Multiparametric Quantitative Imaging Biomarkers for Phenotype Classification: A Framework for Development and Validation.
Journal Article (Journal Article;Review)
This manuscript is the third in a five-part series related to statistical assessment methodology for technical performance of multi-parametric quantitative imaging biomarkers (mp-QIBs). We outline approaches and statistical methodologies for developing and evaluating a phenotype classification model from a set of multiparametric QIBs. We then describe validation studies of the classifier for precision, diagnostic accuracy, and interchangeability with a comparator classifier. We follow with an end-to-end real-world example of development and validation of a classifier for atherosclerotic plaque phenotypes. We consider diagnostic accuracy and interchangeability to be clinically meaningful claims for a phenotype classification model informed by mp-QIB inputs, aiming to provide tools to demonstrate agreement between imaging-derived characteristics and clinically established phenotypes. Understanding that we are working in an evolving field, we close our manuscript with an acknowledgement of existing challenges and a discussion of where additional work is needed. In particular, we discuss the challenges involved with technical performance and analytical validation of mp-QIBs. We intend for this manuscript to further advance the robust and promising science of multiparametric biomarker development.
- Delfino, JG; Pennello, GA; Barnhart, HX; Buckler, AJ; Wang, X; Huang, EP; Raunig, DL; Guimaraes, AR; Hall, TJ; deSouza, NM; Obuchowski, N
- February 2023
Volume / Issue
- 30 / 2
Start / End Page
- 183 - 195
Pubmed Central ID
Electronic International Standard Serial Number (EISSN)
Digital Object Identifier (DOI)
- United States