ESUR/ESUI position paper: developing artificial intelligence for precision diagnosis of prostate cancer using magnetic resonance imaging

Tobias Penzkofer*, Anwar R Padhani, Baris Turkbey, Masoom A. Haider, Henkjan Huisman, Jochen Walz, Georg Salomon, Ivo G Schoots, Jonathan Richenberg, Geert Villeirs, Valeria Panebianco, Olivier Rouviere, Vibeke Berg Logager, Jelle Barentsz

*Corresponding author af dette arbejde

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

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Abstract

Artificial intelligence developments are essential to the successful deployment of community-wide, MRI-driven prostate cancer diagnosis. AI systems should ensure that the main benefits of biopsy avoidance are delivered while maintaining consistent high specificities, at a range of disease prevalences. Since all current artificial intelligence / computer-aided detection systems for prostate cancer detection are experimental, multiple developmental efforts are still needed to bring the vision to fruition. Initial work needs to focus on developing systems as diagnostic supporting aids so their results can be integrated into the radiologists' workflow including gland and target outlining tasks for fusion biopsies. Developing AI systems as clinical decision-making tools will require greater efforts. The latter encompass larger multicentric, multivendor datasets where the different needs of patients stratified by diagnostic settings, disease prevalence, patient preference, and clinical setting are considered. AI-based, robust, standard operating procedures will increase the confidence of patients and payers, thus enabling the wider adoption of the MRI-directed approach for prostate cancer diagnosis.

OriginalsprogEngelsk
TidsskriftEuropean Radiology
Vol/bind31
Udgave nummer12
Sider (fra-til)9567-9578
Antal sider12
ISSN0938-7994
DOI
StatusUdgivet - 2021

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