Computed tomography assessment of response to therapy: tumor volume change measurement, truth data, and error

Michael F. McNitt-Gray, Luc M. Bidaut, Samuel G. Armato III, Charles R. Meyer, Marios A. Gavrielides, Charles Fenimore, Geoffrey McLennan, Nicholas Petrick, Binsheng Zhao, Anthony P. Reeves, Reinhard Beichel, Hyun-Jung (Grace) Kim, Lisa Kinnard

    Research output: Contribution to journalArticlepeer-review

    30 Citations (Scopus)

    Abstract

    RATIONALE AND OBJECTIVES: This article describes issues and methods that are specific to the measurement of change in tumor volume as measured from computed tomographic (CT) images and how these would relate to the establishment of CT tumor volumetrics as a biomarker of patient response to therapy. The primary focus is on the measurement of lung tumors, but the approach should be generalizable to other anatomic regions. MATERIALS AND METHODS: The first issues addressed are the various sources of bias and variance in the measurement of tumor volumes, which are discussed in the context of measurement variation and its impact on the early detection of response to therapy. RESULTS AND RESOURCES: Research that seeks to identify the magnitude of some of these sources of error is ongoing, and several of these efforts are described herein. In addition, several resources for these investigations are being made available through the National Institutes of Health-funded Reference Image Database to Evaluate Response to therapy in cancer project, and these are described as well. Other measures derived from CT image data that might be predictive of patient response are described briefly, as well as the additional issues that each of these metrics may encounter in real-life applications. CONCLUSIONS: The article concludes with a brief discussion of moving from the assessment of measurement variation to the steps necessary to establish the efficacy of a metric as a biomarker for response.
    Original languageEnglish
    Pages (from-to)216-222
    Number of pages7
    JournalTranslational Oncology
    Volume2
    Issue number4
    DOIs
    Publication statusPublished - Dec 2009

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