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Articles Published Processes
3/10/2022 12:08:49 PM | Browse: 434 | Download: 1059
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Received |
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2021-05-17 15:55 |
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Peer-Review Started |
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2021-05-17 15:58 |
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To Make the First Decision |
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Return for Revision |
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2021-07-16 12:29 |
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Revised |
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2021-08-06 21:58 |
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Second Decision |
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2022-02-11 05:52 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2022-02-13 17:12 |
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Articles in Press |
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2022-02-13 17:12 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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2022-02-05 06:08 |
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Typeset the Manuscript |
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2022-03-02 23:45 |
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Publish the Manuscript Online |
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2022-03-10 12:08 |
ISSN |
1948-5204 (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) 2022. 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 |
Oncology |
Manuscript Type |
Retrospective Study |
Article Title |
Computed tomography-based radiomic to predict resectability in locally advanced pancreatic cancer treated with chemotherapy and radiotherapy
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Manuscript Source |
Invited Manuscript |
All Author List |
Gabriella Rossi, Luisa Altabella, Nicola Simoni, Giulio Benetti, Roberto Rossi, Martina Venezia, Salvatore Paiella, Giuseppe Malleo, Roberto Salvia, Stefania Guariglia, Claudio Bassi, Carlo Cavedon and Renzo Mazzarotto |
ORCID |
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Funding Agency and Grant Number |
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Corresponding Author |
Nicola Simoni, MD, Doctor, Doctor, Department of Radiation Oncology, University of Verona Hospital Trust, Piazzale Stefani 1, Verona 37126, Italy. nicolasimoni81@gmail.com |
Key Words |
Computed tomography; Radiomics; Predictive model; Resectability; Locally advanced pancreatic cancer; Radiation oncology |
Core Tip |
The present study proposes a computed tomography (CT)-based radiomics model to predict resectability in locally advanced pancreatic cancer (LAPC) treated with intensive chemotherapy followed by ablative radiation therapy. The model was built, tested, and validated in a homogeneous cohort of LAPC patients, using clinical data and radiomic features extracted from the simulation-CT, and showed a reliable performance to predict surgical resection. If further confirmed, the results of this study may allow integrating radiomic information into the pool of clinical and morphological parameters to consider when a LAPC patient is candidate for surgical exploration after neoadjuvant therapy. |
Publish Date |
2022-03-10 12:08 |
Citation |
Rossi G, Altabella L, Simoni N, Benetti G, Rossi R, Venezia M, Paiella S, Malleo G, Salvia R, Guariglia S, Bassi C, Cavedon C, Mazzarotto R. Computed tomography-based radiomic to predict resectability in locally advanced pancreatic cancer treated with chemotherapy and radiotherapy. World J Gastrointest Oncol 2022; 14(3): 703-715 |
URL |
https://www.wjgnet.com/1948-5204/full/v14/i3/703.htm |
DOI |
https://dx.doi.org/10.4251/wjgo.v14.i3.703 |
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