title: Augmented Reality System for Ultrasound Guidance of Transcatheter Aortic Valve Implantation.
abstract: OBJECTIVE
  Transcatheter aortic valve implantation (TAVI) relies on fluoroscopy and nephrotoxic contrast medium for valve deployment. We propose an alternative guidance system using augmented reality (AR) and transesophageal echocardiography (TEE) to guide TAVI deployment. The goals of this study were to determine how consistently the aortic valve annulus is defined from TEE using different aortic valve landmarks and to compare AR guidance with fluoroscopic guidance of TAVI deployment in an aortic root model.
  
  
  METHODS
  Magnetic tracking sensors were integrated into the TAVI catheter and TEE probe, allowing these tools to be displayed in an AR environment. Variability in identifying aortic valve commissures and cuspal nadirs was assessed using TEE aortic root images. To compare AR guidance of TAVI deployment with fluoroscopic guidance, a TAVI stent was deployed 10 times in the aortic root model using each of the two guidance systems.
  
  
  RESULTS
  Commissures and nadirs were both investigated as features for defining the valve annulus in the AR guidance system. The commissures were identified more consistently than the nadirs, with intraobserver variability of 2.2 and 3.8 mm, respectively, and interobserver variability of 3.3 and 4.7 mm, respectively. The precision of TAVI deployment using fluoroscopic guidance was 3.4 mm, whereas the precision of AR guidance was 2.9 mm, and its overall accuracy was 3.4 mm. This indicates that both have similar performance.
  
  
  CONCLUSIONS
  Aortic valve commissures can be identified more reliably than cuspal nadirs from TEE. The AR guidance system achieved similar deployment accuracy to that of fluoroscopy while eliminating the use and consequences of nephrotoxic contrast and radiation.
authors.affiliation: From the *Division of Cardiac Surgery, Department of Surgery, London Health Sciences Centre, London, ON, Canada; †Canadian Surgical Technologies & Advanced Robotics, Lawson Health Research Institute, London, ON, Canada; ‡Medical Imaging Laboratory, Robarts Research Institute, Western University, London, ON, Canada; and §Department of Surgery, Schulich School of Medicine & Dentistry, and ∥Electrical and Computer Engineering, Western University, London, ON, Canada.
authors.forename: Maria E
authors.initials: ME
authors.lastname: Currie
authors.forename: A Jonathan
authors.initials: AJ
authors.lastname: McLeod
authors.forename: John T
authors.initials: JT
authors.lastname: Moore
authors.forename: Michael W A
authors.initials: MW
authors.lastname: Chu
authors.forename: Rajni
authors.initials: R
authors.lastname: Patel
authors.forename: Bob
authors.initials: B
authors.lastname: Kiaii
authors.forename: Terry M
authors.initials: TM
authors.lastname: Peters
mesh_terms: D001024:Aortic Valve Stenosis / Q000000981:diagnostic imaging / Q000601:surgery*; D017548:Echocardiography, Transesophageal / Q000295:instrumentation / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation; D016343:Monitoring, Intraoperative / Q000295:instrumentation / Q000379:methods; D015588:Observer Variation; D065467:Transcatheter Aortic Valve Replacement / Q000295:instrumentation / Q000379:methods*; D016896:Treatment Outcome; D018084:Ultrasonography, Interventional / Q000295:instrumentation / Q000379:methods