Year: 2021
Type: article
Abstract: Microstructure imaging seeks to noninvasively measure and map microscopic tissue features by pairing mathematical modeling with tailored MRI protocols. This article reviews an emerging paradigm that has the potential to provide a more detailed assessment of tissue microstructure—combined diffusion‐relaxometry imaging. Combined diffusion‐relaxometry acquisitions vary multiple MR contrast encodings—such as b‐value, gradient direction, inversion time, and echo time—in a multidimensional acquisition space. When paired with suitable analysis techniques, this enables quantification of correlations and coupling between multiple MR parameters—such as diffusivity, , , and . This opens the possibility of disentangling multiple tissue compartments (within voxels) that are indistinguishable with single‐contrast scans, enabling a new generation of microstructural maps with improved biological sensitivity and specificity.
Source: Magnetic Resonance in Medicine
DOI: 10.1002/mrm.28963
Authors: Paddy J. Slator, Marco Palombo, Karla L. Miller, Carl‐Fredrik Westin, Frederik Laun, Daeun Kim, Justin P. Haldar, Dan Benjamini, Gregory Lemberskiy, Joao P. de Almeida Martins, Jana Hutter
Institutions: University College London, University of Oxford, Wellcome Centre for Integrative Neuroimaging, Brigham and Women's Hospital, Harvard University, Friedrich-Alexander-Universität Erlangen-Nürnberg, Universitätsklinikum Erlangen, University of Southern California, Uniformed Services University of the Health Sciences, Center for Neuroscience and Regenerative Medicine, Eunice Kennedy Shriver National Institute of Child Health and Human Development, NYU Langone Health, New York University, Lund University, St Olav's University Hospital, King's College London
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,500
Funders: U.S. Department of Defense, Wellcome Trust, UK Research and Innovation, National Institute for Health and Care Research, University College London, European Commission, Deutsche Forschungsgemeinschaft, University College London Hospitals NHS Foundation Trust, National Institutes of Health, Uniformed Services University of the Health Sciences, Engineering and Physical Sciences Research Council, Menzies Centre for Australian Studies, King's College London, University of London, Centre For Medical Engineering, King’s College London, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Institute of Biomedical Imaging and Bioengineering, Eunice Kennedy Shriver National Institute of Child Health and Human Development
Awards: G1066422085, G1247657515, King's College London Medical Engineering Centre of Research Excellence, G1433481316, G1435826916, G155538919, Non invasive assessment of human placental function by quantitative MRI, G2119833926, G2272555850, G2373713996, Neuroimaging Analysis Center (NAC), G2417159676, G2810537366, A biophysical simulation framework for magnetic resonance microstructure imaging, Medical image computing for next-generation healthcare technology, G3164596160, G3283310810, G347048984, G3711895790, Data-driven models for Progression Of Neurological Disease, G4907901724, Non invasive assessment of human placental function by quantitative MRI, G5296857752, G5893523844, King's College London Medical Engineering Centre of Research Excellence, G6027190877, Structure and function of the placenta from implantation to delivery: a next generation MRI approach, Novel Diffusion MRI in Early Psychosis, G8048956295, G8057189669, G8303168876, G8427053510, G8775246936, G8792368603, G8797744537, Next generation in-vivo diffusion imaging at submillimeter resolution, G938335843, G961285871
OpenAlex ID: W3195983515