Low muscle quality on a procedural computed tomography scan assessed with deep learning as a practical useful predictor of mortality in patients with severe aortic valve stenosis

Accurate diagnosis of sarcopenia requires evaluation of muscle quality, which refers to the amount of fat infiltration in muscle tissue. In this study, we aim to investigate whether we can independently predict mortality risk in transcatheter aortic valve implantation (TAVI) patients, using automatic deep learning algorithms to assess muscle quality on procedural computed tomography (CT) scans.