Following its success in early detection of cerebral ischemia, diffusion-weighted imaging (DWI) has been increasingly used
in cancer diagnosis and treatment evaluation. These applications are propelled by the rapid development of novel diffusion models
to extract biologically valuable information from diffusion-weighted MR signals, and significant advance in MR hardware that has
enabled image acquisition with high b-values. This article reviews recent technical developments and clinical applications in
cancer imaging using DWI, with a special emphasis on high b-value diffusion models. The article is organized in four sections.
First, we provide an overview of diffusion models that are relevant to cancer imaging. The model parameters are discussed in
relation to three tissue properties – cellularly, vascularity, and microstructures. An emphasis is placed on
characterization of microstructural heterogeneity, given its novelty and close relevance to cancer. Second, we illustrate
diffusion MR clinical applications in each of the following three categories: (a) cancer detection and diagnosis; (b) cancer
grading, staging, and classification; and (c) cancer treatment response prediction and evaluation. Third, we discuss several
practical issues, including selection of image acquisition parameters, reproducibility and reliability, motion management, image
distortion, etc., that are commonly encountered when applying DWI to cancer in clinical settings. Lastly, we highlight a few
ongoing challenges and provide some possible future directions, particularly in the area of establishing standards via
well-organized multi-center clinical trials to accelerate clinical translation of advanced DWI techniques to improving cancer care
on a large scale.