Automated Stanford classification of aortic dissection using a 2-step hierarchical neural network at computed tomography angiography.
Li-Ting HuangYi-Shan TsaiCheng-Fu LiouTsung-Han LeePo-Tsun Paul KuoHan-Sheng HuangChien-Kuo WangPublished in: European radiology (2021)
• The Stanford classification for aortic dissection is widely adopted and divides it into Stanford type A and type B based on the ascending thoracic aorta dissected or not. • The 2-step hierarchical neural network for Stanford classification of classic aortic dissection achieved high sensitivity (95.45%) and specificity (98.55%) of type A and high specificity in type B and no aortic dissection (94.05% and 94.12%, respectively) in 298 test cases. • The 2-step hierarchical neural network demonstrated moderate agreement (Cohen's kappa: 0.766, p < 0.001) with cardiovascular radiologists in detection and Stanford classification of classic aortic dissection in 298 test cases.