Abstract
Purpose
In the last few years artificial intelligence (AI) has increasingly become a topic
of interest, especially in diagnostic imaging. There are two main expected potential
benefits: workflow effectiveness and diagnostic support systems, particularly as far
as quality assurance is concerned.
Methods
To meet these objectives, it is necessary to define what artificial intelligence in
medicine means and to discuss which detailed steps should be fulfilled, e. g., for
MSK imaging in the daily routine. In addition, this article provides an overview of
what is necessary for an efficient IT-based workflow including the clinical question,
the choice of modalities and investigation protocols, structured reports, and clinical
classification. This is particularly interesting for potential providers, who are
keen to apply new soft skills to support imaging diagnostic processes.
Results
The use of AI-supported diagnostic imaging could result in a paradigm shift from a
modality-oriented to a clinical problem-oriented workflow. In order to streamline
trauma, degeneration, inflammation, and oncology-MSK diagnostic imaging, the potential
benefits of AI-based workflow optimization should be taken advantage of. The following
article describes a five-point plan combining patient expectations and specialized
radiological standards with respect to investigation protocols and reports. Moreover,
this AI-based strategy could help to improve interdisciplinary networking, e. g.,
boards etc., and facilitate the required leap in quality towards “personalized precision
medicine” for the patient. According to the global discussion, there is a need to
point out that it is not currently realistic to replace doctors with AI.
Key Points
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AI as support-system has a paramount clinical impact
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AI in the daily routine could be for work-flow-support (processing) – a physician-replacement
is un-realistic yet
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Standardization of work-flow by AI could be an important contribution of quality assurance
Citation Format
Keywords
artificial intelligence - musculoskeletal imaging - IT-based processing
