Surgical Planning Laboratory Brigham and Women’s Hospital Boston, Massachusetts USA a teaching affiliate of Harvard Medical School Open Source Concepts.

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Presentation transcript:

Surgical Planning Laboratory Brigham and Women’s Hospital Boston, Massachusetts USA a teaching affiliate of Harvard Medical School Open Source Concepts in Image Guided Therapy Ron Kikinis, M.D., Professor of Radiology, Harvard Medical School, Director, Surgical Planning Laboratory, Brigham and Women’s Hospital Founding Director, Surgical Planning Laboratory, Brigham and Women’s Hospital Principal Investigator, the National Alliance for Medical Image Computing, and the Neuroimage Analysis Center Research Director, National Center for Image Guided Therapy

©2007 Surgical Planning Laboratory, ARR Slide 2 Acknowledgments F. Jolesz, C. Tempany, P. Black, S. Wells, CF. Westin, M. Halle, S. Pieper, N. Hata, T. Kapur, A.Tannenbaum, M. Shenton, E. Grimson, P.Golland, W.Schroeder, and many more….

©2007 Surgical Planning Laboratory, ARR Slide 3 Overview Introduction Slicer Robots NA-MIC Open IGT Science: over 500 peer-reviewed papers since 1990

©2007 Surgical Planning Laboratory, ARR Slide 4 Active visualization of medical images to aid in decision making during a procedure. Allows physician to –See Beyond the Surface –DefineTargets –Control the Interventions Enables new procedures, decreases invasiveness, optimizes resection Image Guided Therapy (IGT) Dimaio SP, Archip N, Hata N, Talos IF, Warfield SK, Majumdar A, Mcdannold N, Hynynen K, Morrison PR, Wells WM 3rd, Kacher DF, Ellis RE, Golby AJ, Black PM, Jolesz FA, Kikinis R.: Image-guided neurosurgery at Brigham and Women's Hospital.IEEE Eng Med Biol Mag Sep- Oct;25(5):67-73

©2007 Surgical Planning Laboratory, ARR Slide 5 MIC: The Problem More image data, more complexity Medical Image Computing aims to extract relevant information from images Provided by Odonnell, et al. Provided by Kindlmann, et al. Golby, Archip et al.

©2007 Surgical Planning Laboratory, ARR Slide 6 MIC: The Science Algorithm research Software tool development Biomedical research (applications) Courtesy S. Haker Courtesy R. Jose et al.Courtesy P. Black et al.

©2007 Surgical Planning Laboratory, ARR Slide 7 MIC: The Approach Research and development conducted by interdisciplinary teams Pohl et al.

©2007 Surgical Planning Laboratory, ARR Slide 8 Overview Introduction Slicer Robots NA-MIC Open IGT

©2007 Surgical Planning Laboratory, ARR Slide 9 9 Slicer 3: Software Next Generation of Slicer –At least 80% of code rewritten –> 500K lines of code –Improved Look and Feel (KWWidgets) –Improved Modularity Analysis routines can be used as plugins or command line executables for batch processing –Draws on Multi-Institution Community Courtesy S. Pieper Google: slicer 101

©2007 Surgical Planning Laboratory, ARR Slide 10 Slicer Features Multi-Platform Visualization Filtering Registration Segmentation DTI Quantification IGT Capabilities: device interfaces Plug-in architecture Interfaces into informatics frameworks Specialties Involved: Medical Imaging Applied Math Software Engineering Visualization Statistics Computer Vision Neuroscience Robotics User Interface Information Design …

©2007 Surgical Planning Laboratory, ARR Slide 11 B. Davis, S. Barre, Y. Yuan, W. Schroeder, P. Golland, K. Pohl Segmentation

©2007 Surgical Planning Laboratory, ARR Slide 12 Rigid Registration Overlay Before: After:

©2007 Surgical Planning Laboratory, ARR Slide 13 BWH CWM Toward real-time image guided neurosurgery using distributed and grid computing (with Andriy Fedorov, Andriy Kot, Neculai Archip, Peter Black, Olivier Clatz, Alexandra Golby, Ron Kikinis, and Simon K. Warfield. In Proceedings of the 2006 ACM/IEEE Conference on Supercomputing, Tampa, Florida, November , Non-rigid Deformation (*) Non-rigid alignment of preoperative MRI, fMRI, DT-MRI, with intra-operative MRI for enhanced visualization and navigation In image-guided neurosurgery (with N. Archip, O. Clatz, A. Fedorov, A. Kot, S. Whalen, D. Kacher, F. Jolesz, A. Golby, P.Black, S. Warfield) in NeuroImage, 35(2): , 2007.

©2007 Surgical Planning Laboratory, ARR Slide 14 Fusion of Pre-OP Data Provided by A. Golby

©2007 Surgical Planning Laboratory, ARR Slide 15 Micro Sensor for Tracking Sierra R, Dimaio SP, Wada J, Hata N, Szekely G, Kikinis R, Jolesz F, Links Patient specific simulation and navigation of ventriculoscopic interventions. Stud Health Technol Inform. 2007;125:433-5 Augmented Endoscopy

©2007 Surgical Planning Laboratory, ARR Slide 16 Overview Introduction Slicer Robots NA-MIC Open IGT

©2007 Surgical Planning Laboratory, ARR Slide 17 Feasibility: Next Step: Open 0.5TClosed 3T “Robot-Assisted Needle Placement in Open-MRI: System Architecture, Integration and Validation,” S. P. DiMaio, S. Pieper, K. Chinzei, N. Hata, E. Balogh, G. Fichtinger, C. M. Tempany, R. Kikinis. Studies in Health Technologies and Informatics (Medicine Meets Virtual Reality), 2005;119: Robotic Devices: Hardware

©2007 Surgical Planning Laboratory, ARR Slide 18 “A system for MRI-guided Prostate Interventions,” S. P. DiMaio, G. S. Fischer, S. J. Haker, N. Hata, I. Iordachita, C. M. Tempany, R. Kikinis, G. Fichtinger. Proceedings of IEEE / RAS- EMBS International Conference of Biomedical Robotics and Biomechatronics, February Robot Assembly with Needle Driver Provided by DiMaio et al. IGT Robotics

©2007 Surgical Planning Laboratory, ARR Slide 19 Open robots? Open design specifications Commodity materials Provided by D. Pace et al.

©2007 Surgical Planning Laboratory, ARR Slide 20 Overview Introduction Slicer Robots NA-MIC Open IGT

©2007 Surgical Planning Laboratory, ARR Slide 21 NAMIC: Multi-Site National Alliance for Medical Image Computing From local to wide-area One of seven National Centers for Biomedical Computing funded by NIH Al Hakim et al.

©2007 Surgical Planning Laboratory, ARR Slide 22 NA-MIC: An Alliance of Peers Leadership: –BWH: Ron Kikinis, (Overall PI)‏ Core 1 Algorithms –Utah: Ross Whitaker (Core 1 PI), Guido Gerig‏ –MIT: Polina Golland, Eric Grimson –UNC: Martin Styner –MGH: Bruce Fischl, Dave Kennedy –GaTech: Allen Tannenbaum Core 2 Engineering –Kitware: Will Schroeder (Core 2 PI)‏ –GE: Jim Miller –Isomics: Steve Pieper –UCSD: Mark Ellisman, Jeff Grethe –UCLA: Art Toga Core 3 DBP –BWH: Martha Shenton –Dartmouth: Andy Saykin –UCI: Steve Potkin –UofT: Jim Kennedy DBP 2007 –UNC: H. Cody –BWH: M. Kubicki –Mind Institute: J. Bockolt, C. Gasparovic –Queens University: G. Fichtinger Core 4 Service –Kitware: Will Schroeder Core 5 Training –MGH: Randy Gollub Core 6 Dissemination –Isomics: Steve Pieper, Tina Kapur Core 7 Management –BWH: S. Manandhar, R. Manandhar Provided by Pieper, Kikinis

©2007 Surgical Planning Laboratory, ARR Slide 23 Plus –“Big Science” can be a force multiplier –Development and adoption of best practices –Faster and higher-quality dissemination of new techniques and of new science Minus –Change in culture needed: Replace: –“My research” with –“Our research” NA-MIC is “Big Science”

©2007 Surgical Planning Laboratory, ARR Slide 24 FOSS in NA-MIC Free Open Source –No restrictions on use –No requirement to give back derived code (you decide how much you want to share) –Software I. Courouge et al.

©2007 Surgical Planning Laboratory, ARR Slide 25 The FOSS Value Proposition Cost effective: Reduced duplication High quality: Openness enables validation, debugging and local control Lowers barriers for scientific exchange Fletcher et al.

©2007 Surgical Planning Laboratory, ARR Slide 26 The NA-MIC Kit Designed for Research (but compatible with commercial activities) –FOSS: 3D Slicer, ITK, VTK, KWW –Software engineering methodology Portable: multi-platform cmake Multi-site development: nightly builds dart Quality assurance: automated testing ctest Fischl et al.

©2007 Surgical Planning Laboratory, ARR Slide 27 FOSS and Commercial Use Value-added commercialization is the proper mechanism for clinical use of open research results BSD style licenses are fully compatible with commercial use Automated testing and multi-platform support lower the threshold for the translational work

©2007 Surgical Planning Laboratory, ARR Slide 28 Overview Introduction Slicer Robots NA-MIC Open IGT

©2007 Surgical Planning Laboratory, ARR Slide 29 NCIGT NIH funded National Center for Image Guided Therapy Leverages NA-MIC software platform Open Concepts in IGT: where appropriate

©2007 Surgical Planning Laboratory, ARR Slide 30 The Two Worlds of IGT Clinical devices –Government regulated (for protection of patients) 1.“Freeze” the procedure and devices 2.Characterize/test behavior 3.Document Research devices –Regulated through local research protocols 1.Frequent modifications 2.Characterization/testing is an afterthought 3.Documentation is always behind Siemens

©2007 Surgical Planning Laboratory, ARR Slide 31 Types of IGT Research 1.Testing of devices provided by commercial vendors Performed in a clinical environment 2.Developing new devices Requires dedicated research time and dedicated personnel

©2007 Surgical Planning Laboratory, ARR Slide 32 Proprietary Approaches Hardware is inherently proprietary Funding agencies often require commercialization which results in proprietary approaches Mako Surgical Corp.

©2007 Surgical Planning Laboratory, ARR Slide 33 Consequences Proprietary software and hardware –Scientific exchange is more difficult –Leveraging the work of others becomes more difficult –Locks researchers to the vendor Consequence: Graduate students are forced to duplicate work by others

©2007 Surgical Planning Laboratory, ARR Slide 34 Lessons learned Open science concepts for devices –Open interfaces –Open designs –Increased reliance on commodity technology

©2007 Surgical Planning Laboratory, ARR Slide 35 Open Interfaces USB keys are an excellent example for a successful hardware/software standard: –Devices available from different vendors –Same device works on different computers with a variety of operating systems Opentracker and IGSTK are emerging BSD licensed packages that provide open interfaces to proprietary tracking systems

©2007 Surgical Planning Laboratory, ARR Slide 36 Open IGT for Research Free Open Source Software –NA-MIC methodology allows multi-party development and quality assurance –Potential to bridge the gap between research and clinical devices Open Standards for Hardware interfaces –Computer industry offers good templates: Standardization through ACM and IEEE Open Designs for Research Hardware (remember the Lego robot?)

©2007 Surgical Planning Laboratory, ARR Slide 37 Thank You! For more information: