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CC BY-NC-ND 4.0 · Laryngorhinootologie 2019; 98(S 01): S5-S31
DOI: 10.1055/a-0751-3537
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Eigentümer und Copyright ©Georg Thieme Verlag KG 2019

The Intelligent ENT Operating Room of the Future[*]

Article in several languages: deutsch | English
Markus Pirlich
1   Klinik und Poliklinik für Hals-, Nasen-, Ohrenheilkunde, Universitätsklinikum Leipzig AöR
,
Matthäus Stöhr
1   Klinik und Poliklinik für Hals-, Nasen-, Ohrenheilkunde, Universitätsklinikum Leipzig AöR
,
Thomas Neumuth
2   Innovation Center Computer Assisted Surgery, ICCAS, Universität Leipzig
,
Andreas Dietz
1   Klinik und Poliklinik für Hals-, Nasen-, Ohrenheilkunde, Universitätsklinikum Leipzig AöR
2   Innovation Center Computer Assisted Surgery, ICCAS, Universität Leipzig
› Author Affiliations
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Publication History

Publication Date:
03 April 2019 (online)

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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; DOI: 10.1007/s11548-018-1791-x.. [Epub ahead of print]
    CrossrefPubMedGoogle Scholar
  • 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
    PubMedGoogle Scholar
  • 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
    CrossrefPubMedGoogle Scholar
  • 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
    PubMedGoogle Scholar
  • 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
    CrossrefPubMedGoogle Scholar
  • 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
    Article in Thieme ConnectPubMedGoogle Scholar
  • 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
    CrossrefPubMedGoogle Scholar
  • 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
    PubMed
  • 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]
    PubMed
  • 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
    PubMedGoogle Scholar
  • 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
    CrossrefPubMedGoogle Scholar
  • 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
    CrossrefPubMedGoogle Scholar
  • 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
    PubMedGoogle Scholar
  • 14 Müller J, Zebralla V, Wiegand S, Oeltze-Jafra S. Interactive Visualization of Functional Aspects in Head and Neck Cancer Aftercare. 7th Visual Analytics in Healthcare (VAHC) Phoenix, AZ, USA: 2017
    Google Scholar
  • 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.
    PubMed
  • 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
    PubMed
  • 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
    CrossrefPubMedGoogle Scholar
  • 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
    CrossrefPubMedGoogle Scholar
  • 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
    PubMed
  • 20 Franke S, Meixensberger J, Neumuth T. Multi-perspective workflow modeling for online surgical situation models. J of Biomedical Informatics 2015; 54: 158-166
    CrossrefPubMedGoogle Scholar
  • 21 Budde C, Lissat A, Brüning R. „iDoc“: Unterstützung, aber kein Ersatz. Dtsch Arztebl 2018; 115: 1062-1064
    PubMedGoogle Scholar
  • 22 Kuhn S, Jungmann SM, Jungmann F. Künstliche Intelligenz für Ärzte und Patienten: „Googeln“ war gestern. Dtsch Arztebl 2018; 115: 1066-1069
    PubMedGoogle Scholar
  • 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
    CrossrefPubMedGoogle Scholar
  • 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
    CrossrefPubMedGoogle Scholar
  • 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
    PubMed
  • 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
    PubMed
  • 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
    PubMedGoogle Scholar
  • 28 Pitchford J, Mengersen K. A proposed validation framework for expert elicited Bayesian Networks. Expert Syst Appl 2013; 40: 1627
    PubMedGoogle Scholar
  • 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]
    PubMed
  • 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
    CrossrefPubMedGoogle Scholar
  • 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
    CrossrefPubMedGoogle Scholar
  • 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
    CrossrefPubMedGoogle Scholar
  • 33 MD PnP program website. Available http://www.mdpnp.org/ [last accessed 17 August 2018]
    PubMed
  • 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
    CrossrefPubMedGoogle Scholar
  • 35 Arney D, Plourde J, Goldman JM. OpenICE medical device interoperability platform overview and requirement analysis. Biomed Tech (Berl) 2018; 63: 39-47
    CrossrefPubMedGoogle Scholar
  • 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
    PubMedGoogle Scholar
  • 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
    CrossrefPubMedGoogle Scholar
  • 38 op4.1 program website. Available http://www.op41.de/ [last accessed 18 August 2018]
    PubMed
  • 39 Blaser J. Challenges of Digital Medicine. Praxis (Bern 1994) 2018; 107: 712-716
    CrossrefPubMedGoogle Scholar
  • 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
    CrossrefPubMedGoogle Scholar
  • 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 DOI: 10.1007/978-3-642-54111-7_49
    CrossrefGoogle Scholar
  • 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
    PubMed
  • 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
    Article in Thieme ConnectPubMedGoogle Scholar
  • 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
    PubMedGoogle Scholar
  • 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
    Google Scholar
  • 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
    PubMed
  • 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
    PubMedGoogle Scholar
  • 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
    PubMedGoogle Scholar
  • 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
    Article in Thieme ConnectPubMedGoogle Scholar
  • 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
    Article in Thieme ConnectPubMedGoogle Scholar
  • 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
    Article in Thieme ConnectPubMedGoogle Scholar
  • 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
    Article in Thieme ConnectPubMedGoogle Scholar
  • 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
    CrossrefPubMedGoogle Scholar
  • 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
    CrossrefPubMedGoogle Scholar
  • 55 Oncologists partner with Watson on genomics. Cancer Discov 2015; 5: 788. doi:10.1158/2159-8290.CD-NB2015-090. Epub 2015 Jun 16
    PubMedGoogle Scholar
  • 56 Wright JD. Robotic-Assisted Surgery: Balancing Evidence and Implementation. JAMA 2017; 318: 1545-1547 doi:10.1001/jama.2017.13696
    CrossrefPubMedGoogle Scholar
  • 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
    CrossrefPubMedGoogle Scholar
  • 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
    PubMedGoogle Scholar
  • 59 Noble JH, Dawant BM, Warren FM, Labadie RF. Automatic identification and 3D rendering of temporal bone anatomy. Otol Neurotol. 2009; 30: 436-442
    CrossrefPubMedGoogle Scholar
  • 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
    CrossrefPubMedGoogle Scholar
  • 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
    PubMedGoogle Scholar
  • 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;
    CrossrefPubMedGoogle Scholar
  • 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
    PubMedGoogle Scholar
  • 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
    CrossrefPubMedGoogle Scholar
  • 65 IBM Watson. Available https://www.ibm.com/watson/ [last accessed 25 August 2018]
    PubMed
  • 66 Navify von Roche. Available https://www.navify.com/tumorboard/ [last accessed 26 August 2018]
    PubMed
  • 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]
    PubMed
  • 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 16th World Congress on Medical and Health Informatics, Hangzhou, China, 2017
    PubMed
  • 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 DOI: 10.1016/j.artmed.2014.10.006.. Epub 2014 Nov 1
    CrossrefPubMedGoogle Scholar
  • 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
    CrossrefPubMedGoogle Scholar
  • 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
    CrossrefPubMedGoogle Scholar
  • 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; DOI: 10.1109/TMI.2018.2833868.. [Epub ahead of print]
    CrossrefPubMedGoogle Scholar
  • 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
    Article in Thieme ConnectPubMedGoogle Scholar
  • 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
    CrossrefPubMedGoogle Scholar
  • 75 Molnár-Gábor F. Germany: a fair balance between scientific freedom and data subjects´ rights?. Hum Genet 2018; DOI: 10.1007/s00439-018-1912-1. [Epub ahead of print]
    CrossrefPubMedGoogle Scholar
  • 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
    CrossrefPubMedGoogle Scholar
  • 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
    CrossrefPubMedGoogle Scholar
  • 78 Müller-Stich BP, Büchler MW. Operating rooms of the future. Chirurg 2016; 87: 999-1001
    CrossrefPubMedGoogle Scholar
  • 79 Microfocus website. Available https://www.microfocus.com/de-de/success/stories/md-pnp/ [last accessed 26 August 2018]
    PubMed
  • 80 ICCAS website. Available https://www.iccas.de/ [last accessed 30 August 2018]
    PubMed