Lemke, Heinz - The Digital Operating Room-Revolution or Evolution

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Track 2: Tecnologías para la transformación del sistema sanitario
2.4. Revolución en el quirófano

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Lemke, Heinz - The Digital Operating Room-Revolution or Evolution

  1. 1. The Digital Operating Room- Revolution or Evolution MIHealth 2012, Barcelona May 25th, 2012Heinz U Lemke, PhDTechnical University of Berlin, GermanyInnovation Center Computer Assisted SurgeryUniversity of Leipzig, GermanyResearch Professor of Radiology,University of Southern California, Los Angeles, USAInternational Foundation forComputer Assisted Radiology and Surgery - IFCARSwww.ifcars.org
  2. 2. Content1. Motivation2. DOR, TIMMS and related activities3. Patient- and Process Modelling4. Standards in Surgery5. Conclusion
  3. 3. Innovation Center Computer Assisted Surgery University of Leipzig, GermanyICCAS Project timing: 2005 – 2016Partner institutions: 8Grant volume: 22 Mio € Example of work items: • Patient Modelling • Surgical Workflow Modelling • Surgical PACS/TIMMS • Surgical DICOM • (Surgical IHE) • ... (OR.NET) International Foundation for Computer Assisted Radiology and Surgery - IFCARS Example of work items: • Patient Specific Modelling and MGM • TIMMS and the Digital Operating Room (DOR) • Surgical DICOM (WG 24) and IHE • Education (MICARS and JICARS) • CARS Congresses • ... (ITFoM and OR.NET projects)
  4. 4. Innovation Center Computer Assisted Surgery University of Leipzig, GermanyImplementation of a modular DOR systems architecture at ICCAS
  5. 5. Computer Assisted Digital OR Suite for Endoscopic MISS Problems: Image guided vs. n-D model guided therapy Video Endoscopy Image Manager - C-Arm Images Monitor Report MD’s Staff RN, Tech EEG Monitoring MRI Image - PACS C-Arm Left side of OR Fluoroscopy Laser generator EMG Image view Monitoring boxes Digital endoscopic OR suite facilitates MISS Teleconferencing - telesurgery H-K. Huang, IPI, University of Southern California and John Chiu, California Spine Institute
  6. 6. Examples of DOR devices Source: T. Lüth, MiMed
  7. 7. Examples of vendor specific DOR integration Source: T. Lüth, MiMed
  8. 8. Digital Operating Room (DOR) Maturity Levels Evolutionary Growth Path, (2005-2025++)Functionalities/System Features • Surgical cockpit systems • Model Based Medical Evidence (MBME) • Knowledge and decision • RT access to P2P management, surgical process repos. • Hospital/enterprise wide • Intelligent RT data mining interoperability, • Full voice/gesture control • DOR process redesign with • Clinical quantitative and • Medical TIMMS architect. EMR and signal integration statistical assessment, • RT CAD integration • Pre-op image integration • WF management (engine) incl. device/room control • IHE integration profiles for surgery and intervent. • Intelligent (situation aware) robotic devices … • Basic DICOM in Surgery • Full DICOM in Surgery • Patient specific models • Surgical (flight) recorder • HD video and digital • IO image acquisition • Basic IHE integration • Surgical solution systems •… image acquisition • Navigated Control profiles for surgery and services •… • Boom-mounted devices • Modelling and simulation • Smart walls incl. nD visual. •… •… • Automatic reporting • Intelligent camera • Basic model guided interv. •… •… • Integrated device control • Device interface harmon. • SIP/functional harmon. •… •… •… •… •… •… •… Time Periods2005+: Maturity level 1 2010+: Maturity level 2 2015+: Maturity level 3 2020+: Maturity level 4 2025++: Maturity level 5DOR vendor specific DOR peri-operative DOR intra-operative DOR vendor independent DOR intelligent infrastructureintegration processes optimisation process optimisation integration and processes © Heinz U. Lemke, Febr. 2011
  9. 9. 2015+: Maturity level 3 • DOR process redesign with EMR and signal integration • WF management (engine) incl. device/room control • Full DICOM in Surgery • Basic IHE integration profiles for surgery • Smart walls incl. nD visual. • Basic model guided interv. • SIP/functional harmon. •… 2015+: Maturity level 3 DOR intra-operative process optimisation
  10. 10. Content1. Motivation2. DOR, TIMMS and related activities3. Patient- and Process Modelling4. Standards in Surgery5. Conclusion
  11. 11. Discovering knowledge in data, situations and processes Pathologies Staff and Tools PatientsModels of patients and medical activities (i.e.diagnostic and interventional workflows)
  12. 12. Personalised Medicine Integrated (model based) in the DOR Patient Care EBM, MBME, Mechatronics Processes, (Navigation, Modalities Omics EMR Workflow,IHE ablation, …)(X-ray,CT, US,MRI++,SPECT, PET,OI) Modelling, Integration, Education Biosensors Prediction Planning and (physiology, and Diagnosis metabolism, (Data fusion, Intervention (Simulation, decisionserum, tissue, …) Simulation, CAD, ...) support, validation, …) Data bases (Atlas, P2P repositories, Future ICT-based Infrastructure data grids, ...) EBM – Evidence-based medicine MBME – Model-based medical evidence IHE – Integrating the healthcare enterprise
  13. 13. Personalised Medicine Integrated (model based) in the DOR Patient Care EBM, MBME, Mechatronics Processes, (Navigation, Modalities Omics EMR Workflow,IHE ablation, …)(X-ray,CT, US,MRI++,SPECT, PET,OI) Biosensors (physiology, metabolism,serum, tissue, …) Models of patients and medical activities (i.e.diagnostic and interventional workflows) Data bases (Atlas, P2P repositories, Future ICT-based Infrastructure data grids, ...) EBM – Evidence-based medicine MBME – Model-based medical evidence IHE – Integrating the healthcare enterprise
  14. 14. Personalised Medicine Integrated (model based) in the DOR Patient Care EBM, MBME, Mechatronics Processes, (Navigation, Modalities Omics EMR Workflow,IHE ablation, …)(X-ray,CT, US,MRI++,SPECT, PET,OI) Functional components/engines Biosensors Imaging Kernel for Diagnosis and Modelling Simulation WF and K+D Visualisation and Validation (physiology, Biosensors Management Rep. Manager Intervention metabolism,serum, tissue, …) Data bases (Atlas, P2P repositories, Future ICT-based Infrastructure data grids, ...)
  15. 15. Concept of an ICT architecture and functionalitiesfor Model Guided Therapy (MGT) Repo- Data Exch. Engine sitory Control Images WF and Devices/ Modelling Computing Rep. Validation and K+D Mechatr. tools tools tools tools signals tools tools Imaging Kernel for Diagnosis Visualisation and Modelling Simulation WF and K+D and Validation Rep. Manager Biosensors Management Intervention Therapy Imaging and Model Management System (TIMMS) ICT infrastructure for data, image, model and tool communication for patient model-guided medicine Data and Patient Process Models and information specific models medical records Models
  16. 16. Computer Assisted Digital OR Suite for Endoscopic MISS Problems: Image guided vs. n-D model guided therapy Video Endoscopy Image Manager - C-Arm Images Monitor Report MD’s Staff RN, Tech EEG Monitoring MRI Image - PACS C-Arm Left side of OR Fluoroscopy Laser generator EMG Image view Monitoring boxes Digital endoscopic OR suite facilitates MISS Teleconferencing - telesurgery Courtesy of Dr. John Chiu
  17. 17. MISS ePR Control System Dataflow of Minimally Invasive Spine Surgery ePR IO Imaging Kernel for Visualisation and WF and K+D Rep. Manager Biosensors Management Visualization & Fault- Display Module Fault-tolerant tolerantPre-OP Input Gateway ePR Module 3 1 2 Pre-OP image/data Pre-OP Pre-OP Input Gateway 1) ePR Server Display Image/Data Historical 320Monitoring 2) 6 4 Module Intra-OP InputIntra-OP Gateway 3) Archive/ 5 Intra-OP image/data database 7 Intra-OP 9 Real-time Post-OP Input Display Image/Data Gateway 5 Post-OP AuthoringPost-OP 10 & Display Module Post-OP 8 Data 11 Courtesy of : H-K. Huang, University of Southern California and John Chiu, California Spine Institute
  18. 18. Surgical ePR Control System utilized for endoscopic procedures to insure safe and accurate MISSIntraoperative monitor - live data/”real time” image/data - vital signs, 02 sat , EMG, laser, endoscopic and fluro images Courtesy of : H-K. Huang, University of Southern California and John Chiu, California Spine Institute
  19. 19. Data Exch.Multi-media ePR system for MISS Repo- Engine sitory Control within TIMMS architecture Therapy Imaging and Model Management System (TIMMS) Images WF and Devices/ Modelling Computing Rep. Validation and K+D Mechatr. tools tools tools tools signals tools tools IO Imaging Kernel for Diagnosis and Modelling Simulation WF and K+D Visualisation and Validation Biosensors Management Rep. Manager Intervention Therapy Imaging and Model Management System (TIMMS)ICT infrastructure (based on DICOM-X) for data, image, model and tool communication for patient model-guided therapy Data and Models WF`s, EBM, Models and (Simulated ”cases” intervention information Objects) records
  20. 20. Navigated Control Unit NCUShaver and intranasal drill: ACC sphenoid-clivus, 39 years, maleStep #2: prevention of the skull base by NC Source: G. Strauss
  21. 21. Navigated Control Unit NCUShaver and intranasal drill: ACC sphenoid-clivus, 39 years, maleStep #2: prevention of the periorbit by NC Source: G. Strauss
  22. 22. Data Exch.Multi-media ePR system for MISS Repo- Engine sitory Control within TIMMS architecture Therapy Imaging and Model Management System (TIMMS) Images WF and Devices/ Modelling Computing Rep. Validation and K+D Mechatr. tools tools tools tools signals tools tools IO Imaging Kernel for Diagnosis and Modelling Simulation WF and K+D Visualisation and Validation Biosensors Management Rep. Manager Intervention Therapy Imaging and Model Management System (TIMMS)ICT infrastructure (based on DICOM-X) for data, image, model and tool communication for patient model-guided therapy Data and Models WF`s, EBM, Models and (Simulated ”cases” intervention information Objects) records
  23. 23. Content1. Motivation2. DOR, TIMMS and related activities3. Patient- and Process Modelling4. Standards in Surgery5. Conclusion
  24. 24. “n+1“ Generic and Complimentary Viewpoints from different Domains of Discourse Holistic Viewpoint Anatomic Surgical Information “Integration“ viewpoint viewpoint Physiologic Patients Metabolomic viewpoint viewpointMechanistic/kinetic Genetic Diseases viewpoint viewpoint Other viewpoints: • Informatics • Pedigree • Homeostasis Pathologic viewpoint … • • • Epigenetics Frailty-Syndrom Orthomolecular Radiological viewpoint etc.
  25. 25. Larynx Tumor 25
  26. 26. MTheory: Example of laryngeal carcinoma Information entities are a sample only and not technically or clinically validated
  27. 27. MTheory tree: Example of laryngeal carcinoma Information entities and structure are a sample only and not technically or clinically validated
  28. 28. MTheory graph with attributes: Example of laryngeal carcinoma Information entities, structure and attributes are a sample only and not technically or clinically validated
  29. 29. Concept of an ICT architecture and functionalitiesfor Model Guided Medicine (MGM) Repo- Data Exch. Engine sitory Control Modelling tools WF, K+D tools Images e.g. Curation, e.g. Inferencing, Devices/ Computing Rep. Validation and EBM and MBME, Prediction, Mechatr. Clinical guidel. tools Model updating, tools tools signals P2P best pract.. etc. tools Imaging Kernel for Diagnosis Visualisation and Modelling Simulation WF and K+D and Validation Rep. Manager Biosensors Management Intervention Medical Information and Model Management System (MIMMS) ICT infrastructure based on software engineering and data, information and communication standards/frameworks (e.g. MDA, OSA, DICOM, HL7, IHE etc.) Models and medical records Data and Information e.g. EMR, Patient Process e.g. Outcome reports, OMICs specific models Models Source: Heinz U. Lemke
  30. 30. Top level workflow for minimally invasive reconstruction of the mitral valve S. Jacobs, D. R. Merk, D. Holzhey, V. Falk: Modellbasierte Therapie in der Herzchirurgie
  31. 31. P2P “Best Practice“ PSM/PM representations (knowledge portal) Reference expert knowledge Peer Expert IPeer Expert II Generic models and Repository of workflow patient-spec. models reference models (WFs, SIPs) etc. for medical techniques, WF graph Simulation and operating instructions, EducationPeer Expert III etc. P2P - Peer-to-peer PSM - Patient-specific modelling PM - Process modellingPeer Expert IV Source: Heinz U. Lemke
  32. 32. Content1. Motivation2. DOR, TIMMS and related activities3. Patient- and Process Modelling4. Standards in Surgery5. Conclusion
  33. 33. IT Standards for the DORSurgical DICOM services and IOD`s derived fromTIMMS functionalities and interface requirements Therapy Imaging and Model Management System (TIMMS) WG 24 “DICOM in Surgery“ New integration profiles and the need for a new IHE Domain “Surgery”
  34. 34. WG 24 “DICOM in Surgery“ Project Groups to assist the surgeon• PG1 WF/MI Neurosurgery• PG2 WF/MI ENT and CMF Surgery• PG3 WF/MI Orthopaedic Surgery• PG4 WF/MI Cardiovascular Surgery• PG5 WF/MI Thoraco-abdominal Surgery• PG6 WF/MI Interventional Radiology• PG7 WF/MI Anaesthesia• PG8 S-PACS Functions• PG9 WFMS Tools• PG10 Image Processing and Display• PG11 Ultrasound in Surgery
  35. 35. WG 24 “DICOM in Surgery“Overview of current DICOM supplements• Supplement 132: Surface Segmentation• Supplement 131: Implant Templates• Supplement 134: Implantation Plan SR Document
  36. 36. WG 24 “DICOM in Surgery“ Surface SegmentationSupplement 132 specifies a way to store andcommunicate meshes as DICOM instances, allowingthe storage of the meshes together with the imageson a PACS server.
  37. 37. First proposal for IHE in SurgeryNew integration profiles and the need for a new IHE Domain “Surgery”
  38. 38. Implantation Planning Digital implantation planning is of increasing importance Issue: No commonly accepted file format for implant templates Digital 2D Planning Digital 3D Planning Source: Oliver Burgert
  39. 39. Content1. Motivation2. DOR, TIMMS and related activities3. Standards in Surgery4. Conclusion
  40. 40. Digital Operating Room (DOR) Maturity Levels Evolutionary Growth Path, (2005-2025++)Functionalities/ RevolutionSystem Features after 2025 ? • Surgical cockpit systems • Model Based Medical Evidence (MBME) • Knowledge and decision • RT access to P2P management, surgical process repos. • Hospital/enterprise wide • Intelligent RT data mining interoperability, • Full voice/gesture control • DOR process redesign with • Clinical quantitative and • Medical TIMMS architect. EMR and signal integration statistical assessment, • RT CAD integration • Pre-op image integration • WF management (engine) incl. device/room control • IHE integration profiles for surgery and intervent. • Intelligent (situation aware) robotic devices … • Basic DICOM in Surgery • Full DICOM in Surgery • Patient specific models • Surgical (flight) recorder • HD video and digital • IO image acquisition • Basic IHE integration • Surgical solution systems •… image acquisition • Navigated Control profiles for surgery and services •… • Boom-mounted devices • Modelling and simulation • Smart walls incl. nD visual. •… •… • Automatic reporting • Intelligent camera • Basic model guided interv. •… •… • Integrated device control • Device interface harmon. • SIP/functional harmon. •… •… •… •… •… •… •… Time Periods2005+: Maturity level 1 2010+: Maturity level 2 2015+: Maturity level 3 2020+: Maturity level 4 2025++: Maturity level 5DOR vendor specific DOR peri-operative DOR intra-operative DOR vendor independent DOR intelligent infrastructureintegration processes optimisation process optimisation integration and processes © Heinz U. Lemke, Febr. 2011
  41. 41. Informatics platform/infrastructures as a Repo- Data Exch. reference architecture for the OR.NET project Engine sitory Control Therapy Imaging and Model Management System (TIMMS) Images WF and Devices/ Modelling Computing Rep. Validation and K+D Mechatr. tools tools tools tools signals tools tools IO Imaging Kernel for and Modelling Simulation WF and K+D Visualisation Intervention Validation Biosensors Management Rep. Manager Therapy Imaging and Model Management System (TIMMS)ICT infrastructure (based on DICOM-X) for data, image, model and tool communication for patient model-guided therapy Data and Models of WF`s, EBM, Models and patients ”cases” intervention information records
  42. 42. Summary points• We are at the beginning of a long path in the evolution from the conventional OR towards an intelligent and fully integrated (vendor independent) digital operating room (DOR).• Interdisciplinary cooperation of researchers, clinicians and industry to accommodate multiple view points based on a common understanding of the workflows within a therapeutic domain of discourse is indispensible for the advancement of the DOR.• Standard development based on agreed upon DOR architectures and interfaces is in progress but need to be accelerated.• Because of the complexity of surgical workflows and patient-specific models further research and development on workflow and knowledge and decision management systems is essential.
  43. 43. Questions• How can we bring researchers, clinicians and leading vendors in the field of the DOR onto the same table to define standards?• How can we assess optimization of perioperative and intraoperative processes with respect to patient outcome?• Which role will model-guided surgery (patient-specific models and workflow models) occupy in the evolution of the DOR during the next 10-20 years?
  44. 44. INVITATION to CARS 201216th Annual Conference of the International Society for 30th International Computer Aided Surgery EuroPACS Meeting www.cars-int.org14th International Workshop on 4th EPMA/IFCARS Workshop on Computer-Aided Diagnosis CMI Personalised Medicine and ICT 18th Computed 13th IFCARS/SPIE/EuroPACS Maxillofacial Workshop on Surgical PACS and Imaging Congress the Digital Operating Room
  45. 45. Thank you for your attention

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