kirienko, Arturo Chiti, Marta Scorsetti
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2019-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0210758
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author Luca Cozzi
Tiziana Comito
Antonella Fogliata
Ciro Franzese
Davide Franceschini
Cristiana Bonifacio
Angelo Tozzi
Lucia Di Brina
Elena Clerici
Stefano Tomatis
Giacomo Reggiori
Francesca Lobefalo
Antonella Stravato
Pietro Mancosu
Alessandro Zerbi
Martina Sollini
Margarita Kirienko
Arturo Chiti
Marta Scorsetti
author_facet Luca Cozzi
Tiziana Comito
Antonella Fogliata
Ciro Franzese
Davide Franceschini
Cristiana Bonifacio
Angelo Tozzi
Lucia Di Brina
Elena Clerici
Stefano Tomatis
Giacomo Reggiori
Francesca Lobefalo
Antonella Stravato
Pietro Mancosu
Alessandro Zerbi
Martina Sollini
Margarita Kirienko
Arturo Chiti
Marta Scorsetti
author_sort Luca Cozzi
collection DOAJ
description <h4>Purpose</h4>To appraise the ability of a radiomics signature to predict clinical outcome after stereotactic body radiation therapy (SBRT) for pancreas carcinoma.<h4>Methods</h4>A cohort of 100 patients was included in this retrospective, single institution analysis. Radiomics texture features were extracted from computed tomography (CT) images obtained for the clinical target volume. The cohort of patients was randomly divided into two separate groups for the training (60 patients) and validation (40 patients). Cox regression models were built to predict overall survival and local control. The significant predictors at univariate analysis were included in a multivariate model. The quality of the models was appraised by means of area under the curve and concordance index.<h4>Results</h4>A clinical-radiomic signature associated with Overall Survival (OS) was found significant in both training and validation sets (p = 0.01 and 0.05 and concordance index 0.73 and 0.75 respectively). Similarly, a signature was found for Local Control (LC) with p = 0.007 and 0.004 and concordance index 0.69 and 0.75. In the low risk group, the median OS and LC in the validation group were 14.4 and 28.6 months while in the high-risk group were 9.0 and 17.5 months respectively.<h4>Conclusion</h4>A CT based radiomic signature was identified which correlate with OS and LC after SBRT and allowed to identify low and high-risk groups of patients.
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spelling doaj.art-5304c80a979d463a909a308ecaa273db2022-12-21T19:13:37ZengPublic Library of Science (PLoS)PLoS ONE1932-62032019-01-01141e021075810.1371/journal.pone.0210758Computed tomography based radiomic signature as predictive of survival and local control after stereotactic body radiation therapy in pancreatic carcinoma.Luca CozziTiziana ComitoAntonella FogliataCiro FranzeseDavide FranceschiniCristiana BonifacioAngelo TozziLucia Di BrinaElena ClericiStefano TomatisGiacomo ReggioriFrancesca LobefaloAntonella StravatoPietro MancosuAlessandro ZerbiMartina SolliniMargarita KirienkoArturo ChitiMarta Scorsetti<h4>Purpose</h4>To appraise the ability of a radiomics signature to predict clinical outcome after stereotactic body radiation therapy (SBRT) for pancreas carcinoma.<h4>Methods</h4>A cohort of 100 patients was included in this retrospective, single institution analysis. Radiomics texture features were extracted from computed tomography (CT) images obtained for the clinical target volume. The cohort of patients was randomly divided into two separate groups for the training (60 patients) and validation (40 patients). Cox regression models were built to predict overall survival and local control. The significant predictors at univariate analysis were included in a multivariate model. The quality of the models was appraised by means of area under the curve and concordance index.<h4>Results</h4>A clinical-radiomic signature associated with Overall Survival (OS) was found significant in both training and validation sets (p = 0.01 and 0.05 and concordance index 0.73 and 0.75 respectively). Similarly, a signature was found for Local Control (LC) with p = 0.007 and 0.004 and concordance index 0.69 and 0.75. In the low risk group, the median OS and LC in the validation group were 14.4 and 28.6 months while in the high-risk group were 9.0 and 17.5 months respectively.<h4>Conclusion</h4>A CT based radiomic signature was identified which correlate with OS and LC after SBRT and allowed to identify low and high-risk groups of patients.https://doi.org/10.1371/journal.pone.0210758
spellingShingle Luca Cozzi
Tiziana Comito
Antonella Fogliata
Ciro Franzese
Davide Franceschini
Cristiana Bonifacio
Angelo Tozzi
Lucia Di Brina
Elena Clerici
Stefano Tomatis
Giacomo Reggiori
Francesca Lobefalo
Antonella Stravato
Pietro Mancosu
Alessandro Zerbi
Martina Sollini
Margarita Kirienko
Arturo Chiti
Marta Scorsetti
Computed tomography based radiomic signature as predictive of survival and local control after stereotactic body radiation therapy in pancreatic carcinoma.
PLoS ONE
title Computed tomography based radiomic signature as predictive of survival and local control after stereotactic body radiation therapy in pancreatic carcinoma.
title_full Computed tomography based radiomic signature as predictive of survival and local control after stereotactic body radiation therapy in pancreatic carcinoma.
title_fullStr Computed tomography based radiomic signature as predictive of survival and local control after stereotactic body radiation therapy in pancreatic carcinoma.
title_full_unstemmed Computed tomography based radiomic signature as predictive of survival and local control after stereotactic body radiation therapy in pancreatic carcinoma.
title_short Computed tomography based radiomic signature as predictive of survival and local control after stereotactic body radiation therapy in pancreatic carcinoma.
title_sort computed tomography based radiomic signature as predictive of survival and local control after stereotactic body radiation therapy in pancreatic carcinoma
url https://doi.org/10.1371/journal.pone.0210758
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