Literature DB >> 20640013

Data sets for the qualification of volumetric CT as a quantitative imaging biomarker in lung cancer.

A J Buckler1, L H Schwartz, N Petrick, M McNitt-Gray, B Zhao, C Fenimore, A P Reeves, P D Mozley, R S Avila.   

Abstract

The drug development industry is faced with increasing costs and decreasing success rates. New ways to understand biology as well as the increasing interest in personalized treatments for smaller patient segments requires new capabilities for the rapid assessment of treatment responses. Deployment of qualified imaging biomarkers lags apparent technology capabilities. The lack of consensus methods and qualification evidence needed for large-scale multi-center trials, as well as the standardization that allows them, are widely acknowledged to be the limiting factors. The current fragmentation in imaging vendor offerings, coupled with the independent activities of individual biopharmaceutical companies and their contract research organizations (CROs), may stand in the way of the greater opportunity were these efforts to be drawn together. A preliminary report, "Volumetric CT: a potential biomarker of response," of the Quantitative Imaging Biomarkers Alliance (QIBA) activity was presented at the Medical Imaging Continuum: Path Forward for Advancing the Uses of Medical Imaging in the Development of New Biopharmaceutical Products meeting of the Extended Pharmaceutical Research and Manufacturers of America (PhRMA) Imaging Group sponsored by the Drug Information Agency (DIA) in October 2008. The clinical context in Lung Cancer and a methodology for approaching the qualification of volumetric CT as a biomarker has since been reported [Acad. Radiol. 17, 100-106, 107-115 (2010)]. This report reviews the effort to collect and utilize publicly available data sets to provide a transparent environment in which to pursue the qualification activities in such a way as to allow independent peer review and verification of results. This article focuses specifically on our role as stewards of image sets for developing new tools.

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Year:  2010        PMID: 20640013     DOI: 10.1364/OE.18.015267

Source DB:  PubMed          Journal:  Opt Express        ISSN: 1094-4087            Impact factor:   3.894


  10 in total

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Review 4.  A novel knowledge representation framework for the statistical validation of quantitative imaging biomarkers.

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Review 7.  Cardiac imaging approaches to evaluate drug-induced myocardial dysfunction.

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10.  ESR statement on the stepwise development of imaging biomarkers.

Authors: 
Journal:  Insights Imaging       Date:  2013-02-09
  10 in total

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