Radiomics-based diagnosis of carotid artery stenosis using non-contrast CT: model development and validation

Guoliang Wang; Yuhang Zhang; Xu Liu; Jianqi Ni; Yifeng Shen; Qin Jin

doi:10.1186/s40001-025-03592-2

Abstract

Radiomics analysis of NCCT imaging provides an effective, contrast-free means of identifying carotid artery stenosis. Our model demonstrated robust diagnostic accuracy and clinical potential, especially when contrast-enhanced imaging is contraindicated. Prospective multi-center external validation and further workflow automation are nevertheless required to support broad clinical adoption.

Keywords

Carotid artery stenosisDiagnostic modelingMachine learningNCCTRadiomics

MeSH Terms

HumansCarotid StenosisMaleFemaleRetrospective StudiesAgedMiddle AgedComputed Tomography AngiographyTomographyX-Ray ComputedMachine LearningRadiomics

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Publication Info

Year: 2025
Type: article
Citations: 0
Access: Closed

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APA Style

                            
                                    Guoliang Wang, 
                                
                                    Yuhang Zhang, 
                                
                                    Xu Liu
                                
                                et al.
                            
                            (2025). 
                            Radiomics-based diagnosis of carotid artery stenosis using non-contrast CT: model development and validation. 
                            European journal of medical research
                            
                            .
                            https://doi.org/10.1186/s40001-025-03592-2

Identifiers

DOI: 10.1186/s40001-025-03592-2
PMID: 41372786

Data Quality

Data completeness: 81%