Microstructure imaging by diffusion MRI

Background

In diffusion MRI (dMRI), images are sensitised to water diffusion by the application of magnetic field gradients. Cell membranes hinder the diffusional motion and thereby contribute to the contrast in dMRI. Thus, the diffusion of water molecules is used a probe of tissue microstructure.
 

Specific Work

Data from dMRI is often analysed using diffusion tensor imaging (DTI), which yields image biomarkers that reflect cell density and the orientation coherence of tissue, in terms of the mean diffusivity (MD) and fractional anisotropy (FA), respectively. However, these metrics conflates multiple measures of the microstructure. In our group, we are developing a novel set of technologies for acquisition and analysis of dMRI that we collectively call multidimensional microstructure imaging (MMI). MMI takes advantage of our recent developments for dMRI that enables diffusion encoding by gradient waveforms that goes beyond previous strategies, such as so-called single diffusion encoding. 

Figure above: Diffusional variance decomposition (DIVIDE) can be used to differentiate tumors based on their cell shapes, here illustrated for a meningioma (left) and a glioma (right).

Aims

• To develop and implement MMI as a tool for microstructure imaging.

• Apply dMRI and MMI in studies of neurodegenerative diseases and in oncology.

• Develop software that permits fast and accurate analysis of dMRI and MMI data.

Collaborators

The microstructure imaging group is led by Markus Nilsson, PhD. The research towards our aim is conducted by a large network of scientists, both locally in Lund and at other sites. The main nodes of the collaborator network are described below

Physical Chemistry (LU):

Prof Daniel Topgaard, PhD

Language network (LU):

Mikael Novén

Mikael Roll, PhD

Johan Mårtensson, PhD

Division of Oncology and Pathology (LU):

Elisabeth Englund, PhD

Harvard Medical School, Boston, USA:

Carl-Fredrik Westin, PhD
 

Key References

• The link between diffusion MRI and tumor heterogeneity: Mapping cell eccentricity and density by diffusional variance decomposition (DIVIDE). Filip Szczepankiewicz, Danielle van Westen, Elisabet Englund, Carl-Fredrik Westin, Freddy Ståhlberg, Jimmy Lätt, Pia C. Sundgren, Markus Nilsson. NeuroImage, 2016, in press.
• Q-space trajectory imaging for multidimensional diffusion MRI of the human brain. CF Westin, H Knutsson, O Pasternak, F Szczepankiewicz,
E Özarslan, D van Westen, C Mattisson, M Bogren, L O’Donnell, M Kubicki, D Topgaard, M Nilsson. NeuroImage, 2016. Early view.
• Quantification of Microcirculatory Parameters by Joint Analysis of Flow-Compensated and Non-Flow-Compensated Intravoxel Incoherent Motion (IVIM) Data. A Ahlgren, L Knutsson, R Wirestam, M Nilsson, F Ståhlberg, D Topgaard, S Lasič. NMR Biomed, 2016. Early view.
• Extrapolation-based references improve motion correction of high b-value DWI data: Application in Parkinson’s disease dementia. M Nilsson, F Szczepankiewicz, O Hansson, D van Westen. PLoS ONE 10(11): e0141825.
• Noninvasive mapping of water diffusional exchange in the human brain using filter-exchange imaging. M Nilsson, J Lätt, D van Westen, S Brockstedt, S Lasic, F Ståhlberg, D Topgaard. Magn Reson Med, 2013:69(3):1573-81. 

 
For more information about our diffusion MRI research please contact:

Markus Nilsson, Ph.D.
Associate senior lecturer
Department of Diagnostic Radiology
Faculty of Medicine
Lund University, Sweden
e-mail: markus [dot] nilsson [at] med [dot] lu [dot] se (markus[dot]nilsson[at]med[dot]lu[dot]se)  LU research portal profile: Markus Nilsson

See also the group description in the LU research portal profile:

 Multidimensional Microstructure Imaging