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Updated: Jul 11, 2026
Optimized Management of Endovascular Treatment for Acute Ischemic Stroke
Published on: January 18, 2018
Clot patterns determined by DSA and CTA can help predict intracranial atherosclerotic stenosis in acute ischemic
Jichuan Li1,2, Jianhong Yang1, Xiang Gao3
1Department of Neurology, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, China.
Insights
Clot patterns in large artery occlusions can predict intracranial atherosclerotic stenosis (ICAS) in acute ischemic stroke (AIS) patients. The tapered sign, visible on DSA and CTA, is a key indicator, improving diagnostic accuracy when combined with clinical factors.
Area of Science:
- Neurology
- Radiology
- Vascular Medicine
Background:
- Acute ischemic stroke (AIS) poses significant challenges, with intracranial atherosclerotic stenosis (ICAS) being a major cause.
- Accurate identification of ICAS is crucial for effective treatment strategies in AIS patients.
Purpose of the Study:
- To investigate the reliability of clot patterns observed via digital subtraction angiography (DSA) and computed tomography angiography (CTA) in predicting ICAS.
- To assess the clinical utility of clot patterns in conjunction with other patient factors for enhancing ICAS prediction.
Main Methods:
- Retrospective analysis of 131 AIS patients treated with stent retriever thrombectomy.
- Classification of clot topographies into 'cut-off' or 'tapered' signs.
- Evaluation of clot pattern, age, onset-to-door time, and TOAST classification for ICAS prediction.
Main Results:
- The 'tapered' clot sign was a significant predictor of ICAS, with good agreement between DSA and CTA (73.4%).
- A multivariate model incorporating the tapered sign, age, onset-to-door time, and TOAST classification (LAA) achieved a high predictive area under the curve (AUC) of 0.916.
- Specific subgroups, such as patients over 65 with delayed treatment and a tapered sign, showed a high AUC of 0.897.
Conclusions:
- Clot pattern, particularly the tapered sign observed on DSA and CTA, is a valuable indicator for identifying ICAS in AIS.
- Integrating clot pattern analysis with clinical data significantly improves the prediction of ICAS, aiding in patient management.
Background:
This study examines whether clot patterns at large artery occlusion sites, as observed using digital subtraction angiography (DSA) and computed tomography angiography (CTA), can reliably indicate intracranial atherosclerotic stenosis (ICAS) in acute ischemic stroke (AIS) patients.
Methods:
We conducted a retrospective analysis of patients treated with stent retriever thrombectomy for intracranial occlusions at our institute since 2017, with follow-up assessments conducted at 3 months. The patients were grouped based on the initial angiography clot topographies (i.e., cut-off or tapered signs). We assessed the potential of these topographies in predicting ICAS, including a clinical outcome analysis based on clot pattern, age, Trial of Org 10172 in Acute Stroke Treatment (TOAST) classification, and onset-to-door time.
Results:
Among 131 patients (with a mean age of 66.6 years), the clot pattern emerged as a significant predictor of ICAS. The DSA-based model had a predictive area under the curve (AUC) of 0.745, with 55.1% sensitivity and 94.0% specificity. A multivariate model including age, onset-to-door time, TOAST classification as large artery atherosclerosis (LAA), and the presence of the tapered sign in clot patterns had an AUC of 0.916. In patients over 65 years of age with an onset-to-door time of >5 h and exhibiting a tapered sign in the clot pattern, the AUC reached 0.897. The predictive ability of the tapered sign was similar in DSA and CTA, showing 73.4% agreement between modalities.
Conclusion:
The clot pattern with the tapered sign as observed using DSA is significantly associated with ICAS. Incorporating this clot pattern with age, TOAST classification as LAA, and onset-to-door time enhances the prediction of ICAS. The clot pattern identified by CTA is also a reliable predictor, highlighting the importance of assessing clot patterns in ICAS identification.
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