Decision support systems for clinical radiological practice -- towards the next generation.
The huge amount of information that needs to be assimilated in order to keep pace with the continued advances in modern medical practice can form an insurmountable obstacle to the individual clinician. Within radiology, the recent development of quantitative imaging techniques, such as perfusion imaging, and the development of imaging-based biomarkers in modern therapeutic assessment has highlighted the need for computer systems to provide the radiological community with support for academic as well as clinical/translational applications. This article provides an overview of the underlying design and functionality of radiological decision support systems with examples tracing the development and evolution of such systems over the past 40 years. More importantly, we discuss the specific design, performance and usage characteristics that previous systems have highlighted as being necessary for clinical uptake and routine use. Additionally, we have identified particular failings in our current methodologies for data dissemination within the medical domain that must be overcome if the next generation of decision support systems is to be implemented successfully.
Stivaros
S M
SM
Department of Imaging Science, University of Manchester, Wolfson Molecular Imaging Centre, Manchester, UK. stavros.stivaros@manchester.ac.uk
Gledson
A
A
Nenadic
G
G
Zeng
X-J
XJ
Keane
J
J
Jackson
A
A
D020000:Decision Support Systems, Clinical / Q000592:standards / Q000639:trends*; D005544:Forecasting; D006801:Humans; D011871:Radiology / Q000639:trends*; D011873:Radiology Information Systems; D012984:Software; D019112:Teleradiology / Q000639:trends*