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Published in: BMC Medical Imaging 1/2017

Open Access 01-12-2017 | Research article

CT texture features are associated with overall survival in pancreatic ductal adenocarcinoma a quantitative analysis

Authors: Armin Eilaghi, Sameer Baig, Yucheng Zhang, Junjie Zhang, Paul Karanicolas, Steven Gallinger, Farzad Khalvati, Masoom A. Haider

Published in: BMC Medical Imaging | Issue 1/2017

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Abstract

Background

To assess whether CT-derived texture features predict survival in patients undergoing resection for pancreatic ductal adenocarcinoma (PDAC).

Methods

Thirty patients with pre-operative CT from 2007 to 2012 for PDAC were included. Tumor size and five texture features namely uniformity, entropy, dissimilarity, correlation, and inverse difference normalized were calculated. Mann–Whitney rank sum test was used to compare tumor with normal pancreas. Receiver operating characteristics (ROC) analysis, Cox regression and Kaplan-Meier tests were used to assess association of texture features with overall survival (OS).

Results

Uniformity (p < 0.001), entropy (p = 0.009), correlation (p < 0.001), and mean intensity (p < 0.001) were significantly different in tumor regions compared to normal pancreas. Tumor dissimilarity (p = 0.045) and inverse difference normalized (p = 0.046) were associated with OS whereas tumor intensity (p = 0.366), tumor size (p = 0.611) and other textural features including uniformity (p = 0.334), entropy (p = 0.330) and correlation (p = 0.068) were not associated with OS.

Conclusion

CT-derived PDAC texture features of dissimilarity and inverse difference normalized are promising prognostic imaging biomarkers of OS for patients undergoing curative intent surgical resection.
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Metadata
Title
CT texture features are associated with overall survival in pancreatic ductal adenocarcinoma – a quantitative analysis
Authors
Armin Eilaghi
Sameer Baig
Yucheng Zhang
Junjie Zhang
Paul Karanicolas
Steven Gallinger
Farzad Khalvati
Masoom A. Haider
Publication date
01-12-2017
Publisher
BioMed Central
Published in
BMC Medical Imaging / Issue 1/2017
Electronic ISSN: 1471-2342
DOI
https://doi.org/10.1186/s12880-017-0209-5

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