Promise and pitfalls of quantitative imaging in oncology clinical trials

Brenda F. Kurland, Elizabeth R. Gerstner, James M. Mountz, Lawrence H. Schwartz, Christopher W. Ryan, Michael M. Graham, John M. Buatti, Fiona M. Fennessy, Edward A. Eikman, Virendra Kumar, Kenneth M. Forster, Richard L. Wahl, Frank S. Lieberman

Research output: Contribution to journalArticlepeer-review

78 Scopus citations

Abstract

Quantitative imaging using computed tomography, magnetic resonance imaging and positron emission tomography modalities will play an increasingly important role in the design of oncology trials addressing molecularly targeted, personalized therapies. The advent of molecularly targeted therapies, exemplified by antiangiogenic drugs, creates new complexities in the assessment of response. The Quantitative Imaging Network addresses the need for imaging modalities which can accurately and reproducibly measure not just change in tumor size but changes in relevant metabolic parameters, modulation of relevant signaling pathways, drug delivery to tumor and differentiation of apoptotic cell death from other changes in tumor volume. This article provides an overview of the applications of quantitative imaging to phase 0 through phase 3 oncology trials. We describe the use of a range of quantitative imaging modalities in specific tumor types including malignant gliomas, lung cancer, head and neck cancer, lymphoma, breast cancer, prostate cancer and sarcoma. In the concluding section, we discuss potential constraints on clinical trials using quantitative imaging, including complexity of trial conduct, impact on subject recruitment, incremental costs and institutional barriers. Strategies for overcoming these constraints are presented.

Original languageEnglish (US)
Pages (from-to)1301-1312
Number of pages12
JournalMagnetic Resonance Imaging
Volume30
Issue number9
DOIs
StatePublished - Nov 2012

Keywords

  • CT
  • Cancer
  • Clinical trials
  • MRI
  • PET
  • Quantitative imaging

ASJC Scopus subject areas

  • Biophysics
  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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