The emerging science of quantitative imaging biomarkers terminology and definitions for scientific studies and regulatory submissions.

The development and implementation of quantitative imaging biomarkers has been hampered by the inconsistent and often incorrect use of terminology related to these markers. Sponsored by the Radiological Society of North America, an interdisciplinary group of radiologists, statisticians, physicists, and other researchers worked to develop a comprehensive terminology to serve as a foundation for quantitative imaging biomarker claims. Where possible, this working group adapted existing definitions derived from national or international standards bodies rather than invent new definitions for these terms. This terminology also serves as a foundation for the design of studies that evaluate the technical performance of quantitative imaging biomarkers and for studies of algorithms that generate the quantitative imaging biomarkers from clinical scans. This paper provides examples of research studies and quantitative imaging biomarker claims that use terminology consistent with these definitions as well as examples of the rampant confusion in this emerging field. We provide recommendations for appropriate use of quantitative imaging biomarker terminological concepts. It is hoped that this document will assist researchers and regulatory reviewers who examine quantitative imaging biomarkers and will also inform regulatory guidance. More consistent and correct use of terminology could advance regulatory science, improve clinical research, and provide better care for patients who undergo imaging studies.

Quantitative imaging biomarkers: a review of statistical methods for technical performance assessment.

Technological developments and greater rigor in the quantitative measurement of biological features in medical images have given rise to an increased interest in using quantitative imaging biomarkers to measure changes in these features. Critical to the performance of a quantitative imaging biomarker in preclinical or clinical settings are three primary metrology areas of interest: measurement linearity and bias, repeatability, and the ability to consistently reproduce equivalent results when conditions change, as would be expected in any clinical trial. Unfortunately, performance studies to date differ greatly in designs, analysis method, and metrics used to assess a quantitative imaging biomarker for clinical use. It is therefore difficult or not possible to integrate results from different studies or to use reported results to design studies. The Radiological Society of North America and the Quantitative Imaging Biomarker Alliance with technical, radiological, and statistical experts developed a set of technical performance analysis methods, metrics, and study designs that provide terminology, metrics, and methods consistent with widely accepted metrological standards. This document provides a consistent framework for the conduct and evaluation of quantitative imaging biomarker performance studies so that results from multiple studies can be compared, contrasted, or combined.

US FDA and personalized medicine: in vitro diagnostic regulatory perspective.

Personalized medicine has captured the attention of the public, including patients, healthcare providers, scientists, medical product manufacturers and many others. The US FDA will evaluate many of the products that will allow personalized medicine to be successfully implemented in the USA. This article addresses the FDA's approach to regulation of one component of personalized medicine, in vitro diagnostic devices. It also describes the FDA's efforts to integrate the various medical product regulatory authorities provided by Congress in the Federal Food, Drug and Cosmetic Act to develop effective mechanisms for oversight of medical products used to personalize treatment. Finally, it presents some of the current challenges in in vitro diagnostics oversight that may be of interest for personalized medicine.

Protein-based multiplex assays: mock presubmissions to the US Food and Drug Administration.

As a part of ongoing efforts of the NCI-FDA Interagency Oncology Task Force subcommittee on molecular diagnostics, members of the Clinical Proteomic Technology Assessment for Cancer program of the National Cancer Institute have submitted 2 protein-based multiplex assay descriptions to the Office of In Vitro Diagnostic Device Evaluation and Safety, US Food and Drug Administration. The objective was to evaluate the analytical measurement criteria and studies needed to validate protein-based multiplex assays. Each submission described a different protein-based platform: a multiplex immunoaffinity mass spectrometry platform for protein quantification, and an immunological array platform quantifying glycoprotein isoforms. Submissions provided a mutually beneficial way for members of the proteomics and regulatory communities to identify the analytical issues that the field should address when developing protein-based multiplex clinical assays.

Comparing two medical tests when results of reference standard are unavailable for those negative via both tests.

In studies for comparing the diagnostic accuracy of two qualitative tests, very often the reference standard to confirm the disease status is not applied to all study subjects. We considered a situation when all subjects with a positive result by at least one of the tests had a verified disease status and none of the subjects with both tests negative results had a verification of disease status. In this paper, we discuss whether the information about the ratio of true positive rates and the ratio of false positive rates of two qualitative tests, T(New) and T(Old), is sufficient to draw a conclusion about effectiveness of the T(New). We show that if there is a statistically significant increase in true positive rates and the increase in true positive rates is statistically larger than increase in false positive rates, then a conclusion about effectiveness of test T(New) can be made and this does not require application of the reference standard to the subjects with negative results by both tests. An application of ratio of true positive rates and ratio of false positive rates to post-market studies is also presented.