Clot-based radiomics model for cardioembolic stroke prediction with CT imaging before recanalization: a multicenter study
- PMID: 36066731
- DOI: 10.1007/s00330-022-09116-4
Clot-based radiomics model for cardioembolic stroke prediction with CT imaging before recanalization: a multicenter study
Abstract
Objectives: To develop a clot-based radiomics model using CT imaging radiomic features and machine learning to identify cardioembolic (CE) stroke before mechanical thrombectomy (MTB) in patients with acute ischemic stroke (AIS).
Materials and methods: This retrospective four-center study consecutively included 403 patients with AIS who sequentially underwent CT and MTB between April 2016 and July 2021. These were grouped into training, testing, and external validation cohorts. Thrombus-extracted radiomic features and basic information were gathered to construct a machine learning model to predict CE stroke. The radiological characteristics and basic information were used to build a routine radiological model. A combined radiomics and radiological features model was also developed. The performances of all models were evaluated and compared in the validation cohort. A histological analysis helped further assess the proposed model in all patients.
Results: The radiomics model yielded an area under the curve (AUC) of 0.838 (95% confidence interval [CI], 0.771-0.891) for predicting CE stroke in the validation cohort, significantly higher than the radiological model (AUC, 0.713; 95% CI, 0.636-0.781; p = 0.007) but similar to the combined model (AUC, 0.855; 95% CI, 0.791-0.906; p = 0.14). The thrombus radiomic features achieved stronger correlations with red blood cells (|rmax|, 0.74 vs. 0.32) and fibrin and platelet (|rmax|, 0.68 vs. 0.18) than radiological characteristics.
Conclusion: The proposed CT-based radiomics model could reliably predict CE stroke in AIS, performing better than the routine radiological method.
Key points: • Admission CT imaging could offer valuable information to identify the acute ischemic stroke source by radiomics analysis. • The proposed CT imaging-based radiomics model yielded a higher area under the curve (0.838) than the routine radiological method (0.713; p = 0.007). • Several radiomic features showed significantly stronger correlations with two main thrombus constituents (red blood cells, |rmax|, 0.74; fibrin and platelet, |rmax|, 0.68) than routine radiological characteristics.
Keywords: Acute ischemic stroke; Cardioembolic stroke; Computed tomography; Radiomics; Thrombosis.
© 2022. The Author(s), under exclusive licence to European Society of Radiology.
References
-
- Campbell B, Khatri P (2020) Stroke. Lancet 396:129–142. https://doi.org/10.1016/S0140-6736(20)31179-X - DOI
-
- Peultier AC, Pandya A, Sharma R, Severens JL, Redekop WK (2020) Cost-effectiveness of mechanical thrombectomy more than 6 hours after symptom onset among patients with acute ischemic stroke. JAMA Netw Open 3:e2012476. https://doi.org/10.1001/jamanetworkopen.2020.12476 - DOI
-
- Jovin TG, Chamorro A, Cobo E et al (2015) Thrombectomy within 8 hours after symptom onset in ischemic stroke. N Engl J Med 372:2296–2306. https://doi.org/10.1056/NEJMoa1503780 - DOI
-
- Saver JL, Goyal M, Bonafe A et al (2015) Stent-retriever thrombectomy after intravenous t-PA vs. t-PA alone in stroke. N Engl J Med 372:2285–2295. https://doi.org/10.1056/NEJMoa1415061 - DOI
-
- Campbell B, Mitchell PJ, Churilov L et al (2020) Effect of intravenous tenecteplase dose on cerebral reperfusion before thrombectomy in patients with large vessel occlusion ischemic stroke: the EXTEND-IA TNK part 2 randomized clinical trial. JAMA 323:1257–1265. https://doi.org/10.1001/jama.2020.1511 - DOI
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- No. 81871329/National Natural Science Foundation of China
- No. SHDC12018117/New Developing and Frontier Technologies of Shanghai Shen Kang Hospital Development Center
- No. 2016427/Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant Support
- No. 21PJ1411700/Shanghai Pujiang Program
- No. x-2362/Fundamental Research Funds for the Shanghai Sixth People's Hospital
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