Quality assurance and training procedures for computer-aided detection and diagnosis systems in clinical use.

Published

Journal Article

Computer-aided detection/diagnosis (CAD) is increasingly used for decision support by clinicians for detection and interpretation of diseases. However, there are no quality assurance (QA) requirements for CAD in clinical use at present. QA of CAD is important so that end users can be made aware of changes in CAD performance both due to intentional or unintentional causes. In addition, end-user training is critical to prevent improper use of CAD, which could potentially result in lower overall clinical performance. Research on QA of CAD and user training are limited to date. The purpose of this paper is to bring attention to these issues, inform the readers of the opinions of the members of the American Association of Physicists in Medicine (AAPM) CAD subcommittee, and thus stimulate further discussion in the CAD community on these topics. The recommendations in this paper are intended to be work items for AAPM task groups that will be formed to address QA and user training issues on CAD in the future. The work items may serve as a framework for the discussion and eventual design of detailed QA and training procedures for physicists and users of CAD. Some of the recommendations are considered by the subcommittee to be reasonably easy and practical and can be implemented immediately by the end users; others are considered to be "best practice" approaches, which may require significant effort, additional tools, and proper training to implement. The eventual standardization of the requirements of QA procedures for CAD will have to be determined through consensus from members of the CAD community, and user training may require support of professional societies. It is expected that high-quality CAD and proper use of CAD could allow these systems to achieve their true potential, thus benefiting both the patients and the clinicians, and may bring about more widespread clinical use of CAD for many other diseases and applications. It is hoped that the awareness of the need for appropriate CAD QA and user training will stimulate new ideas and approaches for implementing such procedures efficiently and effectively as well as funding opportunities to fulfill such critical efforts.

Full Text

Duke Authors

Cited Authors

  • Huo, Z; Summers, RM; Paquerault, S; Lo, J; Hoffmeister, J; Armato, SG; Freedman, MT; Lin, J; Lo, S-CB; Petrick, N; Sahiner, B; Fryd, D; Yoshida, H; Chan, H-P

Published Date

  • July 2013

Published In

Volume / Issue

  • 40 / 7

Start / End Page

  • 077001 -

PubMed ID

  • 23822459

Pubmed Central ID

  • 23822459

Electronic International Standard Serial Number (EISSN)

  • 2473-4209

Digital Object Identifier (DOI)

  • 10.1118/1.4807642

Language

  • eng

Conference Location

  • United States