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.

Full Text

Duke Authors

Cited Authors

  • Delfino, JG; Pennello, GA; Barnhart, HX; Buckler, AJ; Wang, X; Huang, EP; Raunig, DL; Guimaraes, AR; Hall, TJ; deSouza, NM; Obuchowski, N

Published Date

  • February 2023

Published In

Volume / Issue

  • 30 / 2

Start / End Page

  • 183 - 195

PubMed ID

  • 36202670

Pubmed Central ID

  • PMC9825632

Electronic International Standard Serial Number (EISSN)

  • 1878-4046

Digital Object Identifier (DOI)

  • 10.1016/j.acra.2022.09.004


  • eng

Conference Location

  • United States