Deep Learning for Automated Classification of Inferior Vena Cava Filter Types on Radiographs.

Purpose: To demonstrate the feasibility and evaluate the performance of a deep-learning convolutional neural network (CNN) classification model for automated identification of different types of inferior vena cava (IVC) filters on radiographs.

Materials And Methods: In total, 1,375 cropped radiographic images of 14 types of IVC filters were collected from patients enrolled in a single-center IVC filter registry, with 139 images withheld as a test set and the remainder used to train and validate the classification model. Image brightness, contrast, intensity, and rotation were varied to augment the training set.

Upper extremity tumor embolization using a transradial artery approach: technical note.

Transradial access is being used with increasing frequency for interventional radiology procedures and offers several key advantages, including decreased access site complications and increased patient comfort. We report the technique of using transradial access to perform preoperative embolization of a humeral renal cell carcinoma metastasis and pathologic fracture. A transradial approach for performing humeral preoperative tumor embolization has not been previously reported, to our knowledge.