The future of PACS.
How will the future of picture archiving and communication systems (PACS) look, and how will this future affect the practice of radiology? We are currently experiencing disruptive innovations that will force an architectural redesign, making the majority of today's commercial PACS obsolete as the field matures and expands to include imaging throughout the medical enterprise. The common architecture used for PACS cannot handle the massive amounts of data being generated by even current versions of computed tomography and magnetic resonance scanners. If a PACS cannot handle today's technology, what will happen as the field expands to encompass pathology imaging, cone-beam reconstruction, and multispectral imaging? The ability of these new technologies to enhance research and clinical care will be impaired if PACS architectures are not prepared to support them. In attempting a structured approach to predictions about the future of PACS, we offer projections about the technologies underlying PACS as well as the evolution of standards development and the changing needs of a broad range of medical imaging. Simplified models of the history of the PACS industry are mined for the assumptions they provide about future innovations and trends. The physicist frequently participates in or directs technical assessments for medical equipment, and many physicists have extended these activities to include imaging informatics. It is hoped that by applying these speculative but experienced-based predictions, the interested medical physicist will be better able to take the lead in setting information technology strategies that will help facilities not only prepare for the future but continue to enjoy the benefits of technological innovations without disruptive, expensive, and unexpected changes in architecture. A good PACS strategy can help accelerate the time required for innovations to go from the drawing board to clinical implementation.
Nagy
Paul G
PG
Department of Diagnostic Radiology, University of Maryland School of Medicine, 22 South Greene Street, Baltimore, Maryland 21201, USA.
D003952:Diagnostic Imaging; D005544:Forecasting; D006801:Humans; D011871:Radiology; D011873:Radiology Information Systems; D014057:Tomography, X-Ray Computed