Artificial intelligence (AI) in diagnostic imaging.
Braunschweig R, Kildal D, Janka RM (2024)
Publication Type: Journal article
Publication year: 2024
Journal
Book Volume: 196
Pages Range: 664-670
Journal Issue: 7
DOI: 10.1055/a-2208-6487
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: · AI as support-system has a paramount clinical impact. · AI in the daily routine could be for work-flow-support (processing) - a physician-replacement is un-realistic yet. · Standardization of work-flow by AI could be an important contribution of quality assurance. CITATION FORMAT: · Braunschweig R, Kildal D, Janka R. Artificial intelligence (AI) in diagnostic imaging . Fortschr Röntgenstr 2024; DOI: 10.1055/a-2208-6487.
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Switzerland (CH)How to cite
APA:
Braunschweig, R., Kildal, D., & Janka, R.M. (2024). Artificial intelligence (AI) in diagnostic imaging. Röfo: Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren, 196(7), 664-670. https://doi.org/10.1055/a-2208-6487
MLA:
Braunschweig, Rainer, Daniela Kildal, and Rolf Matthias Janka. "Artificial intelligence (AI) in diagnostic imaging." Röfo: Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren 196.7 (2024): 664-670.
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