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Publication Name World Journal of Clinical Cases
Manuscript ID 57545
Country/Territory China
Category Engineering, Biomedical
Manuscript Type Retrospective Study
Article Title Radiomics model for distinguishing tuberculosis and lung cancer on computed tomography scans
Manuscript Source Unsolicited Manuscript
All Author List E-Nuo Cui, Tao Yu, Sheng-Jie Shang, Xiao-Yu Wang, Yi-Lin Jin, Yue Dong, Hai Zhao, Ya-Hong Luo and Xi-Ran Jiang
Funding Agency and Grant Number
Funding Agency Grant Number
National Natural Science Foundation of China 81872363
Youth Science and Technology Innovation Leader Support Project RC170497
Shenyang Municipal Science and Technology Project F16-206-9-23
Natural Science Foundation of Liaoning Province of China 201602450
National Key R&D Program of Ministry of Science and Technology of China 2016YFC1303002
Major Technology Plan Project of Shenyang 17-230-9-07
Supporting Fund for Big data in Health Care HMB201903101
2018 Key Research and Guidance Project of Liaoning Province 2018225038
Corresponding author Xi-Ran Jiang, PhD, Associate Professor, Department of Biomedical Engineering, China Medical University, No. 77 Puhe Road, Shenyang 110122, Liaoning Province, China. xrjiang@cmu.edu.cn
Key Words Pulmonary tuberculosis; Lung cancer; Radiomics; Computed tomography; Computer–aided diagnosis; Nomogram
Core Tip Pulmonary tuberculosis (TB) often exhibits great similarities with lung cancer (LC) on computed tomography (CT) images, which may lead to clinical misdiagnosis. Our study evaluated the discriminative performance of peritumoral regions on differentiating between TB and LC. Radiomics features were extracted and selected from preoperative lung CT images. An eight-feature-combined radiomics signature was constructed as an identifier of TB and LC. A radiomics nomogram model was also plotted and validated with calibration curve and decision curve analyses. The good performance of our model could improve current applications of computer-aided diagnosis for pulmonary tuberculosis and lung cancer.
Citation Cui EN, Yu T, Shang SJ, Wang XY, Jin YL, Dong Y, Zhao H, Luo YH, Jiang XR. Radiomics model for distinguishing tuberculosis and lung cancer on computed tomography scans. World J Clin Cases 2020; In press
Received
2020-07-21 11:03
Peer-Review Started
2020-07-21 11:03
To Make the First Decision
Return for Revision
2020-08-08 00:06
Revised
2020-08-12 01:40
Second Decision
2020-09-15 12:14
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief
2020-09-15 23:52
Articles in Press
2020-09-15 23:52
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript
ISSN 2307-8960 (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) 2020. Published by Baishideng Publishing Group Inc. All rights reserved.
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Publisher Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
Website http://www.wjgnet.com
Assistant Editor Assistant Editor
Science Editor Jin-Lei Wang
Reviewer Code 03015897, 02992676, and 03024280
Editorial Director
Journal Chief Editor
Company Chief Editor Lian-Sheng Ma
Language Editor
Production Editor
Responsible Production Editor
Responsible Science Editor
Proofing Editorial Director Jin-Lei Wang
Proofing Editor-in-Chief Lian-Sheng Ma
Manuscript File 57545-Review.docx
Answering Reviewers 57545-Answering reviewers.pdf
Audio Core Tip 57545-Audio core tip.mp3
Biostatistics Review Certificate 57545-Biostatistics statement.pdf
Conflict-of-Interest Disclosure Form 57545-Conflict-of-interest statement.pdf
Copyright License Agreement 57545-Copyright license agreement.pdf
Approved Grant Application Form(s) or Funding Agency Copy of any Approval Document(s) 57545-Grant application form(s).PDF
Signed Informed Consent Form(s) or Document(s) 57545-Informed consent statement.pdf
Institutional Review Board Approval Form or Document 57545-Institutional review board statement.pdf
Non-Native Speakers of English Editing Certificate 57545-Language certificate.pdf
Peer-review Report 57545-Peer-review(s).pdf
Scientific Misconduct Check 57545-Scientific misconduct check.pdf
Scientific Editor Work List 57545-Scientific editor work list.pdf