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Articles Published Processes
11/24/2023 6:27:01 AM | Browse: 193 | Download: 526
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Received |
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2023-08-28 03:50 |
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Peer-Review Started |
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2023-08-28 03:52 |
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To Make the First Decision |
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Return for Revision |
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2023-09-19 06:58 |
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Revised |
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2023-09-20 17:23 |
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Second Decision |
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2023-10-11 23:52 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2023-10-23 08:16 |
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Articles in Press |
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2023-10-23 08:16 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2023-10-26 06:10 |
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Publish the Manuscript Online |
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2023-11-24 06:27 |
ISSN |
1949-8470 (online) |
Open Access |
This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/ |
Copyright |
© The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved. |
Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
Website |
http://www.wjgnet.com |
Category |
Medicine, Research & Experimental |
Manuscript Type |
Retrospective Study |
Article Title |
Radiomics analysis with three-dimensional and two-dimensional segmentation to predict survival outcomes in pancreatic cancer
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Manuscript Source |
Invited Manuscript |
All Author List |
Mohammed Saleh, Mayur Virarkar, Hagar S Mahmoud, Vincenzo K Wong, Carlos Ignacio Gonzalez Baerga, Miti Parikh, Sherif B Elsherif and Priya R Bhosale |
ORCID |
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Funding Agency and Grant Number |
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Corresponding Author |
Carlos Ignacio Gonzalez Baerga, MD, Research Assistant, Department of Diagnostic Radiology, The University of Florida College of Medicine, 655 8th Street West, Jacksonville, FL 32209, United States. carlos.gonzalezbaerga@jax.ufl.edu |
Key Words |
Radiomics; Pancreas; Cancer; Segmentation |
Core Tip |
The use of radiomics to assess pancreatic cancer has been limited. This retrospective study evaluated the performance of 2-dimensional (2D) and 3D radiomic software in determining survival outcomes of pancreatic cancer patients. The mean tumor density was the only variable to reliably predict overall survival (OS) irrespective of the type of analysis. Mean tumor density may be able to differentiate survival and potentially may be help in treatment planning irrespective of the texture analysis software used. Higher skewness [hazard ratio (HR) = 3.067, P = 0.008] and higher kurtosis (HR = 1.176, P = 0.029) correlated with worse OS based on 2D analysis. |
Publish Date |
2023-11-24 06:27 |
Citation |
Saleh M, Virarkar M, Mahmoud HS, Wong VK, Gonzalez Baerga CI, Parikh M, Elsherif SB, Bhosale PR. Radiomics analysis with three-dimensional and two-dimensional segmentation to predict survival outcomes in pancreatic cancer. World J Radiol 2023; 15(11): 304-314 |
URL |
https://www.wjgnet.com/1949-8470/full/v15/i11/304.htm |
DOI |
https://dx.doi.org/10.4329/wjr.v15.i11.304 |
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