Quantitative imaging for evaluation of response to cancer therapy.

Advances in molecular medicine offer the potential to move cancer therapy beyond traditional cytotoxic treatments to safer and more effective targeted therapies based on molecular characteristics of a patient's tumor. Within this context, the role of quantitative imaging as an in vivo biomarker has received considerable attention as a means to predict and measure the response to therapy. For example, the ability to predict the response to therapy quantitatively, early in the drug or radiation therapy regime, would facilitate adaptive therapy trial strategies, that is, that permit alternative treatment regimens in cases where initial therapy response was ineffective. Similarly, the ability to measure the response to therapy should provide a more robust means for both therapy dose management and correlation of imaging results with other laboratory biomarkers. The latter is required for clinical decision making in the clinical setting. The National Cancer Institute (NCI) in collaboration with the Food and Drug Administration (FDA) has therefore promoted a number of initiatives supporting the role of molecular imaging in drug trials. The major goal of these initiatives is the “qualification” of the proposed molecular imaging protocol(s) that can be incorporated into current or future drug trials submitted to the FDA. Clinical research strategies that will help achieve these goals are described in the published literature [1–5].

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[4]  W. Wilson,et al.  FDG-PET lymphoma demonstration project invitational workshop. , 2007, Academic radiology.

[5]  Ram D. Sriram,et al.  Imaging as a Biomarker: Standards for Change Measurements in Therapy workshop summary. , 2008, Academic radiology.

[6]  L. Clarke,et al.  Imaging as a Biomarker for Therapy Response: Cancer as a Prototype for the Creation of Research Resources , 2008, Clinical pharmacology and therapeutics.

[7]  B. Zimmerman,et al.  Standardization of 68Ge/68Ga Using Three Liquid Scintillation Counting Based Methods , 2008, Journal of research of the National Institute of Standards and Technology.

[8]  N Petrick,et al.  Imaging as a Tumor Biomarker in Oncology Drug Trials for Lung Cancer: The FDA Perspective , 2008, Clinical pharmacology and therapeutics.

[9]  L P Clarke,et al.  The Reference Image Database to Evaluate Response to Therapy in Lung Cancer (RIDER) Project: A Resource for the Development of Change‐Analysis Software , 2008, Clinical pharmacology and therapeutics.

[10]  Huiman X Barnhart,et al.  Applications of the repeatability of quantitative imaging biomarkers: a review of statistical analysis of repeat data sets. , 2009, Translational oncology.

[11]  R. Wahl,et al.  From RECIST to PERCIST: Evolving Considerations for PET Response Criteria in Solid Tumors , 2009, Journal of Nuclear Medicine.

[12]  Daniel P Barboriak,et al.  Magnetic resonance assessment of response to therapy: tumor change measurement, truth data and error sources. , 2009, Translational oncology.

[13]  Nicholas Petrick,et al.  Quantitative imaging to assess tumor response to therapy: common themes of measurement, truth data, and error sources. , 2009, Translational oncology.

[14]  Geoffrey McLennan,et al.  PET/CT Assessment of Response to Therapy: Tumor Change Measurement, Truth Data, and Error. , 2009, Translational oncology.

[15]  P. Choyke,et al.  Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. , 2009, Neoplasia.

[16]  Geoffrey McLennan,et al.  Computed tomography assessment of response to therapy: tumor volume change measurement, truth data, and error. , 2009, Translational oncology.

[17]  Nicholas Petrick,et al.  Volumetric CT in lung cancer: an example for the qualification of imaging as a biomarker. , 2010, Academic radiology.