Diffusion MRI in early cancer therapeutic response assessment

被引:70
作者
Galban, C. J. [1 ]
Hoff, B. A. [1 ]
Chenevert, T. L. [1 ]
Ross, B. D. [1 ]
机构
[1] Univ Michigan, Dept Radiol, Ctr Mol Imaging, Ann Arbor, MI 48109 USA
基金
美国国家卫生研究院;
关键词
review article; cancer treatment response; imaging biomarker; functional diffusion map; diffusion-weighted MRI; WEIGHTED MAGNETIC-RESONANCE; ADVANCED RECTAL-CANCER; SQUAMOUS-CELL CARCINOMA; NEOADJUVANT CHEMORADIATION THERAPY; INTRAVOXEL INCOHERENT MOTION; ADVANCED BREAST-CANCER; CONTRAST-ENHANCED MRI; TRANSCATHETER ARTERIAL CHEMOEMBOLIZATION; UNRESECTABLE HEPATOCELLULAR-CARCINOMA; PATHOLOGICAL COMPLETE RESPONSE;
D O I
10.1002/nbm.3458
中图分类号
Q6 [生物物理学];
学科分类号
071011 ;
摘要
Imaging biomarkers for the predictive assessment of treatment response in patients with cancer earlier than standard tumor volumetric metrics would provide new opportunities to individualize therapy. Diffusion-weighted MRI (DW-MRI), highly sensitive to microenvironmental alterations at the cellular level, has been evaluated extensively as a technique for the generation of quantitative and early imaging biomarkers of therapeutic response and clinical outcome. First demonstrated in a rodent tumor model, subsequent studies have shown that DW-MRI can be applied to many different solid tumors for the detection of changes in cellularity as measured indirectly by an increase in the apparent diffusion coefficient (ADC) of water molecules within the lesion. The introduction of quantitative DW-MRI into the treatment management of patients with cancer may aid physicians to individualize therapy, thereby minimizing unnecessary systemic toxicity associated with ineffective therapies, saving valuable time, reducing patient care costs and ultimately improving clinical outcome. This review covers the theoretical basis behind the application of DW-MRI to monitor therapeutic response in cancer, the analytical techniques used and the results obtained from various clinical studies that have demonstrated the efficacy of DW-MRI for the prediction of cancer treatment response. Copyright (C) 2016 John Wiley & Sons, Ltd.
引用
收藏
页数:14
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