A mitral annulus tracking approach for navigation of off‐pump beating heart mitral valve repair. Issue 1 (30th December 2014)

• Record Type: Journal Article
• Authors: Li, Feng P.; Rajchl, Martin; Moore, John; Peters, Terry M.
• Is Part Of: Medical physics. Volume 42:Issue 1(2015)
• Page Start: 456
• Page End: 468
• Publication Date: 2014-12-30
• Subjects: bioelectric potentials -- cardiovascular system -- echocardiography -- image motion analysis -- image registration -- image segmentation -- magnetic sensors -- medical image processing -- navigation -- phantoms -- surgery; Biomedical engineering -- Ultrasonographic imaging -- Segmentation -- Registration -- Neuroscience -- Cardiac dynamics; Echo‐tomography -- Surgical instruments, devices or methods, e.g. tourniquets -- Navigation; Navigational instruments not provided for in groups G01C1/00 to G01C19/00 -- Biological material, e.g. blood, urine; Haemocytometers -- Digital computing or data processing equipment or methods, specially adapted for specific applications -- Image data processing or generation, in general -- Analysis of motion; beating heart mitral valve repair -- image guidance -- ultrasound -- mitral annulus tracking -- real‐time; Multivariate analysis -- Heart -- Cardiac dynamics -- Ultrasonography -- Tracking devices -- Selected area electron diffraction -- Medical image segmentation -- Computer software -- Magnetic sensors; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1118/1.4904022
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Purpose: To develop and validate a real‐time mitral valve annulus (MVA) tracking approach based on biplane transesophageal echocardiogram (TEE) data and magnetic tracking systems (MTS) to be used in minimally invasive off‐pump beating heart mitral valve repair (MVR). Methods: The authors' guidance system consists of three major components: TEE, magnetic tracking system, and an image guidance software platform. TEE provides real‐time intraoperative images to show the cardiac motion and intracardiac surgical tools. The magnetic tracking system tracks the TEE probe and the surgical tools. The software platform integrates the TEE image planes and the virtual model of the tools and the MVA model on the screen. The authors' MVA tracking approach, which aims to update the MVA model in near real‐time, comprises of three steps: image based gating, predictive reinitialization, and registration based MVA tracking. The image based gating step uses a small patch centered at each MVA point in the TEE images to identify images at optimal cardiac phases for updating the position of the MVA. The predictive reinitialization step uses the position and orientation of the TEE probe provided by the magnetic tracking system to predict the position of the MVA points in the TEE images and uses them for the initialization of the registration component. The registration based MVA tracking step aims to locate the MVA points in the images selected by the image based gating component by performing image based registration. Results: The validation of the MVA tracking approach was performed in a phantom study and a retrospective study on porcine data. In the phantom study, controlled translations were applied to the phantom and the tracked MVA was compared to its "true" position estimated based on a magnetic sensor attached to the phantom. The MVA tracking accuracy was 1.29 ± 0.58 mm when the translation distance is about 1 cm, and increased to 2.85 ± 1.19 mm when the translation distance is about 3 cm. In the study on porcine data, the authors compared the tracked MVA to a manually segmented MVA. The overall accuracy is 2.37 ± 1.67 mm for single plane images and 2.35 ± 1.55 mm for biplane images. The interoperator variation in manual segmentation was 2.32 ± 1.24 mm for single plane images and 1.73 ± 1.18 mm for biplane images. The computational efficiency of the algorithm on a desktop computer with an Intel ® Xeon ® CPU @3.47 GHz and an NVIDIA GeForce 690 graphic card is such that the time required for registering four MVA points was about 60 ms. Conclusions: The authors developed a rapid MVA tracking algorithm for use in the guidance of off‐pump beating heart transapical mitral valve repair. This approach uses 2D biplane TEE images and was tested on a dynamic heart phantom and interventional porcine image data. Results regarding the accuracy and efficiency of the authors' MVA tracking algorithm are promising, and fulfill the requirements for surgical navigation.