Predicting and monitoring cancer treatment response with diffusion-weighted MRI

Thoeny, Harriet C; Ross, Brian D (2010). Predicting and monitoring cancer treatment response with diffusion-weighted MRI. Journal of magnetic resonance imaging, 32(1), pp. 2-16. Hoboken, N.J.: Wiley Interscience 10.1002/jmri.22167

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An imaging biomarker that would provide for an early quantitative metric of clinical treatment response in cancer patients would provide for a paradigm shift in cancer care. Currently, nonimage based clinical outcome metrics include morphology, clinical, and laboratory parameters, however, these are obtained relatively late following treatment. Diffusion-weighted MRI (DW-MRI) holds promise for use as a cancer treatment response biomarker as it is sensitive to macromolecular and microstructural changes which can occur at the cellular level earlier than anatomical changes during therapy. Studies have shown that successful treatment of many tumor types can be detected using DW-MRI as an early increase in the apparent diffusion coefficient (ADC) values. Additionally, low pretreatment ADC values of various tumors are often predictive of better outcome. These capabilities, once validated, could provide for an important opportunity to individualize therapy thereby minimizing unnecessary systemic toxicity associated with ineffective therapies with the additional advantage of improving overall patient health care and associated costs. In this report, we provide a brief technical overview of DW-MRI acquisition protocols, quantitative image analysis approaches and review studies which have implemented DW-MRI for the purpose of early prediction of cancer treatment response.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Department of Radiology, Neuroradiology and Nuclear Medicine (DRNN) > Institute of Diagnostic, Interventional and Paediatric Radiology

UniBE Contributor:

Thöny, Harriet C.

ISSN:

1053-1807

Publisher:

Wiley Interscience

Language:

English

Submitter:

Factscience Import

Date Deposited:

04 Oct 2013 14:08

Last Modified:

17 Mar 2015 19:08

Publisher DOI:

10.1002/jmri.22167

PubMed ID:

20575076

Web of Science ID:

000279439600001

URI:

https://boris.unibe.ch/id/eprint/345 (FactScience: 197634)

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