Advanced Diffusion MRI and Its Clinical Applications

Dear Colleagues,

Diffusion magnetic resonance imaging (MRI) has become a pillar of modern clinical imaging with its sensitivity to probe underlying tissue microstructures at the microscopic level, much lower than the achievable image resolution of conventional MRI. With this capability, diffusion MRI can serve as an imaging biomarker for an array of clinical applications ranging from the assessment of acute brain ischemia and neurodegenerative disorders to tumor tissue characterization, which has been essential in the management of cancer in various organs.

The recent advances in the technological developments have substantially improved the data acquisition, processing, and analysis pipeline in diffusion MRI. The advanced image acquisition technologies with reduced field-of-view, non-Cartesian sampling, simultaneous multi-slice imaging, and many others, in conjunction with the use of state-of-the-art machine-learning methods, have substantially improved the quality of the images and increased the speed and reproducibility of data acquisition at high (i.e., 3T) or ultra-high field (i.e., 7T and above). On the other hand, the diffusion MRI research community has continuously been working on improving tissue microstructural characterization by developing advanced data-analysis techniques to extract biologically valuable information from diffusion-weighted MR signals, especially in the high b-value regime. These advancements in technology have had a significant impact on the clinical applications of diffusion MRI, including in areas such as cancer diagnosis and treatment evaluation, determining the severity of tumors, and identifying neurodegenerative diseases.

The goal of this Special Issue, entitled “Recent Advances in Diffusion MRI and Its Clinical Applications”, is to share new perspectives on the most recent research challenges in the field of diffusion MRI. We welcome original research papers, review articles, and case reports that reflect recent technical developments of diffusion MRI and its clinical applications.

Dr. Zheng Zhong
Dr. Muge Karaman
Guest Editors

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