Translating preclinical MRI methods to clinical oncology

David A. Hormuth, Anna G. Sorace, John Virostko, Richard G. Abramson, Zaver M. Bhujwalla, Pedro Enriquez-Navas, Robert Gillies, John D. Hazle, Ralph P. Mason, C. Chad Quarles, Jared A. Weis, Jennifer G. Whisenant, Junzhong Xu, Thomas E. Yankeelov

Research output: Contribution to journalReview articlepeer-review

9 Scopus citations

Abstract

The complexity of modern in vivo magnetic resonance imaging (MRI) methods in oncology has dramatically changed in the last 10 years. The field has long since moved passed its (unparalleled) ability to form images with exquisite soft-tissue contrast and morphology, allowing for the enhanced identification of primary tumors and metastatic disease. Currently, it is not uncommon to acquire images related to blood flow, cellularity, and macromolecular content in the clinical setting. The acquisition of images related to metabolism, hypoxia, pH, and tissue stiffness are also becoming common. All of these techniques have had some component of their invention, development, refinement, validation, and initial applications in the preclinical setting using in vivo animal models of cancer. In this review, we discuss the genesis of quantitative MRI methods that have been successfully translated from preclinical research and developed into clinical applications. These include methods that interrogate perfusion, diffusion, pH, hypoxia, macromolecular content, and tissue mechanical properties for improving detection, staging, and response monitoring of cancer. For each of these techniques, we summarize the 1) underlying biological mechanism(s); 2) preclinical applications; 3) available repeatability and reproducibility data; 4) clinical applications; and 5) limitations of the technique. We conclude with a discussion of lessons learned from translating MRI methods from the preclinical to clinical setting, and a presentation of four fundamental problems in cancer imaging that, if solved, would result in a profound improvement in the lives of oncology patients. Level of Evidence: 5. Technical Efficacy: Stage 3. J. Magn. Reson. Imaging 2019;50:1377–1392.

Original languageEnglish (US)
Pages (from-to)1377-1392
Number of pages16
JournalJournal of Magnetic Resonance Imaging
Volume50
Issue number5
DOIs
StatePublished - Nov 1 2019

Keywords

  • CEST
  • MT
  • cancer
  • diffusion
  • elastography
  • perfusion

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

Fingerprint

Dive into the research topics of 'Translating preclinical MRI methods to clinical oncology'. Together they form a unique fingerprint.

Cite this