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Transcatheter aortic valve implantation (TAVI) is an effective treatment option for patients suffering from symptomatic, severe aortic valve stenosis. Previously, only patients with prohibitive or high surgical risk were TAVI candidates; however, current guidelines already recommend TAVI as a treatment alternative for patients with intermediate surgical risk. Multidetector computed tomography (MDCT) has gained great importance in the periprocedural assessment of patients who undergo TAVI. Due to the three-dimensional image visualization, MDCT allows the evaluation of anatomical structures in a more comprehensive manner compared to echocardiography, the traditional tool used in TAVI patient work-up. By providing accurate measurements of the aortic root, MDCT helps to avoid potential patient-prosthesis mismatch throughout transcatheter valve sizing. Moreover, MDCT is also a feasible tool for access route evaluation and to determine the optimal projection angles for the TAVI procedure. Although the routine MDCT follow-up of patients is currently not recommended in clinical practice, if performed, it could provide invaluable information about valve integrity and asymptomatic leaflet thrombosis. Post-procedural MDCT can provide details about the position of the prosthesis and complications such as leaflet-thrombosis, aortic regurgitation, coronary occlusion, and other vascular complications that can represent major cardiac emergencies. The aim of the current review is to overview the role of MDCT in the pre- and post-procedural assessment of TAVI patients. In the first part, the article presents the role of pre-TAVI imaging in the complex anatomical assessment of the aortic valve and the selection of the most appropriate device. The second part of the review describes the role of MDCT in patients who underwent TAVI to assess potential complications, some of them leading to a major cardiovascular emergency.

journal of cardiovascular emergencies

Role of Multidetector Computed Tomography in Transcatheter Aortic Valve Implantation – from Pre-procedural Planning to Detection of Post-procedural Complications