Abstract
Abstract
Purpose
To develop and validate a combined model incorporating conventional clinical and imaging characteristics and radiomics signatures based on head and neck computed tomography angiography (CTA) to assess plaque vulnerability.
Methods
We retrospectively analyzed 167 patients with carotid atherosclerosis who underwent head and neck CTA and brain magnetic resonance imaging (MRI) within 1 month. Clinical risk factors and conventional plaque characteristics were evaluated, and radiomic features were extracted from the carotid plaques. The conventional, radiomics and combined models were developed using fivefold cross-validation. Model performance was evaluated using receiver operating characteristic (ROC), calibration, and decision curve analyses.
Results
Patients were divided into symptomatic (n = 70) and asymptomatic (n = 97) groups based on MRI results. Homocysteine (odds ratio, OR 1.057; 95% confidence interval, CI 1.001–1.116), plaque ulceration (OR 6.106; 95% CI 1.933–19.287), and carotid rim sign (OR 3.285; 95% CI 1.203–8.969) were independently associated with symptomatic status and were used to construct the conventional model and s radiomic features were retained to establish the radiomics model. Radiomics scores incorporated with conventional characteristics were used to establish the combined model. The area under the ROC curve (AUC) of the combined model was 0.832, which outperformed the conventional (AUC = 0.767) and radiomics (AUC = 0.797) models. Calibration and decision curves analysis showed that the combined model was clinically useful.
Conclusion
Radiomics signatures of carotid plaque on CTA can well predict plaque vulnerability, which may provide additional value to identify high-risk patients and improve outcomes.
Funder
Key Research and Development Project of Liaoning Province of China
Liaoning Provincial “Selecting the Best Candidates by Opening Competition Mechanism” Science and Technology Program
Publisher
Springer Science and Business Media LLC
Subject
Neurology (clinical),Radiology, Nuclear Medicine and imaging
Cited by
3 articles.
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