Prognostic Value of CT Radiomic Features in Resectable Pancreatic Ductal Adenocarcinoma

Abstract In this work, we assess the reproducibility and prognostic value of CT-derived radiomic features for resectable pancreatic ductal adenocarcinoma (PDAC). Two radiologists contoured tumour regions on pre-operative CT of two cohorts from two institutions undergoing curative-intent surgical res...

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Autores principales:	Farzad Khalvati, Yucheng Zhang, Sameer Baig, Edrise M. Lobo-Mueller, Paul Karanicolas, Steven Gallinger, Masoom A. Haider
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2019
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/03bd79d212814901adf8f2deb76f18c1
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spelling	oai:doaj.org-article:03bd79d212814901adf8f2deb76f18c12021-12-02T15:09:38ZPrognostic Value of CT Radiomic Features in Resectable Pancreatic Ductal Adenocarcinoma10.1038/s41598-019-41728-72045-2322https://doaj.org/article/03bd79d212814901adf8f2deb76f18c12019-04-01T00:00:00Zhttps://doi.org/10.1038/s41598-019-41728-7https://doaj.org/toc/2045-2322Abstract In this work, we assess the reproducibility and prognostic value of CT-derived radiomic features for resectable pancreatic ductal adenocarcinoma (PDAC). Two radiologists contoured tumour regions on pre-operative CT of two cohorts from two institutions undergoing curative-intent surgical resection for PDAC. The first (n = 30) and second cohorts (n = 68) were used for training and validation of proposed prognostic model for overall survival (OS), respectively. Radiomic features were extracted using PyRadiomics library and those with weak inter-reader reproducibility were excluded. Through Cox regression models, significant features were identified in the training cohort and retested in the validation cohort. Significant features were then fused via Cox regression to build a single radiomic signature in the training cohort, which was validated across readers in the validation cohort. Two radiomic features derived from Sum Entropy and Cluster Tendency features were both robust to inter-reader reproducibility and prognostic of OS across cohorts and readers. The radiomic signature showed prognostic value for OS in the validation cohort with hazard ratios of 1.56 (P = 0.005) and 1.35 (P = 0.022), for the first and second reader, respectively. CT-based radiomic features were shown to be prognostic in patients with resectable PDAC. These features may help stratify patients for neoadjuvant or alternative therapies.Farzad KhalvatiYucheng ZhangSameer BaigEdrise M. Lobo-MuellerPaul KaranicolasSteven GallingerMasoom A. HaiderNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 9, Iss 1, Pp 1-9 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Farzad Khalvati Yucheng Zhang Sameer Baig Edrise M. Lobo-Mueller Paul Karanicolas Steven Gallinger Masoom A. Haider Prognostic Value of CT Radiomic Features in Resectable Pancreatic Ductal Adenocarcinoma
description	Abstract In this work, we assess the reproducibility and prognostic value of CT-derived radiomic features for resectable pancreatic ductal adenocarcinoma (PDAC). Two radiologists contoured tumour regions on pre-operative CT of two cohorts from two institutions undergoing curative-intent surgical resection for PDAC. The first (n = 30) and second cohorts (n = 68) were used for training and validation of proposed prognostic model for overall survival (OS), respectively. Radiomic features were extracted using PyRadiomics library and those with weak inter-reader reproducibility were excluded. Through Cox regression models, significant features were identified in the training cohort and retested in the validation cohort. Significant features were then fused via Cox regression to build a single radiomic signature in the training cohort, which was validated across readers in the validation cohort. Two radiomic features derived from Sum Entropy and Cluster Tendency features were both robust to inter-reader reproducibility and prognostic of OS across cohorts and readers. The radiomic signature showed prognostic value for OS in the validation cohort with hazard ratios of 1.56 (P = 0.005) and 1.35 (P = 0.022), for the first and second reader, respectively. CT-based radiomic features were shown to be prognostic in patients with resectable PDAC. These features may help stratify patients for neoadjuvant or alternative therapies.
format	article
author	Farzad Khalvati Yucheng Zhang Sameer Baig Edrise M. Lobo-Mueller Paul Karanicolas Steven Gallinger Masoom A. Haider
author_facet	Farzad Khalvati Yucheng Zhang Sameer Baig Edrise M. Lobo-Mueller Paul Karanicolas Steven Gallinger Masoom A. Haider
author_sort	Farzad Khalvati
title	Prognostic Value of CT Radiomic Features in Resectable Pancreatic Ductal Adenocarcinoma
title_short	Prognostic Value of CT Radiomic Features in Resectable Pancreatic Ductal Adenocarcinoma
title_full	Prognostic Value of CT Radiomic Features in Resectable Pancreatic Ductal Adenocarcinoma
title_fullStr	Prognostic Value of CT Radiomic Features in Resectable Pancreatic Ductal Adenocarcinoma
title_full_unstemmed	Prognostic Value of CT Radiomic Features in Resectable Pancreatic Ductal Adenocarcinoma
title_sort	prognostic value of ct radiomic features in resectable pancreatic ductal adenocarcinoma
publisher	Nature Portfolio
publishDate	2019
url	https://doaj.org/article/03bd79d212814901adf8f2deb76f18c1
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Prognostic Value of CT Radiomic Features in Resectable Pancreatic Ductal Adenocarcinoma

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