Quantitative imaging to assess tumor response to therapy: Common themes of measurement, truth data, and error sources Journal Article


Authors: Meyer, C. R.; Armato, S. G. 3rd; Fenimore, C. P.; McLennan, G.; Bidaut, L. M.; Barboriak, D. P.; Gavrielides, M. A.; Jackson, E. F.; McNitt-Gray, M. F.; Kinahan, P. E.; Petrick, N.; Zhao, B.
Article Title: Quantitative imaging to assess tumor response to therapy: Common themes of measurement, truth data, and error sources
Abstract: RATIONALE: Early detection of tumor response to therapy is a key goal. Finding measurement algorithms capable of early detection of tumor response could individualize therapy treatment as well as reduce the cost of bringing new drugs to market. On an individual basis, the urgency arises from the desire to prevent continued treatment of the patient with a high-cost and/or high-risk regimen with no demonstrated individual benefit and rapidly switch the patient to an alternative efficacious therapy for that patient. In the context of bringing new drugs to market, such algorithms could demonstrate efficacy in much smaller populations, which would allow phase 3 trials to achieve statistically significant decisions with fewer subjects in shorter trials. MATERIALS AND METHODS: This consensus-based article describes multiple, imagemodality- independentmeans to assess the relative performance of algorithms for measuring tumor change in response to therapy. In this setting, we describe specifically the example of measurement of tumor volume change from anatomic imaging as well as provide an overview of other promising generic analytic methods that can be used to assess change in heterogeneous tumors. To support assessment of the relative performance of algorithms for measuring small tumor change, data sources of truth are required. RESULTS: Very short interval clinical imaging examinations and phantom scans provide known truth for comparative evaluation of algorithms. CONCLUSIONS: For a given category ofmeasurementmethods, the algorithmthat has the smallest measurement noise and least bias on average will perform best in early detection of true tumor change. Copyright © 2009 Neoplasia Press, Inc. All rights reserved.
Keywords: treatment response; nuclear magnetic resonance imaging; outcome assessment; positron emission tomography; methodology; diagnostic accuracy; consensus; computer assisted tomography; variance; image analysis; tumor volume; clinical assessment; analytic method; molecular imaging; diagnostic imaging; cancer therapy; drug uptake; algorithm; early diagnosis; quantitative analysis; contrast enhancement; image quality; diagnostic error; single photon emission computer tomography; diffusion weighted imaging; perfusion weighted imaging; measurement error; anisotropy; digital imaging and communications in medicine
Journal Title: Translational Oncology
Volume: 2
Issue: 4
ISSN: 1936-5233
Publisher: Elsevier Science, Inc.  
Date Published: 2009-12-01
Start Page: 198
End Page: 210
Language: English
DOI: 10.1593/tlo.09208
PROVIDER: scopus
PMCID: PMC2781075
PUBMED: 19956379
DOI/URL:
Notes: --- - "Cited By (since 1996): 3" - "Export Date: 30 November 2010" - "Source: Scopus"
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  1. Binsheng Zhao
    56 Zhao