A simple and accurate method for computer-aided transapical aortic valve replacement

Abstract Background and purpose Transapical aortic valve replacement (TAVR) is a recent minimally invasive surgical treatment technique for elderly and high-risk patients with severe aortic stenosis. In this paper, a simple and accurate image-based method is introduced to aid the intra-operative gui...

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Bibliographic Details
Published in:Computerized medical imaging and graphics 2016-06, Vol.50, p.31-41
Main Authors: Karar, Mohamed Esmail, Merk, Denis R, Falk, Volkmar, Burgert, Oliver
Format: Article
Language:English
Subjects:
Aortic Valve
Aortic Valve Stenosis
Biomedical image processing
Computer-aided surgery
Finite element method
Heart Valve Prosthesis
Heart Valve Prosthesis Implantation
Humans
Image-guided intervention
Imaging, Three-Dimensional
Implantation
Internal Medicine
Minimally invasive cardiac surgery
Other
Patients
Prosthetics
Surgical implants
Three dimensional models
Tracking
Valves
X-ray fluoroscopy
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Summary:Abstract Background and purpose Transapical aortic valve replacement (TAVR) is a recent minimally invasive surgical treatment technique for elderly and high-risk patients with severe aortic stenosis. In this paper, a simple and accurate image-based method is introduced to aid the intra-operative guidance of TAVR procedure under 2-D X-ray fluoroscopy. Methods The proposed method fuses a 3-D aortic mesh model and anatomical valve landmarks with live 2-D fluoroscopic images. The 3-D aortic mesh model and landmarks are reconstructed from interventional X-ray C-arm CT system, and a target area for valve implantation is automatically estimated using these aortic mesh models. Based on template-based tracking approach, the overlay of visualized 3-D aortic mesh model, landmarks and target area of implantation is updated onto fluoroscopic images by approximating the aortic root motion from a pigtail catheter motion without contrast agent. Also, a rigid intensity-based registration algorithm is used to track continuously the aortic root motion in the presence of contrast agent. Furthermore, a sensorless tracking of the aortic valve prosthesis is provided to guide the physician to perform the appropriate placement of prosthesis into the estimated target area of implantation. Results Retrospective experiments were carried out on fifteen patient datasets from the clinical routine of the TAVR. The maximum displacement errors were less than 2.0 mm for both the dynamic overlay of aortic mesh models and image-based tracking of the prosthesis, and within the clinically accepted ranges. Moreover, high success rates of the proposed method were obtained above 91.0% for all tested patient datasets. Conclusion The results showed that the proposed method for computer-aided TAVR is potentially a helpful tool for physicians by automatically defining the accurate placement position of the prosthesis during the surgical procedure.
ISSN:0895-6111
1879-0771
DOI:10.1016/j.compmedimag.2014.09.005