Title
Image-based computational models for TAVI planning: from CT images to implant deployment.
Abstract
Transcatheter aortic valve implantation (TAVI) is becoming the standard choice of care for non-operable patients suffering from severe aortic valve stenosis. As there is no direct view or access to the affected anatomy, accurate preoperative planning is crucial for a successful outcome. The most important decision during planning is selecting the proper implant type and size. Due to the wide variety in device sizes and types and non-circular annulus shapes, there is often no obvious choice for the specific patient. Most clinicians base their final decision on their previous experience. As a first step towards a more predictive planning, we propose an integrated method to estimate the aortic apparatus from CT images and compute implant deployment. Aortic anatomy, which includes aortic root, leaflets and calcifications, is automatically extracted using robust modeling and machine learning algorithms. Then, the finite element method is employed to calculate the deployment of a TAVI implant inside the patient-specific aortic anatomy. The anatomical model was evaluated on 198 CT images, yielding an accuracy of 1.30 +/- 0.23 mm. In eleven subjects, pre- and post-TAVI CT images were available. Errors in predicted implant deployment were of 1.74 +/- 0.40 mm in average and 1.32 mm in the aortic valve annulus region, which is almost three times lower than the average gap of 3 mm between consecutive implant sizes. Our framework may thus constitute a surrogate tool for TAVI planning.
Year
DOI
Venue
2013
10.1007/978-3-642-40763-5_49
Lecture Notes in Computer Science
Field
DocType
Volume
Computer vision,Aortic valve stenosis,Software deployment,Computer science,Implant,Image based,Aortic valve,Computational model,Aortic Valve Annulus,Volumetric model,Artificial intelligence,Radiology
Conference
8150
Issue
ISSN
Citations 
Pt 2
0302-9743
3
PageRank 
References 
Authors
0.55
2
9
Name
Order
Citations
PageRank
Sasa Grbic18213.77
Tommaso Mansi245445.94
Razvan Ioan Ionasec321326.71
Ingmar Voigt416018.48
Helene Houle5879.62
Matthias John611911.36
Max Schoebinger7102.33
Nassir Navab86594578.60
Dorin Comaniciu98389601.83