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Preface
Author(s) -
Yue Xu,
Gabriella Pasi
Publication year - 2015
Publication title -
web intelligence
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.163
H-Index - 23
eISSN - 2405-6464
pISSN - 2405-6456
DOI - 10.3233/web-150305
Subject(s) - computer science
The reason we are editing this book 10 years after one of us edited a similar publication is that the problem remains regarding how to integrate into optimized diagnostic protocols the vast amount of information that cardiac imaging can yield. At this time, even more so than 10 years ago, technological advances in cardiac imaging enable high-speed and high-resolution imaging of a wide spectrum of phenotypic manifestations related both to anatomy and function of the heart. However, in general, such imaging techniques involve high operational costs in terms of instrumentation/imaging agents and/or human resources/ expertise. Furthermore, the process of integrating the wealth of information obtained by different 3D techniques is still far from allowing direct translation into clinical cardiology. Across countries, educational inequalities probably account for most of the difficulty in achieving meaningful merging of different approaches to cardiac imaging into diagnostic algorithms optimized in terms of clinical efficacy and cost effectiveness. In this regard, even if national rules often make imaging specialists and cardiologists equal in terms of years of training, the educational paths are frequently completely different in terms of clinical experience and crosstalk. The solution to this problem is rather complex, and we believe that important steps forward will occur in this process thanks to growing interaction among the involved scientific medical societies. Great efforts in this direction have already been initiated—for instance, by implementing uniform processes of quality control in cardiology, radiology, and nuclear medicine and by updating guidelines. The unfavorable financial situation currently experienced worldwide will inevitably lead to strict control of the cost-benefit ratio of each technique and to definition of the more accurate, reliable, and reproducible prognostic parameters defining patient outcomes. Wise spending is already becoming a basic component of cardiac imaging, along with growing concerns regarding patient exposure to radiation. Thus, despite towering technological progress and its growing everyday clinical use, the ‘‘circus’’ of cardiac imaging goes on setting new, increasingly advanced, goals and endpoints to enhance diagnostic accuracy and optimize merging of the imaging information spectrum. In order to reach these goals, we must expand our knowledge far beyond

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