Abstract
This review explains in simple terms, accessible to the non-statistician, general principles regarding the correct research methods to develop and then evaluate imaging biomarkers in a clinical setting, including radiomic biomarkers. The distinction between diagnostic and prognostic biomarkers is made and emphasis placed on the need to assess clinical utility within the context of a multivariable model. Such models should not be restricted to imaging biomarkers and must include relevant disease and patient characteristics likely to be clinically useful. Biomarker utility is based on whether its addition to the basic clinical model improves diagnosis or prediction. Approaches to both model development and evaluation are explained and the need for adequate amounts of representative data stressed so as to avoid underpowering and overfitting. Advice is provided regarding how to report the research correctly. KEY POINTS: • Imaging biomarker research is common but methodological errors are encountered frequently that may mean the research is not clinically useful. • The clinical utility of imaging biomarkers is best assessed by their additive effect on multivariable models based on clinical factors known to be important. • The data used to develop such models should be sufficient for the number of variables investigated and the model should be evaluated, preferably using data unrelated to development.