Validated imaging biomarkers as decision-making tools in clinical trials and routine practice: current status and recommendations from the EIBALL* subcommittee of the European Society of Radiology (ESR)

Nandita M. deSouza, Eric Achten, Angel Alberich-Bayarri, Fabian Bamberg, Ronald Boellaard, Olivier Clément, Laure Fournier, Ferdia Gallagher, Xavier Golay, Claus Peter Heussel, Edward F. Jackson, Rashindra Manniesing, Marius E. Mayerhofer, Emanuele Neri, James O’Connor, Kader Karli Oguz, Anders Persson, Marion Smits, Edwin J. R. van Beek, Christoph J. ZechEuropean Society of Radiology

Research output: Contribution to journalReview articleAcademicpeer-review

Abstract

Observer-driven pattern recognition is the standard for interpretation of medical images. To achieve global parity in interpretation, semi-quantitative scoring systems have been developed based on observer assessments; these are widely used in scoring coronary artery disease, the arthritides and neurological conditions and for indicating the likelihood of malignancy. However, in an era of machine learning and artificial intelligence, it is increasingly desirable that we extract quantitative biomarkers from medical images that inform on disease detection, characterisation, monitoring and assessment of response to treatment. Quantitation has the potential to provide objective decision-support tools in the management pathway of patients. Despite this, the quantitative potential of imaging remains under-exploited because of variability of the measurement, lack of harmonised systems for data acquisition and analysis, and crucially, a paucity of evidence on how such quantitation potentially affects clinical decision-making and patient outcome. This article reviews the current evidence for the use of semi-quantitative and quantitative biomarkers in clinical settings at various stages of the disease pathway including diagnosis, staging and prognosis, as well as predicting and detecting treatment response. It critically appraises current practice and sets out recommendations for using imaging objectively to drive patient management decisions.
Original languageEnglish
Article number87
JournalInsights into Imaging
Volume10
Issue number1
DOIs
Publication statusPublished - 1 Dec 2019

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