Regge gave an interesting presentation on getting from bench to desktop with image processing illustrated with his own example on CT colonography. His take home points are that an Imaging lab should be embedded in a cliinical unit, should be cautious with industrial partners, and must start from a clinical problem and build the software on that problem.
Glinkowski presented about what information the clinician really needs. The questions a clinician asks are: what? Where? How? Decision making - what to do? In answering these question the clinicians are heavily depending on imaging an Radiology is essential in answering many of the questions a clinician may have in a muti disciplinary collaborative effort to get the optimal outcome for the patient.
Where we stand on costs and reimbursements of image processing was the topic of a presentation by Turchetti. He started to show that the total healthcare expenditure in Europe and the US is increasing. First cause of this increase is innovation because of growing indications and applications of the innovations, growing area of treatable conditions, increasing use of technologies for the same conditions with less discomfort, broadening definition of diseases and life extending effects. Note that all issues are positive: we live longer and better... Most countries try to tackle these issues with increasing efficiency, redesign of the supply side (closing hospitals, reducing beds, etc), regulation of price and/or quantity of services, and the reduction of the services granted for free and introduction of higher level of co-payment.
The reimbursement mechanism could stimulate efficiency and reduce the opportunistic behavior of hospitals. But if not used properly it could impede the transfer of innovation to the clinical practice.
Studies to calculate real cost of procedures should be promoted and reimbursement should be defined accordingly. Define for which indications the image processing is approriate from a clinical point of view and from a cost effectiveness point of view. Cost and reimbursement should be properly aligned.
In the next presentation Fatehi discussed the composition of the image processing research team including the clinician, radiologist, radiographer, computer scientist, biomedical engineers, and ... He stated that image processing reeserach is done to answer a clinical need, to refine engineering methods and to support management. As stated already many times during the conference he also stresses that imaging research should be a multi-disciplinary effort. The cooperation should include the following topics.
Clinical to Technical:
- Defining the clinical question
- Defining the components of the applications
- Providing the most relevant datatsets
- Defining the workflow before and after the image processing
- Validating the test protocol
- Improving the user interface
Technical to clinical:
- Specify potential methods to achieve the clinical goal
- Specify technical limitations of implementing the application development
- Provide a comparative list of already tested methods in the literature
- Translating the clinical workflow into an engineering language with technical block diagrams
- Keeping engineering standards in the final product/application
- Taking care of the integration issues
- Taking care of the licensing issues
- Providing information about open source to avoid high costs.
Finally, Schilling presented on bridging the radiology/surgery gap. He advocated the introduction of new visualization protocols with higer dimension imaging with direct interaction with the data using easy to use devices. They want to have intuitive 2D and true 3D. Clinical efficacy and worflow can both be optimal using true 3D.
