Browsing by Author "Jackson, V. P."

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    Integrated diagnostics: proceedings from the 9th biennial symposium of the International Society for Strategic Studies in Radiology
    (Springer, 2012) Krestin, G. P.; Grenier, P. A.; Hricak, H.; Jackson, V. P.; Khong, P. L.; Miller, J. C.; Muellner, A.; Schwaiger, M.; Thrall, J. H.; Radiology and Imaging Sciences, School of Medicine
    The International Society for Strategic Studies in Radiology held its 9th biennial meeting in August 2011. The focus of the programme was integrated diagnostics and massive computing. Participants discussed the opportunities, challenges, and consequences for the discipline of radiology that will likely arise from the integration of diagnostic technologies. Diagnostic technologies are increasing in scope, including advanced imaging techniques, new molecular imaging agents, and sophisticated point-of-use devices. Advanced information technology (IT), which is increasingly influencing the practice of medicine, will aid clinical communication and the development of "population images" that represent the phenotype of particular diseases, which will aid the development of diagnostic algorithms. Integrated diagnostics offer increased operational efficiency and benefits to patients through quicker and more accurate diagnoses. As physicians with the most expertise in IT, radiologists are well placed to take the lead in introducing IT solutions and cloud computing to promote integrated diagnostics. To achieve this, radiologists must adapt to include quantitative data on biomarkers in their reports. Radiologists must also increase their role as participating physicians, collaborating with other medical specialties, not only to avoid being sidelined by other specialties but also to better prepare as leaders in the selection and sequence of diagnostic procedures. Key Points • New diagnostic technologies are yielding unprecedented amounts of diagnostic information.• Advanced IT/cloud computing will aid integration and analysis of diagnostic data.• Better diagnostic algorithms will lead to faster diagnosis and more rapid treatment.