BPG is committed to discovery and dissemination of knowledge
Articles Published Processes
8/24/2021 2:07:00 AM | Browse: 743 | Download: 1980
 |
Received |
|
2021-03-13 13:33 |
|
Peer-Review Started |
|
2021-03-13 13:36 |
|
First Decision by Editorial Office Director |
|
2021-06-03 22:54 |
|
Return for Revision |
|
2021-06-04 10:14 |
|
Revised |
|
2021-06-12 14:14 |
 |
Publication Fee Transferred |
|
|
|
Second Decision by Editor |
|
2021-07-05 12:47 |
|
Second Decision by Editor-in-Chief |
|
|
|
Final Decision by Editorial Office Director |
|
2021-07-05 13:11 |
|
Articles in Press |
|
2021-07-05 13:11 |
|
Edit the Manuscript by Language Editor |
|
2021-07-12 14:44 |
|
Typeset the Manuscript |
|
2021-08-17 02:22 |
|
Publish the Manuscript Online |
|
2021-08-24 02:07 |
| 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) 2021. Published by Baishideng Publishing Group Inc. All rights reserved. |
| Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
|
| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
|
| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
| Category |
Gastroenterology & Hepatology |
| Manuscript Type |
Retrospective Study |
| Article Title |
Novel model combined contrast-enhanced ultrasound with serology predicts hepatocellular carcinoma recurrence after hepatectomy
|
| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Hai-Bin Tu, Li-Hong Chen, Yu-Jie Huang, Si-Yi Feng, Jian-Ling Lin and Yong-Yi Zeng |
| ORCID |
|
| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| Startup Fund for scientific research, Fujian Medical University |
2019QH1302 |
|
| Corresponding Author |
Yong-Yi Zeng, MD, PhD, Professor, Department of Hepatobiliary Surgery, Mengchao Hepatobiliary Hospital of Fujian Medical University, No. 312 Xihong Road, Fuzhou 350025, Fujian Province, China. lamp197311@126.com |
| Key Words |
Hepatocellular carcinoma; Recurrence; Prediction; Contrast-enhanced ultrasound; Liver imaging reporting and data system; Alpha-fetoprotein |
| Core Tip |
This study aimed to construct and verify a non-invasive prediction model combining contrast-enhanced ultrasound with serology biomarkers to predict the early recurrence of hepatocellular carcinoma.Records of 292 Local patients of hepatocellular carcinoma (HCC) were selected for analysis. A nomogram predicting early recurrence (ER) named contrasted-enhanced ultrasound (CEUS) model, incorporating tumor diameter, preoperative alpha-fetoprotein level, and LIRADS, was developed. The model showed satisfactory results, the C-index was 0.762 (95%CI: 0.706–0.819). The calibration at 6 mo was desirable.The CEUS model enables the well-calibrated individualized prediction of ER before surgery and may represent a novel tool for biomarker research and individual counseling. |
| Publish Date |
2021-08-24 02:07 |
| Citation |
Tu HB, Chen LH, Huang YJ, Feng SY, Lin JL, Zeng YY. Novel model combined contrast-enhanced ultrasound with serology predicts hepatocellular carcinoma recurrence after hepatectomy . World J Clin Cases 2021; 9(24): 7009-7021 |
| URL |
https://www.wjgnet.com/2307-8960/full/v9/i24/7009.htm |
| DOI |
https://dx.doi.org/10.12998/wjcc.v9.i24.7009 |
All content on this site: Copyright © 1993-2026 Baishideng Publishing Group Inc, its licensors, and contributors. All rights are reserved, including those for text and data mining, AI training, and similar technologies. For all open access content, the relevant licensing terms apply.
