Quantitative diffusion-weighted imaging (DWI) techniques allow the characterization of the microstructural properties of the human brain “in vivo”, and are commonly used in neuroscientific and clinical contexts. By measuring the diffusion of water molecules in neural tissue, DWI can detect subtle changes in cellular integrity and organization, making it particularly valuable for the study of various neurological disorders. The sensitivity of DWI to microstructural alterations has made it indispensable not only for diagnosing but also for understanding the underlying pathophysiological mechanisms of diseases such as acute stroke, multiple sclerosis, and neurodegenerative diseases. However, the inability of simple models, such as standard diffusion tensor imaging (DTI), to visualize complex intravoxel fiber topologies and the limited biological specificity of their metrics have motivated the development of several advanced diffusion MRI techniques. Therefore, over the years, refinements in DWI techniques, including multi-shell imaging, high-angular resolution diffusion imaging (HARDI) techniques, biophysical models (e.g., CHARMED, WMTI, NODDI), and novel diffusion encoding approaches (e.g., b-tensor or double diffusion encoding) have pushed the boundaries of neuroimaging and enabled more accurate and specific characterization of brain tissue properties. With the further development of DWI, its role in neurology is expanding. It encompasses not only diagnostic applications but also the monitoring of treatments and prognoses, shaping the future of precision medicine in neurological care.This Research Topic aims to explore the recent advances and implementations of diffusion-weighted imaging in the field of neurology. We seek to highlight research on novel methodologies, clinical applications, and diagnostic advancements in DWI. By bringing together experts in the field, our primary goal is to foster interdisciplinary discussions that can propel the field forward and enhance our diagnostic and therapeutic approaches to neurological disorders as well as our understanding of the neuropathological processes.We welcome the submission of any type of manuscript supported by the journal (including Brief Research Reports, Perspective, Mini-Review, Original Research, Systematic Review, etc.) pertaining to DWI application in neurological disorders. Possible themes include, but are not limited to:- Innovations in DWI acquisition techniques and post-processing methods.- Novel diffusion encoding approaches holding promise in neurological applications.- Clinical applications of DWI in neurological conditions.- Validation studies comparing DWI findings with other imaging modalities.- Integration of DWI with other neuroimaging techniques for comprehensive brain assessment. Dr. Kevin Koch has received research funding from Siemens Healthcare, Hyperfine, Inc., and GE HealthCare Technologies, Inc. to develop MRI Technology, and is co-inventor on several patents on systems and methods for MRI. The other Topic Editors declare no competing interests with regard to the Research Topic subject.
Quantitative diffusion-weighted imaging (DWI) techniques allow the characterization of the microstructural properties of the human brain “in vivo”, and are commonly used in neuroscientific and clinical contexts. By measuring the diffusion of water molecules in neural tissue, DWI can detect subtle changes in cellular integrity and organization, making it particularly valuable for the study of various neurological disorders. The sensitivity of DWI to microstructural alterations has made it indispensable not only for diagnosing but also for understanding the underlying pathophysiological mechanisms of diseases such as acute stroke, multiple sclerosis, and neurodegenerative diseases. However, the inability of simple models, such as standard diffusion tensor imaging (DTI), to visualize complex intravoxel fiber topologies and the limited biological specificity of their metrics have motivated the development of several advanced diffusion MRI techniques. Therefore, over the years, refinements in DWI techniques, including multi-shell imaging, high-angular resolution diffusion imaging (HARDI) techniques, biophysical models (e.g., CHARMED, WMTI, NODDI), and novel diffusion encoding approaches (e.g., b-tensor or double diffusion encoding) have pushed the boundaries of neuroimaging and enabled more accurate and specific characterization of brain tissue properties. With the further development of DWI, its role in neurology is expanding. It encompasses not only diagnostic applications but also the monitoring of treatments and prognoses, shaping the future of precision medicine in neurological care.This Research Topic aims to explore the recent advances and implementations of diffusion-weighted imaging in the field of neurology. We seek to highlight research on novel methodologies, clinical applications, and diagnostic advancements in DWI. By bringing together experts in the field, our primary goal is to foster interdisciplinary discussions that can propel the field forward and enhance our diagnostic and therapeutic approaches to neurological disorders as well as our understanding of the neuropathological processes.We welcome the submission of any type of manuscript supported by the journal (including Brief Research Reports, Perspective, Mini-Review, Original Research, Systematic Review, etc.) pertaining to DWI application in neurological disorders. Possible themes include, but are not limited to:- Innovations in DWI acquisition techniques and post-processing methods.- Novel diffusion encoding approaches holding promise in neurological applications.- Clinical applications of DWI in neurological conditions.- Validation studies comparing DWI findings with other imaging modalities.- Integration of DWI with other neuroimaging techniques for comprehensive brain assessment. Dr. Kevin Koch has received research funding from Siemens Healthcare, Hyperfine, Inc., and GE HealthCare Technologies, Inc. to develop MRI Technology, and is co-inventor on several patents on systems and methods for MRI. The other Topic Editors declare no competing interests with regard to the Research Topic subject.