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Updated: May 10, 2026
Embolic Middle Cerebral Artery Occlusion MCAO for Ischemic Stroke with Homologous Blood Clots in Rats
Published on: September 17, 2014
Analysis of a clot-based combined radiomics model for predicting embolic etiology in acute ischemic stroke patients
1Department of Radiology, The Affiliated Huaian No.1 People's Hospital of Nanjing Medical University, Huaian 223300, China.
Insights
A new radiomics model accurately predicts acute ischemic stroke subtypes using clot imaging. This aids in selecting the best treatment strategies for better patient outcomes.
Area of Science:
- Neurology
- Radiology
- Medical Imaging
Background:
- Acute ischemic stroke (AIS) is a leading cause of death and disability in China.
- Accurate etiological classification of AIS is critical for effective treatment planning.
- Different causes of AIS significantly impact neurological function recovery.
Purpose of the Study:
- To evaluate the predictive performance of a combined radiomics model for identifying AIS etiological subtypes.
- To compare the efficacy of the radiomics model against clinical and individual imaging-based models.
- To explore the clinical utility of radiomics in guiding AIS treatment selection.
Main Methods:
- Retrospective enrollment of 263 AIS patients with anterior circulation large artery occlusion.
- Segmentation of clot regions of interest (ROIs) from non-contrast computed tomography (NCCT) and computed tomography angiography (CTA) scans.
- Development and comparison of clinical, individual radiomics (NCCT, CTA), and combined radiomics models.
Main Results:
- The combined radiomics model demonstrated superior predictive performance with an AUC of 0.9077 in the testing cohort.
- Radiomics models, particularly the combined NCCT&CTA model, showed significant net benefits in clinical decision curve analysis.
- The combined model outperformed clinical and individual radiomics models in distinguishing AIS etiological subtypes.
Conclusions:
- The developed combined radiomics model shows high predictive accuracy for AIS etiological subtypes.
- This model offers valuable insights for precise recanalization strategy selection in clinical practice.
- Radiomics analysis of clots can enhance personalized treatment approaches for acute ischemic stroke.
Background And Objectives:
Acute ischemic stroke (AIS) remains the primary cause of mortality and disability among adults in China. Different etiologies of acute ischemic stroke (AIS) are considered important factors affecting neurological function. The accurate etiological classification of AIS prior to surgery is crucial. To investigate and explore the predictive value of a clot-based combined radiomics model for identifying the etiological subtypes of acute ischemic stroke.
Materials And Methods:
A total of 263 patients with acute ischemic stroke caused by anterior circulation large artery occlusion were retrospectively enrolled. These were grouped into training (180), testing (45), and external validation cohorts (38). NCCT and CTA scans were adopted to segment region of interest (ROI) of clots. Feature selection was conducted to establish Clinical model, radiomics models (NCCT, CTA, and NCCT&CTA), and combined model.
Results:
The AUCs of the clinical model and radiomics models (NCCT, CTA and NCCT&CTA) in the testing cohort were 0.8288(95 % CI: 0.7174-0.9403), 0.8133(95 % CI:0.6853-0.9414), 0.8075(95 % CI:0.6844-0.9307) and 0.8535(95 % CI:0.6774-1), respectively. The combined model achieved a greater AUC than the other four models in the testing cohort (0.9077 [95 % CI: 0.821-0.9944]). Clinical decision curve analysis (DCA) demonstrated that the radiomics (NCCT&CTA) model and combined model show better net benefits within a relatively wide range of threshold probabilities.
Conclusion:
The combined radiomics model achieved good predictive efficacy for distinguishing the etiological subtypes of acute ischemic stroke and can provide valuable information for the precise selection of recanalization strategies in clinical practice.
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