State of the Art
Clinical Pharmacology & Therapeutics (2008); 84, 4, 448–456 doi:10.1038/clpt.2008.161
The Reference Image Database to Evaluate Response to Therapy in Lung Cancer (RIDER) Project: A Resource for the Development of Change-Analysis Software
SG Armato III1, CR Meyer2, MF McNitt-Gray3, G McLennan4,5,6, AP Reeves7, BY Croft8 and LP Clarke8 ;The RIDER Research Group
- 1Department of Radiology, University of Chicago, Chicago, Illinois, USA
- 2Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
- 3Department of Radiological Sciences, University of California, Los Angeles, California, USA
- 4Department of Medicine, University of Iowa, Iowa City, Iowa, USA
- 5Department of Radiology, University of Iowa, Iowa City, Iowa, USA
- 6Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa, USA
- 7Department of Electrical and Computer Engineering, Cornell University, Ithaca, New York, USA
- 8Cancer Imaging Program, National Cancer Institute, Bethesda, Maryland, USA
Correspondence: SG Armato III, (s-armato@uchicago.edu)
Received 7 June 2008; Accepted 8 July 2008; Published online 27 August 2008.
Abstract
Critical to the clinical evaluation of effective novel therapies for lung cancer is the early and accurate determination of tumor response, which requires an understanding of the sources of uncertainty in tumor measurement and subsequent attempts to minimize their effects on the assessment of the therapeutic agent. The Reference Image Database to Evaluate Response (RIDER) project seeks to develop a consensus approach to the optimization and benchmarking of software tools for the assessment of tumor response to therapy and to provide a publicly available database of serial images acquired during lung cancer drug and radiation therapy trials. Images of phantoms and patient images acquired under situations in which tumor size or biology is known to be unchanged also will be provided. The RIDER project will create standardized methods for benchmarking software tools to reduce sources of uncertainty in vital clinical assessments such as whether a specific tumor is responding to therapy.
