APA
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Hormuth, D., Sorace, A., Virostko, J., Abramson, R., Bhujwalla, Z., Enriquez-Navas, P., … Yankeelov, T. (2019). Translating preclinical MRI methods to clinical oncology. Journal of Magnetic Resonance Imaging.
Chicago/Turabian
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Hormuth, D., A. Sorace, J. Virostko, R. Abramson, Z. Bhujwalla, P. Enriquez-Navas, R. Gillies, et al. “Translating Preclinical MRI Methods to Clinical Oncology.” Journal of Magnetic Resonance Imaging (2019).
MLA
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Hormuth, D., et al. “Translating Preclinical MRI Methods to Clinical Oncology.” Journal of Magnetic Resonance Imaging, 2019.
BibTeX Click to copy
@article{d2019a,
title = {Translating preclinical MRI methods to clinical oncology},
year = {2019},
journal = {Journal of Magnetic Resonance Imaging},
author = {Hormuth, D. and Sorace, A. and Virostko, J. and Abramson, R. and Bhujwalla, Z. and Enriquez-Navas, P. and Gillies, R. and Hazle, J. and Mason, R. and Quarles, C. and Weis, J. and Whisenant, J. and Xu, Junzhong and Yankeelov, T.}
}
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.
