Evaluation of acute pulmonary embolism and clot burden on CTPA with deep learning

ConclusionsDL-CNN achieved a high AUC for the detection of pulmonary emboli and can be applied to quantitatively calculate the clot burden of APE patients, which may contribute to reducing the workloads of clinicians.Key Points• Deep learning can detect APE with a good performance and efficiently calculate the clot burden to reduce the physicians’ workload.• Clot burden measured with deep learning highly correlates with Qanadli and Mastora scores of CTPA.• Clot burden measured with deep learning correlates with parameters of right ventricular function on CTPA.
Source: European Radiology - Category: Radiology Source Type: research