Radiology 2022 May 17:211597. Epub 2022 May 17.
From the Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, 485 Lexington Ave, 2nd Floor, New York, NY, NY 10017 (C.S.M.); Cancer Digital Intelligence Program, University Health Network, Toronto, ON, Canada (M.L.W.); The Russell H. Morgan Department of Radiology and Radiological Science and Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins School of Medicine, Baltimore, Md (M.A.J.); ERT, Pittsburgh, Pa (B.F.K.); and School of Computing, Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada (A.L.S.).
Rapid advances in automated methods for extracting large numbers of quantitative features from medical images have led to tremendous growth of publications reporting on radiomic analyses. Translation of these research studies into clinical practice can be hindered by biases introduced during the design, analysis, or reporting of the studies. Herein, the authors review biases, sources of variability, and pitfalls that frequently arise in radiomic research, with an emphasis on study design and statistical analysis considerations. Read More