Observational Study
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Mar 14, 2024; 30(10): 1377-1392
Published online Mar 14, 2024. doi: 10.3748/wjg.v30.i10.1377
Differential diagnosis of Crohn’s disease and intestinal tuberculosis based on ATR-FTIR spectroscopy combined with machine learning
Yuan-Peng Li, Tian-Yu Lu, Fu-Rong Huang, Wei-Min Zhang, Zhen-Qiang Chen, Pei-Wen Guang, Liang-Yu Deng, Xin-Hao Yang
Yuan-Peng Li, College of Physical Science and Technology, Guangxi Normal University, Guilin, Guangxi 541004, China
Tian-Yu Lu, Department of Gastroenterology, The Affiliated Hospital of South University of Science and Technology, Shenzhen 518000, Guangdong Province, China
Fu-Rong Huang, Zhen-Qiang Chen, Pei-Wen Guang, Liang-Yu Deng, Xin-Hao Yang, Department of Optoelectronic Engineering, Jinan University, Guangzhou 510632, Guangdong Province, China
Wei-Min Zhang, Department of Gastroenterology, Integrated Hospital of Traditional Chinese Medicine, Southern Medical University, Guangzhou 510632, Guangdong Province, China
Co-first authors: Yuan-Peng Li and Tian-Yu Lu.
Co-corresponding authors: Fu-Rong Huang and Wei-Min Zhang.
Author contributions: Huang FR and Zhang WM conceived, designed, and refined the study protocol; Chen ZQ, Guang PW, Deng LY, and Yang XH were involved in the data collection; Li YP, Lu TY, and Chen ZQ analyzed the data; Li YP and Lu TY drafted the manuscript; all authors were involved in the critical review of the results and have contributed to, read, and approved the final manuscript. Li YP and Lu TY contributed equally to this work as co-first authors; Huang ER and Zhang WM contributed equally to this work as co-corresponding authors. The reasons for designating Huang ER and Zhang WM as co-corresponding authors are threefold. First, the research was performed as a collaborative effort, and the designation of co-corresponding authorship accurately reflects the distribution of responsibilities and burdens associated with the time and effort required to complete the study and the resultant paper. This also ensures effective communication and management of post-submission matters, ultimately enhancing the paper’s quality and reliability. Second, the overall research team encompassed authors with a variety of expertise and skills from different fields, and the designation of co-corresponding authors best reflects this diversity. This also promotes the most comprehensive and in-depth examination of the research topic, ultimately enriching readers’ understanding by offering various expert perspectives. Third, Huang FR and Zhang WM contributed efforts of equal substance throughout the research process. The choice of these researchers as co-corresponding authors acknowledges and respects this equal contribution, while recognizing the spirit of teamwork and collaboration of this study. In summary, we believe that designating Huang FR and Zhang WM as co-corresponding authors of is fitting for our manuscript as it accurately reflects our team’s collaborative spirit, equal contributions, and diversity.
Supported by the National Natural Science Foundation of China, No. 61975069 and No. 62005056; Natural Science Foundation of Guangxi Province, No. 2021JJB110003; Natural Science Foundation of Guangdong Province, No. 2018A0303131000; Academician Workstation of Guangdong Province, No. 2014B090905001; and Key Project of Scientific and Technological Projects of Guangzhou, No. 201604040007 and No. 201604020168.
Institutional review board statement: The Institutional review board statement has been exempted since we used wax-embedded tissue sections collected over many years from two hospitals.
Informed consent statement: Patients were not required to give informed consent to the study because the patients to whom these wax-embedded tissue sections belonged have been discharged for a long time, or have moved away from the area, and we are unable to contact them.
Conflict-of-interest statement: There are no conflicts of interest to declare.
Data sharing statement: Technical appendix, statistical code, and dataset available from the co-first author at lutianyu1978@163.com.
STROBE statement: The authors have read the STROBE Statement—checklist of items, and the manuscript was prepared and revised according to the STROBE Statement—checklist of items.
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: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Wei-Min Zhang, PhD, Chief Physician, Director, Department of Gastroenterology, Integrated Hospital of Traditional Chinese Medicine, Southern Medical University, No. 13 Shiliugang Road, Haizhu District, Guangzhou 510632, Guangdong Province, China. weigert@163.com
Received: October 31, 2023
Peer-review started: October 31, 2023
First decision: December 5, 2023
Revised: January 2, 2024
Accepted: February 6, 2024
Article in press: February 6, 2024
Published online: March 14, 2024
Core Tip

Core Tip: Crohn’s disease (CD) is often misdiagnosed as intestinal tuberculosis (ITB). However, the treatment and prognosis of these two diseases are dramatically different. Therefore, it is important to develop a method to identify CD and ITB with high accuracy, specificity, and speed. For the first time the paraffin wax-embedded tissue sections were attached to a metal coating and measured using attenuated total reflectance fourier transform infrared spectroscopy at mid-infrared wavelengths combined with XGBoost for differential diagnosis of CD and ITB. Information on the mid-infrared region can reveal the different histological components of CD and ITB at the molecular level, and spectral analysis combined with machine learning to establish a diagnostic model is expected to become a new method for the differential diagnosis of CD and ITB.