The Intelligent ENT Operating Room of the Future^[*]

Abstract

The increasing plurality and complexity of technical assistance systems pose a challenge for clinically active physicians. Particularly in the operating theater, there is a growing need to integrate medical systems and software solutions into a holistic clinical infrastructure. The primary goal of building a “digital (ENT) operating room of the future” is not just the pure technical improvement of the individual computer-aided equipment and instruments, but rather their dynamic networking and system integration in an open modular system. Promising scientific projects address the question of how to improve the quality, safety and user-friendliness of technical systems in the health care system of the 21st century. The work on SCOT, MD PnP and OR.NET show the various components that make the vision of the ENT operating room of the future tangible and realistic in the overall context.

Key words

Interoperability - system networking - digital operating room - ICCAS - OR.NET

• Literatur

• 1 Franke S, Rockstroh M, Hofer M, Neumuth T. The intelligent OR: design and validation of a context-aware surgical working environment. Int J Comput Assist Radiol Surg 2018; [Epub ahead of print]
• 2 Kasparick M, Rockstroh M, Schlichtling S, Golatowski F, Timmermann D. Mechanism for safe remote activation of networked surgical ans PoC devices using a dynamic assignable controls. Conf Proc IEEE Eng Med Biol Soc 2016; 2016: 2390-2394 doi: 10.1109/EMBC.2016.7591211
• 3 Rockstroh M, Franke S, Hofer M, Will A, Kasparick M, Andersen B, Neumuth T. OR.NET: multi-perspective qualitative evaluation of an integrated operating room based in IEEE 11073 SDC. Int J Comput Assist Radiol Surg 2017; 12: 1461-1469 doi:10.1007/s11548-017-1589-2. Epub 2017 May 8
• 4 Cypko MA, Stoehr M, Oeltze-Jafra S, Dietz A, Lemke HU. A Guide for Constructing Bayesian Network Graphs of Cancer Treatment Decisions. Stud Health Technol Inform 2017; 245: 1355
• 5 Pirlich M, Tittmann M, Franz D, Dietz A, Hofer M. An observational, prospective study to evaluate the preoperative planning tool „CI Wizard“ for cochlear implant surgery. Eur Arch Otorhinolaryngol 2017; 274: 685-694. doi:10.1007/s00405-016-4286-9 Epub 2016 Sep 2
• 6 Boehm A, Müller S, Pankau T, Straub G, Bohn S, Fuchs M, Dietz A. Computer assistance to improve therapy planning for head neck oncology. Laryngorhinootologie 2011; 90: 732-738 doi:10.1055/s-0031-1295410. Epub 2011 Dec 8
• 7 Pankau T, Wichmann G, Neumuth T, Preim B, Dietz A, Stumpp P, Boehm A. 3D model-based documentation with the Tumor Therapy Manager (TTM) improves TNM Staging of head and neck tumor patients. Int J Comput Assist Radiol Surg 2015; 10: 1617-1624 doi:10.1007/s11548-014-1131-8. Epub 2014 Dec 5
• 8 Bieck R, Heuermann K, Schmidt M, Schmitgen A, Arnold S, Dietz A, Neumuth T. Towards an information presentation model of a situation-aware navigation system in functional endoscopic sinus surgery. 15th CURAC Annual Conference, Bern, 2016
• 9 Maktabi M, Birnbaum K, Oeser A, Neumuth T. Situation-dependent medical device risk estimation: Design and Evaluation of an equipment management center for vendor-independent integrated operating rooms. J Patient Saf 2017 [Epub ahead of print]
• 10 Neumann J, Wiemuth M, Burgert O, Neumuth T. Application of activity semantics and BPMN 2.0 in the generation and modeling of generic surgical process models. Int J Comput Assist Radiol Surg 2017; 12 S1 48-49
• 11 Cypko M, Stoehr M, Kozniewski M, Druzdzel MJ, Dietz A, Berliner L, Lemke HU. Validation workflow for a clinical Bayesian network model in multidisciplinary decision making in head and neck oncology treatment. Int J Comput Assist Radiol Surg 2017; 12: 1959-1970
• 12 Cypko M, Wojdziak J, Stoehr M, Kirchner B, Preim B, Dietz A, Lemke HU, Oeltze-Jafra S. Visual verification of cancer staging for therapy decision support. Comput Graph Forum. 2017; 36: 109-120
• 13 Gaebel J, Cypko MA, Oeltze-Jafra S. Considering Information Up-to-Dateness to Increase the Accuracy of Therapy Decision Support Systems. Stud Health Technol Inform 2017; 243: 217-221
• 14 Müller J, Zebralla V, Wiegand S, Oeltze-Jafra S. Interactive Visualization of Functional Aspects in Head and Neck Cancer Aftercare. 7^th Visual Analytics in Healthcare (VAHC) Phoenix, AZ, USA: 2017
• 15 Neumann J, Rockstroh M, Franke S, Neumuth T. BPMNSIX – A BPMN 2.0 Surgical intervention extension. 7th Workshop on Modeling and Monitoring of Computer Assisted Interventions (M2CAI) – 19th International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI 2016), Athens, Greece, 2016.
• 16 Neumann J, Wiemuth M, Burgert O, Neumuth T. Application of activity semantics and BPMN 2.0 in the generation and modeling of generic surgical process models. International Conference on Computer Assisted Radiology and Surgery (CARS 2017), Barcelona, 2017
• 17 Wiemuth M, Junger D, Leitritz MA, Neumann J, Neumuth T, Burgert O. Application fields for the new Object Management Group (OMG) Standards Case Management Model and Notation (CMMN) and Decision Management Notation (DMN) in the perioperative field. Int J Comput Assist Radiol Surg. 2017; 12: 1439-1449
• 18 Uciteli A, Neumann J, Tahar K, Saleh K, Stucke S, Faulbrück-Röhr S, Kaeding A, Specht M, Schmidt T, Neumuth T, Besting A, Stegemann D, Portheine F, Herre H. Ontology-based specification, identification and analysis of perioperative risks. J Biomed Semantics 2017; 8: 36
• 19 Franke S, Rockstroh M, Schreiber E, Neumann J, Neumuth T. Towards the intelligent OR-Implementation of distributed, context-aware automation in an integrated surgical working environment. 19th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), M2CAI, Athens, GR, 2016
• 20 Franke S, Meixensberger J, Neumuth T. Multi-perspective workflow modeling for online surgical situation models. J of Biomedical Informatics 2015; 54: 158-166
• 21 Budde C, Lissat A, Brüning R. „iDoc“: Unterstützung, aber kein Ersatz. Dtsch Arztebl 2018; 115: 1062-1064
• 22 Kuhn S, Jungmann SM, Jungmann F. Künstliche Intelligenz für Ärzte und Patienten: „Googeln“ war gestern. Dtsch Arztebl 2018; 115: 1066-1069
• 23 Turchetti G, Palla I, Pierotti F, Cuschieri A. Economic evaluation of da Vinci-assisted robotic surgery: a systematic review. Surg Endosc. 2012; 26: 598-606
• 24 Tsuda S, Oleynikov D, Gould J, Azagury D, Sandler B, Hutter M, Ross S, Haas E, Brody F, Satava R. SAGES TAVAC safety and effectiveness analysis: da Vinci® Surgical System (Intuitive Surgical, Sunnyvale, CA). Surg Endosc. 2015; 29: 2873-2884
• 25 Birnbaum K, Zebralla V, Boehm A, Dietz A, Neumuth T. „Metric Learning for TNM-Classifications of Patients with Head and Neck Tumors“. CARS 2016 Proceedings. Heidelberg, 2016
• 26 Meier J, Bohn S, Glaser B, Birnbaum K, Boehm A, Neumuth T. „The Treatment Planning Unit: Concept and realization of an integrated multimedia decision support system for multidisciplinary team meetings“. In MedInfo 2015. Sao Paolo, 2015
• 27 Meier J, Dietz A, Boehm A, Neumuth T. “Predicting Treatment Process Steps from Events.”. J Biomedical Inform 2015; 53: 308-319 doi:10.1016/j.jbi.2014.12.003
• 28 Pitchford J, Mengersen K. A proposed validation framework for expert elicited Bayesian Networks. Expert Syst Appl 2013; 40: 1627
• 29 OR.NET-Forschungskonsortium (OR.NET Research Syndicate): OR.NET – Sichere dynamische Vernetzung in Operationssaal und Klinik [Online]. Available http://www.ornet.org [last accessed 28 August 2018]
• 30 Okamoto J, Masamune K, Iseki H, Muragaki Y. Development concepts of a Smart Cyber Operating Theater (SCOT) using ORiN technology. Biomed Tech (Berl) 2018; 63: 31-37
• 31 Maeso S, Reza M, Mayol JA. et al. Efficacy of the Da Vinci surgical system in abdominal surgery compared with that of laparoscopy: a systematic review and meta-analysis. Ann Surg 2010; 252: 254-262
• 32 Tokuda J, Fischer GS, Papademetris X. et al. OpenIGTLink: an open network protocol for image-guided therapy environment. Int J Med Robot 2009; 5: 423-434
• 33 MD PnP program website. Available http://www.mdpnp.org/ [last accessed 17 August 2018]
• 34 Arney D, Goldman JM, Bhargav-Spantzel A, Basu A, Taborn M, Pappas G, Robkin M. Simulation of medical device network performance and requirements for an integrated clinical environment. Biomed Intrum Technol 2012; 46: 308-315
• 35 Arney D, Plourde J, Goldman JM. OpenICE medical device interoperability platform overview and requirement analysis. Biomed Tech (Berl) 2018; 63: 39-47
• 36 Kasparick M, Schlichting S, Golatwoski F, Timmermann D. New IEEE 11073 Standards for interoperable, networked Point-of-Care Medical Devices. Conf Proc IEEE Eng Med Biol Soc 2015; 2015: 1721-1724
• 37 Kasparick M, Schmitz M, Andersen B, Rockstroh M, Franke S, Schlichting S, Golatowski F, Timmermann D. OR.NET: a service-oriented architecture for safe and dynamic medical device interoperability. Biomed Tech (Berl) 2018; 63: 11-30
• 38 op4.1 program website. Available http://www.op41.de/ [last accessed 18 August 2018]
• 39 Blaser J. Challenges of Digital Medicine. Praxis (Bern 1994) 2018; 107: 712-716
• 40 Sharma A, Harrington RA. et. al. Using digital health technology to better generate evidence and deliver evidence-based care. J Am Coll Cardiol 2018; 71: 2680-2690
• 41 Franz D, Hofer M, Pfeifle M, Pirlich M, Stamminger M, Wittenberg T. Wizard-based segmentation for cochlear implant planning. Berlin: Springer; 2014. ISBN: 3-642-54110-0: 258–263
• 42 Franz D, Katzky U et al. Haptisches Lernen für Cochlea Implantationen Konzept – HaptiVisT Projekt. CURAC 2016, Tagungsband, Bern, Uelvesbüll: Der Andere Verlag, 2016, ISBN: 978-3-86247-595-7: 21–26
• 43 Zebralla V, Pohle N, Singer S, Neumuth T, Dietz A, Stier-Jarmer M, Boehm A. Introduction of the screening tool oncofunction for functional follow-up of head and neck patients. Laryngorhinootologie 2016; 95: 118-124
• 44 Bohn S, Meier J, Neumuth T, Wichmann G, Strauss G, Dietz A, Boehm A. Design of an integrated IT platform to support the oncologic ENT treatment process and concept of a surgical planning unit. Int J Comput Assist Radiol Surg 2012; 7: 402-403
• 45 Boehm A, Dornheim J, Müller S, Strauß G, Wichmann G, Dietz A, Preim B. TTM Tumor Therapy Manager. CURAC 2010, Tagungsband, Düsseldorf. In: Burgert O, Kahrs L, Preim B, Schipper J. (eds) 17-20
• 46 Boehm A, Wichmann G, Neumuth T, Pankau T, Müller S, Preim B, Dietz A. Documentation and Visualisation with the TTM (Tumor Therapy Manager) for Panendoscopy: results of workflow analysis of the panendoscopy and the documentation process with or without the TTM. 2012, In: 8th International conference on head and neck cancer, Toronto, Canada
• 47 Cypko M, Hirsch D, Koch L, Stoehr M, Strauss G, Denecke K. Web-tool to support medical experts in probalistic modelling using large bayesian networks with an example of rhinosinusitis. Stud health technol inform 2015; 216: 259-263
• 48 Gaebel J, Cypko MA, Oeltze-Jafra S. Considering information up-to-dateness to increase the accuracy of therapy decision support systems. Stud health technol inform 2017; 243: 217-221
• 49 Haux R. Health Information Systems – from Present to Future?. Methods Inf Med. 2018; 57 S 01 e43-e45 doi:10.3414/ME18-03-0004 Epub 2018 Jul 17
• 50 Prasser F, Kohlbacher O, Mansmann U, Bauer B, Kuhn KA. Data Integration for Future Medicine (DIFUTURE). Methods Inf Med. 2018; 57 S 01 e57-e65 doi:10.3414/ME17-02-0022. Epub 2018 Jul 17
• 51 Winter A, Stäubert S. et al. Smart Medical Information Technology for Healthcare (SMITH). Methods Inf Med 2018; 57 S 01 e92-e105. doi:10.3414/ME18-02-0004 Epub 2018 Jul 17
• 52 Prokosch HU, Acker T. et al. MIRACUM: Medical Informatics in Research and Care in University Medicine. Methods Inf Med. 2018; 57 S 01 e82-e91 doi:10.3414/ME17-02-0025 Epub 2018 Jul 17
• 53 Somashekhar SP, Sepulveda MJ. et al. Watson for Oncology and breast cancer treatment recommendations: agreement with an expert multidisciplinary tumor board. Ann Oncol 2018; 29: 418-423
• 54 Kim YY, Oh SJ. et al. Gene expression assay and Watson for Oncology for optimization of treatment in ER-positive, HER2-negative breast cancer. PloS One 2018; 13: e0200100 doi:10.1371/journal.pone.0200100. eCollection 2018
• 55 Oncologists partner with Watson on genomics. Cancer Discov 2015; 5: 788. doi:10.1158/2159-8290.CD-NB2015-090. Epub 2015 Jun 16
• 56 Wright JD. Robotic-Assisted Surgery: Balancing Evidence and Implementation. JAMA 2017; 318: 1545-1547 doi:10.1001/jama.2017.13696
• 57 Rodt R, Becker B, Kacher A, Jolesz K. 3D visualisation of the middle ear and adjacent structures using reconstructed multi-slice CT datasets, correlating 3D images and virtual endoscopy tot he 2D cross-sectional images. Neuroradiol 2002; 44: 783-790
• 58 Gerber N, Bell B, Gavaghan K. et al. Surgical planning tool for robotically assisted hearing aid implantation. Int J Comput Assist Radiol Surg 2013; 7: 133-136
• 59 Noble JH, Dawant BM, Warren FM, Labadie RF. Automatic identification and 3D rendering of temporal bone anatomy. Otol Neurotol. 2009; 30: 436-442
• 60 Kisser U, Ertl-Wagner B, Hempel JM, Müller J. D’Anastasi Schrötzlmair Anderson-Kisser C, Laubender R, Stelter K, Braun C, Pomschar A. High-resolution computed tomography-based length assessments of the cochlea – an accuracy evaluation. Acta Oto-Laryngol 2014; 134: 1011-1015
• 61 Majdani O, Rau T, Baron S, Eilers H, Baier C, Heimann B, Ortmaier T, Bartling S, Lenarz T, Leinung M. A robot-guided minimally invasive approach for cochlear implant surgery: preliminary results of a temporal bone study. International Journal Proc Comp Assist Radiol Surg 2009; 4: 475-486
• 62 Binder K, Krauss S, Bruckmaier G, Marienhagen J. Visualizing the Bayesian 2-test case: The effect of tree diagrams on medical decision making. PLoS One. 2018; 13: e0195029. doi:10.1371/journal.pone.0195029. eCollection 2018;
• 63 Wu S, Law A, Whipple ME. A Bayesian Network Model of Head and Neck Squamous Cell Carinoma Incorporating Gene Expression Profiles. Stud Health Technol Inform 2017; 245: 634-638
• 64 Do BH, Langlotz C, Beaulieu CF. Bone Tumor Diagnosis Using a Naïve Bayesian Model of Demographic and Radiographic Features. J Digit Imaging 2017; 30: 640-647. doi:10.1007/s10278-017-0001-7
• 65 IBM Watson. Available https://www.ibm.com/watson/ [last accessed 25 August 2018]
• 66 Navify von Roche. Available https://www.navify.com/tumorboard/ [last accessed 26 August 2018]
• 67 Navify tumor board solution. Available http://www.selectscience.net/editorial-articles/first-us-implementation-of-tumor-board-softwarethat-improves-treatment-decision-process-for-cancer-patients/?artID = 46599 [last accessed 26 August 2018]
• 68 Saleh K, Stucke S, Uciteli A, Faulbrück-Röhr S, Neumann J, Tahar K, Ammon D, Schmidt T, Neumuth T, Besting A, Portheine F, Herre H, Kaeding A, Specht M. Using Fast Healthcare Interoperability Resources (FHIR) for the integration of risk minimization systems in hospitals. Proc. of the 16^th World Congress on Medical and Health Informatics, Hangzhou, China, 2017
• 69 Wachs JP, Frenkel B, Dori D. Operating room tool handling and miscommunication scenarios: an object-process methodology conceptual model. Artif Intell Med 2014; 62 Epub 2014 Nov 1
• 70 Haug PJ, Ferraro JP, Holmen J, Wu X, Mynam K, Ebert M, Dean N, Jones J. An ontology-driven, diagnostic modeling system. J Am Med Inform Assoc. 2013; 20 e1 e102-e110. doi:10.1136/amiajnl-2012-001376. Epub 2013 Mar 23
• 71 Andersen B, Kasparick M, Ulrich H, Franke S, Schlamelcher J, Rockstroh M, Ingenerf J. Connecting the clinical IT infrastructure to a service-oriented architecture of medical devices. Biomed Tech (Berl) 2018; 63: 57-68 doi:10.1515/bmt-2017-0021
• 72 Leonard S, Sinha A, Reiter A, Ishii M, Gallia GL, Taylor RH, Hager GD. Evaluation and stability analysis of video-based navigation system for functional endoscopic sinus surgery on in-vivo clinical data. IEEE Trans Med Imaging 2018; [Epub ahead of print]
• 73 Strauss G, Limpert E, Strauss M, Hofer M, Dittrich E, Nowatschin S, Lüth T. Evaluation of a daily used navigation system for FESS. Laryngorhinootologie 2009; 88: 776-781 doi:10.1055/s-0029-1237352 Epub 2009 Oct 8
• 74 Kisser U, Adderson-Kisser C, Coenen M, Stier-Jarmer M, Becker S, Sabariego C, Harréus U. The development of an ICF-based clinical guideline and screening tool for the standardized assessment and evaluation of functioning after head and neck cancer treatment. Eur Arch Otorhinolaryngol 2017; 274: 1035-1043. doi:10.1007/s00405-016-4317-6. Epub 2016 Sep 30
• 75 Molnár-Gábor F. Germany: a fair balance between scientific freedom and data subjects´ rights?. Hum Genet 2018; [Epub ahead of print]
• 76 Voßhoff A, Raum B, Ernestus W. Telematics in the public health sector. Where is the protection of health data?. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz 2015; 58: 1094-1100. doi:10.1007/s00103-015-2222-2226
• 77 Feußner H, Ostler D, Kohn N, Vogel T, Wilhelm D, Koller S, Kranzfelder M. Comprehensive system integration and networking in operating rooms. Chirurg. 2016; 87: 1002-1007
• 78 Müller-Stich BP, Büchler MW. Operating rooms of the future. Chirurg 2016; 87: 999-1001
• 79 Microfocus website. Available https://www.microfocus.com/de-de/success/stories/md-pnp/ [last accessed 26 August 2018]
• 80 ICCAS website. Available https://www.iccas.de/ [last accessed 30 August 2018]