Ruling out rotator cuff tear in shoulder radiograph series using deep learning: redefining the role of conventional radiograph

ConclusionThe deep learning algorithm could accurately rule out significant rotator cuff tear based on shoulder radiographs.Key Points•The deep learning algorithm can rule out significant rotator cuff tear with a negative likelihood ratio of 0.06 and a negative predictive value of 96.6%.•The deep learning algorithm can guide patients with significant rotator cuff tear to additional shoulder ultrasound or MRI with a sensitivity of 97.3%.•The deep learning algorithm could rule out significant rotator cuff tear in about 30% of patients with clinically suspected rotator cuff tear.

Source: European Radiology - February 4, 2020 Category: Radiology Source Type: research