Identification of vulnerable intracranial atherosclerotic plaques via the 3D-HRMR-VWI radiomics model
Motivation: Intracranial artery atherosclerosis (ICAS) is a major stroke cause. Enhancing diagnostic efficiency for plaque vulnerability may aid in risk stratification and targeted treatment. Goal(s): To evaluate the capability of a 3D-HRMR VWI radiomics model in diagnosing vulnerable plaques within intracranial arteries. Approach: Using non-contrast T1WI and enhanced CE-T1WI sequences, 303 stroke patients' plaques were categorized as vulnerable or stable. Radiomic features were extracted and used to construct three diagnostic models, with their performance evaluated through AUC analysis. Results: The combined model demonstrated high diagnostic performance with AUCs of 0.878 in the training set and 0.889 in the test set. Impact: Integrating radiomics into intracranial plaque risk assessment enables quantitative scoring of plaque vulnerability, enhancing diagnostic performance and supporting clinical risk stratification of intracranial atherosclerotic plaques.
Authors
- Jing Zhang (ORCID: https://orcid.org/0000-0001-7530-1121)
- Tianle Wang
- Li Zhu (ORCID: https://orcid.org/0000-0003-2136-3196)
- Tingting Cao (ORCID: https://orcid.org/0000-0002-3688-4691)
Publication Details
- Journal
- Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
- Published
- 2025-09-16
- DOI
- https://doi.org/10.58530/2025/5119
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00