Abstract
Purpose
Interoperability of medical devices based on standards starts to establish in the operating room (OR). Devices share their data and control functionalities. Yet, the OR technology rarely implements cooperative, intelligent behavior, especially in terms of active cooperation with the OR team. Technical context-awareness will be an essential feature of the next generation of medical devices to address the increasing demands to clinicians in information seeking, decision making, and human–machine interaction in complex surgical working environments.
Methods
The paper describes the technical validation of an intelligent surgical working environment for endoscopic ear–nose–throat surgery. We briefly summarize the design of our framework for context-aware system’s behavior in integrated OR and present example realizations of novel assistance functionalities. In a study on patient phantoms, twenty-four procedures were implemented in the proposed intelligent surgical working environment based on recordings of real interventions. Subsequently, the whole processing pipeline for context-awareness from workflow recognition to the final system’s behavior is analyzed.
Results
Rule-based behavior that considers multiple perspectives on the procedure can partially compensate recognition errors. A considerable robustness could be achieved with a reasonable quality of the recognition. Overall, reliable reactive as well as proactive behavior of the surgical working environment can be implemented in the proposed environment.
Conclusions
The obtained validation results indicate the suitability of the overall approach. The setup is a reliable starting point for a subsequent evaluation of the proposed context-aware assistance. The major challenge for future work will be to implement the complex approach in a cross-vendor setting.
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References
Kasparick M, Schlichting S, Golatowski F, Timmermann D (2015) New IEEE 11073 standards for interoperable, networked point-of-care medical devices. In: Proceedings of the 37th IEEE engineering in medicine and biology society (EMBC). IEEE, pp 1721–1724
Andersen B, Ulrich H, Rehmann D, Kock A-K, Wrage J-H, Ingenerf J (2015) Reporting device observations for semantic interoperability of surgical devices and clinical information systems. In: Proceedings of the 37th IEEE engineering in medicine and biology society (EMBC). IEEE, pp 1725–1728
Rockstroh M, Franke S, Hofer M, Will A, Kasparick M, Andersen B, Neumuth T (2017) ORNET: multi-perspective qualitative evaluation of an integrated operating room based on IEEE 11073 SDC. Int J Comput Assist Radiol Surg. https://doi.org/10.1007/s11548-017-1589-2
Katić D, Julliard C, Wekerle A-L, Kenngott H, Müller-Stich BP, Dillmann R, Speidel S, Jannin P, Gibaud B (2015) LapOntoSPM: an ontology for laparoscopic surgeries and its application to surgical phase recognition. Int J Comput Assist Radiol Surg. https://doi.org/10.1007/s11548-015-1222-1
Blum T, Padoy N, Feußner H, Navab N (2008) Modeling and online recognition of surgical phases using hidden Markov models. In: Metaxas D, Axel L, Fichtinger G, Székely G (eds) Medical image computing and computer-assisted intervention-MICCAI 2008. Springer, Berlin, pp 627–635
Lalys F, Riffaud L, Bouget D, Jannin P (2011) An application-dependent framework for the recognition of high-level surgical tasks in the OR. In: Fichtinger G, Martel A, Peters T (eds) Medical image computing and computer-assisted intervention-MICCAI 2011. Springer, Berlin, pp 331–338
Speidel S, Zentek T, Sudra G, Gehrig T, Müller-Stich BP, Gutt C, Dillmann R (2009) Recognition of surgical skills using hidden Markov models. In: Proceedings volume 7261, medical imaging 2009: visualization, image-guided procedures, and modeling, pp 726125-8–726125-8
Kranzfelder M, Schneider A, Fiolka A, Koller S, Reiser S, Vogel T, Wilhelm D, Feussner H (2014) Reliability of sensor-based real-time workflow recognition in laparoscopic cholecystectomy. Int J Comput Assist Radiol Surg 9:941–948. https://doi.org/10.1007/s11548-014-0986-z
Lalys F, Riffaud L, Bouget D, Jannin P (2012) A Framework for the recognition of high-level surgical tasks from video images for cataract surgeries. IEEE Trans Biomed Eng 59:966–976. https://doi.org/10.1109/TBME.2011.2181168
Bouarfa L, Akman O, Schneider A, Jonker PP, Dankelman J (2012) In-vivo real-time tracking of surgical instruments in endoscopic video. Minim Invasive Therapy Allied Technol 21:129–134. https://doi.org/10.3109/13645706.2011.580764
Kranzfelder M, Schneider A, Fiolka A, Schwan E, Gillen S, Wilhelm D, Schirren R, Reiser S, Jensen B, Feussner H (2013) Real-time instrument detection in minimally invasive surgery using radiofrequency identification technology. J Surg Res 185:704–710. https://doi.org/10.1016/j.jss.2013.06.022
Glaser B, Dänzer S, Neumuth T (2015) Intra-operative surgical instrument usage detection on a multi-sensor table. Int J Comput Assist Radiol Surg 10:351–362. https://doi.org/10.1007/s11548-014-1066-0
Neumuth T (2017) Surgical process modeling. Innov Surg Sci. https://doi.org/10.1515/iss-2017-0005
Schmidt A, Beigl M, Gellersen H-W (1999) There is more to context than location. Comput Graph 23:893–901. https://doi.org/10.1016/S0097-8493(99)00120-X
Franke S, Meixensberger J, Neumuth T (2015) Multi-perspective workflow modeling for online surgical situation models. J Biomed Inform 54:158–166
Franke S, Neumuth T (2015) Adaptive surgical process models for prediction of surgical work steps from surgical low-level activities. In: Workshop on modeling and monitoring of computer-aided interventions (M2CAI). Medical Image Computing and Computer Assisted Intervention, Munich, Germany
Franke S, Meixensberger J, Neumuth T (2013) Intervention time prediction from surgical low-level tasks. J Biomed Inform 46:152–159. https://doi.org/10.1016/j.jbi.2012.10.002
Franke S, Neumuth T (2015) Towards structuring contextual information for workflow-driven surgical assistance functionalities. In: 49th annual conference of the German society for biomedical engineering (BMT 2015), Lübeck, Germany
Franke S, Neumuth T (2015) Rule-based medical device adaptation for the digital operating room. In: Proceedings of 37th annual international conference of the IEEE engineering in medicine and biology society. IEEE, Milano, pp 1733–1736
Franke S, Rockstroh M, Schreiber E, Neumann J, Neumuth T (2016) Context-aware medical assistance systems in integrated surgical environments. In: 28th conference of the international society for medical innovation and technology (SMIT), Delft, Netherlands, p 98
Meyer MA, Levine WC, Egan MT, Cohen BJ, Spitz G, Garcia P, Chueh H, Sandberg WS (2007) A computerized perioperative data integration and display system. Int J Comput Assist Radiol Surg 2:191–202. https://doi.org/10.1007/s11548-007-0126-0
Pickering BW, Herasevich V, Ahmed A, Gajic O (2010) Novel representation of clinical information in the ICU: developing user interfaces which reduce information overload. Appl Clin Inform 1:116–131. https://doi.org/10.4338/ACI-2009-12-CR-0027
Kranzfelder M, Staub C, Fiolka A, Schneider A, Gillen S, Wilhelm D, Friess H, Knoll A, Feussner H (2013) Toward increased autonomy in the surgical OR: needs, requests, and expectations. Surg Endosc 27:1681–1688. https://doi.org/10.1007/s00464-012-2656-y
Rockstroh M, Franke S, Neumuth T (2013) A workflow-driven surgical information source management. In: Lemke HU (ed) The international journal for computer assisted radiology and surgery. Springer, Heidelberg, pp 189–191
Neumuth T, Jannin P, Strauss G, Meixensberger J, Burgert O (2009) Validation of knowledge acquisition for surgical process models. J Am Med Inf Assoc 16(1):72–80
Twinanda A, Shehata S, Mutter D, Marescaux J, de Mathelin M, Padoy N (2017) EndoNet: a deep architecture for recognition tasks on laparoscopic videos. IEEE Trans Med Imaging 36(1):86–97
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Funding was provided by Bundesministerium für Bildung und Forschung (DE) (Grant No. 16KT1236).
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Franke, S., Rockstroh, M., Hofer, M. et al. The intelligent OR: design and validation of a context-aware surgical working environment. Int J CARS 13, 1301–1308 (2018). https://doi.org/10.1007/s11548-018-1791-x
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DOI: https://doi.org/10.1007/s11548-018-1791-x