Multiparametric Quantitative Imaging Biomarkers for Phenotype Classification: A Framework for Development and Validation

Jana G. Delfino, Gene A. Pennello, Huiman X. Barnhart, Andrew J. Buckler, Xiaofeng Wang, Erich P. Huang, Dave L. Raunig, Alexander R. Guimaraes, Timothy J. Hall, Nandita M. deSouza, Nancy Obuchowski

Research output: Contribution to journalReview articlepeer-review

3 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)183-195
Number of pages13
JournalAcademic radiology
Issue number2
StatePublished - Feb 2023


  • QIBA
  • multi-class classification
  • multi-parametric quantitative imaging biomarkers (mp-QIBs)
  • multiparametric classification
  • phenotype classification

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging


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