A cognitive engineering framework for the specification of information requirements in medical imaging: application in image-guided neurosurgery

PurposeThis study proposes a framework coming from cognitive engineering, which makes it possible to define what information content has to be displayed or emphasised from medical imaging, for assisting clinicians according to their level of expertise in the domain.MethodWe designed a rating scale to assess visualisation systems in image-guided neurosurgery with respect to the depiction of the neurosurgical work domain. This rating scale was based on a neurosurgical work domain analysis. This scale has been used to evaluate visualisation modes among neurosurgeons, residents and engineers. We asked five neurosurgeons, ten medical residents and ten engineers to rate two visualisation modes from the same data (2D MR image vs. 3D computerised image). With this method, the amount of abstract and concrete work domain information displayed by each visualisation mode can be measured.ResultsA global difference in quantities of perceived information between both images was observed. Surgeons and medical residents perceived significantly more information than engineers for both images. Unlike surgeons, however, the amount of information perceived by residents and engineers significantly decreased as information abstraction increased.ConclusionsWe demonstrated the possibility of measuring the amount of work domain information displayed by different visualisation modes of medical imaging according to different user profiles. Engineers in charge of the design of medical image-guided surgical systems did not perceive the same set of information as surgeons or even medical residents. This framework can constitute a user-oriented approach to evaluate the amount of perceived information from image-guided surgical systems and support their design from a cognitive engineering point of view.

[1]  M. Apuzzo Reinventing neurosurgery: entering the third millennium. , 2000, Neurosurgery.

[2]  Jens Rasmussen,et al.  Information Processing and Human-Machine Interaction: An Approach to Cognitive Engineering , 1986 .

[3]  Arthur J. Helmicki,et al.  The Application of the Ecological Interface Design Approach to Neonatal Intensive Care Medicine , 1998 .

[4]  Anne Miller,et al.  A work domain analysis framework for modelling intensive care unit patients , 2004, Cognition, Technology & Work.

[5]  Michael W. Haas,et al.  Surgical strike: interface design across task domains , 1998, Proceedings Fourth Annual Symposium on Human Interaction with Complex Systems.

[6]  K. J. Vicente,et al.  Cognitive Work Analysis: Toward Safe, Productive, and Healthy Computer-Based Work , 1999 .

[7]  Marcus Watson,et al.  Ecological Interface Design for Anaesthesia Monitoring , 2000, Australas. J. Inf. Syst..

[8]  G. Hounsfield Computed Medical Imaging , 1980, Science.

[9]  Catherine M. Burns,et al.  Modeling a medical environment: an ontology for integrated medical informatics design , 2001, Int. J. Medical Informatics.

[10]  Bernhard Preim,et al.  Combining Silhouettes, Surface, and Volume Rendering for Surgery Education and Planning , 2005, EuroVis.

[11]  Thierry Morineau,et al.  Turing machine as an ecological model for task analysis , 2009 .

[12]  Catherine M. Burns,et al.  Ecological Interface Design , 2004 .

[13]  Pierre Jannin,et al.  Decision Making During Preoperative Surgical Planning , 2009, Hum. Factors.

[14]  Kim J. Vicente,et al.  Ecological interface design: theoretical foundations , 1992, IEEE Trans. Syst. Man Cybern..

[15]  P. Jannin,et al.  Model of Surgical Procedures for Multimodal Image-Guided Neurosurgery , 2003, Computer aided surgery : official journal of the International Society for Computer Aided Surgery.

[16]  Guang-Zhong Yang,et al.  Intra-Operative Visualizations: Perceptual Fidelity and Human Factors , 2008, Journal of Display Technology.

[17]  Greg A. Jamieson,et al.  Bridging the Gap Between Cognitive Work Analysis and Ecological Interface Design , 2003 .

[18]  Thomas Jeffery Wieman,et al.  A systems approach to error prevention in medicine , 2004, Journal of surgical oncology.

[19]  Heinz-Otto Peitgen,et al.  Risk maps for navigation in liver surgery , 2010, Medical Imaging.

[20]  M. Sarter,et al.  The cognitive neuroscience of sustained attention: where top-down meets bottom-up , 2001, Brain Research Reviews.

[21]  Yu Qian,et al.  The State of the Art of Medical Imaging Technology: from Creation to Archive and Back , 2011, The open medical informatics journal.

[22]  Kim J. Vicente,et al.  Ecological Interface Design: Progress and Challenges , 2002, Hum. Factors.

[23]  Kathryn Momtahan,et al.  Applications of ecological interface design in supporting the nursing process. , 2004, Journal of healthcare information management : JHIM.