Classification of Irritable Bowel Syndrome Using Brain Functional Connectivity Strength and Machine Learning
Qi Zhang
Department of Anorectal Surgery, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China
School of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
Search for more papers by this authorYue Xu
Department of Anorectal Surgery, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China
Search for more papers by this authorDingbo Guo
Department of Radiology, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China
Search for more papers by this authorHua He
Department of Anorectal Surgery, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China
Search for more papers by this authorZhen Zhang
Department of Anorectal Surgery, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China
Search for more papers by this authorCorresponding Author
Xiaowan Wang
Department of Anorectal Surgery, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China
Correspondence:
Xiaowan Wang ([email protected])
Siyi Yu ([email protected])
Search for more papers by this authorCorresponding Author
Siyi Yu
School of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
Correspondence:
Xiaowan Wang ([email protected])
Siyi Yu ([email protected])
Search for more papers by this authorQi Zhang
Department of Anorectal Surgery, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China
School of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
Search for more papers by this authorYue Xu
Department of Anorectal Surgery, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China
Search for more papers by this authorDingbo Guo
Department of Radiology, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China
Search for more papers by this authorHua He
Department of Anorectal Surgery, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China
Search for more papers by this authorZhen Zhang
Department of Anorectal Surgery, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China
Search for more papers by this authorCorresponding Author
Xiaowan Wang
Department of Anorectal Surgery, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China
Correspondence:
Xiaowan Wang ([email protected])
Siyi Yu ([email protected])
Search for more papers by this authorCorresponding Author
Siyi Yu
School of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
Correspondence:
Xiaowan Wang ([email protected])
Siyi Yu ([email protected])
Search for more papers by this authorFunding: This work was supported by programs of the National Natural Science Foundation of China (No. 82105032), Chongqing medical scientific research project (Joint project of Chongqing Health Commission and Science and Technology Bureau) (No.2022QNXM075).
Qi Zhang and Yue Xu contributed equally to this article.
ABSTRACT
Background
Irritable Bowel Syndrome (IBS) is a prevalent condition characterized by dysregulated brain–gut interactions. Despite its widespread impact, the brain mechanism of IBS remains incompletely understood, and there is a lack of objective diagnostic criteria and biomarkers. This study aims to investigate brain network alterations in IBS patients using the functional connectivity strength (FCS) method and to develop a support vector machine (SVM) classifier for distinguishing IBS patients from healthy controls (HCs).
Methods
Thirty-one patients with IBS and thirty age and sex-matched HCs were enrolled in this study and underwent resting-state functional magnetic resonance imaging (fMRI) scans. We applied FCS to assess global brain functional connectivity changes in IBS patients. An SVM-based machine - learning approach was then used to evaluate whether the altered FCS regions could serve as fMRI-based markers for classifying IBS patients and HCs.
Results
Compared to the HCs, patients with IBS showed significantly increased FCS in the left medial orbitofrontal cortex (mOFC) and decreased FCS in the bilateral cingulate cortex/precuneus (PCC/Pcu) and middle cingulate cortex (MCC). The machine-learning model achieved a classification accuracy of 91.9% in differentiating IBS patients from HCs.
Conclusion
These findings reveal a unique pattern of FCS alterations in brain areas governing pain regulation and emotional processing in IBS patients. The identified abnormal FCS features have the potential to serve as effective biomarkers for IBS classification. This study may contribute to a deeper understanding of the neural mechanisms of IBS and aid in its diagnosis in clinical practice.
Conflicts of Interest
The authors declare no conflicts of interest.
Open Research
Data Availability Statement
Data are available from the corresponding author upon reasonable request.
Supporting Information
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Appendix S1. |
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