5-D Image Guided Cardiac Ablation Therapy David R Holmes, III, Ph.D. Biomedical Imaging Resource 4th NCIGT and NIH Image Guided Therapy Workshop October 13, 2011 ©2011 MFMER | slide-1 Acknowledgments • Richard Robb, Ph.D. • Douglas Packer, M.D. • Maryam Rettmann, Ph.D. • Fellows • David Kwartowitz, Ph.D. • Jiquin Liu, Ph.D. • Cristian Linte, Ph.D. • Staff • Jon Camp • Bruce Cameron • Sue Johnson ©2011 MFMER | slide-2 Introduction • “If I can see it, I can fix it” • Thor Sundt to Rich Robb (1972) • Visualizing Cardiac Ablation • How can we best leverage the available information to visualize an ablation procedure? • Enhancing Visualization through Refinement • Visual Feedback of Ablation ©2011 MFMER | slide-3 Early Cardiac Ablation • Highly successful procedure (99%) • Some recurrence of fibrillation ©2011 MFMER | slide-4 Early Guidance for Cardiac Ablation • Real-time 3D feedback with functional information ©2011 MFMER | slide-5 Goal of high-dimensional/multi-modal imaging in RF cardiac ablation • Immerse the clinician in the patient • To see all of the data in the real-world context of the patient ©2011 MFMER | slide-6 Image Guided Cardiac Ablation Real Time 3D Position and Orientation Trackers Real-Time 3D Ultrasound Pre-acquired Image Volume(s) Coordinates Images Surface Real-Time EP Registration Patient-Specific Anatomy, EP and Motion Heartbeat Model EP Data Ablation Probe Images Angulation 5D Viewer Fluoroscope Images US Patent Circa 1998 #6,556,695 ©2011 MFMER | slide-7 Components of Multi-modal Image guidance • Registration • Needed for integration of signals • Context (Anatomy) • Needed to guide procedure • Parametric Mapping • Needed for presentation of data • Real-time Feedback • Needed to faithfully represent the patient on the table ©2011 MFMER | slide-8 Visualizing Cardiac Ablation Mapping Patient-Specific Anatomy ©2011 MFMER | slide-9 Image Guided Cardiac Ablation System Biosense System Single PC, Dual Display, Magnetic Field Generator, Catheter Panel Prototype System 4 Computational Servers, High Performance GUI, Dual Display with HUD, Digital Data Acquisition, Video Data Card, High-speed comm. network Phantom Exp. System Validation Phantom Dynamic Respirator Phantom Biosense Catheters Rettmann et al, 2006 ©2011 MFMER | slide-10 System Interface (1) ©2011 MFMER | slide-11 System Interface (2) ©2011 MFMER | slide-12 System Interface (3) ©2011 MFMER | slide-13 Patient Procedures • To date, we have shadowed 4 procedures • Cardiologist uses CARTO XP for guidance • Mayo system captures all data • Cardiologist review after procedure ©2011 MFMER | slide-14 Patient Procedure Results RMS error (mm) Guided Auto Both Surface 4.56003 3.76794 3.66108 Burn 3.30075 3.09241 3.43609 Both 3.96714 3.43955 3.54795 ©2011 MFMER | slide-15 Ongoing Studies • Direct guidance with Mayo mapping system • Recording engineering metrics • Registration accuracy • Repeatability and targeting • Recording clinical metrics • Total procedure time • Time to burn • Patient success rates (eventually) ©2011 MFMER | slide-16 Enhancing Visualization through Refinement Fusing Intra-operative Data ©2011 MFMER | slide-17 Lessons Learned • Cardiologist “likes” the models, but doesn’t necessarily trust them • Image data anatomically faithful, but temporally inaccurate • The electro-anatomical map is temporally accurate, but low fidelity • ICE is temporally accurate and “high” resolution, but lacks the full 3D context • Data must be consistent to be trustworthy ©2011 MFMER | slide-18 Changing the way we look at the data • Stone Carving approach • Sampled points serve as the rough model • Enhance with high-resolution data • Paper Mache approach • Use the high-resolution preoperative data as a scaffold for intra-operative data http://100swallows.wordpress.com/2009/05/20/how-to-carve-a-figure-in-marble/ http://www.flickr.com/photos/buildmakecraftbake/3239252403/ ©2011 MFMER | slide-19 Updating Patient Models Current 3D Model Real-time Data Gross Registration (Tracking) Local Registration (Projection) Fuse Current Model with Local Features Liu et al, 2011 ©2011 MFMER | slide-20 Synthetic experiment Liu et al, 2011 ©2011 MFMER | slide-21 Patient Data (offline) Cameron et al, 2011 ©2011 MFMER | slide-22 Ongoing Studies • Explore visualization techniques for fused models • Conduct targeting exercises with cardiologist to evaluate utility • In phantoms • In animal model ©2011 MFMER | slide-23 Visual Feedback of Ablation Modeling Thermal Response in LA ©2011 MFMER | slide-24 “Unsuccessful Ablation” • 30-50% patients have recurrence • Incomplete Isolation of PV • Temporary stunning masks true ablation • Inadequate visual feedback • Current ablation therapy guidance • Provide remedial representation of burn pattern • No information about the ablation • Temperature distribution, lesion size/pattern etc. ©2011 MFMER | slide-25 Approach • Enhance ablation therapy guidance by modeling thermal interaction using available data • High-resolution CT (pre-operative) as volumetric model • Intra-cardiac Echo (ICE) for local geometry • RF parameters from generator • Approximate tissue response to ablation using simplified thermal model ©2011 MFMER | slide-26 Thermal modeling of lesion growth with radiofrequency ablation devices Isaac A Chang*1 and Uyen D Nguyen2 BioMedical Engineering OnLine 2004, 3:27 doi:10.1186/1475925X-3-27 ©2011 MFMER | slide-27 Image derived thermal conductivity ©2011 MFMER | slide-28 Tissue ablation and charring models ©2011 MFMER | slide-29 Ongoing Studies • Ex-vivo studies underway to estimate tissue parameters and validate model • In-vivo animal studies in early 2012 • Retrospectively analyze clinical cases to determine predictability of the model ©2011 MFMER | slide-30 Concluding Remarks • “If I can see it ….” is necessary, but not sufficient. • “If I can see if and believe it…” • Thus, we put specific emphasis on: • what the clinician wants. • what we can learn from the data. • What we can validate ©2011 MFMER | slide-31 ©2011 MFMER | slide-32