Non-contrast CT-based radiomic signature for screening thoracic aortic dissections: a multicenter study
| Autor: | Litian Chen, Jiner Shu, Jianmin Cheng, Zhichao Sun, Xiaojun Chen, Maosheng Xu, Xianda Lin, Peipei Pang, Yifan Guo |
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| Rok vydání: | 2021 |
| Předmět: |
medicine.medical_specialty
Non contrast ct 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine Humans Medicine Radiology Nuclear Medicine and imaging Retrospective Studies Neuroradiology Aortic dissection Receiver operating characteristic medicine.diagnostic_test business.industry General Medicine medicine.disease Predictive value Confidence interval Aortic Dissection ROC Curve Multicenter study Area Under Curve 030220 oncology & carcinogenesis Angiography Radiology Tomography X-Ray Computed business |
| Zdroj: | European Radiology. 31:7067-7076 |
| ISSN: | 1432-1084 0938-7994 |
| DOI: | 10.1007/s00330-021-07768-2 |
| Popis: | To develop a non-contrast CT-based radiomic signature to effectively screen for thoracic aortic dissections (ADs). We retrospectively enrolled 378 patients who underwent non-contrast chest CT scans along with CT angiography or MRI from 4 medical centers. The training and validation sets were from 3 centers, while the external test set was from a 4th center. Radiomic features were extracted from non-contrast CT images. The radiomic signature was created on the basis of selected features by a logistic regression algorithm. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve, accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were conducted to assess the predictive ability of radiomic signature. The radiomic signature demonstrated AUCs of 0.91 (95% confidence interval [CI], 0.86–0.95) in the training set, 0.92 (95% CI, 0.86–0.98) in the validation set, and 0.90 (95% CI, 0.82–0.98) in the external test set. The predicted diagnosis was in good agreement with the probability of thoracic AD. In the external test group, the diagnostic accuracy, sensitivity, specificity, PPV, and NPV were 90.5%, 85.7%, 91.7%, 70.6%, and 96.5%, respectively. A radiomic signature based on non-contrast CT images can effectively predict thoracic ADs. This method may serve as a potential screening tool for thoracic ADs. • The non-contrast CT-based radiomic signature can effectively predict the thoracic aortic dissections. • This radiomic signature shows better predictive performance compared to the current clinical model. • This prediction method may be a potential tool for screening thoracic aortic dissections. |
| Databáze: | OpenAIRE |
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