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Degenerative aortic stenosis is highly prevalent in the aging populations of industrialized countries and is associated with poor prognosis. Surgical valve replacement has been the only established treatment with documented improvement of long-term outcome. However, many of the older patients with aortic stenosis (AS) are high-risk or ineligible for surgery. For these patients, transcatheter aortic valve replacement (TAVR) has emerged as a treatment alternative. The TAVR procedure is characterized by a lack of visualization of the operative field. Therefore, pre- and intra-procedural imaging is critical for patient selection, pre-procedural planning, and intra-operative decision-making. Incremental to conventional angiography and 2-D echocardiography, multidetector computed tomography (CT) has assumed an important role before TAVR. The analysis of 3-D CT data requires extensive post-processing during direct interaction with the dataset, using advance analysis software. Organization and storage of the data according to complex clinical workflows and sharing of image information have become a critical part of these novel treatment approaches. Optimally, the data are integrated into a comprehensive image data file accessible to multiple groups of practitioners across the hospital. This creates new challenges for data management requiring a complex IT infrastructure, spanning across multiple locations, but is increasingly achieved with client-server solutions and private cloud technology. This article describes the challenges and opportunities created by the increased amount of patient-specific imaging data in the context of TAVR.

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Advanced 3-D analysis, client-server systems, and cloud computing-Integration of cardiovascular imaging data into clinical workflows of transcatheter aortic valve replacement.