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

PURPOSE: This 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.
METHOD: We 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.
RESULTS: A 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.
CONCLUSIONS: We 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.